INCENTIVES FOR SOLID HASTE COLLECTION PERSONNEL
Richard L. Shell
and
Dean 5 f Shupe
UNIVERSITY OF CINCINNATI
DEPARTMENT OF MECHANICAL AND INDUSTRIAL ENGINEERING
Cincinnati, Ohio 45221
Grant No, R801617
project Officer
Oscar W, Albrecht
Solid and Hazardous Waste Research Division
Municipal Environmental Research Laboratory
U.S. Environmental Protection Agency
Office of Research and Development
Municipal Environmental Research Laboratory
Cincinnati, Ohio 45268
-------
DISCLA331ER
This report has been reviewed by the Environmental Research
Center - Cincinnati, U.S. Environmental Protection Agency and
approved for publication. Approval does not signify that the
contents necessarily reflect the views and policies of the U.S.
Environmental Protection Agency, nor does mention of trade
names or commercial products constitute endorsement or recom-
mendations for use.
1,1,
-------
FOREWORD
Cities across the United States are confronted with the
responsibility for providing many essential services on a
relatively fixed income in a time of unprecedented inflationary
costs. Improved productivity in municipal services is one means
of combating this dilemma. As President Gerald R. Ford stated
at the White House on January 14, 1975, "In these troubled
times, it is imperative that labor, management, and government
find ways of working together to bolster the strength of the
American economy. At the heart of our problems is the need to
improve productivity .... We must focus now on ways to
achieve higher levels of productivity ..."
This project examines the feasibility of using incentives
to increase productivity of solid waste personnel. The results
show that incentives are technically feasible and that substan-
tial cost savings can be realized. Hopefully, the findings
reported herein will be valuable in assisting local governments
to increase the productivity of their solid waste collection
workers.
Francis T. Mayo
Director
Environmental Research Center
Cincinnati, Ohio
-------
ABSTRACT
The purpose of this project is to determine the feasibility
of incentive programs for municipal solid waste collection
personnel. Major research areas include an assessment of
union/management/worker behavioral attitudes towards wage in^-
centives; construction of a solid waste generation/collection
computerized data bank; development of work standards utilizing
work measurement techniques; application of time standards to
area route development; design of a prototype wage incentive
program based on area routes with known work content; and
assessment of the impact of an incentive program in the test
City of Covington, Kentucky.
The findings show that wage incentive programs for munici-
pal solid waste personnel are feasible and technically possible,
but 'that political problems more complex than found in private
industry must be dealt with. Substantial cost savings may be
realized through proper design and implementation of time and
monetary incentive programs. In the test City, annual savings
of $113,000 (19 percent of budget) resulted from implementation
of a new collection system utilizing time incentives. An addi-
tional $112,000 (making a total of $225,000 or 38 percent of
budget] savings resulted from a second implementation with
collection frequency reduced from twice to once weekly.
I'D
-------
TABLE OF CONTENTS
PAGE
FOREWORD
ABSTRACT iu
TABLE OF CONTENTS v
LIST OF FIGURES viii
LIST OF TABLES x
ACKNOWLEDGEMENTS xi
OVERVIEW AND BACKGROUND
Summary and Conclusions 1
Recommendations for Future Research 5
The Solid Waste Operating
System in Covington, Kentucky 6
Political Constraints 6
INCENTIVE SYSTEMS
Introduction 10
Review of Classical Direct
Monetary Incentive Plans 11
Use of Direct Wage Incentives
In Industry 16
Survey of Incentive
Programs for Public Employees 17
A Prototype Wage Incentive Program
for Solid Waste Personnel 23
Evaluating an Incentive Program 30
Footnotes 31
MOTIVATION AND JOB PERFORMANCE
Introduction 32
Motivation and Performance Overview 33
Job Satisfaction 35
Sociometric Analysis for
Crew Selection 33
Footnotes 42
v
-------
TABLE OF CONTENTS/ (CONTINUED)
PAGE
4 PERSONAL CHARACTERISTICS AND ABSENTEEISM
FOR SOLID WASTE COLLECTION'WORKERS
Introduction 45
Causes of Absenteeism 49
Worker Environment in Covington,
Kentucky 51
Methodology of Investigation and
Variable Identification 53
Relationships Between Demographic
Characteristics and Absenteeism 56
Conclusions 69
Footnotes 71
WORK MEASUREMENT
Techniques Available 73
Application of Techniques 74
Work Sampling for Solid Waste
Collection Activities in Covington,
Kentucky 75
Solid Waste Collection Standards
D eve1opment 8 4
Footnotes 97
COMPUTERIZED DATA BANK
Introduction 99
Description of Programs 102
Overall System 118
Footnotes 120
WASTE COLLECTION ROUTE DEVELOPMENT AND RESULTS
Introduction 121
Alternative Collection Route Designs 121
Economic Analysis and Cost Savings
Comparison of Waste Collection
Alternatives 122
Implementation 136
Conclusions 149
BIBLIOGRAPHY 150
y-z.
-------
TABLE OF CONTENTS/ (CONTINUED)
PAGE
9 APPENDIX 163
Sample Employee Preference Choice Form 164
Cover Letter For Employee Preference 165
Street Collection Data Form 166
Weigh Station Record Form 167
Partial Map of Covington With Block
Identification Numbers 168
Computer Program for Work Sampling
Values 169
Sample Computer Output of Automated
Route Design 171
Sample Computer Output of Detail Route
Design for Team I 174
Sample Computer Output of Detail Route
Design for Team II 179
Sample Ordinance for Once-a-week Collec-
tion 183
Sample Ordinance for Twice-a-week Collec-
tion 187
Sample Announcement for Citizen Notifi-
cation 191
Example of Newspaper Coverage Prior to
Collection Alternative Selection 192
Newspaper Citizen Notification Prior
to Change Over 194
Summary of Team Assignments 195
Driver Guidelines 196
Foreman's Activities 197
-------
LIST OF FIGURES
PAGE
Figure
1 State and Local Deficits 1
2 Breakdown of Refuse Handling Costs 1
3 Covington Municipal Garage 7
4 Collection Truck Crew 7
5 Rear Packer Truck, 18 Cubic-Yard 8
6 Curbside Setout 8
7 Earning Opportunities Under Classical Wage
Incentive Plans 14
8 Local Government Usage of Employee
Incentives 18
9 Detroit, Michigan Savings Formula 21
10 Flint, Michigan Savings Formula 22
11 Sociometric Analysis Matrix 39
12 Three-Man Crew 41
13 Residential, Single Unit 76
14 Residential, Multi-unit 77
15 Downtown 78
16 Maximum Delay Conditions 78
17 Minimum Delay Conditions 79
18 Field Measurement of Truck Velocity,Level
Terrain 88
19 Field Measurement of Truck Velocity, Incline 88
20 Average Truck Velocity 89
21 Laboratory Street Collection Model 91
22 Manual Collection Times 92
23 Walk/Ride Crossover Points 95
24 Example Map of Stop-By-Stop Field Survey 99
25 Survey Data Verification 103
26 Block Generation Program 104
27 Block Data File Verification 106
28 Block Classification 107
29 Regression Data 109
30 Density Report 111
31 Predictive Results 112
32 ID File Verification 113
33 Route Design 115
34 Route Design, Modified 116
35 Automatic Route Design 117
36 Overall System Flow 119
wiii.
-------
LIST OF FIGURES (.CONTINUED)
PAGE
37 Team Area Route Map, Alternative I:
Five-Day Collection; Five-Day Work Week;
Twice-a-Week Pickup; Three-Man Crew 126
38 Team Area Route Map, Alternative II:
Four-Day Collection; Four-Day Work Week;
Twice-a-Week Pickup; Three-Man Crew 127
39 Team Area Route Map, Alternative III:
Four-Day Collection; Five-Day Work Week;
Twice-a-Week Pickup; Three-Man Crew 128
40 Team Area Route Map, Alternative III-A:
Four-Day Collection; Five-Day Work Week;
Twice-a-Week Pickup; Two-Man Crew 129
41 Team Area Route Map, Alternative IV:
Five-Day Collection; Five-Day Work Week;
Once-a-Week Pickup; Three-Man-Crew 130
42 Team Area Route Map, Alternative IV-A:
Five-Day Collection; Five-Day Work Week;
Once-a-Week Pickup; Two-Man Crew 131
43 Annual Savings Comparison of Six Waste Col-
lection Alternatives 137
44 Truck Area Route Maps for Team I Mon-Thur
Collection, Alternative III-A 140
45 Truck Area Route Maps for Team I Tue-Fri
Collection, Alternative III-A 141
46 Truck Area Route Maps for Team II Mon-Thur
Collection, Alternative III-A 142
47 Truck Area Route Maps for Team II Tue-Fri
Collection, Alternative III-A 143
48 Truck Area Route Maps for Team I Mon-Tue-Wed
Collection, Alternative IV 144
49 Truck Area Route Maps for Team I Thur-Fri
Collection, Alternative IV 145
50 Truck Area Route Maps for Team II Mon-Tue-
Wed Collection Alternative IV 146
51 Truck Area Route Maps for Team II Thur-Fri
Collection, Alternative IV 147
52 Example, Citizen Notification Map for
Mon-Tue-Wed Collection, Alternative IV 148
^x
-------
LIST OF TABLES
PAGE
Table
1 Public/Private Sector Collection Comparison 47
2 Manpower Distribution by Job Categories 48
3 Demographic Characteristics By Race 58
4 Correlation Coefficients of Personal
Characteristics and Measures of
Absenteeism ' 60
5 Correlation Coefficients of Previous
Experience Characteristics and Measures
of Absenteeism 62
6 Correlation Coefficients of Personal
Characteristics and Measures of Absen-
teeism Among White Employees 63
7 Correlation Coefficients of Previous
Experience Characteristics and Measures
of Absenteeism Among White Employees 65
8 Correlation Coefficients of Personal Char-
acteristics and Measures of Absenteeism
Among Black Employees 66
9 Correlation Coefficients of Previous Experi-
ence Characteristics and Measures of
Absenteeism Among Black Employees g-,
10 Parking, Traffic, and Delay Index by Area j-
11 Waste Collection Activity Codes on
12 Original Field Data Summary g-,
13 Adjusted Field Data Summary 09
14 Work Classification, Frequency of Occurrence g"
15 Summary of Historical Field and Time Data
for 1442 Blocks 86-
16 Collection Times, Riding 93
17 Collection Tines, Walking 94
18 Classification of Blocks 105
19 Comparison of Waste Collection Alternatives 123
-------
ACKNOWLEDGEMENTS
This study was completed by Professors Richard L. Shell, PE7
and Dean S. Shupe, PE, College of Engineering at the University
of Cincinnati, Cincinnati, Ohio. Mr. Oscar W. Albrecht, Solid
and Hazardous Research Division, Municipal Environmental Research
Laboratory, Environmental Research Center - Cincinnati, served as
Project Officer.
The authors acknowledge the cooperation of Ray C. Trenkamp,
Superintendent of Public Works, Jack Brimbery, Assistant Super-
intendent, and the Public Works staff; Bernard A. Grimm, Mayor,
and the other City of Covington, Kentucky Commissioners, Paul
H. Royster, City Manager, Harry Patterson and other staff mem-
bers; Al Van Hagen, Business Agent, and Stanley S. Harmon,
President, District Council No. 51, the American Federation of
State, County, and Municipal Employees, AFL-CIO, and the men of
its Local 237. Acknowledgement is also extended to all members
of the UC research team with special thanks to Caroline Boyer,
Satish Chandra, Ved Malhotra, Paul Popp, Ron Shebanek, and the
typing support staff for their effort.
XT,
-------
1 OVERVIEW AND BACKGROUND
SUMMARY AND CONCLUSIONS
Introduction
Municipal governments, caught in the continuing squeeze of
inflation, must provide labor-intensive services from a rela-
tively fixed income base. The magnitude of the problem is
illustrated by recent Commerce Department data as shown in
Figure 1. The collection of solid waste is a major municipal
function offering manifold opportunities for productivity im-
provement. Historically, collection has been characterized by
high manpower costs. Typically, about three-fourths of solid
wastes costs are required for collection labor (Figure 2},
COLLECTION
CAPITAL
DISPOSAL
CAPITAL
DISPOSAL
MANPOWER
1970 71 72 73 74 ' 75
Source: U.S. Commerce Department
FIGURE 1. STATE AND LOCAL GOVERNMENT
BUDGET SURPLUS/DEFICITS
COLLECTION MANPOWER
71.2%
Source:
FIGURE 2.
Battelle Research Outlook
Volume 3, Number 3
A BREAKDOWN OF COSTS TO
COMMUNITIES FOR REFUSE
HANDLING
1
-------
While it is predicted that new technology developments will
increase waste collection productivity, systems in the foresee-
able future will remain highly labor intensive. Dramatic
changes that reduce the labor requirement, such as sewer trans-
port of solid wastes, are not likely to occur for some time.*
The need is clear for increasing the productivity of human
resources.
Objective
One method to increase human productivity is to provide
positive incentives for performance. The objective of this
project is to determine the feasibility of time and wage incen-
tives for municipal solid waste collection/disposal personnel.
Problem Statement
The problem of developing a wage incentive program for
solid waste workers is twofold. The first requirement is
technical — to accurately compute work content for a given
collection method. The second aspect is the behavioral problem
associated with political constraints, individual motivation
and job performance, and human interaction (e.g., citizens,
city management, union/workers).
Report Overview
The Report consists of seven major sections. Section 1
provides general background information and an overview. Sec-
tion 2 addresses wage incentive systems. The Section reviews
classical direct wage incentive plans and their current appli-
cation in industry. Wage incentive programs for public em-
ployees in the United States are surveyed, and a prototype in-
centive program for solid waste workers is structured.
Sections 3 and 4 are concerned with behavioral problems
relating to incentives. Section 3 reviews motivation and per-
formance as it relates to job satisfaction, and presents a
method for selecting collection crews/teams through sociometric
analysis. Section 4 describes personal characteristics of
solid waste workers. Causes of absenteeism are identified, and
relationships developed between absenteeism and worker demogra-
phic characteristics.
*Albrecht, O.W., and Oberacker, D.A.,"Sewer Transport of House-
hold Refuse, A Replacement For The Refuse Truck," News of En-
vironmental Research in Cincinnati, U.S. Environmental Protec-
tion Agency, May 9, 1975.
-------
Section 5 discusses the application of work measurement
techniques and the development of time standards for waste col-
lection activities. Section 6 describes the computerized data
bank which has been constructed on a stop-by-stop basis for the
entire test city. The major computer programs and their capa-
bilities are outlined.
The results of Sections 5 and 6 are utilized in Section 7
to develop waste collection truck area routes. Six alternative
truck area route plans with team time incentives have been
designed for the test city. Nonmarket and cost-savings compari-
sons of the six alternative plans are presented. Two implemen-
tations are described. The alternative plan first implemented
(Alternative III-A} maintained twice-a-week frequency and re-
duced crew size from three to two workers. The second imple-
mentation (Alternative IV) provided once-a-week collection with
three-worker crews. Annual savings of the first implementation
were approximately $113,000. The second implementation which
occurred eight months later, realized an additional $112,000
annual savings ($225,000 total or 38 percent of the original
budget).
Conclusions
The following summarizes major conclusions of this project:
1} A wage incentive program for municipal solid
waste collection/disposal personnel is feasible
and technically possible. In any incentive pro-
gram, private or government, human maturity and
integrity are required of all participating
groups. In private industry, the incentive pro-
gram involves only management and workers/unions
while in contrast, municipal government is politi-
cally more complex. A multiplicity of groups
have vested interests in municipal operations,
i.e., the citizens, city commissioners, mayor,
city manager, subordinate administrators, and the
workers/unions. The management function is usually
more diffuse and transitory than in the private
sector. No single decision-making authority
exists because typically municipalities operate
with the triumvirate of the commission, mayor, and
city manager. The complexity is further compound-
ed by legislative and civil service restrictions,
2) Increased productivity and substantial cost savings
may be realized through proper design and imple-
mentation of time and monetary incentive programs.
In the test City, annual savings of $113,000 (19
percent of budget) resulted from the new collec-
-------
tion system utilizing time incentives. In addi-
tion, business collection services were expanded
to a larger number of customers, and a new large
item pickup service was added for residential and
business customers. The implementation of wage
incentives would realize additional cost savings.
3) Management's ability to compute work content is
necessary if it is to measure efficiency and to
respond effectively to changes influencing waste
collection, e.g., changes in collection equipment,
method, or frequency. To eliminate the difficul-
ties inherent with using a 'base year' in deter-
mining incentives, the ability to compute work
content is mandatory.
4) Time-predictive models for work content must be
accurate yet flexible and easy to apply if they
are to be accepted and implemented on an on-going
basis by public works personnel. These models
must be based on work measurement analysis of the
collection/disposal methods. Historical truck
time-out and time-in data is not adequate because
they do not necessarily reflect the amount of
time spent working.
5) In addition to the work measurement analysis, de-
tailed waste generation information is required
for the time-predictive models because of the im-
pact of waste volume on work content. Such de-
tailed information may be obtained either from a
waste predictive model or extensive field surveys.
Since no adequate waste predictive model is now
available, the present investigation required a
stop-by-stop field survey.
6) In assignment of collection truck crews, the de-
lineation of route areas is most crucial, i.e.,
the work content of the route area assigned to an
individual truck crew must equal a standard or
incentive day.
7) Sequential routing within the assigned area is
best accomplished by public works management and
collection personnel utilizing their experience
and knowledge of the collection areas. Typically,
collection areas consist of only a few square
blocks, thus easily permitting heuristic design.
Also, most motivation and job performance inves-
tigations show that workers perform at higher
overall productivity levels if they have been in-
volved in some design and planning of their jobs.
-------
Therefore, theoretical modeling of the coll-
ection sequence, e.g., the Chinese Postman,
Eulerian Tour, and Traveling Salesman algo-
rithms have little practical value.
8) Worker performance will be improved with
proper job design and crew selection.
9) Worker job satisfaction will be enhanced with
improved motivation and performance.
10) Certain personal and previous experience
characteristics indicate worker absenteeism
patterns for waste collection, e.g., age,
number of dependents, previous illness, and
previous employment.
RECOMMENDATIONS FOR FUTURE RESEARCH
The following projects should be considered for
future research:
1) The demonstration of wage incentives for
waste collection based on collection work
content.
2) The development of a prototype technical
support system to assist solid waste man-
agement in initiating desirable changes.
The system would consist of three major
elements: First, the establishment of a
block-by-block data base, second, the for-
mulation of additional models for predict-
ing collection/disposal work content and
overall operating costs, and third, the
design and implementation of a management
information system to provide on-line
capability through computer-linked termi-
nals or mini-computers in the public works
offices.
3) The identification of waste generation
predictors to forecast the volume of wastes
emanating from specific geographic areas
on an on-going basis.
4) The development of work standards for var-
ious collection methods and equipment with
particular emphasis on emerging technologies
-------
THE SOLID WASTE OPERATING SYSTEM IN COVINGTON, KENTUCKY
The City of Covington, Kentucky, in the Metropolitan Greater
Cincinnati area, served as the test city for this project. As a
mid-American city with a 1970 Census population of over 50,000,
Covington solid waste collection/disposal operation is represen-
tative of medium size U.S. cities with respect to methods and
equipment, job categories, climate, topography, socioeconomic
characteristics, and union-municipal relationships.
Solid waste collection and disposal in Covington is performed
by the Solid Waste Division of the Department of Public Works
housed in the Municipal Garage (Figure 3). Collection is
accomplished by truck crews using rear packers as illustrated in
Figures 4 and 5. Citizens are responsible for curbside setout,
and typically use cans and bags for containers (Figure 6). Until
recently, all solid waste was disposed of at a sanitary landfill
in south Covington. In early 1975, the City opened a transfer
facility located near the Garage, with final disposal contracted
to a neighboring county landfill.
The collection system in operation at the beginning of this
project had developed historically with little modification over
the past two or three decades. The resultant effect was that the
existing routes were not balanced from the standpoint of either
time or quantity of waste collected. The workers were required
to complete an eight-hour day independent of actual time required
for collection.
POLITICAL CONSTRAINTS
The political constraints existing in municipal government
are more complex than typically found in private industry -
These constraints affect not only costs but also restrain free-
dom of action in developing, implementing, and maintaining an
incentive program. In some cities, the political environment
may be so difficult that incentives are not feasible.
Political constraints may be categorized as follows:
Multiplicity of Interested Groups
Many groups have interests in and impact on the operation
of a municipality. These groups include:
1} Citizens: individuals, organized special interest
groups Ce.g., Chamber of Commerce, neighborhood and
civic organizations).
-------
Figure 3. Covington Municipal Garage
ON
AN
11,1,
:i
."•-. u
|f TF'lf
' I ' UiL
p
f-T
^ »4
'
;
e » * i
'!
-;
Figure 4. Collection Truck Crew
-------
ni
. •
*
I
HJ'.f KTO OU! CITY '
•; '.. 'T
.^..^^. . . „ ..», »MU., . ... '
Figure 5. Rear Packer Truck, 18 Cubic-Yard
i.
•
i IH I
llllllli-1
'-
,^-
'
»-*-•"'
* ^^
r- - ..—17V» ; ,. f-**- - P^-HH ,««|^,,j PP^JT, j»
1 . - "'" ' V* t'
Uy 1J '
-• .^ f
•'• •>. ij\ >>-^r. i
• •"" '< • 'Ji
1 ' •» A* M:~^,^^
' '-'W; «W'rr-i ,-'' "''
WF- ' :"'' -• '..
I
.• ^
Figure 6. Curbside Setout
-------
21 City management: mayor, commissioners, city manager,
department heads, and subordinate administrative
personnel.
3). Union/workers: individual employees, different bargain^-
ing groups, and workers excluded from incentive pro-
grams .
Characteristics of Management
In contrast to a private corporation, municipal management
is often diffuse in its decision-making activities and transi-
tory in leadership responsibility. There is no single overall
authority in the typical city. Major decisions are usually
influenced by at least several of the groups listed above. The
city manager serves at the discretion of a majority of the com-
mission. The commission members are elected by the citizens and
are influenced by public opinion as expressed individually or
through organized special interest groups. Frequently, the
unions are politically active, and exert strong influence on
public opinion and election outcomes. Meanwhile, city depart-
ment heads, while organizationally reporting to the city manager,
usually operate with a sense of independence and security pro-
vided through the civil service system.
Because of the nature of the appointment and elective pro-
cess, city managers and commissioners generally experience a
high rate of turnover, resulting in short-term accountability.
Consequently, much time is expended in the "learning" process,
with efficiency reduced, and long-range planning impaired.
Legislative Constraints
The successful planning, implementation, and maintenance of
a wage incentive program is also constrained by numerous legis-
lative restrictions. Examples include:
11 Civil service regulations governing personnel policies,
e.g., hiring and layoff, job bidding, and wage levels.
2) State laws restricting the right to strike or regulat-
ing bargaining, e.g., Ohio Ferguson Act and the New
York Taylor Law.
31 Laws specifying length of work day or denying payment
of incentive bonuses.
-------
2 INCENTIVE SYSTEMS
INTRODUCTION
Among the major problems confronting an organization is the
improvement of productivity through more efficient use of lim-
ited resources. While this problem is shared by both industrial
and governmental organizations, it is particularly important to
a municipality as it is pressed to maintain its service-oriented,
labor-intensive functions in the face of inflation while on a
relatively fixed income base.
One approach to the problem of increasing productivity is
to motivate employees to increase their production either through
increased effort and/or improved methods. A unit output of pro-
duction may be a tangible physical product such as a solid state
electronic circuit board, or a less tangible unit such as number
of arrests, or building inspections.
One method for motivating employees is to compensate them
for increased productive output. Any compensation offered for
improved performance or behavior is, in a broad sense, an -in-
centive .
Incentive plans can be divided into three broad categories:
direct monetary, indirect monetary, and non-monetary.-'-* Under
a direct monetary plan, each employee is compensated directly
for his or her output or increased output. Direct plans can be
either individual or group. Under the group plan, each member
of the group is compensated an equal percent of bonus for the
group's increased output.
Under indirect monetary plans, the employee's compensation is
not a direct function of his individual or group output. Exam-
ples of indirect monetary plans include profit sharing, fringe
benefits, and retirement benefits. Non-monetary plans do not
involve any type of payment or other financial renumeration.
Rather, they provide other benefits such as job enrichment,
free time, or better working conditions to be discussed later
in Section 3.
* References and footnotes at end of Section,
10
-------
Incentive plans are not new. The Chaldeans developed the
principle of the incentive wage plan in 400 B.C.2 Piece work
payment, payment for each unit of output, has existed for cen-
turies. The trade guilds of the Middle Ages set standards for
quality and quantity. Modern wage incentive plans were devised
in the late nineteenth and early twentieth centuries.
The use of time study techniques to set standards for wage
incentives was introduced by Frederick W. Taylor. Taylor pre-
sented the results of his studies in 1895 and advocated high
wages associated with high productive output. Methods work
studies were pioneered by the Gilbreths in the 1910's.
REVIEW- OF CLASSICAL DIRECT MONETARY INCENTIVE PLANS
In order to establish a proper perspective for a solid
waste wage incentive program, the major incentive plans are
briefly reviewed below.
Piecework
Straight piecework is the oldest and simplest form of in-
centive payment systems. Under piecework, the worker is paid
a fixed monetary amount for each piece produced. There is no
floor guaranteed wage. Direct labor costs are fixed at a con-
stant level, at all levels of output. Straight piecework is no
longer used in the United States due to federal minimum wage
legislation.
Manchester Plan
The Manchester Plan combines a piece rate with a guaranteed
minimum time wage. The Manchester is one of the most common forms
of incentives in industry today due to its simplicity. The plan
offers an incentive for management to keep production running
smoothly due to the minimum wage floor.
Standard Hour Plan
The Standard Hour Plan or 100 percent Time Premium Plan is
similar to the Manchester Plan. Both have a minimum wage
guarantee and both pay a 100 percent premium over standard.
The main difference in the plans is that under the Manchester
Plan, the rate is price'per piece; while under Standard Hour
the rate is time per piece. The worker is paid for standard
hours worked rather than actual hours worked. If the worker
produces ten hours worth of output in an eight hour day, he is
paid for ten hours. The Standard Hour Plan is used extensively
throughout manufacturing industries.
11
-------
Halsey Premium Plan
The Halsey Premium Plan was developed in 1890 before the
publication of Taylor's time study techniques. Output standards
were based on foreman's estimates or on averages of past perfor-
mance. The time value of production in excess of standard was
shared by management and the worker, usually at a fifty-fifty
rate. Since standards were set by historical data rather that
time study, they were rather loose and inconsistent. The fifty-
fifty division of value added was incorporated to protect manage-
ment from runaway rates.
Rowan Premium Plan
The Rowan Premium Plan is similar to the Halsey Plan in many
respects. The main difference is that the Halsey Plan compensates
the worker at a constant rate, while the Rowan Plan compensates
at a decreasing rate. The employer was protected to a greater
extent from loose standard rates. However, the decreasing rate
scale is more complicated for the employees to understand.
Taylor Differential Piece Rate Plan
Taylor believed that lower unit production costs could be
quickly achieved if high procedures were generously rewarded
and low procedures were penalized. The work standards under
the Taylor Plan were set by time and methods study.
Under the plan, two piece rates were assigned to each job.
A higher rate, higher than the normal rate, lower than the normal
piece rate, was paid to workers who did not achieve the stan-
dard. The differential occurred at one hundred percent of the
standard rate. The Taylor Differential is not used in this form
today as it penalizes the sub-standard worker. Variations of
the plan do exist with a guaranteed earnings floor.
Gantt Task and Bonus Plan
The Gantt Plan is very similar to the Taylor Plan except
that a basic day rate is guaranteed. Also, the Taylor Plan
rate is expressed in standard time per piece.
Emerson Efficiency Bonus Plan
The Emerson Plan g-uarantees a fixed base rate and incor-
porates an empirically determined sliding scale of bonuses
to sub-standard workers, beginning at two-thirds of standard
efficiency. The standard is set high and the sixty-six per-
cent efficiency standard was considered to be the normal rate,
on the average.
12
-------
Emerson Plan bonuses range from 0.25 percent at sixty-six
percent of efficiency to twenty percent at rates above one
hundred percent of efficiency. The Emerson Plan enables new
employees or apprentices to earn an incentive from the beginning
of their employment.
Bedaux Point System
The Bedaux System reduces all work to a standard time.
Each operation is time studied and rated by points. Each point
represents the normal amount of work of one operator in one min-
ute of time. A minimum pay rate is guaranteed and the premium is
divided between direct and indirect labor, usually at a ratio
of seventy-five percent to the former, and twenty-five percent
to the latter.
Most of the above^plans are variations of the others. The
main difference in the plans is how the rate is expressed, in
price per piece or standard time per piece. Figure 7 is a
graphical representation of the various plans and their compen-
sation rates.3
Group Incentive Plans
The most common type of group incentive plan is profit
sharing. Profit sharing is an indirect form of incentive, and
therefore does not have the advantage of being transferred
directly and immediately into the worker's paycheck. Non-profit
organizations, of course, can not participate in this type of
program.
Group incentive plans have many advantages over individual
incentive plans: clerical and inspection systems are simplified,
time study and cost systems are simplified, the spirit of team-
work increases mutual helpfulness, reduces labor turnover, and
decreases idle time, and indirect workers can be included.4
On the other hand, the larger the group, the less the indi-
vidual responds to the plan and a greater degree of group leader-
ship and cooperation is required. Many of the group plans are
indirect incentive plans, among these are the Kaiser Steel,
Scanlon and Rucker plans.
Kaiser Steel Sharing Plan
The Kaiser Steel PlanS grew out of a strike settlement in
1959. The Plan guaranteed employment to employees displaced by
technology or changes in work practices. The employment stan-
dard was based on the number of employees needed to produce a
ton of steel in the base year 1961. Natural attrition of em-
ployees would reduce employment to actual production requirements
13
-------
w
CO
H
g
W
cu
s
H
w
Q
DAILY PRODUCTION IN PERCENT OF STANDARD
Figure 7. Earning .Opportunities Under Wage Incentive Plans
14
-------
The Plan incorporated a cost reduction incentive. Labor
and operating costs per ton of steel were computed and used as
a standard. Total savings in a subsequent period were reduced
by capital investment and the balance was shared at the rate of
32.5 percent for employees and 67.5 percent for management.
The Plan was very successful in its early years. In the
first year of Plan operation, bonus payments averaged about
fifty cents an hour. In the third year, however, bonus pay-
ments averaged eighteen cents an hour and employee discontent
with the system grew. Kaiser revised the bonus and liberalized
the computation method in 1967.
Scanlon Plan
The Scanlon Plan6 is similar to the Kaiser Plan and was also
designed to reduce costs in a steel mill. The Plan is a value-
added plan. The incentive formula is a percentage relationship
between value added to raw materials (expressed by total sales
values) and total payroll.
Several principles are explicit in the Plan:
1) Major participation is essential
at all organizational levels.
2) Productivity or efficiency gains are
to be paid on a regular basis, the
amount to be determined by the
success of the organization.
3) The Plan should be implemented within
the context of the collective bargaining
agreement, but maintained separately
after installation.
The bonus was to be distributed seventy-five percent to
all employees and twenty-five percent to the firm. Twenty-
five percent of the bonus was held until the end of the year to
cover any deficit period.
The base ratio, under the Plan, equals the sum of the fac-
tory payrolls, salaries, holiday, and vacation pay divided by
net sales, plus or minus changes in inventory.
The Rucker Plan is similar to the Scanlon Plan. The main
difference is in the analyses of the standards of efficiency
Both the Scanlon and the Rucker Plans established employee
committees to make suggestions and to help in coordinating the
plans.
15
-------
Memorial Hospital MERIT Plan
The MERIT Plan7, an acronism for Memorial Employees Retire-
ment Incentive Trust, is an example of an indirect incentive
plan for a non-profit organization.
The criterion used in the plan was savings in budgeted
expenses. The savings were placed in an employee retirement
trust fund.
A base period of 1958-1960 was established using an effi-
ciency base of controllable expenses divided by total operating
revenue. An efficiency improvement percentage is computed by
subtracting the current years percentage from the base period.
The hospital's contribution to individual earnings of employees
is determined by the ratio of their earnings to total payroll.
Other Group Plans
The above group plans are all indirect in nature. The in-
crease in productive output or in cost savings by an individual
employee or group canot be translated directly into increased
earnings. The above plans do, however, include indirect as well
direct workers in the plan.
Any of the individual direct incentive plans enumerated
earlier can be extended to form a group plan. The group should
be homogeneous and concerned with a single defined operation,
e.g., solid waste collection. Each employee shares equally in
the incentive bonus calculated on the output of the group.
Piece-rate and Standard Hour plans are the most common direct
group incentive plans.
USE OF DIRECT WAGE INCENTIVES IN INDUSTRY
A U.S. Government survey of 574 firms with wage incentives
showed an average decrease in unit costs of twelve percent, an
increase in takehome pay of seventeen percent and an increase in
productivity of thirty-eight percent.8
The above results notwithstanding, an earlier Factory
Magazine survey showed the application of both wage incentives
and work measurement to be decreasing in manufacturing indus-
tries. 9 The magazine surveyed 751 manufacturing plants in
twenty-one industries and compared the results with a similar
survey conducted in 1959. In 1959, sixty percent of the plants
used work measurement and fifty-one percent used wage incentive
payment systems. In 1965, only forty-eight percent of the firms
used work measurement and forty-one percent employed wage incen-
tive systems. Small manufacturing plants (500 or fewer
16
-------
employees) moved away from both work measurement and wage incen-
tives. Large plants continued steady in their use of incentives
but increased work measurement applications. The survey further
showed that union participation in the administration of incen-
tives had fallen off. Of the plants using incentives, however,
ninety-three percent reported a reduction in operating costs,
seventy-seven percent reported an increase in morale and eighty-
seven percent reported that incentives helped supervisors.
Nearly twice as many plants reported quality increases as re-
ported quality decreases.
While wage incentive use has been decreasing in manufac-
turing especially in the smaller plants, there has been an in-
crease of incentive use in service related activities. The pay-
off of a properly administered wage incentive system is substan-
tial. A trend currently exists toward group incentives and away
from individual incentive plans as they are easier to administer
and increase worker morale through teamwork.
SURVEY OF INCENTIVE PROGRAMS FOR PUBLIC EMPLOYEES
Although monetary incentives have been widely used in
manufacturing industries for several decades, their application
to the service-oriented sector of the economy (including most
governmental activities) has been limited. Accompanying the
recent shift in the United States economy from one of manufac-
turing to service has been a growing interest in the use of in-
centive programs for service-oriented public employees. The
diversity of current incentives for government employees is
illustrated in Figure 8 recently published by the National Com-
mission on Productivity and Work Quality.^0 The broad categor-
ies are not necessarily distinct. For example, a wage incentive
program for solid waste personnel could involve the concepts of
piece-work (wages a direct function of work output), shared
savings (cost savings shared by the public entity and the ap-
propriate employees), task system or time incentive (employees
free to leave work following completion of assigned collection
route), productivity bargaining (sharing formulas subject to
negotiation), and work standards for measuring work output.
The Commission reports that 1) the application of piece-
work incentives in local government is very limited but ex-
pected to increase-'--'-, 2) work standards are rarely used as a
basis for monetary incentives12, and 3) productivity bargaining
is relatively new to public employees primarily because more
explicit work standards are needed.13
A survey of monetary incentives currently in use or recent-
ly attempted by state and local governments for sanitation per-
sonnel is provided below. The listing excludes cash awards for
outstanding service or suggestions.
17
-------
00
Local Government Usage of Employee Incentives: A Summary of Survey Results from 509
Jurisdictions as of August-December 1973 *
Incentive
Educational Incentives
Output-Oriented Merit
Increases
Task Systems
Suggestion Awards
Attendance Incentives
Variations in Working
Hours
Safety Incentives
Job Enlargement
Work Standards
Performance Targets
Performance Bonuses
Productivity Bargaining
Competition & Contests
Shared Savings
Piecework
Others '
None
Total Items Reported
COLUMN 1
Cities
25-50,000
No.
of
Cities
Re-
porting
Use
22
17
17
6
7
6
4
2
2
4
0
2
1
0
0
0
7
90
% of
10
Respond-
ents
55
43
43
15
18
15
10
5
5
10
0
5
3
0
0
0
18
—
COLUMN 2
Cities Larger
than 50,000
No.
of
Cities
Re-
porting
UH
218
135
131
93
85
77
73
54
37
41
27
20
14
3
3
23
30
1,034
% of
315
Respond-
ent*
69
43
42
30
27
24
23
17
12
13
9
6
4
1
1
7
10
—
COLUMN 3
Counties Larger
than 100,000
No.
of
Counties
Report-
ing
Use
63
61
9
29
26
33
14
17
27
10
5
5
0
1
0
7
47
307
% of
154
Respond-
ents
41
40
6
19
17
21
9
11
18
7
3
3
0
1
0
5
31
—
COLUMN 4
Total of all Cities
and Counties
(Col. 1 + Col.
2 + Col. 3)
No.
of
Cities/
Counties
Report-
ing
Use
303
213
157
128
118
116
91
73
66
55
32
27
15
4
3
30
84
1,431
% of
50*
Respond-
ents
60
42
31
25
23
23
18
14
13
11
6
5
3
1
1
6
17
—
COLUMN 5
Evaluation of the
Incentive
Programs
No.
of
Re-
ported
Evalua-
tions
14
22
17
8
12
19
5
4
0
0
4
2
1
2
1
0
—
Ill
% of
Total
No.
of
Pro-
grams
Re-
ported
(Col. 5 -=-
Col. 4
7
10
11
6
10
16
6
6
0
0
13
7
7
67
33
0
—
8
1 A total of 772 survey questionnaires were mailed: 52 to cities 25-50,000 in population, 408 to cities of more than 50,000, and 312 to
counties of more than 100,000 population. 76.9 percent of these jurisdictions responded.
2 This includes career development programs, nonmonetary rewards and recognition (e.g., service pins, banquets), deferred compensation,
attendance at seminars, and negative incentives (e.g., denial of step increases).
Source: National Commission on Productivity and Work Quality, Employee
incentives To Improve State and Local Government Productivity,
1975, p. 7 ~~ "~
Figure 8. Local Government Usage of Employee Incentives
-------
Sacramento, California
Qualifying employees who accummulate six or more days of unused
sick leave in a single year may choose to receive a partial
cash payment.
St. Petersburg, Florida
The commercial collection crew with the highest weight per load
average receives small monthly bonuses.
Kansas City, Missouri
All field employees in the solid waste division are divided into
seven competitive teams of about 17 employees each. At the end
of each 6-month period, each member of the team with the fewest
total number of preventable vehicular accidents plus preventa-
ble personal injuries wins a $20 cash bonus.
Phoenix, Arizona
All nonsupervisory and first-level supervisory personnel of the
sanitation department were divided into 29 groups. Every mem-
ber of a group accident-free for 28 consecutive days received a
$5 cash award. After a substantial decline in reported acci-
dents the first year, the rate leveled off and subsequently be-
gan to rise. After discontinuance of the incentive in December
1973, accident rates climbed to their preincentive level. Cur-
rent management does not favor paying employees for good safety
practices.
Washington, D.C.
In 1971 contract negotiations, sanitation workers agreed to an
increase in the standard day's work in exchange for a 2 percent
pay increase. In addition, the contract provides for increased
participation by sanitation employees through a Productivity
Committee comprised of labor and management representatives.
The Committee meets monthly to resolve labor-management con-
flicts and receive employee complaints.
Council Bluffs, Iowa
During 1974 negotiations with a local bargaining unit organized
within the public works department, City management required
that all future salary and benefit increases would be contin-
gent on maintenance of current productivity standards. Speci-
fication of productivity work standards is planned following
legalization of collective bargaining (July 1975).
Lake Charles, Louisiana
In 1973, as part of a new union contract, the City agreed to
share with its sanitation employees any savings in workman's
compensation insurance refunds resulting from reduced accident
19
-------
rates. The savings realized are being shared with, the employees
in the form of a permanent 5,5 percent annual merit increase
effective May- 19.74,
Detroit, Michigan
As a result of negotiations precipitated by the introduction of
larger packer trucks, the City of Detroit and its sanitation
workers agreed in July 1373 to share resulting savings "50-50"
between the City and the workers. Nearly everyone in the san-
itation department directly involved in solid waste collection
Cover 1,000 individualsl are included in a single bonus group.
The bonuses are apportioned among the group members according
to time spent on waste collection activities. The total
amount of the cash bonus to be distributed each quarter is cal-
culated from a rather complex formula (Figure 9). which weights
four performance factors: man-hours per ton, overtime reduc-
tion, routQ completion, and cleanliness. Early bonuses averaged
5 and 6 percent of salaries, declining somewhat in more recent
quarters. City officials have reported that individual incen-
tive is reduced somewhat by the largeness of the bonus group.
Flint, Michigan
In September 1973, the City and the local union ratified a con-
tract which introduced both a time incentive or task system and
an annual monetary bonus for cost savings. According to Flint
officials, a prerequisite of both the task system and shared-
savings plan is that collection routes be closely balanced
among all crews and designed to represent a fair day's work.
Between August 1973 and January 1974 Flint's routes were
equalized using heuristic routing techniques. The new task sys-
tem permits a crew to go home after six hours if its route is
completed. If assigned to assist another crew, overtime is
earned past the six hours. All members of the waste collection
division including supervision (about 65 individuals} are mem-
bers of the monetary incentive group, and share equally in any
earned annual bonus. The bonus is based on a formula involving
overtime savings, quality, and reduced costs per ton (Figure 10).
In renewing the contract agreement, provision was added for
reducing the bonus on an individual basis for unexcused absences,
and the addition of $2000 to the bonus pool for each employee
reduction below a base level. The program has been generally
successful, but some problems arose with respect to employees
excluded from the incentive. City and union officials recommend
that jurisdictions comtemplating such an incentive program
should 1) gather the necessary baseline data before designing
the program, 2} involve the employees in plan formulation, and
3} keep it simple.
20
-------
Shared Savings Formula for Sanitation Workers: Detroit, Michigan
The quarterly productivity bonus earned by the sanitation employees is computed from
the following formula:
Total Bonus for Employees='/i X Bonus PoolX Productivity Index
Bonus Pool: Maximum potential savings for the first year was estimated in advance at $2.3
million. This sum was allocated among the four quarters of the year to form a bonus
pool for each quarter. Estimated savings were predicated on completely eliminating
unscheduled overtime and a manpower savings through reducing the number of routes.
Productivity Index: The productivity index (PI) converts the potential savings (bonus poo!)
into an estimate of savings actually realized. This coefficient, which can vary between
0 and 1, numerically weights and integrates the four factors deemed of greatest importance
to improving collection:
PI=0.5x(Paid Man-Hours Per Ton Factor) + 0.2X(Overtime Reduction Factor) + 0.2
X(Route Completion Factor)+O.lx(Collection Quality Factor)
Paid Man-Hours Per Ton Factor: This is computed from the following formula:
/1973 Average Man-Hours Per Ton\ /Average Man-Hours Per Ton for \
\ for the Quarter / \the Corresponding Quarter in 1972/
(Average Man-Hours Per Ton for\ /Optimal Man-Hours Per Ton\
the Corresponding Quarter in 1972/ \ for the Quarter /
Daily reports on the paid man-hours per ton for each collection area are averaged for
an entire quarter. "Optimal" performance is determined by averaging the lowest 1
percent of all daily man-hours-per-ton figures generated in the corresponding quarter of
the previous year.
Overtime Reduction Factor: The formula for calculating this factor is:
(Average Overtime for the Previous \ /Overtime in Corresponding\
3 Years / V Period of 1973 /
(Average Overtime for the Previous 3 Years)
Only unscheduled overtime is included; overtime to make up for holidays is not counted.
Route Completion Factor: The contribution of route completions to the final productivity
index is computed from the following formula:
/Percent of Route Completions f°r \—90 percent
\ the Current Quarter /
100 percent—90 percent
An optimum of 100 percent route completions is sought However, 90 percent was
selected as the minimum at which positive credit would begin to be earned. Routes must
be completed without use of overtime in order to be counted.
Collection Quality Factor: This factor, measured by the cleanliness of the collection routes,
is included to ensure that speedier, more efficient waste collection does not come at the
expense of spills, missed pickups, etc. Since no cleanliness monitoring system has been
set up yet neither positive nor negative contributions are included in the productivity index.
The City is developing a cleanliness rating system based on subjective assessments by
trained inspectors using photographic standards defining various levels of cleanliness.
The total quarterly bonus is converted to an hourly rate by dividing by the total eligible
regular man-hours applied during the quarter. The bonus pool is then apportioned among
participating employees according to time spent on waste collection duties.
Source: National Commission on Productivity and Work
Quality, Employee Incentives To Improve State
and Local Government Productivity, 1975, pp.83,84
Figure 9. Detroit, Michigan Savings Formula
21
-------
Bonus per Person=
Waste Collection Division Shared Savings Formula: Flint, Michigan
jlan is based on the following formula, who:
it performance over the fiscal year:
'/i X Productivity Coefficient X Dollars Saved
The shared-savings plan is based on the following formula, whose components are evaluated
by averaging relevant performance over the fiscal year:
Number of Employees Affected
Overtime Reduction Component * -(-Quality Component 2+Route
Productivity Coefficient= ^ . . _,
Completion Component ••
Dollars Saved=OTS + (ACTXIT)
OTS=Overtime saved, the difference in overtime use between fiscal years 1973 and 1974.
Overtime for snow removal and spring cleanup week is excluded, but other scheduled
overtime (e.g., to make up for holidays) is counted.
ACT=Cost per ton in fiscal year 1973—Cost per ton in fiscal year 1974. Cost per ton is
determined by dividing total direct labor (including overtime) plus equipment costs by
tonnage collected.
IT=Total tonnage collected in fiscal year 1974—Tonnage collected in fiscal year 1973.
Number of Employees Affected=All employees in the waste collection division, including
management (adjusted for partial shares for retired or transferred workers).
1 Overtime Reduction Component (with respect to the average for the past three fiscal years)
0.5 if overtime
0.4 if overtime
0.3 if overtime
0.2 if overtime
0.1 if overtime
s reduced by 25 percent
s reduced by 20 percent
s reduced by 15 percent
s reduced by 10 percent
s reduced by 5 percent
0.0 if overtime does not change
2 Quality Component
0.2 if the number of valid complaints is less than or equal to 5 percent of the number of collection
stops
0.1 if valid complaints number more than 5 percent but less than or equal to 10 percent of the stops
0.0 if valid complaints are greater than 10 percent of the stops
3 Ronte Completion Component
0.3 if 17 of the 20 daily routes are completed without need for overtime
0.2 if 16 routes are completed without need for overtime
O.I if 14 routes are completed without need for overtime
0.0 if less than 14 routes are completed without need for overtime
Source: National Commission on Productivity and
Work Quality, Employee Incentives To Improve
State and Local Government Productivity,
1975, p. 93.
Figure 10. Flint, Michigan Savings Formula
22
-------
A PROTOTYPE WAGE INCENTIVE PROGRAM FOR SOLID WASTE PERSONNEL
Objectives
The major requirements of a wage incentive program are two'
fold:
11 Political; All involved parties - elected officials,
citizens, public works management, and workers/union -
must be agreeable to the concept of time and direct
monetary- incentives. On an on-^going basis, the city
must continue to support the program fairly, e.g. de~
fend the program to the citizens and to municipal em-
ployees not included in the incentive plan, maintain
competitive base earnings, and share cost savings
equally.
21 Technical: All collection route areas must contain
accurately calculated work content. An example of col-
lection route design is included in Section 7,
In addition, a wage incentive program must satisfy the
requirements of three major groups: citizens, management, and
the workers/union. These group requirements are;
Citizens:
11 Pickup must occur on the scheduled day.
2) Frequency of collection must be acceptable.
31 Collection must be completed with minimum littering.
41 Respect must be given to property and privacy, e.g,,
can damage, noise.
Management:
11 Total operating cost must not exceed budget.
2) Level and quality of service should be maintained or
improved.
31 Productivity should be increased. If accomplished
through incentives, the program should be acceptable
to most employees.
Worker/Union:
11 Job security must be guaranteed,
23
-------
21 Wage levels must be competitive with comparable jobs
in the geographic area/ and increase with, the cost
of living,
31 Required work levels must be physiologically reason-
able, and work assignments throughout the group must
be balanced and equitable.
System Constraints
The following constraints are inherent in solid waste col-
lection/disposal operations;
II The daily work assignment is fixed. That is, the
waste should be collected on the scheduled days as
announced to the citizen. This is particularly true
for curbside pickup because of citizen set-out and the
associated litter problems. In addition, the citizen's
collection schedule is relatively inflexible,
2) The daily work content is variable. While the work
assignment is relatively well defined and unchanging,
the work content required for completing the assign-
roent varies monthly, weekly, and even daily due to a
multitude of factors such as the weather, traffic,
equipment breakdown, accidents and illnesses, disposal
delays, and changing waste generation patterns.
3} The work is accomplished by crews, each consisting
typically of a driver and one or two laborers with a
loadpacker truck. With multi-member crews, the collec-
tion method is both variable and complex, generally in-
volving simultaneous activities.
4} Holiday schedules should be planned to provide collec-
tion service for all citizens.
5J The pay and skill levels of the collection personnel
are usually low.
6} The work assignments of certain direct and indirect
labor other than the collection crews are closely re-
lated to direct collection labor, for example, the col-
lection foremen and the landfill equipment operators.
7} Activities of workers and/or management may be re-
stricted by state and/or local laws and regulations.
Tf each collection area is to be picked up consistently on
its scheduled day, provision must be made for handling the
fluctuations that occur in the work content of a collection area
24
-------
from day to day. Management has only two alternatives for
dealing with these variations on a day to day basis: either to
make changes in the manpower and/or equipment assigned to the
task (and these changes must of course be discrete rather than
continuous), or to allow the time required for the task to vary
either into overtime or into "undertime" (in which case the men
may be idle a portion of the day). Generally, municipalities
tend to avoid consistent overtime, choosing instead to permit
the crews to complete their assignments early. If the men are
allowed to leave work on completion of the assignment and are
paid for a complete day, the program provides a time incentive
("task system"). Although time incentive programs are frequently
used and offer certain advantages to both management and workers,
they do require balanced work assignments if the system is cost
effective and fair to individual employees. On a day-to-day
basis, balanced work assignments are difficult to maintain between
individual crews due to uncontrollable factors, especially
sudden equipment failure. On a year-to-year basis, variations
in waste generation patterns tend to develop in individual crew
collection areas thereby requiring updating of the route assign-
ments. An approach used by some larger municipalities to reduce
the inequities between individual crews is to group several
crews together into a team under the field supervision of a fore-
man. The team approach not only provides a mechanism for dealing
with daily fluctuations in the work loads of its member crews
but also tends to average out inevitable changes in waste gener-
ation patterns occurring in a dynamic city, thereby requiring
somewhat less frequent route revision.
General Guidelines
Wage incentive programs for solid waste operations should
be tailored for local conditions by municipal management. How-
ever, certain general guidelines are applicable to all locations.
These guidelines include the following:
1. Management and workers must clearly understand all
essential aspects of the program. To facilitate this
understanding, the program must be straight-forward
and simple.
2. A wage incentive program should also provide time
incentives.
3. Workers/union should have meaningful involvement in the
design and implementation of the program.
4. The program should permit the workers to elect the
level of incentive earnings through selection of
work content assignments.
25
-------
51 The ^incentive group size sliould be 35 small as mana-
gerially feasible, consistent with, system constraints.
61 Time and direct monetary incentives- must be based on
accurate work content determined by work, measurement
techniques,
7) The employees should be guaranteed job security.
81 The connection between incentive pay and actual per-
formance should be direct and clearly understood by the
workers. Incentive earnings should be paid timely,
91 Guarantees of necessary supportive services, e.g.,
backup men and equipment, supervisory assistance, and
field communication equipment, must be included in the
program.
101 The program should encourage regular worker attendance,
minimum overtime, and acceptable quality of service.
Ill Base wage levels for workers and supervision must be
competitive with comparable jobs in the geographic
area, and reflect appropriate cost-of-living increases,
121 Savings should be shared equally between the city and
employees because this arrangement would most likely
satisfy all interested groups.
131 The program should encourage implementation of improved
methods or equipment.
141 The program should not preclude productivity bargaining
between workers/union and management.
151 Attention should be given to properly informing the
public of the benefits of an incentive program.
16} The program should provide for periodic review of work
methods and standards, and incentive earnings.
Recommended Program; Elective Incentive Contract
If these two major requirements for program design are ful-
filled and the guidelines followed, then a wage incentive pro-
gram may be developed that allows for elective participation by
individual work groups. The project results in the test City
strongly indicate that such a program not only would be cost
effective, but also offer high probability of long term success.
26
-------
A program with, elective participation may be defined as an
Elective Incentive Contract (E-ICL program. Fundamental to the
EIC program are the following;
II Collection is accomplished through incentive groups or
teams consisting of approximately three to nine trucks
and their assigned crews under the supervision of a
field foreman,
2) All supportive personnel, e.g., superintendent, mainte-
nance, and disposal, receive an incentive bonus based
on the average of all teams.
3) Each team is assigned a collection route area requiring
an average 6.5-hour standard work day, thereby providing
a 1.5 hour daily time incentive. Team members are paid
for eight hours and are permitted to leave after their
respective team area has been collected.
4) In addition to the 6.5-hour standard work day, individ-
ual teams may elect to contract additional work content
in return for a wage incentive bonus,
To illustrate the EIC program, consider a small solid waste
collection/disposal system requiring two collection teams. Both
teams initially consist of five rearloading packers and drivers,
five laborers, and a field foreman. Team 1 contracts the
standard 6.5-hour work day and receives base salaries without a
w^ge incentive bonus. Team 2 contracts for a 7.5-hour work day
and receives base salaries plus a wage incentive calculated by
the simple equation below:
Wage Incentive _ (Contract Day - Standard Day! 100
(percent) ~ 8 hours
For a 7.5-hour contract day, the computation is:
Wage Incentive _ C7.5-6.51 100 _ -^ 5%
(percent] 8.0
Assuming a 30 percent overhead (^including fringe benefits) , the
manpower reduction savings resulting from the 7.5 hour contract
work day are:
Manpower Reduction Savings = C$200/weekl C1.54} C1.30) =
$400/week
Labor savings to the city is equal to the manpower reduc-
tion savings less bonus payments to team workers, foreman, and
supportive personnel. Bonus payments to the workers would a-
mount to $250 (10 workers @ $25 eachl. Assuming that bonus
payments to the foreman and support personnel amount to $50, the
27
-------
net labor savings to the city would be:
Net Labor Savings
To City " $40Q " $25° ~ $5° = $100/week
In addition to these savings, the city would realize equip-
ment savings associated with the reduction in manpower. For
each crew reduced (2 workers), there is a reduction of one
truck. Assuming a weekly truck cost of $200, the equipment
savings would be:
Equipment = .
Savings -^ ($200/week) = $154/week
In this example, total weekly savings to the city equals
$254, while the total weekly bonus payments to workers (includ-
ing foreman and support-personnel) equal $300. Obviously,
truck and manpower reductions can only occur in integer units.
A second example illustrates how the program would respond
to introduction of equipment improvements resulting in cost
savings with no change in work content. Assume that the ten
rearloaders with two-man crews are replaced by fourteen side-
loaders with one-man crews. This represents a reduction of six
men. The resulting weekly labor savings including fringe bene-
fits would be:
Labor Savings = C$200) (6) (1.3) = $1560/week
Assuming the weekly incremental equipment cost for four trucks
amounts to $800, then the net weekly savings is $760. It is
recommended that the city and the workers share in the savings
from equipment improvements the first year. Following this
time, the city would retain any on-going savings. On this
basis, a $380 equipment implementation weekly bonus would be
distributed among the participating employees. This would a-
mount to over $20 weekly for each employee, or an annual total
individual implementation bonus of over $1000. Since this is a
one-time bonus, it should not be included in the weekly pay
check, but preferably distributed in two payments, e.g., 20 per-
cent paid soon after implementation of the new equipment and the
remaining 80 percent at the end of one year.
Since under the EIC program, the work groups contract to
complete their elected collection assignment, overtime pay is
avoided except for scheduled holidays. Care must be exercised
during implementation of collection improvements to avoid em-
ployee layoffs if possible. Consequently, actual savings may
lag implementation until manpower levels are adjusted through
attrition or reassignment.
28
-------
A__Comparison of the Elective Incentive Contracts with Existing
Programs in Detroit and Flint/ Michigan
Within the last two years, wage incentive plans have been
implemented in Detroit and Flint, Michigan, as described earlier.
These two plans and the proposed EIC have the following similari-
ties:
1) No employee shall be laid off as a result of the in-
centive program.
2) Savings shall be shared between employees and the city.
3) Most waste collection employees including supervision
participate in the incentive.
4) All plans utilize task Ctime incentive) or modified
task systems.
The Detroit plan differs from the EIC in the following
features:
1) The principal measure of productivity in the Detroit
plan is man-hours per ton.
2) A standard day's work is defined as the completion of a
single 25-yard packer route.
3} Bonus is calculated with a rather complex formula.
4) Some employees still receive overtime pay at the ex-
pense of group bonus.
The differences of the Flint plan include the following:
1) The principal measure of productivity in the Flint
plan is cost per ton.
2) The bonus formula is fairly complicated.
3) Some employees still earn overtime, reducing group
bonus.
4) Landfill personnel elected to receive 10£ per hour
base pay increase in lieu of participating in the in-
centive .
5) For each worker eliminated, $2000 is added to the bonus
pool for sharing.
6) Individuals are penalized for absenteeism with reduc-
tion of incentive earnings.
29
-------
7} On renegotiation of the incentive agreement, the
.workers/union were guaranteed a minimum incentive bonus
of $.10 per hour.
Three major differences between the EIC and the Detroit and
Flint plans are:
1) In the EIC, work content is determined from detailed
field data and application of work measurement tech-
niques. Detroit and Flint both base their incentives
on a prior "base" year.
2) The EIC program has a relatively small incentive group
consisting of a small number of truck-crews and a fore-
man. Both 'Detroit and Flint include the entire work
force in a single group.
3) In the EIC, bonuses are paid weekly. Detroit presently
pays quarterly and Flint annually.
EVALUATING AN INCENTIVE PROGRAM
The purpose of an incentive program is to increase pro-
ductivity through the more efficient use of available resources.
Increased productivity can effect two major changes in a solid
waste system. First, improvements can be realized in citizen
service, e.g., increased collection frequency, reduction of
litter, and reduction of incompleted routes. Second, acceptable
service is maintained while lowering annual costs. Consequently,
an incentive program should be evaluated on the basis of its
resulting savings and citizen services provided.
In evaluating savings, the following should be included:
1) The savings resulting from the initial program imple-
mentation. These savings are relatively easy to measure
as they occur during a short time period.
2) The on-going annual equipment and personnel savings re-
sulting from the incentive program. These savings
should be determined by evaluating the current operat-
ing year costs with and without incentives, as opposed
to comparing with a prior base year.
In program evaluation, services must be compared consis-
tently- For example, if littering increases because of hurried
collection to earn an incentive bonus, then real productivity
may not be improved.
Finally, the program must have good prospects for longevity.
It must continue to be economically and politically acceptable
to all concerned parties.
-------
FOOTNOTES
Niebel, B. W., Motion and Time Study, Irwin, Homewood,
1972, p. 605. ~
2
Marriott, R., Incentive Payment Systems, Slaples, London,
1957, p. 18.
Bauroback, C. M. , Structural Wage Issues in Collective
Bargaining, Heath, Lexington, 1971, p. 146.
4
Marriott, p. 66.
Dunn, J. D., & Rachel, F. M., Wage and Salary Administra-
tion: Total Compensation Systems, McGraw-Hill, New York, 1971,
p. 251.
Ross, T. L., & Jones, G. M., "An Approach to Increased
Productivity: The Scanlon Plan", Financial Executive, Vol. 40,
No. 23, Feb. 9, 1972, p. 23-29.
Dunn & Rachel, p. 256-258.
8"Innovation is Changing Old Ideas on Incentives", Industry
Week, Vol. 167, No. 24, July 27, 1970, p. 24-33.
9Schultz, G. V., "Plants' Incentives Slump Badly over Last
6 Years", Factory, Vol. 123, No. 6, June, 1965, p. 68-79.
10National Commission on Productivity and Work Quality,
Employee Incentives to Improve State and Local Government Pro-
ductivity, March, 1975, p. 7.
i:LNational Commission on Productivity and Work Quality,
p. 73.
12National Commission on Productivity and Work Quality,
p. 112.
13National Commission on Productivity and Work Quality,
p. 79.
31
-------
3 MOTIVATION AND JOB PERFORMANCE
INTRODUCTION
Job performance and specifically individual differences in
job performance have long occupied the attention of social science
researchers, industrial engineers, and managers. Early research
effort was directed mainly toward minimizing or eliminating dif-
ferences in job performance through, training and job design.
The investigations by Frederick W. Taylor, Frank B. Gilbreth,
and others were designed to serve the interests of effective
factory management. Their central aim was to reduce human vari-
ability, to make the work process as machine-like as possible
using time-and-motion studies and specialization (the division
of labor). Workers were relegated to the status of physical
resources necessary for production. Little effort was made to
understand why individuals differed in their productivity on
similar jobs.
The view of the worker as merely a physical resource was
abruptly and radically challenged by the findings of the Haw-
thorne studies (Roethlisberger and Kickson, 1939). This was a
major research effort designed to identify the relevance of
situational factors to employee productivity. Since that time,
the study of work behavior has shifted toward an emphasis on
what could be called the "human" side of work. Today, management
is largely concerned with the most efficient deployment and
organization of man and machine. There is almost as much inter-
est in adapting the machine to particular characteristics of the
human operator as in adapting the human being to the machine.1*
Voluminous research literature exists on the technical con-
ditions of work. Both organized labor and industry, as well as
government, spend millions annually in seeking out the most
efficient and beneficial uses of human labor resources. Much of
what is known about human work has become available only during
the last two or three decades, as a result of this shift in em-
phasis. 2 Today, no one would argue against the idea that such
factors as worker ability, motivation, training, organizational
structure, organizational clinate, and various human relations
policies all have some direct or indirect relationships on how
*References and footnotes at end of Section,
32
-------
the employee behaves on the job. Many social scientists have
constructed theories regarding the relationship between job
attitudes, job satisfaction, motivation, and ultimate job
performance.
The ultimate goal in developing a theory of work motivation
is to help understand and predict the conditions under which a
person will be motivated to work and those under which a person
will not. The motivational framework for job performance will
aid in understanding the conditions under which people will be
willing to engage in creative, change-oriented behavior and
under which they will accept the introduction of change and
innovation necessary in a dynamic world. While this type of
behavior is_dependent upon other variables in addition to moti-
vation, motivation is crucial as one of the mechanisms by which
one can interpret and predict these types of behavior.
The results of behavioral research studies and subsequent
theories as to the attitude-motivation-productivity complex
already fill volumes. While there are many cases on record
where the traditional system of rewards and punishments has
worked quite well to improve output performance, there are many
where it has not, and it is partially because of these puzzling
inconsistencies in work behavior that interest in this area has
been so great.
MOTIVATION AND PERFORMANCE OVERVIEW
In recent years, efforts have been directed toward linking
human motivation with performance and productivity levels.
Much of the emphasis has been on the psychological and sociolo-
gical aspects of work. This orientation is rooted principally
in the common interests of managers and behavioral scientists
in gaining greater productivity, not so much by improving the
technology as by improving the motivational climate. New ways
are being sought to meet the technological demands, and at the
same time to provide the opportunity for the employee to sat-
isfy his fundamental need for involvement in work that has
personal relevance and meaning.3/ 4
Some of the principal concepts that have emerged from
current behavioral science research are concerned with the
division of labor and the relation between the work a person
does and his mental health and motivation. A Conference Board
study5 found widespread interest in the application of behavioral
science technology to the work situation. What was found was
that several firms were trying to improve the quality and
challenge of work in order to increase employee motivation.
This movement is diverse, and the theories of how to mesh organ-
izational requirements with individual goals differ, but the
common approach has been centered on manipulation of the job
33
-------
content instead of manipulation of the employee to fit the job.
The current focus is on job design for motivation.
The design or redesign of jobs has a single purpose1 to
increase both employee motivation and productivity. Several
approaches have been and are being used with varying degrees of
success concerning job redesign. These include primarily: job
rotation, job enlargement, job enrichment, and work simplification
with these techniques being used separately or in combination.
Job rotation often implies rotating an employee through a
series of departments or jobs for short periods of time for the
purpose of orientation. It can be used as a training or develop-
ment tool in moving an employee through a series of operations
to broaden his knowledge and perspective of the total operation.
In job design, the rotation usually is within a prescribed series
of tasks; the jobs themselves are not redesigned or modified, and
the worker's responsibility is for the specialized part of the
operation that he performs at any given time.
Job enlargement denotes the addition of one or more related
tasks to the basic job. The employee learns to perform several
steps in the operation required to make a product or perform a
service. The responsibility is enlarged from one specialized
job to include other related sequences.
Much of the early work in job design for motivation took the
form of job enlargement. Proponents of job enlargement cite
reduced fatigue, relief from boredom of highly specialized work,
and broadened work skills as motivational factors. The underlying
assumption is that the bigger the job, the more intrinsically
satisfying it is. There has also been some criticism that job
enlargement has little possitive impact on employee satisfaction.
Another form of job design is work simplification. Although
this technique may sound somewhat contradictory in that it takes
on the connotation of work specialization or the further division
of labor espoused by Taylor et. al., it is different in that its
aim is to break the work processed down into their smallest seg-
ments in the hope that unnecessary steps can be eliminated, or
combining steps where possible. It is often used as a part of
job enrichment efforts since employees can participate in ana-
lyzing jobs and redesigning them for greater efficiency. In doing
so, the worker becomes intimately involved in the planning and
design of the work under his control. Several small research
projects have been documented in the professional journals.
Many of these projects were conducted under actual working con-
ditions in functioning organizations; but, only a few job design
projects for larger organizations have been reported. Some of
these are regarded as 'blassics," notably those projects or
experiments within General Electric,7 IBM,8 imperial Chemical
Industries ,9 and American Telephone and Telegraph Company1^1.
34.
-------
The Conference Board study (Rush, 1971) examined job design pro-
jects on six other large companies, although these projects for
the most part could be called "pilot" projects. The six companies
investigated in this report were: Arapahoe Chemicals, Texas
Instruments Inc., U.S. Internal Revenue Service, Weyerhauser Co.,
Valley National Bank, PPG Industries, and the Monsanto Company.
The results of studies on these job design projects indicate
that transforming the various job design techniques or theories
into the actual working situation is difficult at best. The
Conference Board study makes it apparent that one job design
technique is rarely used alone. For example, the Weyerhauser
effort relied strongly on work simplification, but an equal em-
phasis was put on interpersonal competence and teamwork. The
PPG Industries case illustrates the enlargement for production
and maintenance workers. In the Monsanto study, the section on
chemical operators in a nylon plant is an example of job rotation
combined with job enrichment.
The ultimate in job design application would be what Rush
refers to as an "autonomous or semi-autonomous work group" an
idealized organizational construct that some job design advocates
dream about, but that rarely exists in its "pure" form in prac-
tice' . The work group is organized into a work unit with a
common product or service function. Within the framework of the
larger organization's long and short range objectives, the group
as a whole is accountable for predetermined quantity and quality
of output. But beyond this accountability, the organization per-
mits the group to operate independently. The manner in which
they plan, organize, perform, and control their work is left up
to the group, as is the behavior and performance of the group's
members. The group is accountable to management and the indi-
vidual members are accountable to the group.
The lack of most companies to employ job design techniques
on a broad scale indicates that barriers to job design exist.
Little and Warr classify these barriers as job factors and
organizational factors^, while Rush declares these barriers
to be organizational and attitudinall^. As discussed in Section
1, political barriers also exist in a governmental framework.
In addition to job design techniques, several other methods
have been proposed to stimulate the motivational climate of the
work situation. These include incentive plans as previously
discussed in Section 2 and modification of the work week. In
industry, some companies have switched to the four-day week
instead of the traditional 8-hours, five-days-a-week system.
As discussed later in Section 7, one waste collection alternative
involves the use of a four-day work week. For those collection
systems that are politically constrained to a twice-a-week
pickup, the four-day-work-week alternative is superior to the
others in terms of simplification of design. This alternative
permits a minimum of three days between collections, and
35
-------
simplifies holiday work week schedules.
JOB SATISFACTION
Worker job satisfaction has gradually emerged as a prime
focus of modern organization development. In the past, job
satisfaction was studied mainly as an isolated variable for its
possible predictive usefulness in understanding worker job
performance. However, recent research has viewed job satisfaction
as a dependent variable, worthy of independent study, and also
investigated to determine its relationship to other factors that
may affect worker behavior.
The question of how job satisfaction influences job perform-
ance is not clearly answered. In an early paper published by
Crockett and Brayfield (1955) , it was suggested that an explicit
theoretical linkage existed between satisfaction, motivation,
and the organization's goal of productivity. The authors
conclude:
It makes sense to us to assume that individuals
are motivated to achieve certain environmental
goals and that the achievement of these goals
result in satisfaction. Productivity is seldom a
goal in itself, but more commonly a means to goal
attainment. Therefore, we might expect high satis-
faction and high productivity to occur together
when productivity is perceived as a path to certain
important goals and when these goals are achieved-^.
Hence, it was not determined that a relationship existed between
productivity and worker morale.
Frederick Herzberg and his associates^5i ^6 used a semi-
structured interview technique to get respondents to recall
events experienced at work which resulted in a marked improvement
or a marked reduction in their job satisfaction. Content analysis
of the interviews suggested that certain job characteristics
led to job satisfaction, while other job characteristics led to
job dissatisfaction. For example, job achievement was related
to satisfaction while working conditions were related to dis-
satisfaction. The researchers concluded that satisfaction and
dissatisfaction are not simple opposites, therefore, a two-factor
theory of satisfaction is required.
Although Herzberg and others-^, continue to develop research
methodologies to test the two-factor theory, conflict surrounding
the soundness of the theory has delayed its general confir-
mation^, 19.
36
-------
Job satisfaction has been defined by J. C. Wofford as the
overall attitude of well-being with regard to the job and its
environment, with satisfaction being a function of the difference
between an individual's strength of needs and the fulfillment of
those needs on the job. To distinguish job satisfaction from job
motivation, Wofford defines the latter as the tendency to per-
form or to expend effort required to maintain a high quantity
and/or quality of output. He described motivation as a multi-
plicative function of the individuals' strength of needs and the
expectancy that performance will result in need gratification.
Thus, motivation is the variable which leads to relevant rewards
via performance and effort, while satisfaction is determined by
the difference between the expectancy of rewards and the actual
attainment of those rewards. The motivation-performance inter-
action is antecedent to satisfaction. Although job satisfaction
can influence an individual's evaluation of the strength of needs
and the expectancy function of his next behavioral decision. In
this frame, the motivation, performance and satisfaction model
is somewhat sequential. It is, at this point, not clear that
satisfaction alone influences the degree of motivation toward
relevant goals. For example, a person may be highly motivated
to perform in such a way as to lead to perceived rewards despite
previous disappointments. However, researchers generally agree
that motivation and performance are antecedent to satisfaction.
In summary, this Section has reviewed research findings
relating to worker motivation, job performance and job satis-
faction. It is evident that firm solutions to organization prob-
lems in this area are not available. Even more fioticeable is the
absense of literature dealing specifically with these problems
as they relate to solid waste collection/disposal. Analyzing
the results from available research investigations and suggestions
in the literature, the following general conclusions are offered
for solid waste collection/disposal operations:
1) Solid waste workers will attain higher levels of
motivation with incentive programs,
2) Worker performance will be improved with proper
job design,
3) Worker job satisfaction will be enhanced with
improved motivation and performance,
4) An effective solid waste collection/disposal
system would utilize group assignments (teams).
Results of incorporating these conclusions into the solid waste
operations of the test City are included in Section 7.
37
-------
SOCIOMETRIC ANALYSIS FOR CREW SELECTION
A team incentive approach was utilized in this research
because the work group has considerable influence over pro-
ductivity. The members of each work group must be able to in-
teract favorably in order to increase their effectiveness. If
tension and distrust exists among members of the team, then their
effectiveness as a group will be diminished..
Typically, crew selection is conducted in a random manner
without any regard as to crew preferences. Since the make-up
of the work group is so critical to the success of any team incen-
tive, employee preference was utilized as a basis for work group
selection in this study. The method used for the selection of the
crew and team work groups was the technique of sociometric anal-
ysis. The sociometric technique is a method for establishing
work groups, based on employee preference, through the use of
a simple questionnaire.
The employees of the test City were asked to choose other
employees with whom they wanted to work and to choose employees
with whom they did not want to work. Appendix 9.1 is a sample
choice form and Appendix 9.2 is the cover letter that accompanied
the choice forms. The raw data was then analyzed through the
use of choice matrices. Figure 11 is an example of a matrix
used to evaluate mutual choices by the Laborers. The actual
results of the analysis is described in the subsequent paragraphs.
The purpose of this analysis was to recommend crews and
teams based on employee preferences. Two teams were constructed,
each with several three-man truck crews and foreman. The recom-
mended team selection was based on the positive and negative
choices of the Drivers and Laborers. Laborers were asked to
choose other Laborers and Drivers. Drivers were asked to choose
Laborers and other Drivers. All but one of the Drivers and twenty-
two out of twenty-eight Laborers participated.
Four basic sets of data were examined:
1) Laborers choosing other Laborers
2) Laborers choosing other Drivers
3) Drivers choosing Laborers
4) Drivers choosing other Drivers
The four sets of data were individually tabulated on matrix
coding forms to reveal preferences and to simplify the procedure.
Since the members of the three-man crews must work more
closely together than the crews within a team, priority was
given to crew selection over team selection.
38
-------
CHOOSER
«—t CM !><•*• cnry to t^ oo en o t—i CNI N~V crt-rv UD
en o11—i cxihacr LOIOI-^OO
rvi rxi rxi cxt rM rvi r\i t^vi r\i._
+ DENOTES POSITIVE CHOICE
- DENOTES NEGATIVE CHOICE
O DENOTES RECIPROCAL CHOICE
Figure 11. Sociometric Analysis Matrix
39
-------
The following priorities were established:
1) Laborers choosing Laborers for crew selection
2) Laborers choosing Drivers and Drivers choosing
Laborers for crew selection
3) Drivers choosing Drivers for team selection
4) Commercial and Large Item Pickup crew selection
Laborer-Laborer Matching
An attempt was made to maximize the number of matched pairs,
that is, the number of Laborers who want to work with each
other.
Results: 1) Seven of the eight Laborer crews are matched
pairs.
2) One of the crews resulted from a one-way
choice.
3) There are no negative choices in this group.
Laborer-Driver and Driver-Laborer Matching
An attempt was made to maximize the number of matched pairs
between Drivers and at least one of the Laborers in a crew.
Results: 1) Six of the eight crews involved a matched
pair between the Driver and at least one
Laborer.
2) Two of the eight crews involve a one-way
choice of Drivers by Laborers.
3) There are no negative choices in this group.
Driver-Driver Matching
An attempt was made to minimize the number of negative
choices among the Drivers within each of the two teams.
Results: 1) On one there are no negative choices.
2) On the other team there is one negative
choice.
40
-------
Commercial and Large-Item Pickup Crew Selection
An attempt was made first to have a one-way choice between
the Driver and the Laborer, and second to minimize negative
choices between the Drivers of the commercial routes and the
Drivers of the teams they are assigned to.
Results: 1) Both of the commercial crews involve a one-
way choice between Laborer and Driver. The
large-item crew involves neither a positive
nor a negative choice.
2) There is one negative choice between the
Driver of the commercial route and the other
Drivers on one team; there are two negative
choices on the other team.
The sociometric technique is an effective method for develop-
ing collection teams based on employee preference. The procedure
is quite simple, yet the benefits derived from the standpoint of
work group interaction are substantial. Figure 12 shows a typi-
cal crew of driver (center) and two laborers following implemen-
tation.
' ,i
<< (
Figure 12. Three-Man Crew
41
-------
FOOTNOTES
Efforts to enhance the effectiveness of the use of the
physical objects and facilities people use and to maintain or
enhance certain desirable human values in this process is often
referred to as "human factors engineering." The process of in-
dustrial job designing, with its many human and technical im-
plications, is thoroughly treated by Ernest J. McCormick, Human
Factors Engineering , McGraw-Hill, 1970; 3rd edition. The
interested reader can also refer to Alphonse Chapanis , "On the
Allocation of Functions Between Men and Machines," Readings in
Organizational and Industrial Psychology, G. A. Yukl and K. N.
Wexley, eds . , Oxford University Press, 1971, pp. 521-30-
excellent development of the historical and psychologi-
cal concepts of human work, with emphasis on the "work personali-
ty" is discussed by Walter S. Nef f , Work and Human Behavior ,
Atherton Press, 1968. In addition, Abraham K. Korman traces
this shift in emphasis by industrial engineers and psychologists
towards the human sides of work in the introductory chapter of
his book, Industrial and Organizational Psychology, Prentice-
Hall, 1971, pp. 3-17.
, Ronald K. and Shell, Richard L., "End of the Line
at Lordstown," Business and Society Review, No. 3, Autumn, 1972.
McCormick, Ernest J., "The Industrial Engineering/Human
Factors Interface," Human Factors , Vol. 11 (April, 1969), p. 109,
^Rush, Harold M. F., "Behavioral Science --- Concepts and
Management Application," Studies in Personnel Policy, No. 216,
National Industrial Conference Board, 1969.
6Little, Alan and Warr , Peter, "Who's Afraid of Job En-
richment?" Personnel Management, Vol. 3, February, 1971, p. 34.
"^Sorcher, Melvin and Meyer, Herbert H., "Motivation and
Job Performance," Personnel Administration, Vol. 3, February,
1971.
, J. , Overbagh, W./ Palmer, G., and Piersol, D.,
"Enriched Jobs Mean Better Inspection Performance," Industrial
Engineering , November, 1969-
^Paul, William J. , "Robertson, Keith B. and Herzberg,
Frederick, "Job Enrichment Pays Off," Harvard Business Review,
March- April, 1969.
, Robert N., Motivation Through the Work Itself,
American Management Association, Inc., 1969.
42
-------
Rush, Harold M. F., "Job Design for Motivation: Experi-
ments in Job Enlargement and Job Enrichment," pp. 15-16 and Rush,
"Motivation Through Job Design," pp. 55-56.
•^Little and Warr, op. cit., pp. 36-37.
13Rush, Harold M. F., "Job Design for Motivation: Experi-
ments in Job Enlargement and Job Enrichment," The Converence
Board, Report No. 515, 1971, pp. 20-30.
14Brayfield, A. H. and Crockett, W- H., "Employee Attitudes
and Employee Performance", Psychological Bulletin, Vol. 52,
1955, p. 416.
-^Herzberg, F., Mausner, B. and Snyderman, B. B., The
Motivation to Work, Wiley, 1959.
•^Herzberg, F., Work and the Nature of Man, World Publish-
ing Company, 1966.
For a review see M. D. Dunnett, J. P. Campbell, and M. D.
Habel, "Factors Contributing to Job Satisfaction and Job Dissatis-
faction in Six Occupational Groups", Organizational Behavior and
Human Performance, Vol. 2, 1967, pp. 143-74. C. L. Hulin and
P. A. Smith, "An Empirical Investigation of Two Implications of
the Two-Factor Theory Job Satisfaction", Journal of Applied
Psychology, Vol. 51, 1967, pp. 396-402.
18
See C. A. Lindsay, E. Martin, and L. Gorlow, "The Herzberg
Theory: A Critique and Reformulation", Journal of Applied
Psychology, Vol. 51, 1967, pp. 330-39. J. R. Hendircks and
L.A. Mischkind, "Empirical and Theoretical Limitations of the
Two-Factor Hypothesis of Job Satisfaction", Journal of Applied
Psychology, Vol. 51, 1967, pp. 19-200. G. B. Graen and C. L.
Hulin, "An Addendum to an Empirical Investigation of Two Impli-
cations of the Two-Factor Theory of Job Satisfaction", Journal
of Applied Psychology, LII, August, 1968, pp. 341-42. Articles
exemplifying this controversy are: Donald P. Schwab and Larry
L. Cummings, "Theories of Performance and Satisfaction: A
Review," Industrial Relations, Vol. 9, October, 1970, pp. 408-30;
John W. Slocum, Jr., "Performance and Satisfaction: An Analysis,"
Industrial Relations, Vol. 9, October 1970, pp. 431-6; Martin G.
Wolf, "Need Gratification Theory: A Theoretical Reformulation
of Job Satisfaction/Dissatisfaction and Job Motivation," Journal
of Applied Psychology, Vol. 54, February, 1970, pp. 87-94; F. J.
Landy, "Motivational Type and the Satisfaction-Performance
Relationship," Journal of Applied Psychology, Vol. 55, August,
1971, pp. 406-13.
43
-------
Bobbitt, J. R. and Behling, 0., "Defense Mechanisms as
an Alternate Explanation of Kerzberg's Motivator-Hygiene Results'
Journal of Applied Psychology, Vol. 56, No. 1, 1972, pp. 24-27.
Also see L. C. Waters and C. Waters, "An Empirical Test of Five
Versions of the Two-Factor Theory of Job Satisfaction", Organi-
zational Behavior and Human Performance, Vol. 7, No. 1, 1972,
pp. 18-24.
20
Wofford, J. C., "The Motivational Bases of Job Satisfac-
tion and Job Performance," Personnel Psychology, Vol. 24, No. 3,
1971, pp. 501-18.
44
-------
PERSONAL CHARACTERISTICS AND ABSENTEEISM FOR SOLID WASTE
COLLECTION WORKERS
INTRODUCTION
The purpose of this Section is to examine personal charac-
teristics of individuals working in collection operations, and
to determine relationships between certain employee demographic
factorsl* and worker absenteeism. The population investigated
was comprised of blue collar employees permanently assigned to
the collection and disposal of municipal solid waste in Coving-
ton, Kentucky.
Factors2 relating to age, marital status, number of depen-
dents, reported level of formal education, previous employment
history, military service, height, weight, race and arrest record
form a discernible pattern of characteristics which relate to the
measures of absenteeism for this group of workers.
Information on race was not available on the majority of the
employment application forms, in accordance with government reg-
ulations, but was provided by the solid waste management. Using
all information, the absentee record and personal history profiles
across two racial groups was examined.
Basic Manpower Issues in Solid Waste Management
According to a 1973 study by Applied Management Science,
Inc. (AMS) , "The solid waste management field in the United
States consists of 227,000 people: 125,000 of whom are employed
by the 10,678 private contracters, and 102,000 of whom work for
the 2,982 municipal and county agencies. "3 it was estimated
that 170,000 of these workers are assigned specifically to the
collection task. "Absenteeism is important not only because of
lost man-days, but also because it may reflect the worker's
attitude toward his job and management's personnel policies.
At the unskilled level o-f the solid waste field (laborers and
drivers), the absenteeism rate is 6.2 days per man per year. "4
* References and footnotes at end of Section.
45
-------
This figure would indicate that absenteeism in this work system
is not a significant problem in general. However, there is
"considerable variability in absenteeism among cities and this
variance can be traced (in part) to diverse management policies."-
For example, it is reported that Atlanta has an extremely high
absenteeism (20 percent of work force off on a normal day, with
as high as 40 percent on some Mondays). AMS concluded that
"This absenteeism results from a system which permits such be-
havior; management penalizes people who are absent only by dock-
ing their pay. The management philosophy in Atlanta favors
"job support" rather than efficiency so there are definite ten-
dencies to be lenient with absenteeism and give unlimited chances
to people who are absent frequently."6
In addition to absenteeism data, AMS noted differences in
the turnover rates and crew sizes between public and private
sector solid waste collection operations. "The high turnover
rate observed among unskilled laborers is primarily voluntary. . .
This suggests that the hard, physical working conditions at the
lower levels are too severe for many, and they quit. This could
also result from the relative dissatisfaction of unskilled work-
ers with their jobs. The contrast between public and private
systems shows higher turnover in the private sector at all job
levels except management and supervisory personnel and great
disparities at the skilled levels (8.5 percent.for public, 21.4
percent for private) and unskilled levels (30.3 percent for
public, 58.9 percent for private)."^
In the matter of crew size, AMS reports that the profit
motive of the private sector drives management to minimize truck
crew size, increase the number of tons of solid waste collected
per man per day, as well as the number of tons collected per
truck per day. Table 1 outlines typical differences between pub-
lic and private waste collection/disposal systems.
General Descriptive Information
As shown in Table 2, there are approximately 227,000 persons
employed in management of solid waste. Of this number, approxi-
mately 170,000 are involved in the collection function. In the
public sector, 90,587 workers are classified as skilled and
unskilled laborers out of a total of 101,892.
The high ratio of unskilled/skilled workers to management/
supervisory/clerical personnel is indicative of the "labor
intensiveness" found in certain local government functions.
Labor intensiveness in the public sector is due in part to the
stronger presence of unions, the notion of "job support" versus
efficiency, and the tacit public sector objective of providing
jobs, primarily at the unskilled level, as an alternative to
having individuals placed on unemployment or overburdened relief
46
-------
TABLE 1
PUBLIC/PRIVATE SECTOR COLLECTION COMPARISON
Public
Mean
Private
Mean
Case Study
Public Systems
Men per Truck
2.5
1.6
3.0 Minneapolis
4.1 Milwaukee
4.5 Atlanta
Tons per Man 3 . 0
per Day
Tons per Truck 7 . 6
per Day
6.1 2.5
2.0
1.9
1.6
1.3
9.1 5.7
6.1
6.5
7.4
5.6
Fort Worth
Minneapolis
Tacoma
Milwaukee
Atlanta
Tacoma
Minneapolis
Milwaukee
Fort Worth
Atlanta
Source: Applied Management Science, Inc.:
Manpower Profile and Analysis in
the Field of Solid Waste Management
(Vol. II), p. 8.1, Jan. 16, 1973.
roles. AMS notes that; "The basic policy to be faced . . . con-
cerns the public sector's legitimate role as an employerfiof last
resort or a transitional employer of the disadvantaged."
Volume Managed and Health Considerations in Solid Waste Collection
There are two additional conditions that affect the solid
waste collection worker. One is the volume of solid waste gen-
erated and collected; and secondly, the associated health hazards.
Each day, approximately 1.3 billion pounds of municipal
solid waste^ is generated in this country. This converts to
approximately 6 pounds per citizen per day.10 The cost to the
public for this service is estimated at $5 billion annually.
Typically, the average collection worker handles three to six
tons of solid waste daily. For performing this work load,
usually under less than-desirable working and environmental con-
ditions, the solid waste worker (laborer) can expect to earn an
average of $111.00 weekly. For every job category except
clerical/secretarial, employees in the private sector have a
higher mean gross weekly salary than employees in the public
sector.
47
-------
TABLE 2
MANPOWER DISTRIBUTION BY JOB CATEGORIES
Job Categories
Total
Number Employed
Local Government
Collection/
Transportation 9,395
Disposal/Other 2,075
Skilled Laborers: 99,791
Maintenance 8,967
Collection/
Transportation 80,046
Disposal/Other 10,803
Unskilled Laborers: 84,729
Collection/
Transportation 79,964
Disposal/Other 4,765
TOTALS 226,739
5,078
1,208
36,243
2,179
27,193
6,871
54,344
51,583
2,761
101,892
Private
Managerial
General
Other
Clerical
Super/Foreman :
19,835
19,212
623
10,914
11,470
2,723
2,356
367
2,296
6,286
17,113
16,856
257
8,619
5,177
4,323
854
63,591
6,788
52,873
3,930
30,402
28,385
2,071
124,092
Source: Applied Management Science, Inc.: Manpower
Profile and Analysis in the Field of Solid
Waste Management (Vol. II), p. 19, Jan. 16,
1973.
In addition to the lower salary levels, typically workers in
solid waste have limited opportunity for promotion and raises due
to the absence of career ladders built into the organization
structure. However, it should be noted that public sector em-
ployees have access to more non-direct financial benefits than
private sector employees. These benefits often include: paid
sick leave, contributory and/or non-contributory medical-surgical
insurance, group life insurance and retirement plans.
Perhaps the most striking characteristic of employment in
the solid waste field is the extremely high accident rates
experienced by solid waste workers and the degree of exposure
to and incidence of occupation-related health problems. ^Review
of accident or injury frequency rates indicates that solid waste
collection exceeds that of all other occupations including log-
ging and meat cutting. For example, in 1970 the rate was four
times that experienced by coal miners, and nine times that of
the average industrial worker. Nearly 25 percent of all injuries
48
-------
sustained are to the eye.11 The most frequent health problems
encountered include frostbite, falliculitus (caused by personal
hygiene and over-dressing in inclement weather), and xerosis, as
well as other common forms of occupational dermatosis. Gellin
and Zavon note that, "The stigmata or occupational marks (bruises
on legs and hands, etc.) were not sources of complaint . . .
[but] were accepted by them [the solid waste workers] as 'badges
of the trade1. "l2
Another health problem, centered mainly in high density ur-
ban areas, is the inhalation of carbon monoxide (CO) as a result
of the workers being in the immediate vicinity of the sanitation
trucks while performing their task. One study, conducted in
New York City, found that: "There is no doubt that levels of
carbon monoxide in the immediate vicinity of functioning sanita-
tion trucks are excessive. These increased working environmental
levels result in increased absorption of CO and cause a definite
increase in the carboxy-hemoglobin levels of sanitation crews.']1
The study concluded that, "A significant number of men absorbed
enough CO to raise their COHg levels to what is medically con-
sidered hazardous."14
CAUSES OF ABSENTEEISM
This subsection provides a brief analysis of the causes of
absenteeism as related to workers in general. In addition to
this information, a review of selected literature highlights
relevant previous research regarding the relationship of demo-
graphic variables to worker absence.
The causes of absenteeism are as complex as its results.
One cause is the level of job satisfaction. Vroom states that
workers make daily decisions whether or not they will appear for
work.15 He notes that, "If, on a given day, the consequences
expected from not working are more attractive than those expected
from working, the worker would be predicted to be absent. The
large number and the variable nature of the consequences of
being present and being absent from work on a given day makes any
precise determination of who will be absent, and when, unfeasible
if not impossible ... To the extent to which the worker derives
satisfaction from participating in his work role, we would assume
that there would be a force acting on him to be present at work.
It would seem to make little difference what characteristics of
the work role are the source of these rewards. The only require-
ment is that the attainment of the rewards is dependent on being
present at work."16
In addition to job satisfaction, worker attendance is
affected by other intervening variables such as quality and style
of management, concordance of goal structures, and availability
49
-------
of performance incentives.
Another way to approach the problem of absenteeism is to
determine the relationships, if any, between certain employee
demographic information, usually captured on a personal history
document such as a standard employment application form, and
the absentee records of persons presently employed in the primary
work system. If there exists statistically significant relation-
ships between several personal history factors and present absentee
records, a predictive capability can be developed regarding the
efficacy of recruiting and selecting individuals for inclusion
in a performance-oriented work group.
Review of Existing Knowledge
A review of the existing knowledge on the subject of
absenteeism reveals a limited amount of information as to the
relationship between personal history or demographic factors and
absenteeism.
Shepherd notes that, "Absence was higher for single men.
Those with two dependents had a minimum of absences.""
Baumgartel and Sabol reported the results of their research
on a population of 3,900 non-supervisory employees of a major
U.S. airline.18 There were two major objectives to the study:
First, they tested the prediction that the larger the size of the
location (or "Plant"), the higher the absenteeism. The investi-
gation concluded that smaller organizations have less absenteeism.
The second objective of the study was to determine how age, wage
rate, seniority, and job classification were related to absentee-
ism. From analyzing a sub-sample of white collar women workers,
the investigators concluded that a positive correlation did exist
between absence frequency and the seniority, wage level, and age
(length of time) on job. For blue collar men, the [common factor]
age, "appears to bear a consistently flat relationship with
absenteeism among the population."1° The authors concluded that,
"In contrasting the findings for blue collar workers with those
of the other three groups, it can be concluded that age among
production workers is not a markedly significant variable."20
Naylor and Vincent investigated job success criterion based
on the age, marital status, and number of dependents of 220 fe-
male clerical workers.21 The criterion of job success was
absenteeism from work over a six-month period. The independent
and dependent variables were dichotomized in the following manner:
Marital Status = Married or Single
Age = 32 or more; or less than 32
Number of De-
pendents = One or more; or none
Absent = 4 days or more; or less than 4 days
50
-------
Using item correlation, multiple correlation, and Chi-square,
the researchers reported that only one of the variables—the num-
ber of dependents—showed a significant relationship with
absenteeism (x2 = 7.99, dF = 1, r = 4.24).
In a related investigation, Scollay analyzed the responses
of 200 employees to a group of personal history items in relation
to the criterion of average salary increase.22 Of these items,
Scollay found 88 of 176 possible items to be significant at the
10% level (r = .15). He concluded that, "until further work has
been done to prove their usefulness for individual prediction,
personal history forms are at best an adjunct to the interview
and test battery."23
In a subsequent report, Scollay used the information de-
veloped in the 1956 study to attempt a cross-validation of per-
sonal history data from a specific occupational group (sales
managers) against the salary increase criterion. A major de-
parture in this study is the use of individuals from a homogenous
occupational level, rather than selecting employees across
occupational levels. Using the personal history data of 116
subjects, Scollay applied the triserial-r statistic developed by
Jaspen to the weighted score. The result was that the "correla-
tions are high enough to justify the assumption of success, [as]
defined in this study, can be predicted on the basis of personal
history items, whose validities were determined in a separate
study with a different criterion."2^
Minor used self-reported biographical data from standard
employee application forms to construct a selection instrument
which would enable prediction of probable tenure for female
clerical applicants in an insurance company.26 Employing a
sample of 440 clericals, Minor labeled 11 of 32 predictor
variables as being critical to tenure. These variables included:
age at time of application; number of children; tenure on pre-
vious jobs; and marital status at time of application. Minor
concluded that employee application blanks could be scored, and
hiring made on the basis of a critical score below which the
individual would not be hired. The decision for placement, how-
ever, would be made in light of extra-organizational considera-
tions such as the level of current labor market conditions and
the selection ratio necessary to fulfill organization needs.
Robinson utilized a weighted application blank to predict
clerical turnover. He found age, education, and marital
status to be sensible and interpretable variables for differenti-
ating between short-term and long-term employees.
WORKER ENVIRONMENT IN COVINGTON, KENTUCKY
Personnel data was obtained from Public Works Department
records. As of January 1, 1974, there were 38 full-time blue
51
-------
collar employees (all Civil Service) directly engaged in col-
lection and disposal. Of these 38, 12 were drivers (Laborer II),
and 26 were "laborers" (collectors, Laborer I, II) . Because of
absenteeism, 13 temporary employees were assigned to the Public
Works Department to fill in for absent workers. In 1973, the
Covington work group collected approximately 26,000 tons of solid
waste from approximately 19,000 dwelling units. This would mean
that 8,000 pounds or 4 tons of solid waste material were handled
per laborer per day. Comparing this figure to those in Table 1,
Covington was above the national average (3.0 tons per man per
day) in the amount of waste collected per worker.
The job classification of laborer and driver are defined
under the rules and regulations of the Civil Service System of
the City of Covington. As an employee under this system, the
wo'rker is entitled to 12 days excused sick leave per year.
Those days not used in any calendar year will be accrued until
such time as the employee has earned a total of 240 days. At
the time of retirement he will receive a lump sum remuneration
for these days equivalent to 200 working days. In the event
of death immediately prior to or following retirement, the
widow of the deceased employee will receive a lump sum payment
equivalent to the full 240 days of sick leave.
In addition to allowed sick leave, the employee may be
absent from work on legal holidays. If emergency holiday work
is scheduled, the worker receives 1-1/2 or double time rate,
depending on the holiday. If the employee works on the following
days, he earns 1.5 times the normal rate:
- Franklin D. Roosevelt's birthday (January)
- Abraham Lincoln's birthday (February)
- George Washington's birthday (February)
- Memorial Day (May)
- Independence Day (July)
- Labor Day (September)
- Columbus Day (October)
- 1/2 day for Good Friday
On the following holidays, he earns double the normal rate:
- New Year's Day (January)
- Thanksgiving Day (November)
- Christmas Day (December).
This list of legal holidays represents 10.5 days the employ-
ee could be away from the job. In addition, each employee earns
the right to paid vacation days which are determined by length
of service:
10 working days 18 employees
13 working days 9 employees
52
-------
15 working days 3 employees
20 working days _5 employees
35"
Weighted Average, x = 12.5 days/man
Out of the 260 working days in the year, the average
worker may miss 12 + 10.5 + 12.5, or 35 days work with pay
annually. When added to the number of days absent due to injury,
or other reasons, the total days missed represents a sizeable
portion of the work year.
The hourly wage rate for laborers and drivers was between
$3.36 and $3.96 as outlined below:
Labor Class II
Step 1, @ $3.36 = 2 employees
Step 2, @ $3.63 = 8 employees
Step 3, @ $3.69 = 25 employees
x = $3.65
$3.65 per hour or $146.00 per week (higher than
the national average of $111.00 per week)
In addition to the prevailing wage rate, the employees are
entitled to a comprehensive benefit package, most of which is
non-contributory -
METHODOLOGY OF INVESTIGATION AND
VARIABLE IDENTIFICATION
For the 35 workers analyzed, total absenteeism averaged
22.7 days per man during calendar 1973, nearly 4 times the
national average of 6.2 days. Of this total, 11.6 days were
identified as being unexcused absences. The objectives of this
area of the investigation are to:
1) Determine if an employee's age, marital status,
number of reported dependents, and education at the
time of application are related to present
absenteeism.
2) Determine if previous behavior characteristics such
as criminal arrest, present (at time of application)
indebtedness, discharge from previous employment
(for cause; i.e., fired), number of, jobs held prior
to application, previous experience with absenteeism
as a result of illness, and experience with military
service have any relationship to present absenteeism.
53
-------
3) Determine if other personal characteristics such
.as height, weight, and race have any relationship
to present levels of absenteeism.
Data Collection
The data for this investigation was collected through a
census of pre-employment application forms for workers present-
ly employed as of January 1, 1974. Additional information
including absenteeism, injury, and available sicktime was
provided by management. In addition, a series of interviews
with management personnel provided information on mission, means,
and characteristics of the task function.
Of the 38 men employed in the system, the data for 3 of the
workers was incomplete and was therefore not included in the
analysis. Analysis of the data for the remaining 35 workers
included:
1) The mean and standard deviation of each variable
were computed.
2) A series of regression analyses were performed
to predict the variability in the dependent
variable (absentee rate/score) based on its
convariance with all the independent variables.
Descriptive Statistics and Variable Identification
For the purpose of analysis and interpretation, the
assignment of variable codes to demographic data is as
follows:
Var 1: Chronological age at the time the application
is submitted to the City.
Var 2: Age of the employee as of 12/31/73
Var 3: Marital status of the employee as reported at
the time of application
Var 4: Number of dependents as of data of application
Var 5: Record of arrest, at time of hire
Var 6: Record of employee having been terminated
(fired) from employment position prior to
date of application
Var 7: Record of financial indebtedness reported at
time of application
54
-------
Var 8: Record of work time missed during two years
previous to date of application
Var 9: Weight (in pounds) of the employee as- reported
at date of application
Var 10: Height (in inches) of the employee as reported
at date of application
Var 11: Level of education reported by the employee at
date of application
Var 12: Record of military service as reported on date
of application
Var 13: Number of jobs previously reported held by employee
thru at date of application
Var 16:
Var 13 Var 14 Var 15 Var 16
0 0 0 0=1 job
0 0 0 1=2 jobs
0 0 1 0=3 jobs
0 1 0 0=4 jobs
1 0 0 0=5 jobs
The number of jobs reported is limited to
5 due to the construction of the employment
application form.
Var 17: Race of applicant
Variables 18 through 24 were used independently as criterion
variables during the analysis of data, other than descriptive
statistics.
Var 18: Number of sick days employee has accrued as
of 1/1/74
Var 19: Number of days the employee was absent as a
result of reported illness during 1973
Var 20: Number of days employee was away from his job
due to unexcused absence
Var 21: Number of days employee was absent as a result
of job-related injury
Var 22: Number of days employee was absent for other
reasons, such as jury duty, or death in family.
Var 23: Total number of days employee was absent
from work during 1973
55
-------
Var 24: Number of sick days employee had accrued as
of 1/1/74
RELATIONSHIPS BETWEEN DEMOGRAPHIC
CHARACTERISTICS AND ABSENTEEISM
The descriptive statistics of each variable for the 35
workers are as follows:
MEAN STD. DEV. LOCKE
Var 1 Age at time of x a
application 27.4 yrs. 6.5 yrs.
Var 2 Age at present 34.1 yrs. 9.0 yrs. 33.8 11.5
Var 9 Weight 168.8 Ibs. 26.6 Ibs.
Var 10 Height 69.9 in. 2.7 in.
Var 11 Education 10.0 yrs. 1.8 yrs. 9.5 2.8
Var 4 Number of de- 4.0 dep. 2.8 dep.
pendents (for
married & widowed
only)
The above figures designated as "Locke" are from the results of
a recent comprehensive investigation into the sources of
satisfaction and dissatisfaction among solid waste employees made
by Edwin A. Locke and R.J. Whiting of the University of Maryland
(personal communication). The study encompassed 3,327 public
and private waste collection/disposal agencies drawn from a
stratified random sample. From these agencies, 911 solid waste
employees (629 blue collar) were interviewed concerning job
attitudes. The research indicates that blue collar waste manage-
ment employees were less satisfied with their work than white
collar, but were more satisfied than employees at the same job
levels in other types of work.
Var 3: Marital Status:
Single = 12 (30 percent)
Married = 21 (65 percent)
Divorced/Separated = 2(5 percent)
Var 13
thru
Var 16: Number of Jobs Reported Held
1 job = 23 percent
2 jobs = 22 percent
3 jobs = 25 percent
4 jobs = 22 percent
5 jobs = 8 percent
56
-------
Var 5
Var 6
Var 7
Var 8
Var 12
Var 17
Arrest
Fired
Debt
Reported Illness
Military Service
Race -
White
Black
(None)
47 percent
11 percent
5 percent
88 percent
40 percent
69 percent
31 percent
Among the Dependent Variables, the statistical analysis
reveals:
MEAN STD. DEV. RANGE
"(Days)
Var 18
Var 19
Var 20
Var 21
Var 22
Var 23
Var 24
Sick days, accrued 1973
Days excused absence
Days unexcused
Days absent—injury
Other absences
Total days absent
Sick days accrued 1974
18.7
9.4
11.6
1.7
.08
22.7
21.1
14.3
5.6
15.1
6.0
.5
18.3
15.1
1-72
1-22
0-72
0-35
0-3
2-91
5-79
Variable 23 indicates that the average number of days missed
due to excused or unexcused absenteeism was 22.7, or more than
one month per year. Of this amount, an average of 11.6 days
(Var 020) were categorized as unexcused. At an average hourly
wage rate of $4.65, the average worker is losing approximately
$340 per year in gross wages as a result of unexcused absentee-
ism.
Descriptive Statistics by Race
Table 3 provides information on demographic characteristics
by race. According to this information, the average black
worker is slightly older, less educated, more likely to be
married and have an arrest record. In addition, the average
black worker has more total days absent, more days absent with-
out pay, and more days absent as a result of work related
injury. Caution should be exercised to the significance of
this information because of the large standard deviations
associated with variable averages.
Tests for Statistical Significance: All Workers (N=35)
Table 4 illustrates the coefficients of correlation between
eight personal history characteristics and each of the measures
of absenteeism. The Table reveals that there is a significant
correlation between the marital status of the worker and the
number of days absent (excused) for reasons other than sickness
or injury. It can be concluded that absence for other reasons
will be greater among married workers than among non-married
57
-------
TABLE 3
DEMOGRAPHIC CHARACTERISTICS BY RACE
00
Var
Var
Var
Var
Var
Var
Var
Var
001
002
009
010
Oil
003
004
013
thru
Var
Var
Var
Var
Var
Var
Var
Var
016
005
006
007
008
012
018
019
Age at time of application
Age at present
Weight
Height
Education
Marital Status :
Single (9 people)
Single (2 people)
Married (13 people)
Married (8 people)
Div./Sep. (1 person)
Div./Sep. (1 person)
No . of Dependents
(Married only) x =
No. of Previous Employers
1 job
2 jobs
3 jobs
4 jobs
5 jobs
Record of Arrest
Report of Being Fired
Debt
Reported Illness
Military Service
No. of Days Avail. (1973)
No. of Days Excused Absence
x
26.5
32.3
164.7
69.4
10.6
42.0
54.0
4.0
3.6
16.
13.
21.
25.
25.
42.
8.
8.
1.
38.
16.
8.
0
0
0
0
0
0
0
0
3
0
5
8
WHITE
a
yrs. 6.9 yrs.
yrs. 8.7 yrs.
Ibs. 28.4 Ibs.
in. 2.7 in.
yrs . 1.9 yrs .
percent
percent
percent
percent
percent
percent
percent
percent
percent
percent
percent
days
percent
10.4
6.0
BLACK
x a
29
38
177
69
9
18
73
9
3
28
0
27
27
18
55
18
45
23
10
.5
.0
.8
.7
.8
.0
.0
.0
.6
.0
.0
.0
.0
.0
.0
.0
.0
.5
.5
yrs. 5.4 yrs.
yrs. 8.7 yrs.
Ibs. 20.4 Ibs.
in. 2.7 in.
yrs . 1.5 yrs .
percent
percent
percent
percent
percent
percent
percent
percent
percent
percent
percent
22.5
4.7
-------
WHITE BLACK
x a x
Var 020 No. of Days Unexcused Absence 10.1 14.9 15.0 10.5
Var 021 No. of Days Absent-Injury .9 1.63 3.3 10.5
Var 022 No. Other Absences' 0.0 0.0 .27 .9
Var 023 Total Days Absent 19.8 18.8 29.1 16.1
Var 024 No. of Days Avail. (1974) 19.9 10.4 23.6 22.7
LF1
-------
TABLE 4
CORRELATION COEFFICIENTS OF PERSONAL CHARACTERISTICS
AND MEASURES OF ABSENTEEISM
Age at time of application
Age at present
Marital status
Number of Dependents
Weight
Height
Education
Race
# OF
SICK
DAYS
ACCRUED
(1973)
.174
.325
.048
.235
-.010
-.209
-.313
T.218
# OF
DAYS
EXCUSED
ABSENCE
(SICK)
.274
.340*
.089
.426*
.032
-.174
-.261
-.143
# OF
DAYS
UNEXCUSED
ABSENCE
-.138
-.109
.244
.055
.082
.293
.059
-.153
# OF
DAYS
ABSENT
DUE TO
INJURY
.049
-.024
-.052
.166
-.019
-.062
-.057
-.186
# OF
DAYS
OTHER
.015
-.002
.681**
-.135
.021
-.133
-.129
-.253
TOTAL
ABSENT
-.013
.006
.230
.226
.072
.164
-.053
-.238
TOTAL
AVAIL.
(1974)
.094
.223
.043
.058
-.067
-.188
-.207
-.115
* significant at a = 0.05
** significant at a = 0.01
-------
workers. This may mean that work missed was due to death in the
spouse's family, demands for care of children, or other family
reasons. The Table also indicates that there is a significant
relationship between the number of dependents reported at the
time of hire and the number of days absent due to excused illness.
Therefore, it may be generally concluded that the more, dependents
a worker has the more he can be expected to be absent as a result
of reported illness. This could indicate the exposure of the
worker to communicable diseases as a result of the interaction of
his family with others would make him more prone to being absent
from work as a result of being exposed to and contracting common
illness such as colds, or flu.
It is also important to note that race has no relationship
to absenteeism in this work system, nor does education, height,
weight, or age at the time of hire. However, there is a
statistically significant relationship between present age and
the number of days absent as a result of excused absence. This
may mean that younger workers are more sturdy, or less prone to
job affecting illness, or it may be an indication that older
workers with many dependents are using excused (paid) sick leave
in order to care for the needs of their families.
Table 5 illustrates the coefficient of correlation between
six previous experience characteristics and each of the measures
of absenteeism. The Table reveals only one previous experience
characteristic, having had five previous jobs, to be related to
a measure of absenteeism in a statistically significant manner.
It should be noted at this point that the attitude of the worker
and management in the test city was that the sick leave permitted
with pay is an earned right that should be exercised regardless
of whether or not the employee is actually sick. For this rea-
son it is extremely difficult, all other things being equal, to
draw conclusions as to the significance of the relationships
with the independent variables.
Tests for Statistical Significance: White Workers (N=24)
Table 6 illustrates the coefficients of correlation between
the eight personal history characteristics of the white workers
and their relationship to each of the measures of absenteeism.
The Table reveals more statistically significant relationships
than when all workers, black and white, are analyzed as a group.
There is a significant relationship between the present age of
the worker and the number of days absent as a result of using
paid sick leave. It can be concluded that the time off the job
due to reported sickness will increase with the white worker's
age. As can be expected, the relationship between the number of
dependents and the incidence of sick leave are also positively
correlated.
61
-------
TABLE 5
CORRELATION COEFFICIENTS OF PREVIOUS EXPERIENCE CHARACTERISTICS
AND MEASURES OF ABSENTEEISM (N=35)
Record of Arrest
Record of Previous Job
Termination
to Record of Debt
Work Missed due to Illness
Military Service
Previous Employment:
2 jobs
3 jobs
4 jobs
5 j obs
# OF
SICK
DAYS
ACCRUED
(1973)
.289
.043
-.019
-.041
,.059
..176
..053
-.002
-.055
# OF
DAYS
EXCUSED
ABSENCE
(SICK)
-.009
-.218
.117
.104
.282
-.159
-.039
.025
.348*
# OF
DAYS
UNEXCUSED
ABSENCE
-.286
.003
.006
.015
-.035
.091
-.020
.041
.097
# OF
DAYS
ABSENT
DUE TO
INJURY
.170
-.101
-.069
-.071
-.200
-.072
-.110
-.107
-.017
# OF
DAYS
OTHER
-.157
-.062
T.042
-.047
.210
-.093
-.101
.315
-.053
TOTAL
ABSENT
-.187
-.099
.017
.019
-.001
.000
-.068
.015
.179
TOTAL
AVAIL.
(1974)
.278
.130
-.059
-.077
-.061
.247
-.009
-.073
-.181
* significant at a = 0.05
-------
TABLE 6
CORRELATION COEFFICIENTS OF PERSONAL CHARACTERISTICS AND MEASURES
OF ABSENTEEISM AMONG WHITE EMPLOYEES (N=24)
U)
Age at time of Application
Age at Present
Marital Status
Number of Dependents
Weight
Height
Education
// OF
SICK
DAYS
ACCRUED
(1/73)
.245
.362
.189
.282
-.001
-.495*
-.367
// OF
DAYS
EXCUSED
ABSENCE
(SICK)
.339
.396*
.039
.557**
-.093*
-.164
-.252
# OF
DAYS
UNEXCUSED
ABSENCE
-.182
-.107
-.125
.166
.124
.438*
-.121
# OF
DAYS
ABSENT
DUE TO
INJURY
-.192
-.240
-.161
-.261
.139
.177
-.164
// OF
DAYS
OTHER
ftftft
ftftft
ftftft
•A- ft ft
ftftft
ftftft
ftftft -
TOTAL
ABSENT
-0.052
.021
-.101
.289
.081
.311
.001
TOTAL
AVAIL.
(1/74)
.099
.231
.231
-.029
.015
-.498**
-.281
* significant at a = 0.05
** significant at a. = 0.01
'** coefficient of correlation cannot be computed
-------
In this white work group sub-sample, there is a positive
relationship between the height of the worker and the number of
days of unexcused absence. The Table indicates this relation-
ship is significant at the a = 0.05 level and is therefore
significantly related to the number of days accrued by the
worker at the beginning of the 1973 and 1974 work years. Al-
though this could be a spurious correlation, there are some
medical significances associated with this finding. For example,
it may be the case that for taller workers more strain is placed
on the back and spine as a result of the inadequate leverage
when lifting the solid waste containers. The Table further indi-
cates that no statistically significant relationship exists among
the remaining personal characteristics of white workers and the
various measures of absenteeism.
Table 7 displays the coefficient of correlation between pre-
vious experience characteristics of white workers and the various
measures of absenteeism. There is a statistically significant
inverse relationship at the a = 0.05 level between the record of
previous job terminations and the number of days absent due to
excused sickness. From this it can be predicted that the worker
who has been previously terminated from a place of employment is
likely to miss fewer work days as a result of sickness. Table
7 also reveals a relationship between the number of previous jobs
the worker had reported and two measures of absenteeism.
Tests for Statistical Significance: Black Workers (N=ll)
Table 8 illustrates the coefficients of correlation between
the eight personal characteristics of the black solid waste
worker and measures of absenteeism. As was the case in the pre-
vious analyses, the marital status of the worker has a statisti-
cally significant relationship to several measures of absenteeism.
There is a positive relationship between marital status and the
number of days unexcused absence, at the a = 0.01 level, number
of days absent for other excused, and with the total number of
absences. As is the case in all instances, no causality can be
associated as a result of the correlation of variables.
Table 9 reveals an interesting relationship among variables
in the form of the record of arrest and the number of unexcused
absences. In this sub-population, there is an inverse relation-
ship between the incidence of arrest and the worker being away
from the job for unexplained or unexcused reasons. However, there
is also another relationship that is statistically significant.
This is the positive relationship between the incidence of
military service and the number of days missed due to excused
sickness.
Finally, Table 9 also reveals statistically significant
relationships between the number of jobs previously held by the
black worker and the excused absences and total days available.
64
-------
FABLE 7
CORRELATION COEFFICIENTS OF PREVIOUS EXPERIENCE CHARACTERISTICS
AND MEASURES OF ABSENTEEISM AMONG WHITE EMPLOYEES (N=24)
-------
TABLE 8
CORRELATION COEFFICIENTS OF PERSONAL CHARACTERISTICS AND MEASURES
OF ABSENTEEISM AMONG BLACK EMPLOYEES (N=ll)
CTi
Age at time of application
Age at Present
Marital Status
Number of Dependents
Weight
Height
Education
# OF
SICK
DAYS
ACCRUED
(1/73)
.023
.235
-.111
.189
-.184
.029
-0.248
# OF
DAYS
EXCUSED
ABSENCE
(SICK)
-.087
.079
.146
-.132
.380
-.248
-.193
# OF
DAYS
UNEXCUSED
ABSENCE
-.166
-.295
.789**
-.344
-.183
-.052
.0167
# OF
DAYS
ABSENT
DUE TO
INJURY
.133
-.072
-.081
.456
-.227
-.204
.028
# OF
DAYS
OTHER
-.090
-.153
.989**
-.389
-.095
-.281
-.176
TOTAL
ABSENT
-.116
-.317
.806**
-.093
-.219
-.271
-.032
TOTAL
AVAIL .
(1/74)
.056
.216
-.123
.158
-.301
.097
-.123
* significant at a. = 0.05
** significant at 0. = 0.01
-------
TABLE 9
CORRELATION COEFFICIENTS OF PREVIOUS EXPERIENCE CHARACTERISTICS
AND MEASURES OF ABSENTEEISM AMONG BLACK EMPLOYEES (N=ll)
Record of Arrest
Record of Previous Job
Terminiation
Record of Debt
Work Missed Due to
Illness
Military Service
Previous Employment :
2 jobs
3 jobs
4 jobs
5 jobs
# OF
SICK
DAYS
ACCRUED
(1/73)
.456
.218
ft**
ft**
.138
.449
-.329
.374
ftft*
# OF
DAYS
EXCUSED
ABSENCE
(SICK)
.029
.048
ftft*
***
.707**
-.375
-.075
.658**
ftft*
*
// OF
DAYS
UNEXCUSED
ABSENCE
-.593*
.048
ft**
***
.094
-.303
.262
.221
***
# OF
DAYS
ABSENT
DUE TO
INJURY
.298
-.154
***
ft**
-.298
.154
-.199
-.199
ft**
// OF
DAYS
OTHER
-.346
-.149
***
**ft
.345
-.149
-.194
.516
***
TOTAL
ABSENT
-.387
-.049
ft**
***
.125
-.509
.089
.302
***
TOTAL
AVAIL.
(1/74)
.381
.237
**ft
ftft*
-.078
.533*
-.246
.133
ft*
* significant at a = 0.05
** significant at a = 0.01
•;;•,';* coefficient of correlation cannot be computed.
-------
Step-Wise Regression
Step-wise regression is utilized to select the independent
variables that provide the best prediction. The significance of
the regression-coefficient variable is measured by the F statis-
tic. If the F statistic is insufficient, the regression sequenc-
ing terminates. The formula for this is represented as follows:
= bn + b,x, + b0x0 + . . . b x
0 11 22 n n
where:
Y = dependent variable
b_ = constant term
bn = b value of the nth independent variable
The equation for each of th'e following dependent variables
is as follows:
1) Var 018: No. of Days Available, 1973
(10 percent level of significance)
Y „ = 4.79 (days) + 0.46 (Var 004) + [-.216(Var Oil)] +
[-4.18(Var 006)] + 4.99(Var 013) +
[-3.31(Var 005)] + .09(Var 018) + [-2.48(Var
016)] + .12(Var 002) + [-0.81(Var 017)] +
.01(Var 009)
Due to similarity of the dependent variables, the detail
results of step-wise regression is shown only for Var 020,
the number of unexcused absences, and Var 023, the number of
total absences.
2) Var 020: Number of Unexcused Absences
(10 percent level of significance)
Y = -135.15 + 0.24(Var 010) + 2.41(Var 003) +
^U [-4.74(Var 005)] + 1.34(Var 004) +
[-0.63(Var 001)] + 8.69(Var 013) +
[-6.07(Var 017)] + [-0.14(Var 018)]
3) Var 023: Total Number of Absences
(10 percent of significance)
Y 3 = 29.1 + -9.3(Var 017)
1 = White
where: Var 017 = Race and Q _ Black
From this equation it may be concluded for the test City
that the average white worker was absent approximately 20 days
per year. The average black worker was absent approximately 29
days during the year.
68
-------
CONCLUSIONS
In general, the investigation provided affirmative evidence
as to the existence of statistically significant relationships
between the following personal and previous experience charac-
teristics of the solid waste collection workers in the test City
and various measures of absenteeism. The most important charac-
teristics are:
1) Age: It appears that the presumption that younger
workers are more likely to be absent from work does
not hold in this work system. In fact, it was indi-
cated that as age increases, the number of days missed
due to illness increases. This may be due in part to
the demanding physical nature of the work itself or
to increased family responsibilities.
2) Number of Dependents: From the analysis conducted,
it appears that the more dependents the solid waste
worker has, the more likely he is to be absent from
work due to excused illness. This may be a result
of the increased opportunity to contract communicable
illnesses from members of his family, or it may
be the case that the large number of dependents who
are themselves ill require the worker's attention
and he exercises his option to use 12 days per
year paid sick leave to manage this off-the-job
responsibility.
3) Race: From the step-wise regression, the average white
worker in the test city was absent approximately 20
days annually, while the average black worker was
absent approximately 29 days annually.
Recommendations
The following recommendations for personnel administration
are suggested:
1) That information provided to the city as a result
of the prospective employee completing the application
form be verified in full regarding those elements
that may affect absence behavior, i.e., arrest and
previous employment.
2) That incentives be initiated to reduce absenteeism.
3) A change be made in the recruitment and testing
of solid waste personnel that provides management
with more effective decision information regarding their
selection. One example of this change would be to
eliminate from the employment application form
69
-------
requests for information that are ineffective as
inputs into management's decision process. For
example, the question of previous illness, and/or
the incidence of debt.
70
-------
FOOTNOTES
Personal history data submitted at the time of job
application.
2
At the time of application and as of 12/31/73.
Cited in Manpower Profile and Analysis in the Field
of Solid Waste Management (Vol. 1), by Applied Management Science,
Inc. (unpublished manuscript prepared for U.S. Environmental
Protection Agency under Contract No. 68-03-0041), 1973, p.4.
4
IBID, p. 7.
5IBID, p. 7.
6IBID, p. 7.
7IBID, p. 7.
8IBID, p. 16.
9
Municipal wastes include residential, commercial, demoli-
tion, street and alley sweeping, and miscellaneous.
First Report to Congress, Resource Recovery and Source
Reduction, 3rd Ed., U.S. Environmental Protection Agency, 1974.
11Gellin, Gerald A. and Zavon, Mitchell R., "Occupa-
tional Dermatosis of Solid Waste Workers," ARCH Environmental
Health, Vol. 20, April, 1970, pp. 510-515.
12IBID, P. 151.
Cimino, Joseph A. and Raab, Richard, "Study of the Carbon
Monoxide Emission from Sanitation Trucks and Levels of Carbo-
xyhemoglobin in Workers" (Environmental Protection Administration:
New York City, October 1967).
1 4
IBID, p. 9.
Vroom, Victor H., Work and Motivation, John Wiley and
Sons, Inc., New York, 1964.
16IBID, p. 178.
Shepherd, W.J., "Absence from Work in Relation to Wage
Level and Family Responsibility," Journal of Industrial Medicine,
1958, Vol. 15, 53-61.
1 p
Baumgartel, Howard and Sabol, Ronald, "Background and
Organizational Factors in Absenteeism1', Personnel Psychology,
1959, Vol. 12, pp. 431-443.
71
-------
19IBTD, p. 439.
20
IBID, p. 440.
21
Naylor, James C. and Norman L. Vincent, "Predicting
Female Absenteeism," Personnel Psychology, 1959, Vol. 12, pp. 81'
84.
22
Scollay, R.W., "Validation of Personal History Items
Against a Salary Increase Criterion," Personnel Psychology,
1956, Vol. 9, pp. 325-335.
23IBID, p. 335.
24
Scollay, R.W., "Personal History Data as a Predictor
of Success"; Personnel Psychology, 1957, Vol. 10, pp. 23-26.
25IBID, p. 26.
2 6
Minor, Frank J., "The Prediction of Turnover of Clerical
Employees"; Personnel Journal, Vol. 51, May, 1963, pp. 393-402.
27
Robinson, David D., "Prediction of Clerical Turnover in
Banks by Means of a Weighted Application Blank"; Journal of
Applied Psychology, Vol. 56, No. 3, 1972, p. 282.
72
-------
5 WORK MEASUREMENT
TECHNIQUES AVAILABLE
In general, the work measurement techniques available for
establishing time standards for manual work include judgement of
management, historical records, observation time study, work
sampling, and predetermined motion-time systems.
The management judgement techniques considers the influence
of variables directly affecting the time required to perform the
task in question. It also considers, by the very nature of
judgement, many extraneous variables that influence actual time.
The judgement technique, for this reason, is not regarded as
accurate or consistent.
Historical records suffer from the same shortcomings as
management judgement, and neither technique offers a sound basis
for methods improvements. For example, in waste collection,
records of truck time out and in are not sufficient to calculate
work content time standards.1*
Observation time study, while more scientific than the
methods discussed above, also relies on judgement when a per-
formance rating factor is applied to the average actual time
to obtain the normal time. This technique is more consistent
than historical and judgement techniques and can be used for
analysis of most waste collection activities.
Work sampling, a statistically sound technique, can produce
accurate results. Random observation work sampling is useful
for longer cycle supportive types of solid waste collection/
disposal operations, e.g., landfill and garage activities.
Short interval systematic sampling is useful to determine
avoidable and unavoidable delays in the collection process.
Work sampling does not lend itself to the microscopic measure-
ment and analysis of short cycle, highly repetive elements which
are prevalent in curbside collection activities.
A predetermined motion-time system, e.g., MTM, or Work
Factor is recommended to perform analysis and measurement of
detailed collection activities at curbside.
*References and footnotes at end of section.
73
-------
APPLICATION OF TECHNIQUES
2
A study was completed by Quon, Charnes, and Wersan to
simulate collection in Winnetka, Illinois. Their main objective
was to predict the effect of changes in truck capacity, service
density (stops/mile), waste at a stop, and haul distance on
collection efficiency. Historical data for 43 truck trips was
used for one service density. Haul velocities were obtained
from a prior California study. Much of this work was used in a
later study by Truitt, Liebman and Kruse3'4 to devise mathemati-
cal models for calculating collection times in the northwest
quadrant of Baltimore. The de ficiencies of this study in-
cluded its concentration on short range objectives, lack of
ability to predict the impact of new collection methods, and no
development of collection areas. Both the Winnetka and Balti-
more studies were based entirely on limited historical data.
Several other investigations5'6'^ have also relied on historical
data.
A project was completed by Wyskida '° to determine solid
waste collection routes for Huntsville, Alabama. Three types
of block-by-block information were obtained for route develop-
ment :
1) Time the collection crew expends from the beginning of
one block to the end of the same block,
2) Street identification,
3) Travel time required for the collection vehicle to
move to and from various segments of the City and the
landfill.
Collection times were recorded for approximately 5000
blocks by field timing, thus eliminating the use of historical
techniques, and obtaining much improved results over previous
work. Average collection times were then calculated by type of
collection customer within four defined City zones.
In 1969, Stone10 completed a study to compare the effi-
ciencies of one-, two- and three-man crews for collecting
residential solid waste. Field observations were conducted of
the collection process in four municipal systems and two private
systems in Southern California. This data provided a basis for
establishing time standards, and was used to simulate the col-
lection of a given route by a single truck and crew. The report
recommended that additional studies expand the use of engineered
work measurement for evaluating waste collection.
Between 1969 and 1970, Xenia, Ohio11 applied work measure-
ment to assist in the redesign of collection routes. Individual
routes were designed to require 320 to 420 minutes of daily
74
-------
collection time C5.3 to 7.0 hours). One minute was allowed for
each, residential customer, and an average collection time for
each commercial customer was individually measured. One-quarter
of a minute was deducted from each stop not requiring backdoor
pickup, and one-tenth of a minute was deducted if plastic bags
were used.
More recent work by Shell and Shupe-1-2 developed a com-
puterized model to predict work content for residential waste
collection in Cincinnati, Ohio. The total start and completion
time was divided into five major elements.
1) Time out and in from the garage
2) Time for truck travel to and from and time at the
disposal site
3) Time at individual stops
4) Time for double sided collection
5) Time for travel between stops.
Limitations for this investigation were:
1) Field work measurement was not completed for all time
elements
2) Since no detail stop-by-stop waste generation and con-
tainer data was available, work content within a given
sub-district was averaged among the total number of
assigned crews.
The most useful waste collection standards require that
work content for individual intersection-to-intersection times
be computed using appropriate work measurement and stop-by-stop
waste generation data.13,14
WORK SAMPLING FOR SOLID WASTE COLLECTION ACTIVITIES
The work-sampling field study was designed to randomly
observe collection activities throughout the City of Covington.
Travel activities to and from the disposal site and garage were
excluded from the study. After surveying the City, it was
determined that certain delays would be dependent upon the type
of area in which the data were gathered. For this reason,
Covington was classified into three general area types.
The first type was the Residential — single un.it (SRES) as
illustrated in Figure 13. This includes both city and suburL>an
75
-------
OF
y,
•
•
••
-i
•
.
I
I
. .
Figure 13. Residential, Single Unit
areas in which the single family dwelling is the predominant
type of housing. A characteristic of this type of area is the
necessity of one stop for each individual family unit, and
mostly off-street parking.
The second area type is the Residential—multi-unit (MRES)
as illustrated in Figure 14. Under this category is found those
areas in which the multi-family housing units are the major type
of dwellings. This includes housing projects ana apartment
buildings not included on commercial collection routes. A
characteristic of this type of area is the ability to often col-
lect in one stop the solid waste of several family units.
The final area included in the study is the downtown area
(DTWN) as illustrated in Figure 15. Within this category are
found those housing units in the downtown area and the smaller
businesses that are not collected on commercial routes. The
percentages total samples taken in each area type were:
SRES
MRES
DTWN
52.05%
21.51%
26.44%
When making the observations in each area an estimate was
made of irking and traffic conditions, and the amount of delay
76
-------
I
- ..
..*—- ,
Figure 14. Residential, Multi-unit
based on the following four-point scale:
None = 1.0
Light = 2.0
Medium = 3.0
Heavy = 4.0
The weighted average results of these estimates are presented
in Table 10.
Table 10. Parking, Traffic, and Delay Index by Area
AREA
SRES
MRES
DTWN
PARKING
2.7
3.3
4.0
TRAFFIC
1.7
2.0
4.0
DELAY
ESTIMATE
1.9
3.0
4.0
This data indicates that in the DTWN area collection activities
are significantly affected by delays over which the crew has no
control. Figure 16 illustrates the conditions of maximum delay,
: leant i Lays will ^Iso occur to a lesser extent in the
multi-unit residential areas. Minimum delay is encountered in
the single unit resiuouci^l areas, as illustrated by Figure 17.
77
-------
'
.
•.~s f-f— r-»
" i FT
'
•
,
Figure 15. Downtown
/ 7 r"~" >!
,' J- i ...
<
- .
-^i—. •-
r
Figure 16. Maximum Delay Conditions
78
-------
I • "« .-• - r r ~~-~*ir* y f —r «rr
I
•
-
'
•
"
Figure 17. Minimum Delay Conditions
Approximately 3000 work sampling observations were recorded
over a 10-week period. These observations were grouped by
activity, using the codes in Table 11.
79
-------
Table 11. Waste Collection Activity Codes
Activity Code
not available for recording NA
emptying cans ECC
emptying bags ECB
emptying equivalent cans ECE
walking with full cans WCC
walking with full bags WCB
walking with equivalent cans WCE
walking with empty cans WEC
walking without bags--same stop WEB
walking without equivalent cans--same stop WEE
walk to next stop WK
ride to next stop RD
compacting ' PK
site preparation SP
truck backing BK
litter pickup LT
break BRK
The following Tables summarize the data gathered in the
study. Table 12 outlines the functional breakdown, as a percen-
tage of crewmen's total work activity based on the total data
(column 2), and according to the three previously mentioned
areas types (columns 3-5). Percentages were calculated by
dividing the number of specific activity observations by the
total number of observations, and multiplying by 100 (reference
computer program, Appendix 9.6). Table 13 lists percentage of
occurrence adjusted to remove the effects of unrecorded observa-
tions (those noted as NA—not available). The adjusted data
will be used in later analysis.
The work sampling activities were grouped into the following
three classifications:
1) Activities that are productive work , that is, a direct
part of the collection process of loading the waste in-
to the truck.
2) Activities that are supportive productive work. These
are indirect activities including delays that are
largely dependent on the physical environment in which
the operations are taking place.
3) Those activities that are non-productive and not part
of the solid waste collection process (i.e., personal
breaks). These are controllable directly by the crew.
80
-------
Table 12. Original Field Data Summary
PERCENTAGE OF OCCURRENCE
ACTIVITY
CODE
NA
ECC
ECB
ECE
WCC
WCB
WCE
WEC
WEB
WEE
WK
RD
PK
SP
BK
LT
BRK
AVERAGE FOR
ALL THREE
AREAS
2.
13.
2.
3.
6.
3.
2.
4.
0.
0.
18.
12.
10.
8.
1.
0.
6.
980
686
235
817
425
911
328
935
559
186
249
663
335
845
862
838
145
SRES
SINGLE
RESIDENCE
3
12
2
1
5
4
1
6
0
0
21
13
12
10
1
0
2
.120
.132
.253
.733
.546
.506
.560
.239
.347
.173
.317
.345
.305
.572
.906
.693
.253
MRES
MULTI
RESIDENCE
3
17
3
4
7
5
1
1
0
0
12
7
6
6
2
0
18
.286
.841
.286
.695
.042
.164
.878
.878
.000
.000
.208
.981
.103
.573
.817
.939
.312
DTWN
DOWNTOWN
2
13
1
7
7
1
4
4
1
0
16
14
9
7
1
1
4
.465
.732
.480
.394
.746
.761
.225
.577
.408
.352
.549
.789
.507
.042
.056
.056
.930
81
-------
Table 13. Adjusted Field Data Summary
PERCENTAGE OF OCCURRENCE
ACTIVITY
CODE
ECC
ECB
ECE
WCC
WCB
WCE
WEC
WEB
WEE
WK
RD
PK
SP
BK
LT
BRK
AVERAGE FOR
ALL THREE
AREAS
14.
2.
3.
6.
4.
2.
5.
0.
0.
18.
12.
10.
9.
1.
0.
6.
09
29
91
59
0-1
39
06
57
19
71
98
60
07
91
86
33
SRES
SINGLE
RESIDENCE
12
2
1
5
4
1
6
0
0
21
13
12
10
1
0
2
.52
.32
.79
.72
.65
.61
.43
.36
.18
.99
.76
.69
.90
.97
.71
.32
MRES
MULT I
RESIDENCE
18
3
4
7
5
1
1
0
0
12
8
6
6
2
0
18
.41
.39
.85
.25
.33
.94
.94
.00
.00
.64
.27
.32
.81
.92
.97
.97
DTWN
DOWNTOWN
14
1
7
7
1
4
4
1
0
16
15
9
7
1
1
5
.08
.44
.58
.94
.82
.33
.69
.45
.36
.97
.16
.75
.22
.08
.08
.05
82
-------
The first classification, productive work/is comprised of
the following:
1) Emptying of waste containers ECC
ECB
ECE
2) Carrying full containers to truck WCC
WCB
WCE
3) Returning emptied containers or WEC
walking to get others at same stop WEB
WEE
The supportive productive category is comprised of the
following:
1) To next stop SK
RD
2) Compacting and truck position PK
BK
3) At curbside or street SP
LT
The non-productive activity is personal time, BRK.
Table 14 below presents frequency of occurrence for each
work classification by area.
Table 14. Work Classification, Frequency of Occurrence
WORK CLASSIFICATION
Productive work
Supportive productive
work
Worker controlled
breaks
AVERAGE(%)
39.08
54.13
6.33
SRES (%)
35.58
62.02
2.32
MRES(%)
43.29
37.93
18.97
DTWN C%
43.68
51.26
5.05
These results show that in all areas significantly less than
one-half of the workers' time is spent in direct productive work
(loading solid waste). In the SRES area, nearly two-thirds of
the time is spent in supportive productive activities of the job
83
-------
The maximum break time, 18.97 percent, was observed in the MERS
area.
The following major conclusions regarding work sampling
are offered:
1) Work sampling is a useful technique for analyzing
waste collection work activities. The method is valua-
ble for determining the percentage of time required for
productive and supportive work, and non-productive
activities.
2) Over one-half of the waste collection work day in the
field (excluding disposal time) is consumed in suppor-
tiVe activities. These activities include unavoidable
delays which are beyond the control of the worker. An
example of an unavoidable equipment delay is compacting,
which requires over 10 percent of the collection time.
SOLID WASTE COLLECTION STANDARDS DEVELOPMENT
The results of work measurement permit the establishment of
work standards, that is, standard times that accurately reflect
a normal work rate for an average worker. The work measurement
techniques utilized in this study include work sampling as ex-
plained in the last Subsection, observation time study, and MTM.
Field Observations
Field observations were completed for the following major
areas:
1) Stop-by-stop street and containerization data.
2) Intersection-to-intersection times.
3) Elemental times, e.g., walk, compact, delays.
4) Crew walk patterns during pickup.
5) Truck velocities between stops.
Stop-by-stop data: Detailed stop-by-stop data was recorded
by field survey teams that accompanied the waste collection
crews as they collected all existing routes. Nearly all loads
from surveyed routes were weighed before disposal at the land-
fill. All of the information was coded and stored in files on
either magnetic tape for batch processing or on disks for real-
time on-line computer retrieval (reference Section 6).
84
-------
Intersection Times: In addition to stop-by-stop data ob-
tained for the entire City of Covington, total collection times
were recorded for 1442 blocks. These data blocks with field
times were utilized to create a separate data file, readily
sortable and accessible by any one or combination of data para-
meters, e.g., street width, or stop distance. Table 15 sum-
marizes the containerization and distance data for the blocks
according to seven arbitrary collection categories.
While the data blocks with field times were available for
a multiple linear regression analysis, the results were tempered
with judgement based on the work measurement analysis. For ex-
ample, regression analysis yields the following time equation
from the data for double-sided collection, street width greater
than three cars, stop distance greater than 100 feet (sample
size = 65):
T = .206 + .0439(B) + .0783(0) + .2110 (EC) + .00281(D)
where:
T = Block collection time in minutes
B = Number of bags
C = Number of cans
EC = Number of equivalent cans
D = Distance in feet between intersections
The constants are of the correct magnititudes and the resulting
coefficient of correlation R is a reasonable .864. However,
for other categories, e.g., double-sided, width less than 4 cars,
stop distance less than 100 feet, the constants resulting from
linear regression analysis are unreasonable and in some cases,
negative, while R values are between .5 to .6. This clearly
indicates that regression analysis alone is inadequate for es-
tablishing the linear constants for the collection time equation,
and that work measurement analysis must be completed.
Elemental Times: While intersection-to-intersection times
are useful for confirming calculated time standards applied to
a given block, intersection times alone are inadequate for set-
ting standards. Instead, work measurement must be applied to
all elements of the collection operation, e.g., travel between
stops, time to pick up containers from curbside, transport to
truck, compact time. Results from the field indicate that un-
obstructed walk velocities are near MTM normal time (5.3 TMU's/
foot or 5.2 feet/second), both with and without containers.
Once the loading hopper is filled, 25 to 30 seconds are required
for most trucks to compact. While some simultaneous activity
may occur during compaction (preparation to dump, some dumping,
return of empties), the majority of the time is an unavoidable
delay. Since 8 to 10 cans will fill the hopper, the compaction
85
-------
Table 15. SUMMARY OF HISTORICAL FIELD AND TIME DATA FOR 1442 BLOCKS
CATEGORY
SS < 100ft
SS >100ft
SS com-
bined
DS Scans
3S ^lOOft
<13cans
OS >100ft
>3cans
DS >100ft
SAM-
PLE
SIZE
205
164
369
635
228
145
65
TlME,min.
x a-
3.780
2.732
3.314
5.378
4.373
2.855
2.846
2.41
2.11
2.34
3.7;
2.73
2.54
2.53
BAGS (L)
x a
4.39
3.68
2.04
3.31
5.3
4.2
2.7
6.8
CANS (L)
x a
LI. 40
7.88
4.26
5.11
36.2
5.8
4.1
4.9
EQ.C. (L)
x a
2.53
2.11
.98
2.51
20.2
3.7
2.11
5.4
BAGS (R)
X O
5.75
2.81
4.44
5.01
3.33
1.35
1.06
5.84
3.48
5.14
15.1
4.4
3.36
2.7
CANS (R)
x a
11.7'
6.03
9.22
10.53
7.62
2.72
2.11
7.70
5.54
7.39
17.9
6.2
3.6";
3.5'
EQ.C. (R)
X a
3.63
2.32
3.05
1.78
1.60
.91
1.09
6.26
4.83
5.70
3.34
3.0
4.3
3.7
DISTANCE,
feet
x a
368
399
382
385
339
387
400
178
266
222
188
134
252
254
STOPS
X
5.68
2.35
4.20
7.2
5.8
2.5
2.4
\VG . STOP
DIST. ,ft
X
68
198
126
58
64
172
197
00
SS: Single-Sided Collection
DS: Double-Sided Collection
x: Arithmatic Mean
a: Estimated Standard Deviation
(L): Left Side of Street
(R): Right Side of Street
-------
delay time prorated on an individual can basis may be as high as
4 seconds.
Other unavoidable delays form an important segment of the
total collection time and vary considerably throughout the city.
Included are delays due to street and pedestrian traffic, clean
up at setout site and rear of truck, parking congestion and
traffic lights. As discussed in the last section, work sampling
techniques were used to estimate delay times and causes.
Crew Walk Patterns During Pickup: A complexity inherent
in setting standards for multi-man crews arises from the varia-
tions in crew walk patterns. Although the interaction patterns
among the two workers and the truck are somewhat different for
each crew, certain patterns predominate. Field observations
were used to establish crew and truck patterns. The major
categories observed were:
1) Single-sided collection with no curbside parking
(therefore truck approaches curb).
2) Single-sided collection with parking, thereby requiring
manual transport of containers to and from truck.
3) Double-sided collection without right curb parking.
4) Double-sided collection with right curb parking.
For stops that are closely spaced, the workers will walk between
stops, while for interstop distances greater than a certain criti-
cal distance, time is saved by riding the truck. This cross-over
distance, which is clearly a function of truck velocity, walk
speed, and walk patterns, is examined in more detail later in
this Subsection.
Truck Velocities Between Stops: The truck used in the
velocity analysis was a standard eighteen cubic yard rear load
packer truck supplied by the City of Covington, and was three-
fourths filled. Truck velocities were measured over distances
of 50 to 200 feet at 50 feet intervals as shown in Figures 18
and 19. On the basis of these measurements, average velocities
for each of the distances were then computed and are graphically
depicted in Figure 20.
Laboratory
On the basis of field observations, the manual process of
collecting solid waste was divided into the following seven
elements for laboratory simulation:
1) Walk from truck to container set-out loccttl .1.
87
-------
(
<
k
I
-
J,
Figure 18. Field Measurement of Truck Velocity, Level Terrain
.
.-5.
'
-X
'
•3L
. 9
_ -
E'igure 19. Field Measurement of Truck Velocity, Incline
88
-------
I" T" i
Q
S
o
o
w
CO
W
H
U
O
H
O
w
-rrirhTti+H
' ' I i ! • ' 1
i ' \ ~ '• ' ! • ' T~!
: ! !•' : : /.• : ! : i ! : ! i ' .• • ; ' j i M ! • : ; ;
_:5a::::75^ :100 ::125:v: 150 175: 200 225
250
DISTANCE BETWEEN STOPS, LEVEL TERRAIN (FEET)
Figure 20. Average Truck Velocity
89
-------
2) Grasp and pickup full containerCs).
3) Walk to truck with full containerCs).
4) Dump container (si.
5) Walk back to container storage location with empty
container Cs} .
6) Place empty containerCs) on the ground.
7) Walk back to truck.
A typical two-lane city street, as shown in Figure 21, was simu-
lated in the laboratory. The collection truck was placed in a
lane so that the walking distance from the truck to the storage
locations on each side .of the street were twelve and nineteen
feet, respectively.
Each of the above seven elements of the collection process
were then stopwatch timed over a number of trials. The resulting
total times were leveled over a number of trials and a normal
time for each step in the process was determined. This process
was repeated with variations in the number and type of containers
picked up, and varied for the twelve and nineteen feet distances.
The normal times for each of the steps were then added together
to determine the total normal time required for pickup of a
given number of containers from one or both sides of the street
by one and two laborers. As an example of the results, the time
data for collection of cans from one side of the street is shown
in Figure 22.
On the basis of manual collection and truck movement times,
collection times were computed for crews riding the truck between
collection stops. The results are shown in Table 16. Adjusting
the normal walking velocity CMTM) for angle movement, the average
forward walking velocity between stops was three feet per second.
The resulting total collection times as computed for crews walk-
ing are shown in Table 17. These results permit crossover points
to be determined as illustrated in Figure 23. This Figure repre-
sents the total time for one-sided collection by one worker. N
is the number of cans. Tw is walking time, Tr is the riding time.
The theoretical walk/ride crossover point appears to be at some
distance greater than 50 feet, that is, the crew should walk be-
tween stops spaced less than 50 feet apart.
Summary and Conclusions
On the basis of the field observations and laboratory simu-
lations, time predictive equations have been developed for major
collection categories, e.g., single-sided collection with average
stop spacing greater than 100 feet. The collection time required
90
-------
12
\
19
w
u
PH XI
U
Q P
<; &
O EH
J
12'
12
w
O
O
w
s
H
<
EH
£5
O
u
Figure 21. Laboratory Collection Model
91
-------
r—r-r T • ;li "•~1~r-" i
I . ' ! • '/ \ r ' : '
NUMBER OF CANS AT ONE SIDE (SINGLE SIDED COLLECTION)
Figure 22. Manual Collection Times
92
-------
Table 16. COLLECTION TIMES, RIDING5''
N s DSTP VTRK RD Tr
1
2
3
4
5
6
0 00 18.26
0 00 26.68
0 00 44.94
0 00 53.36
0 00 71.62
0 00 80.04
DSTP VTRK RD Tr
15 1.4 10.7 28.96
15 1.4 10.7 37.38
15 1.4 10.7 55.64
15 1.4 10.7 64.06
15 1.4 10.7 82.32
15 1.4 10.7 90.74
DSTP VTRK RD Tr
30 2.80 10.7 28.96
30 2.80 10.7 37.38
30 2.80 10.7 55.64
30 2.80 10.7 64.06
30 2.80 10.7 82.32
30 2.80 10.7 90.74
DSTP VTRK RD Tr
60 5.4 11.1 29.36
60 5.4 11.1 37.78
60 5.4 11.1 56.04
60 5.4 11.1 64.46
60 5.4 11.1 82.73
60 5.4 11.1 91.14
N
1
2
3
4
5
6
DSTP VTRK RD Tr
100 7.4 13.5 31.76
100 7.4 13.5 40.18
100 7.4 13.5 58.44
100 7.4 13.5 66.86
100 7.4 13.5 85.12
100 7.4 13.5 93.54
DSTP VTRK RD Tr
150 9.9 15.2 33.46
150 9.9 15.2 41.88
150 9.9 15.2 60.14
150 9.9 15.2 68.56
150 9.9 15.2 86.82
150 9.9 15.2 95.24
DSTP VTRK RD Tr
200 10.65 18.8 37.06
200 10.65 18.8 45.48
200 10.65 18.8 63.74
200 10.65 18.8 72.16
200 10.65 18.8 90.42
200 10.65 18.8 98.84
CO
"Cans only for single sided collection by one man riding to next stop.
N = No. of cans
DSTP = Distance to next stop in feet
VTRK = Average velocity of truck in feet/sec.
RD = DSTP/VTRK in seconds
Tr = Total collection time in seconds
-------
Table 17. COLLECTION TIMES, WALKING-
N
1
2
3
4
5 '
6
DSTP WLK TW
0 0 14.26
0 0 22.65
0 0 39.91
0 0 4-5.30
0 0 59.56
0 0 67.95
DSTP WLK TW
15 5 19.26
15 5 27.65
15 5 4-4.91
15 5 50.30
15 5 64.56
15 5 72.95
DSTP WLK TW
30 10 24.26
30 10 32.65
30 10 49.91
30 10 55.30
30 10 69.56
30 10 77.95
DSTP WLK TW
60 20 34.26
60 20 42.65
60 20 59.91
60 20 65.30
60 20 79.56
60 20 87.95
DSTP WLK TW
120 40 54.26
120 40 62.65
120 40 79.91
120 40 85.30
120 40 99.56
120 40 107.95
Cans only for single sided collection by one man walking to next stop.
VMAN = Forward Velocity of Collector = 3 ft/sec
N = No. of cans
DSTP = Distance to next stop in feet
WLK = DSTP/VMAN in seconds
TW = Total collection time in seconds
-------
CO
/ "i I > " 1 i i ; ' '
DISTANCE BETWEEN STOPS (FEET)
N=Nuraber of cans, Tw=Time walking, TR=Time riding
Figure 23. Walk/Ride Crossover Points
9S
-------
for a given block face is predicted by inputing into the appro-
priate equation containerization counts and street lengths for
the block. These results were utilized in Section 7 for waste
collection route development in the test City.
It is concluded that management's ability to estimate work
time is essential if it is to:
1) Provide equitable, balanced work assignments, thereby
controlling overtime and minimizing interpersonnel and
union/management conflicts.
2) Monitor on a continuing basis the productivity of various
components of the existing collection/disposal system.
3) Respond to changing geographical waste generation
patterns resulting from new construction, abandonment
and demolition, annexation, and other shifts in land
use.
4) Project the impact of possible changes in service level
such as changes in collection frequency, setout service,
or containerization, e.g., cans to bags.
5) Evaluate new equipment available on the market such as
higher density load packers, or one-worker sideloaders.
6) Plan for major changes in collection constraints, e.g.,
changes in disposal sites or crew size.
7) Implement a monetary incentive program to encourage
higher productivity by sharing savings with personnel.
96
-------
FOOTNOTES
Shell, R. L., and Shupe, D. S., "Work Standards for Waste
Collection," Proceedings, Annual Systems Conference, American
Institute of Industrial Engineers, 1973.
2
Quon, J. E., Charnes, A., and Wersan, S.J., "Simulation
and Analysis of a Refuse Collection System," Journal of the
Sanitary Engineering Division, American Society of Civil
Engineers, Vol. 91, No. SA5, October 1965.
Truitt, M. M., Liebmann, J. C., and Kruse, C. W., "Simula-
tion Model of Urban Refuse Collection," Journal of the Sanitary
Engineering Division, American_Society of Civil Engineers, Vol.
93, No. SA2, April 1969.
4
Truitt, M. M. , Liebmann, J. C., and Kruse, C. W-, Mathe-
matical Modeling of Solid Waste Collection Policies, Volumes 1
and 2, USPHS Publication 2030, 1970.
Bubier, R. H., "Modern Refuse Vehicle Routing," Public
Management, August 1973.
Shupe, D. S., and R. L. Shell, "Balancing Waste Collection
Routes," Journal of Environmental Systems, Vol. 1, No. 4,
December 1971.
Clark, R. M., and Gillean, J. L., Systems Simulation and
Solid Waste Planning: A Case Study, Report 67015-73-12,
National Environmental Research Center, USEPA, 1973.
o
Wyskida, R. M., and Gupta, J. N. D., "IE's Improve Cities
Solid Waste Collection," Industrial Engineering, Vol. 4, No. 6,
June 1972.
g
Wyskida, R. M., "A Logical Approach to Solid Waste Collec-
tion Routing," Proceedings, Twenty-fifth Anniversary Conference
American Institue of Industrial Engineers, 1973.
Stone, R. and Company,Inc., A Study of Solid Waste Collec-
tion Systems Comparing One-Man with Multi-Man Crews, USPHS
Publication 1892, 1969.
Employee Incentives To Improve State and Local Government
Productivity, National Commission on Productivity and Work
Quality, Pub. No. CP75015, Washington, D.C., 1975.
12
Shell, R. L., and D. S. Shupe, "Predicting Work Content
for Residential Waste Collection," Industrial Engineering, Vol.
5, No. 2, February 1973.
97
-------
13
Shell, R. L., and D. S. Shupe, Pilot Research Project for
the City of Cincinnati, Department of Public Works, Division of
Waste Collection, University of Cincinnati, 1971.
•^Fuertes, L. A., Hudson, J. F., and Marks, D. H., Analysis
Model for Solid Waste Collection, Department of Civil Engineer-
ing, Massachusetts Institute of Technology, 1972.
98
-------
6 COMPUTERIZED DATA BANK
INTRODUCTION
The data bank consists of several files containing solid
waste information on every collection stop in Covington with
physical and geographical characteristics of each block face.
The stop-by-stop data was obtained by field survey teams
that accompanied the waste collection crews as they collected
all existing routes (Street Collection Data Form, Appendix 9.3).
A typical route trace pattern is shown below in Figure 24. Nearly
all loads from surveyed routes were weighed by a local feed supply
==~~rlFS== ™i':\\i£="a==^Js:=Ss^:l\ii fffl**»*W-\r<
Figure 24. Example Map of Stop-
By-Stop Field Survey
99
-------
company before disposal at the landfill (Weigh Station Record
Form, Appendix 9.4).
All of the information was coded and stored in files on
either computer magnetic tape for batch processing or on direct-
access devices for real-time online computer retrieval.
This data base was created to provide detailed information
about the test City that can be rapidly accessed, sorted, and used
for computation and analysis. Since the information stored in
the data bank was critical to all subsequent computations, it
was essential that data errors be minimized. Therefore, all
data transfer operations were verified during the data computer-
ization.
The remainder of this Section describes the methodology used
to develop the data bank, including the transfer of information
from the field survey, and defines the data classification format.
Encoding
The first task following completion of the field survey
forms was to determine how the information should be transferred
onto a standard (80-column) IBM card. This was achieved by
assigning codes for different segments of the information. There
are over 700 streets in the City and each street was given a nu-
merical code number for identification purposes (see Appendix
9.5). A separate file containing all street names with their
identification codes was stored on magnetic tape.
The coding of the survey information required data class-
ification as follows:
Summary Record: This record summarized the collection data
for a given route on a given day. The Summary data contains the
following specific information:
Date of the survey
Route number (existing)
Truck number
Time at the start of the day
Truck mileage at the start of the day
Number of trips to the landfill (loads)
Total number of bags collected
Total number of cans collected
100
-------
Total number of equivalent cans collected
Header Record: During pickup, the path of a collection
crew was recorded as a sequential series of approximately
straight-line street segments, each identified (for example) as
"on Pike from 8th to 12th." The header record contained physical
and geographical data for a given street segment. The information
coded on this record is:
Street segment identification (on , from , to )
Street width
Parking, if any, on the left side of the street
Parking, if any, on the right side of the street
Load number
Time at the first stop in the pickup run
Stop Record: This record contained information on every
collection stop with in the City. In general, there are several
stops in each street segment and for each of these stops there
was on record containing the information:
Stop number
Containerization, left side of street
1) Number of bags
2) Number of cans
3) Number of equivalent cans
Containerization, right side of street
1) Number of bags
2) Number of cans
3) Number of equivalent cans
Number of loadpacking cycles, if any
Delay from normal operation, if any
Those stops located near intersections within a street segment
contain the following additional information:
101
-------
Name of the street reached
Time at new street intersections
Distance travelled (in map inches)
All data was key punched on IBM cards and then copied on
magnetic tape by using the IBM utility program IEBGENER.1*
Information on tape permits ease in handling and provides effi-
cient retrieval.
DESCRIPTION OF PROGRAMS
There were 14 major programs in the overall collection sys-
tem. In this subsection, each major program is discussed.
Program 1, Survey Data Verification
This program used the coded survey data as input and then
printed out a report for every route for each day in a tabular
form with the coded information displayed in a systematic manner.
This output was checked against the original survey data. Key
punching errors were corrected and the survey file was modified
by using the IBM Utilities Program IEBUPDTE.2 Finally, a second
output report was compared with the original survey data to in-
sure an error-free data file.
A block diagram of the Program to generate the report is
given in Figure 25.
Program 2, Block Generation Program
This Program used the coded survey data and generated indi-
vidual block data records for all routes in the City. The gener-
ated blocks were then stored on magnetic tape in the Block Data
File.
This program divided the entire information of the survey
into several smaller segments related to a block on a given
street. Figure 26 shows the schematic diagram for the Program.
In addition to other physical and geographical information, this
data also included the length of the block and the field-recorded
time for collection of particular blocks, which were used in the
linear relationship development as previously outlined in Sec-
tion 5.
*References and footnotes at end of Section,
102
-------
Read
Summary
Record
Set
the
counters
Read
Header
Record
Print
Information
Print total
for the
pickup run
Print
Information
for this
Stop
Header
Summary
Print Summar
total for
the route
Figure 25. Survey Data Verification
103
-------
Read
Summary
Record
Read
Header
Record
Set the
counters
Read
Stop
Record
Assign
Block and
Store
Header
Summary
Figure 26. Block Generation Program
104
-------
Program 3, Block Data File Verification
To verify the Block Data File, a program was written which
accepted the Block Data File as input and printed out a report
in tabular format. This printed report was then compared with
the original survey data, and all errors were modified by using
the IBM utilities Program IEBUPDTE.2
The block diagram for this Program is given in Figure 27.
Program ;4, Block Classification
One of the uses for the Block Data File was to have infor-
mation on complete blocks for statistical analysis and develop-
ment of time-predictive equations. To accomplish this, data
was classified according to the following characteristics:
Single-sided collection
Double-sided collection
Average distance between stops
Width of the street for double-sided collection
Table 18 outlines the six groups of data available for analysis
and equation development.
Table 18. Classification of Blocks
Single or
Group Double Sided
Pickup
Average Distance
Between Stops
Street Width
for Double
Sided Pickup
1
2
3
4
5
6
Single
Single
Double
Double
Double
Double
<100
>100
<100
<100
>100
>100
ft.
ft.
ft.
ft.
ft.
ft.
<3
>3
<3
>3
cars
cars
cars
cars
The block diagram for this Program is shown in Figure
28, and the output was stored in file call Classified Blocks.
Program 5, Classified Block Sorting
The Classified Block Data File was sorted according to the
various groups using the IBM SORT/MERGE Program.
105
-------
Read a
Block
Record
Print the
heading and
Description
ir
Add to the
counters
Read a
record
No
Zero the
counters
Yes
Print
Summary
of the
Route
Figure 27. Block Data File Verification
106
-------
Read a
Block
Record
_ . , ., How „.
Single / . ^
_, ,^ ,, xmany sid
Sided \. f ,
icked
Figure 28. Block Classification
107
-------
Program 6, Regression Data
Field collection times were not recorded for all blocks.
Therefore, for later use in developing time-predictive equations,
a separate file was compiled from the total block file by selec-
ting only those blocks with times recorded. The data was stored
in a file called Regression Data. Figure 29 shows the block
diagram of this Program.
Program 7, Regression Analysis
An extensive regression analysis was performed using the
Regression Data as input to the BMD package program BMD03R.4
This program performs regression analysis for multiple variables
and has the option of combination. This was extremely helpful
in the analysis of different classification groups. The following
variables were used in the analysis:
Field recorded collection time
Length of block
Total number of bags collected
Total number of cans collected
Total number of equivalent cans collected
Total number of stops in the block
The transformed variables for the double-sided pickup were:
Total number of bags
Total number of cans
Total number of equivalent cans
Program 8, Sorting Block Data
This Program arranged the block file data according to route
number, day of collection, and the specific load in the day.
The output of the program was stored in Sorted Block File. Sorting
was achieved by using the IBM SORT/MERGE Program.3
Program 9, Density Report
In order to predict the weight of the solid waste generated
by stop, it was necessary to determine an average weight per
container (bag or can). This was accomplished by averaging the
net weight: of each load over its container count. This Program.
used the Sorted Block File as input and computed average weights
108
-------
Yes
Yes
Set
Group
Counters
Read a
Block
Record
No
Store this
Block record
in Regressioji
File
Update
Group
Counter
Figure 29. Regression Data
109
-------
for each load by route and day, for the entire City.
The block diagram for this Program is given in Figure 30.
Program 10, Predictive Results
After calculating the waste densities by load and obtaining
time-predictive linear equations through work measurement and
regression analyses, the solid waste generation time for each
block were computed by this program. The input for this pro-
gram consisted of the Block Data File together with the time-
predictive linear equations and the density calculations. The
Program output printed the results in tabular form and also
stored the output in the Prediction File. Figure 31 shows the
block diagram for this program.
The predictions were compared with the field-recorded time
and weight values. Since the predicted weights and times were to
be utilized in on-line route development, they were filed by
block number on disk storage.
Program 11, File Verification
In order to properly access the block time and weight data,
it was necessary to identify the data blocks by map location.
For this purpose, identification (ID) numbers were assigned to
every block in the City (1 through 1210), using a large scale
map (Appendix 9.5). The data block numbers were then identified
by the appropriate ID numbers according to first or second collec-
tion. This file was stored on disk and called the ID File. Time
and weight information for any street in the City was obtained
by locating the street on the map and entering its ID number into
the terminal.
Before designing the routes, it was considered appropriate
to verify the ID File. For this purpose, a verification program
was developed to automatically provide a printout for all the
ID numbers in the City. The output was then verified and corrected
The block diagram of this Program is given in Figure 32.
Program 12, Route Design
After verifying all data and files, a program was written
to design collection routes. One of the objectives in designing
the routes was to provide for active involvement of Public Works
personnel in the project. This suggested the development of a
system simple to operate and requiring minimal training. Also,
it was desirable to provide flexibility so that a route could
easily be changed and the impact of such a change be known immedi-
ately. To accomplish this, an on-line terminal system was used
to design the route area alternatives included later in Section 7.
This system was programmed for conversational mode and required
110
-------
Set
Counters
Read
Weight
Data
Add to
Counters
No
Read a
Record
Zero
Load
Counters
Zero
Day
Counters
Print
Day
Summary
No
Print
Load
Summary
No
Zero the
route
Counters
Yes
Print
Route
Summary
Add to
City
Counters
Figure 30. Density Report
111
-------
Set functions
for Predic-
tive Results
Read
Block
Record
Predict
Weight and
Time
Print
the
information
Store
results in
Prediction
file
Figure 31. Predictive Results
112
-------
ID FILE VERIFICATION
NO
Print
Title
Read blocks
for this
ID
Print the
Information
Yes
c
Stop
Figure 32. ID File Verification
113
-------
minimal training for operation. Using the Route Design Program,
changes could be obtained quickly. The Program incorporated
several logic checks to minimize design mistakes, e.g., an error
message is printed if a block ID number is entered more than once.
The program requested the user to input ID numbers, one at
a time, in any order desired as determined from the ID map. For
each new ID number, predicted time and weight, clock time, and
cumulative weight was printed. When the truck becomes full, the
user was informed and asked to input map distance to the landfill.
The clock was then advanced to allow for disposal time. Appro-
priate provision was also made for lunch, refueling, and return
to garage. In designing a route, the user had the option of
deleting one or more ID numbers previously included, in order to
assure final route balancing.
The block diagram for this program is given in Figure 33.
Program 13, Route Design (Modified)
This program was similar to Program 12, with a more condensed
output. After the user has become familiar with route development
using Program 12, an abbreviated output could be obtained with
this Program. Warning messages were still displayed during route
design, but time and weight data was provided only for completed
loads or at the end of the planned work day.
Figure 34 outlines the block diagram of this program.
Program 14, Automatic Route Design
The previous two programs for route design involved manual
entry of ID numbers. In order to reduce the time required for
route design, an ID Sequence File was established by reading
the ID's from the map, starting from the northwest corner of the
City. Each ID number was stored in its proper sequence in the
ID Sequence File.
After the ID Sequence File was established, it was important
that this be verified for any omissions or duplication. To accom-
plish this, a program was written which scanned the file and re-
ported any discrepancy in the data. Detected errors were then
corrected on the terminal system.
The automatic route design program functions exactly like
Programs 12 and 13 except that it did not require individual
manual input for the ID numbers. The input to the program was
read from the ID Sequence File. Minor modifications have been
effected on this Program to develop and evaluate the collection
system alternatives shown later in Section 7. The block diagram
for this Program is given in Figure 35.
114
-------
Yes
No
Set
-ounters
Information
on pass
Find weight
and time
for this ID
Print time
and weight
for this ID
fYes
Travelling time
to the land-fill
Update clock
and counters
Print
Summary of
the Load
Print Report on
the truck route
Figure 33,
Route Design
115
-------
Set
Counters
Yes
No
Information on
Pass
Find weight
and time for
this ID
the truck
full?
Yes
Update Clock
and Counters
Print
Summary of
the load
Print report
on the
truck route
Yes
Figure 34. Route Design (Modified)
116
-------
Set
Counters
Yes
Print
Route
Report
No
Request
distance
and pass
Read ID fron
ID sequence
file
Find weight
and time fox
this ID
Yes
Update
Counters
Figure 35. Automatic Route Design
117
-------
OVERALL SYSTEM
The purpose of this subsection is to briefly summarize the
relationships and the interactions among all major programs and
files beginning with the field survey and continuing through
route design. The overall system flow is illustrated in Figure
36.
The first step in the project was to verify the survey data.
After verification, a program was run to generate the Block Data
File. This File was also verified, and used to classify the
blocks in the City into six groups. This generated the Classified
Block File and, after sorting, was utilized to obtain the Regression
File for regression analysis. The Regression Program used output
from the Regression File and yielded several functions that were
used for predictive purposes.
At this point, the Block Data File was sorted again to
generate the Sorted Block File. The Density Program used field
weight data and the Sorted Block File as input and computed
densities of solid waste containerization. These densities,
equations from the regression analysis, and work measurement
data were used to predict the amount of solid waste generated
for each block and the time required for its collection. This
information was stored in the Prediction File. The ID File for
the City and the Prediction File were used as input for designing
the routes. All data files for the overall system are listed
below:
Block Data File
Classified Block File
ID File
ID Sequence File
Prediction File
Regression File
Sorted Block File
Survey Data File
118
-------
Classifica
tion of
Blocks
Program
i
Classified
Block
File
Program
to Group
for Regres-
sion
Regression
File
I
Regression
Program
Block Genera-
tion Program
Density
Program
Sorted
Block
File
Prediction
Program
Prediction
File
Route
Design
Programs
Automatic
Route
Design
Figure 36.
Overall System Flow
119
-------
FOOTNOTES
ilEBGENER, "IBM System/360 Operating System: -Utilities",
Order No. GC28-6586-13, International Business Machines Corpor-
ation, Fourteenth Edition (January, 1972), pp. 117-132.
2IEBUPDTE, "IBM System/360 Operating System: Utilities",
Order No. GC28-6586-13, International Business Machines Corpor-
ation, Fourteenth Edition (January, 1972), pp. 179-198.
3"OS Sort/Merge Program", Order No. GC28-6543-8, Interna-
tional Business Machines Corporation, Ninth Edition (February,
1973) .
4"BMD Biomedical Computer Programs", University of California
Publications in Automatic Computation, No. 2, (Ed. W. J. Dixon),
University of California Press, 1971, pp. 258-275.
120
-------
7 WASTE COLLECTION ROUTE DEVELOPMENT AND RESULTS
INTRODUCTION
One of the essential ingredients of a successful time or
wage incentive program is the capability to predict the work
content of waste collection as translated into equitable route
assignments. Before describing the development of route assign-
ments, it would be helpful to review the premises on which the
route development was structured.
As stated in Section 2, a group incentive is recommended,
where each group or team consists of several collection crews
and their respective field foreman. The number and size of the
teams for a given city is a function of the work content for
waste collection, the salient geographical characteristics, and
the total size of the collection work force.
Each team is assigned a collection area on a given day.
The team works as a cohesive unit under the direction of its
foreman, that is, the member crews share the work load until the
job is completed. No one leaves work until the team area is,
totally collected, unless permitted by the foreman.
On a day-to-day basis, the workers 'have a time incentive,
that is, they may leave work on completion of their team's as-
signed area. For wage incentive programs each team periodically
has the opportunity to participate in the review of the length
of its standard day, with work increases accompanied by appro-
priage incentive bonuses.
ALTERNATIVE COLLECTION ROUTE DESIGNS
The technical problem in area route design is to partition
the city into team collection areas, each defined in such a way
as to provide the desired standard or incentive work day for the
team. The total work content must account for all work time
elements: the sum o£ the pickup times (as computed for each
block face by the predictive equations, reference Section 5),
travel times, disposal time, refueling time, and allowance for
unavoidable delays.
121
-------
An automatic simulation program incorporating all of the
above work time elements was utilized to compute the total work
content for each collection day. (Program 14 in Section 6). A
sample partial output is shown in Appendix 9.7. Fixed inputs
to the program included collection frequency, crew size, and
length of work day. Output yielded the number of crews required
for collection for the entire City.
Six alternative collection area plans were prepared for the
Covington City Commission, each providing a standard work week of
approximately 32 hours (Table 19 with associated Figures 37 thru
42). All alternatives except II were 5-day work weeks (average
6.5 standard hours per day) while Alternative II was a 4-day
week (average 8.0 standard hours per day). Alternatives I, II,
III and IV were designed for 3-man crews. Alternatives III-A
and IV-A were 2-man crews. Alternatives I, II, III, and III-A
provided twice-a-week pickup. Alternatives IV, and IV-A pro-
vided once-a-week pickup.
ECONOMIC ANALYSIS AND COST SAVINGS
COMPARISON OF WASTE COLLECTION ALTERNATIVES
Annual costs were computed for each collection alternative,
All costs for collection were included except certain overhead
costs common to all alternatives, e.g., the Public Works Super-
intendent and staff, supervisory vehicles, building and land
use, nonvehicle equipment, backup equipment, and overtime re-
quired for Alternatives IV and IV-A (holiday week, Saturday col-
lection) .
Annual Costs
The annual cost for each collection alternative may be
estimated as follows:
Annual Cost = Truck Cost + Crew Cost + Overhead
1) Truck Cost
Capital Costs:
First Cost (P) = $15,000
Salvage Value (F) - $ 500
Capital Recovery
Factor (A/P):
122
-------
TABLE 19. COMPARISON OF WASTE COLLECTION ALTERNATIVES
DESCRIPTION
AVG, WORK
DAY (HOURS)
STRENGTHS
WEAKNESSES
ORIGINAL
ALT. I
ALT. II
5-day collection; 8.0
5-day work week;
twice-a-week pickup
Total crews:
13 Res. and
Comm. (3-man)
5-day collection; 6.5
5-day work week;
twice-a-week pickup
Total crews:
8 Res. (3-man)
2 Comm. (2-man)
IcT
4-day collection; MT:
4-day work week; HF:
twice-a-week pickup
Total crews:
8 Res. (3-man)
2 Comm. (2-man)
IcT
8.5
7.5
MH and TF
collection
Utilizes crews
all 5 days
Extra commercial
route capacity
Special Item
pickup by Comm.
crews for W
MH and TF
Collection
Utilizes crews
all 4 days
Special item
pickup by comm.
crews added for
M, T, H, F
Simple route
areas
Unbalanced routes
No special item pickup
No time incentive
Inequitable commercial/
institutional service
Certain Areas with T-H, M-W,
W-F pickup
Route Areas more complex with
Team I split on Wed.
Uncertainty of T-H, M-W and W-F
pickup schedule on waste volume
Holiday week collection more
difficult
Long days, with M and T requiring
approximately 8 1/2 hours
Greater difficulty with late-
afternoon traffic
Collection service not available
on Wed.
Possible difficulties with. 4-day
week; requires union renegotia-
tion of working agreement
-------
TABLE 19 (Comr.)
ALT. Ill DESCRIPTION
AVG, WORK
DAY HOURS
STRENGTHS
WEAKNESSES
4-day collection;
5-day work week;
twice-a-week
pickup
Total crews:
10 Res. (3-man)
2 Comm. (2-man)
MT:
HF:
7.0
6.0
M-H and T-F
collection
Extra commercial
route capacity
Special item
pickup added on
Wednesday
Simple route
areas
Management of Wednesday
assignments
More restricted special
item pickup
ALT. Ill A
4-day collection;
5-day work week;
twice-a-week pickup
Total crews:
12 Res. (2-man)
2 Comm. (2-man)
ur
MT:
HF:
7.0
6.0
M-H and T-F
collection
Extra commercial
route capacity
Special item
pickup added on
Wednesday
Simple route areas
Management of Wednesday
assignments
More restricted special
item pickup
-------
TABLE 19 (CONT.)
ALT. IV DESCRIPTION
AVG, WORK
DAY HOURS
STRENGTHS
WEAKNESSES
Ln
ALT. IV A
5-day collection;
5-day work week;
once-a-week pickup
Total crews:
6 Res. (3-man)
2 Coinm. (2-man)
6.5
Utilizes crews
all 5 days
Extra commercial
route capacity
Once-a-week pickup
Requires overtime pay
for holiday work weeks
(Saturday collection)
Special item pickup
by commercial crews
added for Wednesday
Simple route areas
5-day collection
5-day work week;
once-a-week pickup
Total crews:
8 Res. (2-man)
2 Comm. (2-man)
IcT
6.5
Utilizes crews Once-a-week pickup
all five days _ Requires overtime pay
Extra commercial ._,.., n ,
for holiday work weeks
route capacity , , . ,
(Saturday collection)
Special item
pickup by com-
mercial crews
added for Wednesday
Simple route areas
-------
>1oN - THURW
J* tvtaafrtts^L- -11 j-1* -- ///
L*f«««i i I—i r—. -v ///
r=HRSi/§
\,C4t / - '• \ S °^--l .. -^_- •-, v » .v -. --
Figure 37. Team Area Route Map, Alternative I: Five-Day
Collection; Five-Day Work Week; Twice-a-Week
Pickup; Three-Man Crew
126
-------
Figure 38. Team Area Route Map, Alternative II: Four-Day
Collection; Four-Day Work Week; Twice-a-Week
Pickup; Three-Man Crew
121
-------
Figure 39.
Team Area Route Map, Alternative III: Four-
Day Collection; Five-Day Work Week; Twice-a-
Week Pickup; Three-Man Crew
128
-------
Figure 40. Team Area Route Map, Alternative III-A: Four
Day Collection; Five-Day Work Week; Twice-a-
Week Pickup; Two-Man Crew
129
-------
,
u- I/--THPQ &
if«.Iu^s3\i
4HWED
Figure 41,
Team Area Route Map, Alternative IV: Five-Day
Collection; Five~Day Work Week; Once-a-Week
Pickup; Three-Man Crew
130
-------
isi^LJWsrii
EUS-iaJJJ^ C3 \ if*
3'UliisJfeJLJVn^"
^rsc^rrt/
f%tef^i\ute
0 !r-JL3,^;-%r:
^p,^c=f [jjvu^^uu^: '.N.^ge
Ji3U\^r7y^AV« D^r^vr^ES
4%\ \« \\Hr-r>JgDL4s==^,r^
-^'oT^^ Jure "VfllU \& ,.--::---
"• V>\\*J ^-- «™r nn
«/r^ i.i HI
^^1i^S:|sQllt ji^g'^SP^. 1
" THUR ' " " ""
Figure 42. Te,?.ra Area Route Map, Alternative IV-A: Five-
Day Collection; Five-Day Work Week; Once-a-
Week Pickup; Two-Man Crew
131
-------
where:
i = annual interest = 8 percent
n = life in years = 5
A/P = Q.-08(1.08)5 = 0
(1.08)5~1
Sinking Fund Factor (A/F) :
A/F = - -
A/F = - ^ - = 0.1705
(1.08) -1
Equivalent Annual = $15 , 000 (. 2505) - $500(.1705)
Capital Cost (A)
$3673/Truck
Operating Costs :
Fuels, Lubricants = $14 . 00/Truck-day
Tires , Maintenance
Supplies = 5.00
Subtotal = $19. 00/Truck-day
Total Truck Costs:
Total Cost = Capital Cost + Operating Cost
5-day collection: $3,673 + ($19) (52) (5) = $8,613/truck
4-day collection: $3,673 + ($19) (52) (4) = $7 ,625/truck
2) Crew Cost
Drivers:
Wages $153.60/week
Pensions (20%) (wages) 30.72
Soc. Sec. (5.85%) (wages) 8.99
Workmen's Comp. (6%) (wages) 9.22
Medical $594 * 52 11.42
Subtotal $213.95/week
$11,125. 40/year
132
-------
Laborers;
Wages
Pension, Social Security
Workmen's Comp. (31.85%) (wages)
Medical
Subtotal
3) Overhead
Supervisory Personnel:
Assistant Superintendent
Wages
Pension, Social Security
Workmen's Comp.
Medical
Subtotal
Foreman
Wages
Pension, Social Security
Workmen's Comp.
Medical
Subtotal
Maintenance Personnel
Wages
Pension, Social Security
Workmen's Comp.
Medical
Subtotal
$145.15/week
46.23
11.42
$202.80/week
$10,545.60/year
$234.21/week
74.60
11.42
$320.23/week
$16,651.96/year
$188.24/week
59.95
11.42
$259.61/week
$13,499.72/year
$165.00/week
52.55
11.42
$228.97/week
$ll,906.44/year
133
-------
Indirect Savings From Manpower "Available" on Wednesdays
Alternatives III and III-A provided four day collection
in a five day work week. Consequently, manpower was available
on Wednesdays for other waste collection assignments. Because
all workers would receive pay for Wednesday, these indirect
savings are not included in the annual savings comparison
summary (Figure 43).
1) Driver:
42 nonholiday wks.
(52 wks./yr. )
1 day/wk.
(5 days/wk.)
($11,125.40) = $1797/
driver
2) Laborer:
4_2 !_
(52) (5) (10,545.60) = $1703/laborer
3) Foreman:
£2 !_
(52) (5) ($13,499.72) = $2180/foreman
Economic Comparison of Alternatives
1) Original System (5-day pickup)
13 trucks @ $8,613.00
13 drivers @ $11,125.40
26 laborers @ $10,545.60
Overhead
1 asst. superintendent @ $16,651.96
2 foremen @ $13,499.72
1 maintenance @ $11,906.44
Total
2) Alt. I (5-day pickup, twice a week)
10 trucks @ $8,613
10 drivers @ $11,125.40
18 laborers @ 10,545.60
Overhead
Total
Direct Savings
Over Original
$111,969
144,630
274,186
16,652
26,999
11,906
$586,342
$55,557
$ 86,130
111,254
189,821
55,557
$442,762
$143,580/year
134
-------
3) Alt. II (4-day week, 4-day pickup, twice a week)
10 trucks @ $7,625 $ 76,250
10 drivers @ $11,125.40 111,254
18 laborers @ $10,545.60 189,821
Overhead 55,557
Total $432,881
Direct Savings $153,461/year
Over Original
4) Alt. Ill (4-day pickup, twice a week)
12 trucks @ $7,625 $ 91,500
12 drivers @ $11,125.40 133,505
22 laborers @ $10,545.60 232,003
Overhead 55,557
Total $512,565
Direct Savings $ 73,777
Over Original
Savings from available manpower
on Wed. (12 drivers, 22 laborers,
2 foremen) 63,401
Total Savings $137,178/year
Over Original
5) Alt. III-A (4-day pickup, twice a week)
14 trucks @ $7,625 $106,750
28 drivers @ $11,125.40 311,511
Overhead 55,557
Total $473,818
Direct Savings $112,524
Savings from available manpower
on Wed. (28 drivers) 54,677
Total Savings $167,201/year
135
-------
6) Alt. IV (5-day pickup, once a week)
8 trucks @ $8,613 $ 68,904
8 drivers @ $11,125.40 89,003
14 laborers @ $10,545.60 147,638
Overhead 55,557
Total $361,102
Savings $225,240/year
7) Alt. IV-A (5-day pickup, once a week)
10 trucks @ $8,613 $ 86,130
20 drivers @ $11,125.40 225,508
Overhead 55,557
Total $364,195
Savings $222,147/year
A summary of annual cost savings for each collection alter-
native is shown in Figure 43.
IMPLEMENTATION
Six collection alternatives were developed for City Com-
mission consideration. Comparisons of each were provided to
aid the Commission in selection of an alternative for imple-
mentation. In preparation for implementation, tasks and sched-
ules were outlined.
Tasks
The following list of tasks was utilized for implementa-
tion:
1) Commission: Select alternative.
2) Commission: Approve enacting ordinances. Sample ordi-
nances for once-a-week and twice-a-week collection are
given in Appendices 9.10 and 9.11.
3) City Manager's Office and U.C. Planners: Meet with
Union management for information and discussion,
followed by meetings with the membership if requested.
4) City Manager's Office and U.C. Planners: Arrange for
preliminary public information explaining salient char-
acteristics of the new system, including benefits,
136"
-------
u>
H
CD
U)
n >
o 3
H- d
(t> p)
o M
rt
H- co
O &
3 <
H-
> 3
rt w
(D
4 O
3 O
0) 3
n-^o
H- fU
< H
0) H-
cn en
O
rt
hj X
S's-
V^D ^t
H-PJ
53 W
(D rt
I—i (D
O
O
Cfi
rt
TWICE-A-WEEK PICKUP
$586,000
13 PACKER
39 MEN
$443,000
$433,000
$512,000
$473,000
14 PACKER
28 MEN
*• ONCE-A-WEEK PICKUP
$361,000
8 PACKERS
22 MEN
$364,000
ORIGINAL
II
III
IIIA
IV
IVA
O
X
H
o
o
en
t-3
Co
o
CO
§
H
a
Q
CO
-------
savings, and new services.
5) City Manager's Office and Public Works Management:
Review existing Public Works two-way communication
system.
6) Public Works Management: Select the crew/team assign-
ments and notify men,
7) Public Works Management: Explain incentive program to
employees.
8) Public Works Management and U.C. Planners: Finalize
team and truck route area assignments.
9) Public Works Management: Contact all existing and
prospective high volume citizens to determine collection
frequency and containerization for each new high volume
stop.
10) City Manager's Office and Public Works Management:
Establish accounting/billing system for high volume
optional services.
11) Public Works Management and U.C. Planners: Develop
initial high volume routes.
12) Public Works Management: Plan special item pickup.
13) City Manager's Office: Inform citizens of new routes,
procedures for special item pickup, and implementation
schedule. A sample announcement for citizen notifi-
cation is shown in Appendix 9.12.
Final Schedule
After completion of the above tasks and immediately pre-
ceding implementation, the following schedule is recommended:
1) U.C. Planners: Meet with team foremen to discuss team
crews, truck areas, and foremen's role. Time: Monday
before D-Day.
2) U.C. Planners: Meet with foremen and drivers to dis-
cuss team areas, truck areas, and hand out maps. Time:
Wednesday before D-Day.
3) U.C. Planners and all collection personnel: Dry run of
loadpackers over assigned route areas. Time: Saturday
before D-Day.
138
-------
4) U.C. Planners and all collection personnel: Change-
over to new collection systems. Time: Monday, D-Day.
5) U.C. Planners and all collection personnel: Accompany
field foremen during the initial operation of the new
routes. Time: First five days following D-Day.
First Implementation - August 5, 1974
During July, 1974, after several weeks of consideration,
the City Commission selected Alternative III-A. This alter-
native continued twice-a-week collection service, but reduced
crew size from three to two. Appendix 9.13 illustrates the cov-
erage provided the implementation by one of the local newspapers.
Upon selection of Alternative III-A, the tasks and schedules
were followed by all parties, as previously outlined. Citizens
were notified of the new collection schedule by radio, TV, and
newspaper advertisements (Appendix 9.14). Utilizing the socio-
metric analysis described in Section 3, team assignments were
prepared on the basis of individual preferences. The results
are shown in Appendix 9.15. Area route assignments for all truck
crews were prepared using the detail route design computer pro-
gram (Program 13, Section 6). Example computer outputs for
Team I and Team II are shown in Appendices 9.8 and 9.9. Truck
route maps as shown in Figures 44, 45, 46, and 47 were provided
to all drivers and foremen. In addition, driver and foreman
guidelines (Appendices 9.16 and 9.17) were handed out during the
training sessions.
Second Implementation - April 14, 1975
After several months of successful operation of Alternative
III-A, during the final phases of budget planning for the next
fiscal year, it became apparent to City management that a sub-
stantial financial deficit would occur. Consequently, further
operating budget reductions would be necessary. In the Department
of Public Works, it was recommended that collection frequency
be reduced from twice to once weekly. In March, 1975, the
Commission made the decision to implement Alternative IV, which
offered the lowest costs for waste collection.
As a result of this decision, tasks and a schedule similar
to the first implementation were followed. New area route maps
as shown in Figures 48, 49, 50, and 51 were prepared and dis-
tributed to all truck crews and foremen. An example citizen
notification map is shown in Figure 52. The areas shown in Fig-
ure 52 for each collection day conform to the detail crew route
area maps as shown in Figure 50.
139
-------
H ;
Figure 44. Truck Area Route Maps for Team I Mcn-Thur
Collection, Alternative III-A
140
-------
Figure 45. Truck Area Route Maps for Team I Tue-Fri
Collection, Alternative III-A
141
-------
u IHElk \\\o
Figure 46
Truck Area Route Maps for Team II Mon-Thur
Collection, Alternative III-A
142
-------
Figure 47.
Truck Area Route Maps for Team II Tue-Fri
Collection, Alternative III-A
143
-------
1
IM
ill
[i!
!!i!
«?
ijii
?
£
5
*i
. IL
K"~
Figure 48.
Truck Area Route Maps for Team I Mon-Tue-Wed
Collection, Alternative IV
144
-------
Figure 49.
Truck Area Route Maps for Team I Thur-Fri
Collection, Alternative IV
145
-------
Figure 50,
Truck Area Route Maps for Team II Mon-Tue-Wed
Collection, Alternative IV
146
-------
Figure 51.
Truck Area Route Maps for Team II Thur-Fri
Collection, Alternative IV
147
-------
Figure 52.
Example Citizen Notification Map for Mon-Tue-
Wed Collection, Alternative IV
148
-------
CONCLUSIONS
To deal with changing constraints and multiple service ob-
jectives effectively, municipal management must be able to devel-
op options for action. In providing waste collection services
particularly, it is important that multiple alternatives be
available and that the impact of each alternative be predicted
prior to possible implementation. This flexibility is provided
by the ability of accurately computing work content through the
application of work measurement and detailed field data.
Both implementations were successful. The first implemen-
tation realized approximate savings at an annual rate of $113,000
while retaining twice-a-week frequency. The second implementation
providing once-a-week collection realized an additional $112,000
annual savings ($225,000 total, 38 percent of original budget).
The quality of service was consistently maintained or improved
during both implementations. Prior to the first implementation,
Covington had no incentive program. Both alternatives included
a time incentive, and provided the technical basis for a mone-
tary incentive. At this time, the City Commission has not yet
elected to pursue a wage incentive program.
149
-------
8 BIBLIOGRAPHY
"A New Productivity Yardstick," Business Week, May 13,
1972.
Adams, J. S. and Jacobsen, P. R.,, "Effects of Wage Ineq-
uities on Work Quality," Journal of Abnormal and
Social Psychology, Vol. 69, 1964.
Adams, J. S. and Rosenbaum, W. E.,"The Relationship of
Worker Productivity to Cognitive Dissonance About
Inequities," Journal of Applied Psychology, Vol. 46,
1962.
Albrecht, O. W. and Oberacker, D. A., "Sewer Transport
of Household Refuse, A Replacement for the Refuse
Truck," News of Environmental Research in Cincinnati,
U.S. Environmental Protection AgencyT" MaY 9 r 1975~
Altman, S., Beltrami, E., Rappaport, S. and Schoepfle, G. K.,
"Non-Linear Programming Model of Crew Assignments for
Household Refuse Collectionp " IE E E Trans a c t i ojns_ on
Systems, Man, and Cybernetics, SMC-1 (3), July~1971.
Andrews, I. R. "Wage Inequity and Job Performance: An
Experimental Study t" Journal of Applied Psychology,
Vol. 51, 1967.
Atkinson, J. W. An Introduction of Motivation, Van
Nostrand, 1964.
Atkinson, J. W. and Birch, D., The Dynamics of Action,
Wiley, 1970.
Atkinson, J. W. and Feather, N. T. Eds., A Theory of
Achievement Motivation, Wiley, 1966.
Barnes, Ralph M. Motion and Time Study: Design and
Measurement of Work, Sixth Ed., Wiley, 1968.
Barr, D. W. "Improving Office Productivity," Office,
Vol. 75, Jan, 1972.
Baumback, C. M., Structural Wage Issues in Collective
Bargaining, Heath, (Lexington), 1971, p. 146.
Baumgartel, Howard and Ronald Sabol, "Background and
Organizational Factors in Absenteeism," Personnel
Psychology, 1959, Vol. 12, pp 431-443.
Berelson, B. and Steiner, G. A. Human Behavior, Harcourt
Brace, and World, 1964.
150
-------
Bernstein, Harry, "Experiment Begun in Three-Day Week,"
Cincinnati Enquirer (May 1, 1973), p. 6, a's copy-
righted from the Los Angeles Times.
Bobbitt, H. R. and Behling, O., "Defense Mechanisms As
An Alternate Explanation of Herzberg's Motivator-
Hygiene Results," Journal of Applied Psychology,
Vol. 56, 1972.
Bodner, R. M. , Cassell, E. A., and Andros, P. J., "Optimal
Routing of Refuse Collection Vehicles," Journal of
Sanitary Engineering Division, Proceedings, American
Society of Civil Engineers, 96 (SA4), August, 1970.
Boyer, R. M., and Shell R. L., "End of the Line at Lordstown,"
Business and Society Review, No. 3, Autumn, 1972.
Bramley, E., "Labor Costs Up, Productivity Off," Airline
Management, Vol. 3, October, 1971.
Brayfield, A. and Crockett, W., "Employee Attitudes and
Employee Performance," Psychological Bulletin, Vol.
52, 1955.
Bubier, R. H., "Modern Refuse Vehicle Routing," Public
Management, August, 1973.
Caruth, D. L. "Work Measurement and the Smaller Bank,"
Burroughs Clearing House, Vol. 56, November, 1972.
Chapanis, Alphonse, "On the Allocation of Functions Between
Men and Machines, " Readings in Organizational and In-_
dustrial Psychology (Gary A. Yukl and Kenneth N. Wexley,
Eds.),Oxford University Press, 1971.
Chung, Kae H., "A Markov Chain Model of Human Needs: An
Extension of Maslow's Need Theory,"Academy of Manage-
ment Journal, Vol. 12, June, 1969.
Chung, Kae H., "Toward a General Theory of Motivation and
Performance," California Management Review, Vol. 11,
Spring, 1969-
Cimino, Joseph A. and Richard Raab, "Study of the Carbon
Monoxide Emission from Sanitation Trucks and Levels of
Carboxyhemoglobin in Workers" Envaronme_nt_al Protection
Administration (New York City), October, 1967 .
Clark R. M., and Gillean, J. L., Systems Simulation and Solid
Ivaste Planning: A Case Study, Report 67015-73-12,
National Environmental Research Center, USEPA, 1973.
151
-------
Colin, J. M., "After X and Y Comes Z," Personnel Journal,
Vol. 50, January, 1971.
Cordtz, D., "City Hall Discovers Productivity," Fortune,
Vol. 84, October, 1971.
Coyle, R. G. and Martin, M. J. C., "The Economics of Refuse
Collection," Operational Research Quarterly,
20 (Special Conference Issue}, April, 1969.
Grossman, Richard M., and Nance, Harold W., Master Standard
Data; The Economic Approach to Work Measurement,
McGraw-Hill, 1962.
Dalton, G. W., Lawrence, P- R., and Greiner, L. E., Eds.,
Organizational Change and Development, Irwin, 1970.
Davis, L. E., "Job Satisfaction Research: The Post-Industrial
View," Industrial Relations, Vol. 10, 1971.
Dudley, N. A., Work Measurement, MacMillian (London), 1968,
Dunn, J. D. and Stephens, Elvis Co., Management of Personnel;
Manpower Management and Organizational Behavior, McGraw-
Hill, 1972.
Dunn, J. D. and Rachel, F. M., Wage and Salary Administration:
Total Compensation Systems, McGraw-Hill, New York, 1971,
p. 251.
Dunnette, M. D., Cambell, J. P., and Habel, M. D., "Factors
Contributing to Job Satisfaction and Job Dissatisfaction
in Six Occupational Groups," Organizational Behavior
and Performance, Vol. 2, 1967.
Employee Incentives to Improve State and Local Government
Productivity, National Commission on Productivity and
Work Quality, Pub. No. CP75015, March, 1975.
Feather, N. T., "Level of Aspiration and Performance Vari-
ability," Journal of Personality and Social Psychology,
Vol. 6, May, 1967.
Fein, M., "Work Measurement: Concepts of Normal Pace,"
Industrial Engineering, Vol. 4, (9), September, 1972.
Fein, M., "Work Measurement Today," Industrial Engineering,
Vol. 4, (8), August, 1972.
Fein, M., "A Rational Approach to Normal in Work Measurement,"
Journal of Industrial Engineering, Vol. XVIII, (6), June,
1967.
152
-------
Fein, M., Rational Approaches to Raising Productivity,
Monograph Series No. 5, American Institute of~
Industrial Engineers, 1974.
Festinger, L. A., A Theory of Cognitive Dissonance, Row,
Peterson, and Co.,1957.
Fisher, J. F., "Methods Management with MTM," Office,
Vol. 75, January, 1972.
Ford, Robert N., Motivation Through the Work Itself,
American Management Association, Inc., 1969.
Fuertes, L. A., Hudson, J. F., and Marks, D. H., Analysis
Model for Solid Waste Collection, Department of
Civil Engineering, Massachusetts Institute of Tech-
nology, 1972.
Galbraith, Jay R. , "Some Motivational Determinants of
Job Performance," The Journal of Industrial Engineering,
Vol. 18, No. 4, April, 196~7 .
Galbraith, Jay R. and Cummings, Larry L., "An Empirical
Investigation of the Motivational Determinants of Task
Performance: Interactive Effects Between Instrumen-
tality - Valence and Motivation- Ability," Organizational
Behavior and Human Performance, Vol. 2, August, 1967.
Gellerman, Saul W. , Motivation and Productivity, American
Management Association, Inc., 1963.
Gellin, Gerald A. and Zavon, Mitchell R., "Occupational
Dermatosis of Solid Waste Workers," ARCH Environmental
Health, Vol. 20, April, 1970, pp. 510-515.
Georgopoulas, B. S., Mahoney, G. M., and Jones, N. W. , "A
Path-Goal Approach to Productivity," Journal of Applied
Psychology, Vol. 41, 1957.
Gilbreth, Frank B., Motion Study, Van Nostrand, 1911.
Gilbreth, L. M., The Psychology of Management, MacMillian, 1919.
Grace, W. E. , "Planning and Organizing a Work Measurement
Program," Management Accounting, Vol. 52, July, 1970.
Graen, George B., "Instrumentality Theory of Work Motivation:
Some Experimental Results and Suggested Modifications,"
Journal of Applied Psychology Monograph, Vol. 53, April,
T969~.
153
-------
Graen, G. B., and Hulin, C. L., "An Addendum to an Empirical
Investigation of Two Implications of Two-Factor Theory
of Job Satisfaction," Journal of Applied Psychology,
LII, 1968.
Gunn, Bruce, "The Dynamic Synthesis Theory of Motivation,"
Management Science, Vol. 14, June, 1968.
Hackman, J. Richard and Porter, Lyman W. "Expectancy Theory
Predictions of Work Effectiveness," Organizational
Behavior and Human Performance, Vol. 3, November, "1968.
Hackman, Ray C., The Motivated Working Adult, American
Management Association, Inc., 1969.
Handy, R, and Harwood, E. C., A Current Appraisal of the
Behavioral Sciences, Revised Edition, Behavioral Research
Council, 1973.
Hendricks, J. R. and Mischkind, L* A., "Empirical and Theoret-
ical Limitations of the Two-Factor Hypothesis of Job
Satisfaction," Journal of Applied Psychology, Vol. 51,
1967.
Herzberg, Frederick, Mausner, B., and Synderman, J., The
Motivation to Work, Wiley, 1959.
Herzberg, Frederick, et al. Job Attitudes; Review of Research
and Opinion, Psychological Service of Pittsburgh, 1957,
Herzberg, F., Work and the Nature of Man, World Publishing
Company, 1966.
Herzberg, Frederick, "One More Time: How Do You Motivate
Employees?" Harvard Business_Review, Vol. 46, January,
1968.
Hilgert, R. L. "An Overview to Motivation and Supervisory
Management," Manage, Vol. 24, Nov/Dec., 1971.
Hulin, C. L., and Smith, P- A., "An Empirical Investigation
of Two Implications of the Two-Factor Theory of Job
Satisfaction," Journal of Applied Psychology, Vol. 51,
1957.
Hunt, J. B. and Hill, H. W., "The New Look in Motivational
Theory and Organization Research in Human Organizations,"
Human Organizations, Vol. 23, No. 2, 1969.
154
-------
Hutchinson, J. G., Managing a Fair Days Work, Michigan
Press, 1963.
Hyatt, J. C., "Productivity Push," Wall Street Journal,
Vol. 52, April 25, 1972.
"Innovation is Changing Old Ideas on Incentives," Industry
Week, Vol. 167, No. 24, July 27, 1970, p. 24-33.
Irwin, Francis A., Intentional Behavior and Motivation: A
Cognitive Theory, J. B. Lippincott Company, 1971.
Jinich, Carlos and Niebel, Benjamin, "Synthetic Leveling—
How Valid?" Industrial Engineering, Vol. 2, (5), May,
1972. =
Jurisdictional Guide to Productivity Improvement Projects,
Handbook for Public Officials, 2nd Edition, NationaT
Commission on Productivity and Work Quality, CP75011,
1975.
Karger, D. W., and Bayha, F. H. Engineered Work Measurement
Second Ed., McGraw-Hill, 1965.
Klee, A. J., "The Psychology of Solid Waste Management,"
Reporter of the American Public Works Association
May, 1969.
Korman, Abraham K. "Self Esteem as a Moderator of the
Relationship Between Self-Perceived Abilities and
Vocational Choice," Journal of Applied Psychology,
Vol. 41, 1967.
Korman, Abraham K. "Expectancies as Determinants of
Performance," Journal of Applied Psychology, Vol.
55, No. 3, 197.1.
Korman, Abraham K. Industrial and Organizational Psycho-
logy, Prentice-Hall, 1971.
Krick, E. V. Methods Engineering, Wiley, 1962.
Lachter, L. E. "Goal For Year Ahead is Work Smarter,"
Administration Management, Vol. 33, June, 1972.
Landry, F. J. "Motivational Type and the Satisfaction-
Performance Relationship," Journal of Applied
Psychology, Vol. 55, No. 5, 1971.
155
-------
Lawler, Edward E. and Porter, Lyman W. "Antecedent Attitudes of
Effective Managerial Performance," Organizational Behavior
and Human Performance, Vol. 2, May, 1967.
Lawler, Edward E. and Porter, Lyman W- Managerial Attitudes and
Performance, Irwin, 1968.
Lesieur, F. G. Ed., The Scanlon Plan, MIT Press, 1958.
Likert, Rensis, The Human Organization, McGraw-Hill, 1967.
Lindsay, C. A., Martin, E., and Gorlow, L., "The Herzberg
Theory: A Critique and Reformulation," Journal of
Applied Psychology, Vol. 41, 1967.
Little, Alan and Warr, Peter "Who's Afraid of Job Enrichment?"
Personnel Management, Vol. 3, February, 1971.
Little, J. D. C., Murty, K. G., Sweeney, L. W. and Karel,
C. "An Algorithm for the Travelling Salesman Problem"
Operations Research 11(6) , November-December, 1963.
Lofy, Ronald J., Techniques for the Optimal Routing and
Scheduling of Refuse Collection Vehicles, Ph.D.
Dissertation, University of Wisconsin, 1971.
Lopez, Felix M., Evaluating Employee Performance. Chicago:
Public Personnel Association, 1968.
Macrov, David, Incentives to Work, Jossey-Bass Inc. (San
Francisco) 1970.
Madsen, K. B., Theories of Motivation, Munksgaard, (.Copenhagen)
1968.
Maher, J., Overbagh, W., Palmer, G., and Piersol, D.
"Enriched Jobs Mean Better Inspection Performance,"
Industrial Engineering, November, 1969.
Manpower Profile and Analysis in the Field of Solid Waste
Management (Vol. 1), by Applied Management Science,
Inc. (unpublished manuscript prepared for U.S.
Environmental Protection Agency under Contract No.
68-03-0041), 1973, p. 4.
Marks, D. H. and Liebman, J. C. Mathematical Analysis of
Solid Waste Collection, USPHS Publication 2104, 1970.
Marriott, R., Incentive Payment Systems, Slaples, London,
1967.
156
-------
Maslow, A. H. "A Theory of Motivation," Psychological
Review, Vol. 50, 1943.
Maynard, Harold B., Stegemerten, G. J., and Schwab, John
L. Methods-Time Measurement, McGraw-Hill, 1948.
Maynard, Harold B. (Ed.-in-Chief). Industrial Engineering
Handbook, Third Ed., McGraw-Hill, 1971.
McClelland, David C.; Atkinson, J.W.; Clark, R. A.; and
Lowell, E. L. The Achievement Motive, Appleton-
Century-Crofts, 1953.
McClelland, David C. The Achieving Society, Van Nostrand,
1961.
McCormick, Ernest J. "The Industrial Engineering/Human
Factors Interface," Human_Factors, Vol. 11, April,
1969.
McCormick, Ernest J. Human Factors Engineering, 3d
Edition, McGraw-Hill, 1970.
McGregor, Douglas The Human Side of Enterprise, McGraw-
Hill, 1960.
Minor, Frank J., "The Prediction of Turnover of Clerical
Employees," Personnel Journal, Vol. 51, May, 1963.
Morrow, Robert Lee Time Study and Motion Economy, Ronald
Press, 1946.
Mundel, Marvin E. Motion and Time Study, Prentice-Hall,
1970.
Murray, Henry A. et al. Explorations in Personality,
Oxford University Press, 1939.
Myers, Scott M., Every Employee a Manager, McGraw-Hill,
1970.
Nadler, Gerald Work Design: A Systems Concept, Revised
Ed., Irwin, 1970.
Nadler, Gerald Work Systems Design: The Ideals Concept,
Irwin, 1967.
Nadler, Gerald Work Design, Irwin, 1963.
Nadler, Gerald Motion and Time Study, McGraw-Hill, 1955.
157
-------
Naylor, James C. and Norman L. Vincent, "Predicting
Female Absenteeism," Personnel Psychology, 1959,
Vol. 12, pp. 81-84.
Neff, Walter S., Work and Human Behavior, Atherton
Press, 1968.
Niebel, B. W. , Motion and Time Study, Irwin, 6th ed., 1972.
Opportunities for Improving Productivity in Solid Waste
Collection,National Commission on Productivity,
NCP73012, 1973.
Owen, E. H., "Computer Program Cut Costs of Urban Solid
Waste Collection," Public Works, 101(1), January, 1970.
Paul, William J., Robertson, Keith B., and Herzberg, Frederick,
"Job Enrichment Pays Off," Harvard Business Review,
March-April, 1969.
Phillips, D. L., "Revised Refuse Procedure Cuts Budget,"
The American City, 86(4), April 1971.
Prien, Erich P., Barrett, Gerald V., and Svetlik, Byron,
"The Prediction of Job Performance," Personnel Adminis-
tration, Vol. 30, March, 1967.
"Productivity Improving," Industry Week, Vol. 169, June 21,
1971.
Productivity, Fourth Annual Report, National Commission on
Productivity and Work Quality, CP75003, 1975.
Quon, A. M., Charnes, A., and Wersan, S. J., "Simulation
and Analyses of a Refuse Collection System," Journal
of the Sanitary Engineering Division, American Society
of Civil Engineers, 91, SA5, 17-36, October, 1965.
Rachel, F. M. and Caruth, D. L., "Work Measurement," Manage-
ment Services, Vol. 6, June, 1969.
Rating Committee of the Society for the Advancement of Manage-
ment, Rating of Time Studies, 1952.
Raynor, J. 0., "Future Orientation and Motivation of Immediate
Activity: An Elaboration of the Theory of Achievement
Motivation," Psychological Review, Vol. 76, 1969.
Refuse Collection and Disposal, An Annotated Bibliography,
USPHS Publication 91, Supplements A-F, 1951-1963T
158
-------
Refuse Collection Practice, 3rd Edition, Interstate, 1966.
Repp, W., "Motivating the Now Generation," Personnel Journal,
Vol. 50, July, 1971.
Reuter, V. G., "Work Measurement Practices," California
Management Review, Vol. 14:24-30, Fall, T9T1~.
Richardson, F. L. W. and Walker, Charles R., Human Relations in
an Expanding Company, Labor and Management Center, Yale
University, 1948. ~
Robinson, David D., "Prediction of Clerical Turnover in Banks by
Means of a Weighted Application Blank," Journal of Applied
Psychology, Vol. 56, No. 3, 1973, p. 282.
Roethlisberger, F. J. and Dickson, W. J., Management and The
Worker, Harvard University Press, 1939.
Rosekraus, F. M., "Choosing to Suffer as a Consequence of
Expecting to Suffer: A Replication," Journal of Personali-
ty and Social Psychology, Vol. 7, 1967"!
Ross, Timothy L. and Jones, Gardner M., "An Approach to Increased
Productivity: The Scanlon Plan," Financial Executive,
Vol. 40, February, 1972.
Rothgeb, W. L. , "Computerized Refuse Collection,'-' Public Works,
101(4), April, 1970.
Rush, Harold M. F., "Behavioral Science—Concepts and Management
Application," Studies in Personnel Policy, No. 216,
National Industrial Conference Board, 1969.
Rush, Harold M. F., "Job Design for Motivation: Experiments in
Job Enlargement and Job Enrichment," The Conference Board,
Report No. 515, 1971.
Rush, Harold M. F., "Motivation Through Job Design," The
Conference Board RECORD, Vol. 8, January, 1971.
Schatz, H. E., "Uses of Work Management," Management Services,
Vol. 6, November, 1969.
Schultz, G. V. "Plants' Incentives Slump Badly Over Last 6
Years," Factory, Vol. 123, No. 6, June, 1965, p. 68-79.
Schuster, Jay R., Clark, Barbara, and Rogers, Miles, "Testing
Portions of the Porter and Lawler Model Regarding the
Motivational Role of Pay," Journal of- Applied Psychology
Vol. 55, No. 3, 1971.
159
-------
Scollay, R. W., "Validation of Personal History Items Against
a Salary Increase Criterion," Personnel Psychology, 1956,
Vol. 9, pp. 325-335.
Scollay, R. W., "Personal History Data as a Predictor of
Success," Personnel Psychology, 1957, Vol. 10, pp. 23-
26.
Scott, Richard D. and Richard W. Johnson, "Use of the Weighted
Application Blank in Selecting Unskilled Employees,"
Journal of Applied Psychology, Vol. 51, No. 5, 1967,
pp. 292-395"
Shebanek, R., Shell, R. L. and Shupe, D. S., "Crew Assignment
Aids Municipal Management," Proceedings, Twenty-Fifth
Annual Institute Conference, American Institute of In-
dustrial Engineers, 1974.
Shell, R. L. and Shupe, D. S., "Work Standards for Waste
Collection," Proceedings, Annual Systems Engineering
Conference, American Institute of Industrial Engineers^,
1973, ~
Shell, R. L. "Work Measurement for Indirect Labor Activities,"
Industrial Management, Vol. 13 (11), November, 1971.
Shell, R. L., and Shupe, D. S., "Predicting Work Content for
Residential Waste Collection," Industrial Engineering,
Vol. 5 (2), February, 1973.
Shell, R. L., and Shupe, D. S., "Predictive Model for Waste
Collection," Proceedings, Twenty-Third Annual Institute
Conference, American Institute of Industrial Engineers,
1972.
Shell, R. L., and Shupe, D. S., "A Study of the Problems of
Predicting Future Volume of Wastes," Solid Wastes Manage-
Ment Refuse Removal Journal, Vol. 15 (3), March, 1972.
Shell, R. L., and Shupe, D. S., Pilot Research Project for
the City of Cincinnati, Department of Public Works,
Division of Waste Collection,University of Cincinnati,
1971.
Shepherd, W. J., "Absence from Work in Relation to Wage Level
and Family Responsibility," Journal of Industrial Medicine,
1958, Vol. 15, pp. 53-61.
Shupe, D. S., and Shell, R. L., "Balancing Waste Collection
Routes," Journal of Environmental Systems, Vol. 1 (4),
December, 1971.
160
-------
Slocum, John W., "Performance and Satisfaction: An
Analysis," Industrial Relations, Vol. 9, October,
1970.
Smith, Elizabeth A. and Gude, Gerald F., "Reevaluation
of the Scanlon Plan as a Motivational Technique,"
Personnel Journal, Vol. 50, December, 1971.
Sorcher, Melvin and Meyer, Herbert H., "Motivating Factory
Employees," Personnel, Vol. 45, January, 1968.
Sorcher, Melvin and Meyer, Herbert H., "Motivation and Job
Performance," Personnel Administration, Vol. 31,
July, 1968.
Spriegel, W. R. and Myers, C. E., Ed., The Writings of
the Gilbreths, Irwin, 1953.
Stone, R. and Company Inc., A Study of Solid Waste Collec-
tion Systems Comparing One-Man with Multi-Man Crews,
USPHS Publication 1892, 1969.
Straiger, M. G., "We Automated Residential Refuse Collection,"
The American City, 85 (11), November, 1970.
Sutermeister, Robert A., People and Productivity, 2nd Edition,
McGraw-Hill, 1969.
Sutermeister, Robert A., "Employee Performance and Employee
Need Satisfaction—Which Comes First?" California
Management Review, Vol. 13, No. 4, Summer, 1971.
Taylor, Frederick W., The Principles of Scientific Management,
Harper, 1971
"Temporaries Set the Pace for Regular Help," Office, Vol. 74,
December, 1971.
"The Job Blahs: Who Wants to Work?" Newsweek, March 26, 1973.
"The Push To Boost Government Productivity," Business Week,
May 13, 1972.
Truitt, M. M., Liebman, L. C. and Kruse, C. W., "Simulation
Model of Urban Refuse Collection," Journal of the
Sanitary Engineering Division, Proceedings, American
Society of Civil Engineers, 95 (SA2), April, 1969.
Truitt; M, M. , Liebman, J. C. and Kruse, C. W. ,, Mathematical
Kpdaliiig of Solid Waste Collection Policies, Vols. 1 and
2, USPHS Publication 2030, 1970.
161
-------
Uris, A., "Can Employees Manage Themselves?" S.A.M. Advanced
Management Journal, Vol. 36, No. 2, 1971.
Vollman, Thomas E., Operations Management, Addison-Wesley,
1973.
Vroom, Victor H., Work and Motivation, Wiley, 1964.
Waters, L. C. and Waters, C., "An Empirical Test of Five
Versions of the Two-Factor Theory of Job Satisfaction,"
Organizational Behavior and Human Performance, Vo1. 7
No. 1, 1972.
Weiner, B., "The Affects of Unsatisfied Achievement-Related
Motivation on Persistence and Subsequent Performance,"
Journal of Personality, Vol. 33, 1965.
Witt, W. E., "Work Measurement of Indirect Labor," Management
Accounting, Vol. 53, November, 1971.
Wofford, J. C., "The Motivational Bases of Job Satisfaction Job
Performance," Personnel Psychology, Vol. 24, No. 3, 1971.
Wolf, Martin G., "Need Gratification Theory: A Theoretical
Reformulation of Job Satisfaction/Dissatisfaction and Job
Motivation," Journal of Applied Psychology, Vol. 54,
February, 1970^
Wyskida, R. M., "A Logical Approach to Solid Waste Collection
Routing," Proceedings, Twenty-Fifth Anniversary Conference,
American Institute of Industrial Engineers, 1973.
Wyskida, R. M. and Gupta, J. N. D., "lE's Improve City's Solid
Waste Collection," Industrial Engineering, Vol. 4, No. 6,
June, 1972.
Yukl, G. A., and Wexley, K. N., Eds. Readings in Organizational
and Industrial Psychology, Oxford University Press (London),
1971.
Zander, A., Forward, J., and Albert R., "Adaptation of Board
Members to Repeated Failure or Success by Their Organiza-
tion," Organizational Behavior and Human Performance,
Vol. 4, 1969.
162
-------
9 APPENDIX
9.1 Sample Employee Preference Choice Form
9.2 Cover Letter for Employee Preference
9.3 Street Collection Data Form
9.4 Weigh Station Record Form
9.5 Partial Map of Covington With Block Identification Numbers
9.6 Computer Program for Work Sampling Values
9.7 Sample Computer Output of Automated Route Design
9.8 Sample Computer Output of Detail Route Design for Team I
9.9 Sample Computer Output of Detail Route Design for Team II
9.10 Sample Ordinance for Once-a-week Collection
9.11 Sample Ordinance for Twice-a-week Collection
9.12 Sample Announcement for Citizen Notification
9.13 Example of Newspaper Coverage Prior to Collection
Alternative Selection
9.14 Newspaper Citizen Notification Prior to Change Over
9.15 Summary of Team Assignments
9.16 Driver Guidelines
9.17 Foreman's Activities
163
-------
APPENDIX 9.1
Mr.
LABORERS
Thaddeus Avery
Archie Britton
Gary Carpenter
Chester Centers
Steven Findley
Thomas Griffin
William Hall
Jerry Harris
Billy Hitch
Richard Hughes
Robert Humphrey Jr.
Michael Irwin
Peter Jaquish
Steven Klein
Phillip Kraus
William Landrum
James Maddox
Arthur Marks
Charles Menke
William Miller
Maurice Mitchell
Fred Penis',-:
Please write the first and last
names of five laborers you want
to work with. Please list five
names only, no more and no less.
Please write the first and last
names of five laborers you do not
want to work with. Please list
five names only, no more and no
less.
Ronald Powers
Michael Rassche
Gerald Speakes
Robert Tabb
Jack Thomas
Mi cha el Van Euss
164
-------
APPENDIX 9,2
Mr.
As you know, Covington is trying to improve waste
collection operations.
Permanent collection crews are being set up so that you
will be able to work with the same people every day, as
long as no one is absent.
Each truck crew will be made up of one Driver and two
Laborers. Four of these crews will work together as a
team to pick up each day's routes.
Since you will be working with the same people every
day, it is very important that you work with the men
you like and get along with.
The Local Union has agreed to help in finding out who
you want to work with. On the next page is an alpha-
betical list of the Laborers. Please pick five Laborers
you want to work with and five Laborers you don't want
to work with. Write your choices on the next page.
Every effort will be made to put you on a crew and team
with the men you want to work with, but every man may
not get his first choices. This can happen if nearly
everyone chooses the same men.
Please do not show your list to anyone else, just fold
the paper and put it in the box. The only people who
will see the list will be those who set up the crews
and teams. Thank you.
165
-------
Page
APPENDIX 9,3
CITY OP COVINGTON
DEPARTMENT OP PUBLIC WORKS
STREET COLLECTION DATA
Street
Prom
To
Day: M T W H F
Date:
Width:
2 cars
3 cars
^ cars
more than
Parking (L)
No Parking
Parking (R)
No Parking
CD
M
ctf
Comments: (Note any
delays or deviations
from normal collection, m
e.g., driver helping, M
cans not at curb, en
truck backing, etc.)
CO
c
ctf
o
rH
O -H
* ^ • s
•H to pj CO W i-HW
-------
APPENDIX 9,4
CITY OF COVINGTON
DEPARTMENT OF PUBLIC WORKS
WEIGH STATION RECORD
Day: M T W H F
Date:
Truck Number
Time
Gross Weight
Pavement
Drj^ 'Wet
167
-------
APPENDIX 9,5 PARTIAL MAP OF COVINGTON WITH BLOCK
IDENTIFICATION NUMBERS
fcr \&«r» r-r^fftUES hnMn'
«,?gK\iva *u
1 0
U[IU(Jt/-l"iJ =='ii--^—.-' hn \f\n 71\'
stSf^fei) [i^lSn
caawminjTbftV fioLfe^Rn^S
uuuwijLiim jorj iU'-'LJ^-/-H ,—r" - -" n u —r
i^^^^S3SS^r
s^^^2mP»^B^^ ^lljtes •
^^^^ra\ \Cn^^ %ff ^r. 3 ^s^yrf°
»^^M\ir ^
A VTOJT^ \ TOS^L^ft l^^;feJ^f^ - ^ c^v^
,,m^^ ,:^f^^«3fe^^
" fcM^f-l
1 i* -".'-—nCip iVL ^P^ - 'i V-\?S/.^ liM^-'-T^" -'-.,- v "
^^-^i\; .^nU,^U ...--, iiJ v^=-,-'- ,,;. ^ ;-• ,,,,„.MV.V.
168
-------
APPENDIX 9,6 COMPUTER PROGRAM FOR WORK SAMPLING VALUES
SJflR WCRKSANP C51TYY HUMPHREYS/SHELL
C BASIC UfiRK SAMPLING STATISTICS
1 INTFGFR ARFA.ACTIV
? niN'FNSTCN /iPFA (1077) .f AMIG77) , ^CTIV(1U77>
3 filMFNSI PfV ACT( 17),PERT( 17) ,PERA{ 17) *PERR<17)
A riVFNSICN ST/JTT (17 ),STA7A( 17»,S7/STBJ 17)
c R I N E N S I P N A R t A P «4 )
f HATA ARFARnj/' NA • / , A REA P C 2 ) / * SR E S * / , ARE AB f 3 ) / s MRE S ' / *
1 /SRFARC4 )/' PTUN8/
I DATA AC7(1)/«NA ' / . A CT I 2 ) / ' ECC 9 / , A C T C 3 ) / s E C 8' i , A CT f 4 )/ « ECE s / » AC7 { 5
? }/ »Wr.C« X,ACTC6 )/«Wf 8« /, ACTS 7 I/ «fcCE s /rACT* Bl/8 WEC V,ACT<9) /« WEB8/,
liCT(lO) /•WFF'/./Bf.Tdl J/'XK « / . AC T f 12. )/ e RD s / , ACT i 13 ) / • PK «/«ACT(14
4)/«SP «/.ACT(15 )/'RK S/,ACT(16)/SLT l/«ACT(17)/'BkK'/
F m I NUV=i .1077
<5 RFAHI 5. "sCO 5 AREA {MJPJoMAMNlN), AC II V/INUM3
10 500 FORMATS 17X II ,6X II. 12)
11 IF(ARFAJMJV) .EC.OGC Tf ^1
1? 1 rnM
1 ? 31 M N =
1 4 FM M = !M
i8? cn in
If 1C ARFA« I S =ARFA (1)4-1
17 nn 2 KI=I.<
C IMTI £1. I7F COUNTERS
IP i;;uf = o,
ic nn ii 1=1.17
2C ST/STTU )=0 .
Pi STATAC I )=0.
77 11 STATRI I )=0 .
?? CN7A=0.
P4 CIMTR=Q.
C CAThER STATISTICS
7 * n n i .s = i. N i. w
?6 IF(ARFAI.I) .NF.K1 )PC TO
77 5 L I" = SUM 41 .
-------
APPENDIX 9,6, CONTINUED
?F T = ACTIV{J)-H
P<3 STATIC IS=STATT C I Ul.
34 3 fDNTINUF
C CAICUIATF FFRC.FM CF CRSERVATICNS FCR E^CH ACTIVITY
^ TFf.^iiM.Fo.o, ir,n Tn 2
^6 nr i ^ K = I . \i
-11 PFRT(K)=STAT71KJ-MGO./SLV
•^c 1^ PFRRCK >=STATP( K muO./
f. WRITF STATISTIC?
40 UR TTF J6.60 )^RF/5RfKl J
41 60 FDRIVAT{ 1H1 ,3CX.« ARF* = « ,44)
4? WR ITF(ft.61 )
4^ M FHRVATf 1H0.25X. 'ACTIVITY CCCUR ENf E ' , /, 3X, ' { NUMB ER OF TIMES ACTIVI
?TY nB^FRVFD/TOTAL MJNBEP OF CQ S EF V/ST IONS ) • >
44 URITF {(S.6? I
45 6? FORMATt IHu.llX , 'ACTIVI TV TCT^i. MAN A MAN Bs)
4A CO 14 L=l. 17
41 kRITFl6.6Gl)ACTfL).PFRT(l i,FERA(LJ,PER8RJ
4fi 601 FORMAT{ 1H0.20X. A3, 7X,F6 .3, 4X,F 6,3»4X,F6.3{
4<5 14 fPNTINUF
<5C y CONTINUF
51 STHP
«5p FNP
JFNTRY
-------
APPENDIX 9,7 SAMPLE COMPUTER OUTPUT OF AUTOMATED ROUTE DESIGN
RUN
ONEDAY 15:06 03/23/75 SUNDAY
MAP DISTANCE ?
WHICH SIDE DO YOU WANT TO WORK WITH
LEFT = 1
RIGHT = 2
72
WANT TO CHANGE THE STARTING ID #
?0
LOAD # 1
LOAD # 2
WEIGHT=10544 LB
WEIGHT= 9849 LB
TIME 10:54
TIME 1:57
LAST ID
LAST ID
360
44
MAP
?20
DISTANCE ?
LOAD # 1 WEIGHT=10448 LB TIME 10:43
LOAD # 2 WE!GHT= 9902 LB TIME 2: 5
LAST ID # 1088
LAST ID # 351
MAP DISTANCE ?
LOAD # 1
LOAD # 2
LOAD # 3
WEIGHT= 9666 LB
WEIGHT=10162 LB
WEIGHT= 2357 LB
TIME 10540 LAST ID # 345
TIME 1 : 48 LAST I D iC 344
TIME 2:59 LAST ID # 312
********************+ +I-* :M-' *********;
171
-------
MAP DISTANCE ?
LOAD # 1
LOAD'# 2
LOAD # 3
WEIGHT^1001 1 LB
WE1GHT= 9360 LB
WEIGHT= 4382 LB
TIME 10:33
TIME 1:29
TIME 3: 0
LAST ID
LAST ID
LAST ID
308
439
334
MAP DISTANCE ?
LOAD # 1
LOAD # 2
LOAD # 3
WEIGHT=
WEIGHT=
WEIGHT^
9476 LB
9593 LB
4544 LB
TIME
TIME
TIME
10: 33
1 :24
2: 56
LAST
LAST
LAST
ID
ID
ID
323
329
287
MAP DISTANCE ?
LOAD # 1 WEIGHT= 9593 LB TIME 10:18 LAST ID t 328
LOAD # 2 WEIGHT=10203 LB TIME 1:14 LAST ID # 448
LOAD # 3 WEIGHT= 6290 LB TIME 2:57 LAST ID # 414
MAP DISTANCE ?
LOAD # 1
LOAD # 2
LOAD # 3
WEIGHT= 9473 LB
WEIGHT= 9897 LB
WEIGHT= 6910 LB
TIME 10:24 LAST ID # 451
TIME 1:11 LAST ID # 1198
TIME 3: 2 LAST ID # 461
:^ **************************#***#******#**#***#******** =t
172
-------
,MAP DISTANCE ?
LOAD # i
LOAD # 2
LOAD # 3
WEIGHT= 9858 LB
UE1GHT=10234 LB
WEIGHT= 762id LB
TIME 10:14
TIME 12s 57
TIME 2:55.
LAST ID
LAST ID
LAST I D
510
465
480
MAP DISTANCE ?
LOAD # 1 WEIGHT= 9869 LB TIME 10:23 LAST ID # 597
'LOAD # 2 WEIGHT= 9627 LB TIME 1:12 LAST ID # 570
LOAD # 3 WEIGHT= 6701 LB TIME 2:59 LAST ID # 558
*********
MAP
713
DISTANCE ?
LOAD # 1
LOAD # 2
LOAD # 3
WEIGHT= 9757 LB
WEIGHT= 9513 LB
WEIGHT= 7670 LB
TIME 10:23 LAST ID # 535
TIME 12:57 LAST ID # 578
TIME 2:54 LAST ID # 566
MAP
710
DISTANCE ?
LOAD t 1
LOAD # 2
LOAD # 3
WEIGHT=10485 LB
WEIGHT= 9460 LB
WEIGHT= 7199 LB
TIME 10:20 LAST ID # 714
TIME 12:58 LAST I D # 707
TIME 2:55 LAST ID # 694
173
-------
APPENDIX 9,8 SAMPLE COMPUTER OUTPUT OF DETAIL ROUTE DESIGN
PLEASE PUNCH THE ESTIMATED MAP-DISTANCE IN INCHES
FROM THE GARAGE TO THE FIRST STOP
79
TIME AT THE FIRST STOP IS 81 6
ALLOWING 8.0 MINS. FOR FUELLING
CLOCK TIME IS 8:14
NOW GO AHEAD AND START PUNCHING THE ID'S
ID #
7790
ID #
7791
ID #
7789
ID #
7788
ID #
7433
ID #
7786
ID #
7787
ID #
7785
ID i
1792
16.7 1565 8:31
37.3 3468 8:52
55.4 5187 9:10
68.6 6508 9:23
77-6 7313 9:32
84.2 7944 9:39
86.5 8124 9:41
88.9 8325 9:43
103.9 9503 9:58
174
-------
#*** THE LOAD IS FULL ****
PLEASE ENTER THE DISTANCE IN MAP-INCHES FROM THE ROUTE TO
•THE LAND-FILL
78
THIS LOAD WEIGHS 9503 POUNDS
TOTAL WEIGHT IN THE ROUTE = 9503 POUNDS
TOTAL TIME IN COLLECTION = 103.9 MINS.
TIME SPENT IN TRAVELLING = 1 1 . 4" MINS.
TOTAL COLLECTION TIME IN THE ROUTE = 103 MINS.
TIME SPENT AT THE LAND-FILL = 10.0 MINS.
CLOCK TIME IS 10; 19
ID #
7793
ID #
7782
ID
7783
ID #
7847
ID #
7781
ID #
7780
ID #
7784
ID #
7817
ID *
7779
ID #
7866
132.2
136.3
.5
1 47. 1
1 53.5
156.7
158.7
180. 1
195.8
2457
2861
3389
3845
4457
4797
4947
6580
8110
10: 47
10: 51
10: 56
11: 2
11: 8
11:11
11:13
1 1 : 34
1 1 : 50
175
-------
205.9 9101 12: 0
NOW IT IS TIME FOR THE LUNCH. WE SHALL
ADVANCE THE CLOCK BY 30 MINUTES.
ALLOWING 8.0 MINS. FOR FUELLING
CLOCK TIME IS 1 2: 38
***# THE LOAD IS FULL **##
PLEASE ENTER THE DISTANCE IN MAP-INCHES FROM THE ROUTE TO
THE LAND-FILL
?8
THIS LOAD WEIGHS 9101 POUNDS
TOTAL WEIGHT IN THE ROUTE = 18604 POUNDS
TOTAL TIME IN COLLECTION = 205.9 MINS.
TIME SPENT IN TRAVELLING = 11.4 MINS.
TOTAL COLLECTION TIME IN THL ROUTE = 308 MINS.
TIME SPENT AT THE LAND-FILL = 10.0 MINS.
CLOCK TIME IS 12: 59
ID #
7864
210.2 307 Is 3
ID »
7865
212.1 399 1: 5
ID #
7863
222.6 1346 1:16
ID #
7862
233.1 2293 1s27
ID *
7841
247.6 3596 1:41
ID #
7840
254.0 4203 1:47
ID #
7822
261.1 4798 1:54
ID #
7821
176
-------
267.8 5101 2: 1
PLEASE NOTE THAT THE QUITTING TIME IS APPROACHING
PLEASE PRINT THE MAP DISTANCE IN INCHES TO THE LANDFILL
?6
ALSO NOTE THAT IT WILL TAKE ABOUT 4.3 MINS
TO GO TO THE LANDFILL AND 10.0 MINS
AT THE LAND-FILL. NOW YOU CAN FINISH THE LOAD
BY PUNCHING A DUMMY ID# = 7777
ID #
7904
TIME 2.1 6
272.6 5342 2: 6
ID #
7902
TIME 2: 7
273.6 5387 2: 7
ID f
7688
TIME 2:16
283. 1 5993 2: 16
ID #
7901
TIME 2: 18
285.4 6188 2:18
ID #
7735
TIME 2:20
287.5 6368 2:20
ID #
7737
TIME 2:36
303.5 7624 2:36
ID #
77777
**** THE LOAD IS FULL ****
PLEASE ENTER THE DISTANCE IN MAP-INCHES FROM THE ROUTE TO
THE LAND-FILL
76
177
-------
THIS LOAD WEIGHS 7624 POUNDS
TOTAL WEIGHT IN THE ROUTE = 26228 POUNDS
TOTAL TIME IN COLLECTION = 303.5 MINS.
TIME SPENT IN TRAVELLING = 4.3 MINS.
TOTAL COLLECTION TIME IN THE ROUTE = 611
TIME SPENT AT THE LAND-FILL = 10.0 MINS.
CLOCK TIME IS 2: 50
MINS,
END OF THE ROUTE
TOTAL TIME= 303.5
TOTAL WEIGHT= 26228
NO. OF LOADS = 3
POUNDS
THE FOLLOWING ID'S HAVE BEEN INCLUDED IN THE ROUTE
433
785
821
901
DO YOU WANT
?0
688
786
822
9p2
1 TO
735
787
840
0
DESIGN
737
788
841
A NEW
779
789
847
ROUTE
780
790
862
781
791
863
782
792
864
783
793
865
784
817
866
STOP
TIME 3 SECS.
OFF
OFF AT 18: 56
PROC. TIME...
TERM. TIME...
16
246
SEC.
MIN.
178
-------
APPENDIX 9.9, SAMPLE COMPUTER OUTPUT OF DETAIL ROUTE DESIGN
ON AT 19:57 03/23/75 SUNDAY LINE 1
USER NUMBER,PASSWORD--BUSOO 1.,BUSMGT
READY
LOAD NEWMOD1
READY
RUN
NEWMOD1 19:59 03/23/75 SUNDAY
DO YOU WANT ABBREVIATED OUTPUT?
YES=1
N0=0
I S IT A NEW ROUTE?
YES=1
N0=0
PLEASE PUNCH THE ESTIMATED MAP- DISTANCE IN INCHES
FROM THE GARAGE TO THE FIRST STOP
721
TIME AT THE FIRST STOP IS bilb
ALLOWING 8.0 WINS. FOR FUELLING
CLOCK TIME IS 8:23
NOW GO AHEAD AND START PUNCHIHG THE ID'S
I D #
7367
5.0 436 8:28
ID #
7366
7.4 653 8:30
ID #
7467
14.0 1332 6:37
ID #
?368
179
-------
ID #
7370
29.1 2687 8:52
ID #
7369
30.6 2778 8:54
ID
7361
36.8 3370 9: 0
ID f
7320
38.8 3485 9: 2
ID #
71094
39-9 3560 9: 3
ID #
7319
ID #
7363
47.7 4087 9:11
54.9 4583 9: 18
ID #
7365
61.3 5182 9:24
ID #
7364
64.0 5377 9527
ID #
7359
ID #
71093
ID #
71089
I D #
71090
68.2 5798 9:31
76.1 6537 9:39
78.1 6729 9:41
82.5 7122 9:45
180
-------
83.0 7152 9:45
ID f
7318
94.3 8124 9: 56
ID #
7360
109.1 9413 10:11
**** THE LOAD IS FULL ****
PLEASE ENTER THE DISTANCE IN MAP-INCHES FROM .THE ROUTE TO
THE LAND-FILL
720
THIS LOAD WEIGHS 9413 POUNDS
TOTAL WEIGHT IN THE ROUTE = 9413 POUNDS
TOTAL TIME IN COLLECTION = 109.1 MINS.
TIME SPENT IN TRAVELLING = 28.4 MINS.
TOTAL COLLECTION TIME IN THE ROUTE .= 109 MINS.
TIME SPENT AT THE LAND-FILL = 10.0 MINS.
CLOCK TIME IS 10: 49
ID #
71096
126. 4 1 195 11: 6
ID f
71091
130.0 1420 11:10
ID #
71086
132.8 1631 11:13
ID #
71085
136.1 1948 11:16
I D #
7358
138.6 2135 11:19
ID #
7357
141.8 2383 11:22
ID t
7356
148. 3 2859 1 1 : 29
ID t
7349 181
-------
154.8 3482 11:35
ID #
7317
164.8 4279 11:45
ID #
71092
175.4 5082 11:56.
ID #
71088
190.7 6459 12:11
NOW IT IS TIME FOR THE LUNCH. WE SHALL
ADVANCE. THE CLOCK BY 30 MINUTES.
ID #
7350
194.1 6805 12:44
ID #
7355
203.1 7680 12:53
ID #
7351
222.5 9802 1:12
ALLOWING 8.0 MINS. FOR FUELLING
CLOCK TIME IS 1 : 20
**** THE LOAD IS FULL ****
PLEASE ENTER THE DISTANCE IN MAP-INCHES FROM THE ROUTE TO
THE LAND-FILL
719
THIS LOAD WEIGHS 9802 POUNDS
TOTAL WEIGHT IN THE ROUTE = 19215 POUNDS
TOTAL TIME IN COLLECTION = 222.5 MINS.
TIME SPENT IN TRAVELLING = 27.0 MINS.
TOTAL COLLECTION TIME IN THE ROUTE = 331 MINS.
TIME SPENT AT THE LAND-FILL = 10.0 MINS.
GLJ1CK TIME IS 1 : 56
182
-------
APPENDIX 9,10 SAMPLE ORDINANCE FOR ONCE-A-WEEK COLLECTION
COMMISSIONERS' ORDINANCE NO.
AN ORDINANCE REGULATING THE CONTAINERIZATION AND
COLLECTION OF GARBAGE, TRASH, GARDEN TRASH, AND
CERTAIN NON-COMBUSTIBLE REFUSE IN THE CITY OF
COVINGTON, KENTUCKY: PRESCRIBING CONDITIONS FOR
CONTAINERIZATION AND FOR COLLECTION BY THE PUBLIC
WORKS DEPARTMENT.
WHEREAS, the City of Covington will implement a new
collection system including new route areas, uniform
collection schedules, revised collection location and
storage requirements, an initiative program for waste
collection employees, and the addition of large item
special pickup service.
NOW, THEREFORE
BE IT ORDAINED BY THE BOARD OF COMMISSIONERS OF THE
CITY OF COVINGTON, KENTON COUNTY, KENTUCKY:
Section 1
DEFINITIONS
Definitions for the following are as stated in Commission-
ers' Ordinance No. 0-49-72: GARBAGE, TRASH, NON-COMBUSTIBLE
REFUSE, GARDEN TRASH, INDUSTRIAL PROCESSING WASTES, and PERSON.
In addition, for the purpose of this ordinance, the
following are defined:
HEAVY USER: A person whose setout on a scheduled collection
day exceeds forty (40) bags, or twenty (20) cans or their
equivalent as defined below.
GARBAGE AND TRASH CONTAINERS:
1) CAN: A metal or plastic container normally sold as a
"garbage can" with capacity between ten (10) and thirty
(30) gallons with handles suitable for lifting. Cans con-
taining garbage must have lids and be watertight.
2) BAG: A plastic or paper container normally sold as a
"trash bag."
3) HEAVY USER CONTAINER: A steel container, with lid, of up
to two-cubic-yard capacity that .is designed for rear load-
ing collection as specified by the Department of Public
Works.
183
-------
UNEXCUSED ABSENTEEISM WITHOUT PAY:
Being absent for any part of a scheduled work day for rea-
sons other than absences allowed with pay.
Section 2
INITIATIVE PROGRAM
New collection route areas shall be implemented during the
month of August, 1973 that will provide a time initiative for
waste collection personnel. The route areas shall be assigned
to teams consisting of trucks, crews, and foremen, and each area
shall be designed for an approximate six and one-half (6 1/2)
hour work day, thus providing an average of one and one-half
(1 1/2) hours daily time initiative for team members. No mem-
ber of a team shall conclude his work day without permission of
the team foreman until that team's assigned area has been col-
lected. The collection route areas shall be reviewed periodi-
cally to adjust for variations- in work content due to changing
characteristics of the City in order to maintain the time initia-
tive program.
For the initiative program to operate successfully absen-
teeism without pay shall be considered excessive and shall con-
stitute inefficiency as outlined in KRS 90.360 when any employee
accumulates three (3) such occurrences during a calendar month.
Section 3
COLLECTION
FREQUENCY
All persons within the City of Covington shall be provided
with once-a-week scheduled collection service and large item
pickup service on a call basis as described in Section 5. Addi-
tional collections shall be provided on request to an approval
by the Superintendent of Public Works according to the following
schedules:
Heavy User Containers:
Additional Pickups Monthly Charge
Per 1st Each Additional
Week Container Container Dumped
1 $20.00 $3.00
2 $30.00 $6.00
184
-------
Heavy User Containers (Continued)
Additional Pickups Monthly Charge
Per 1st Each Additional
Week Container Container Dumped
3 $40.00 $9.00
4 $50.00 $12.00
Bags, Cans, or their Equivalent:
Additional Pickups Monthly Charge
Per 1st 20 Cans/ Ea. Addt'1 20
.Week Equiv./40 Bags Cans/Equiv./40 Bags
1
2
3
4
ALLEY COLLECTION:
Alley collection shall be provided where alleys permit
adequate passage and clearance for collection and where re-
quested by the majority of users concerned. Request shall be
directed to the Superintendent of Public Works for his approval,
HEAVY USERS:
New heavy users shall provide heavy users containers for
collection. New multiple family dwellings with five or more
dwelling units shall provide heavy user containers for collec-
tion. Existing heavy users shall be encouraged to provide
heavy user containers for collection wherever possible.
Section 4
$20.00
$30.00
$40.00
$50.00
$3.00
$6.00
$9.00
$12.00
CONTAINER REQUIREMENTS FOR COLLECTION
1) CAN: Maximum weight of a loaded can shall not exceed fifty
(50) pounds.
2) BAG: Each bag shall be properly tied or otherwise secured
at the top and shall be loaded so as to permit handling for
collection without tearing.
3) OTHER: A non-containerized amount of trash or garden trash
185
-------
not exceeding the volume and weight limits of a can shall
be suitably bound, boxed, or packaged to permit handling
for collection without coming apart.
4) LOCATION: Heavy user containers shall be located where
they are readily accessible from the public right of way
and shall be placed at the curb line or approved alley
location on the scheduled collection day(s). In those
cases where setout space is not available, the user shall
provide setout upon arrival of the collection vehicle, so
that City employees are not required to enter private
property.
5) CONDITION OF CONTAINERS: All cans and heavy user contain-
ers shall be maintained in good condition and repair, and
shall be subject to inspection at setout by waste collection
personnel. Containers in unsatisfactory condition shall be
marked as condemned by Public Works supervisory personnel,
and, as a service to the user, shall be removed at its next
setout.
Section 5
LARGE ITEM SPECIAL PICKUP SERVICE
Special two-man pickup service shall be provided on a "call"
basis to persons desiring to dispose of individual items not
exceeding two-hundred (200) pounds which cannot be collected by
the regular collection vehicle, such as furniture, appliances,
hardware, or other items approved by the Superintendent of
Public Works. Persons desiring this service shall call the
Public Works Department and give their name, address, and de-
scriptions of item(s) to be collected. They will be advised
when to set these items out. Items must be placed at the curb-
line or at approved alley location, so that City employees are
not required to enter private property- Special pickup service
does not apply to loose materials such as loose trash, loose
garden trash, or industrial processing wastes.
186
-------
APPENDIX 9,11, SAMPLE ORDINANCE FOR TWICE-A-WEEK COLLECTION
COMMISSIONERS' ORDINANCE NO.
AN ORDINANCE REGULATING THE CONTAINERIZATION AND
COLLECTION OF GARBAGE, TRASH, GARDEN TRASH, AND
CERTAIN NON-CUMBUSTIBLE REFUSE IN THE CITY OF
COVINGTON, KENTUCKY; PRESCRIBING CONDITIONS FOR
CONTAINERIZATION AND FOR COLLECTION BY THE PUBLIC
WORKS DEPARTMENT.
WHEREAS, the City of Covington will implement a
new collection system including new route areas,
uniform collection schedules, revised collection
location and storage requirements, an initiative
program for waste collection employees, and the
addition of large item special pickup service.
NOW, THEREFORE,
BE IT ORDAINED BY THE BOARD OF COMMISSIONERS OF
THE CITY OF COVINGTON, KENTON COUNTY, KENTUCKY:
Section 1
DEFINITIONS
Definitions for the following are as stated in Commissioners'
Ordinance No. 0-49-72: GARBAGE, TRASH, NON-COMBUSTIBLE REFUSE,
GARDEN TRASH, INDUSTRIAL PROCESSING WASTES, and PERSON.
In addition, for the purpose of this ordinance, the fol-
lowing are defined:
HEAVY USER: A person whose setout on a scheduled collec-
tion day exceeds thirty C30) bags, or fifteen (15) cans or their
equivalent as defined below.
GARBAGE AND TRASH CONTAINERS:
1) CAN: A metal or plastic container normally sold as a
"garbage can" with capacity between ten CIO) and thirty
C30) gallons with handles suitable for lifting. Cans con-
taining garbage must have, lids and be water tight.
187
-------
2) BAG: A plastic or paper container normally sold as a "trash
bag".
3) HEAVY USER CONTAINER: A steel container, with, lid, of up
to two-cubic-yard capacity that is designed for rear loading
collection as specified by the Department of Public Works.
UNEXCUSED ABSENTEEISM WITHOUT PAY:
Being absent for any part of a scheduled work day for reasons
other than absences allowed with pay.
Section 2
INITIATIVE PROGRAM
New collection route areas shall be implemented that will
provide a time initiative for waste collection personnel. The
route areas shall be assigned to teams consisting of trucks,
crews, and foremen, and each area shall be designed for an ap-
proximate six and one-half (6%) hour work day, thus providing
an average of one and one-half (1%) hours daily time initiative
for team members. No member of a team shall conclude his work
day without permission of the team foreman until that team's
assigned area has been collected. The collection route area
shall be reviewed periodically to adjust for variations in work
content due to changing characteristics of the City in order
to maintain the time initiative program.
For the initiative program to operate successfully, absen-
teeism must be minimized. Unexcused absenteeism without pay
shall be considered excessive and shall constitute inefficiency
as outlined in KRS 90.360 when any employee accumulates three (3)
such occurrences during a calendar month.
Section 3
COLLECTION
FREQUENCY:
All persons within the City of Covington shall be provided
with twice-a-week scheduled collection service and large item
pickup service on a call basis as described in Section 5. Addi-
tional collections shall be provided on request to and approval
by the Superintendent of Public Works according to the following
schedules:
188
-------
HEAVY USER CONTAINERS
Additional Pickups
Per
Week
(if on Wed.)
2
3
Monthly Charge
1st Each Additional
Container Container Dumped
$30.00
10.00
40.00
50.00
$3.00
1.00
6.00
9.00
BAGS, CANS, OR THEIR EQUIVALENT:
Additional Pickups
Per
Week
(if on Wed.)
2
3
Monthly Charge
1st 15 Cans/ Ea. Addt'1 15
Equiv./30 Bags Cans/Equiv./30 Bags
$30.00
10.00
40.00
50.00
$3.00
1.00
6.00
9.00
ALLEY COLLECTION;
Alley collection shall be provided where alleys permit
adequate passage and clearance for collection and where requested
by the majority of users concerned. Requests shall be directed
to the Superintendent of Public Works for his approval.
HEAVY USERS;
New heavy users shall provide heavy users containers for
collection. New multiple family dwellings with five or more
dwelling units shall provide heavy user containers for collection,
Existing heavy users shall be encouraged to provide heavy user
containers for collection wherever possible.
Section 4
CONTAINER REQUIREMENTS FOR COLLECTION
1) CAN: Maximum weight of a loaded can shall not exceed fifty
(50) pounds.
189
-------
2) BAG: Each, bag shall be properly tied or otherwise secured
at the top and shall be loaded so as to permit handling for
collection without tearing.
3) OTHER: A non-containerized amount of trash or garden trash
not exceeding the volume and weight limits of a can shall
be suitably bound, boxed, or packaged to permit handling
for collection without coming apart.
4) LOCATION: Heavy user containers shall be located where they
are readily accessible from the public right of way and
shall be placed at the curb line or approved alley location
on the scheduled collection days. In those cases where
setout space is not available, the user shall provide set-
out upon arrival of the collection vehicle, so that City
employees are not required to enter private property.
5) CONDITION OF CONTAINERS: All cans and heavy containers
shall be maintained in good condition and repair, and shall
be subject to inspection at setout by waste collection
personnel. Containers in unsatisfactory condition shall be
so marked by Public Works supervisory personnel, and, as a
service to the user, shall be removed at its next setout.
Section 5
LARGE ITEM SPECIAL PICKUP SERVICE
Special two-man pickup service shall be provided on a "call"
basis to persons desiring to dispose of individual items not ex-
ceeding two-hundred (200) pounds which cannot be collected by the
regular collection vehicle, such as furniture, appliances, hard-
ware, or other items approved by the Superintendent of Public
Works. Persons desiring this service shall call the Public Works
Department and give their name, address, and descriptions of
item(s) to be collected. They will be advised when to set these
items out. Items must be placed at the curbline or at approved
alley location, so that City employees are not required to enter
private property. Special pickup service does not apply to loose
materials such as loose trash, loose garden trash, or industrial
processing wastes.
190
-------
APPENDIX 9,12 SAMPLE FOR CITIZEN NOTIFICATION
1JLP_Q_R_I_A_N_I U_N_OJL!LC_E_M_E_N_I
CITY OF COVINGTON
COVINGTON, KENTUCKY
DEAR CITIZEN:
AS YOU MAY KNOW/ THE ClTY HAS BEEN WORKING FOR THE PAST
SEVERAL MONTHS TO DEVELOP NEW WASTE COLLECTION ROUTES, THE
INCREASED EFFICIENCY OF THE NEW ROUTES WILL ALLOW TWICE-A-WEEK
COLLECTION FOR THE ENTIRE ClTY/ IMPROVED COMMERCIAL AND INSTI-
TUTIONAL COLLECTION, AND LOWER OVERALL COLLECTION COSTS,
EFFECTIVE MONDAY/ THE NEW COLLECTION ROUTES WILL
BE IMPLEMENTED/ THUS REQUIRING THAT EACH FAMILY DETERMINE THEIR
"PICKUP DAYS," PLEASE TAKE A MINUTE TO DETERMINE YOUR LOCATION
ON THE MAP (REVERSIDE SIDE), AND IDENTIFY YOUR SCHEDULED PICKUP
DAYS, THIS INFORMATION WILL ALSO BE PUBLISHED IN THE NEWSPAPERS
DURING THE WEEK OF
CERTAIN COMMERCIAL AND INSTITUTIONAL STOPS WILL BE
NOTIFIED INDIVIDUALLY CONCERNING THEIR PICKUP SCHEDULE,
THANKS FOR HELPING IMPROVE YOUR CITY,
191
-------
APPENDIX 9,13 EXAMPLES OF NEWSPAPER COVERAGE
PRIOR TO COLLECTION ALTERNATIVE
SELECTION
The Kentucky Post, Tuesday, March 19, 1974
Once a week trash collection service for the Qty of
Covinglori appears almost certain now.
The reduction in collections from two to one a week in
3H effort to save city funds probably will go into effect in
June.
A poll of the commissioners and the mayor last night
indicated near unanimity on trimming one collection, ac-
cording to Commissioner George Wermeling.
Commissioner Carl Bowman's "yes and no" answer
about the reduction made him the only question mark on
the five-man commission, Wermeling said.
The amount saved by the cutback depends on whether
the city contracts for the service with a private company
or continues to have the Public Works Dept. handle the
city's garbage.
Whatever the savings—estimates range up to about
5240,000 annually—they will be used for salary or benefit
increases for city employes.
The commission is scheduled to meet Thursday with
representatives of a city employes' union which is irate
over plans to contract out trash collection, the city's
apparent inability to meet pay increase demands, and
icecn'Jy-adopted personnel ordinances wluch allegedly
violate the working agreement with the city.
The main topic of the agenda will be trash collection
plans, which could trim 40 full and part-time Public
Works employes from the payroll.
The attorney for the union recently told The Kentucky
Post the union would take no action until the city actually
accepted a bid from a private trash collector.
He hinted the union would go to the court if this hap-
pens.
A decision is expected to be made on trash collection
plans in the next month before the city finally approves
its S7.3 million operating budget for 1974.
192
-------
APPENDIX 9,13, CONTINUED
The Kentucky Post, Tuesday, May 21, 1974
-
f
BY GREG PAETH
Kentucky Post Slslt Writer
Members of the union
•which represents 200 non-uni-
formed Covington employes
talked strike Monday night.
But Union Treasurer Wil-
liam Sturgeon said members
finally voted by a "heavy
majority" to accept a resolu-
tion reducing city sanitation
crews from three to two men.
He refused to disclose the
exact vote.
The resolution coincides
with city commission decision
which would retain twice-
weekly garbage collections
while trimming the size of
sanitation department crews.
The union had supported
retention of three-men crews
with once-a-week trash collec-
tion.
"It's their ballgame, so
we're playing with them,"
said Sturgeon.
Sturgeon said the union
plan would have saved the
city about $225,000. He said
the city would realize savings
of only $113,000 with the plan
city commissioners favor.
Sturgeon criticized the two-
man crew plan as being "un-
safe," adding that "it prob-
ably won't work in thi; city."
The union treasurer, who
works in the city's horsing de-
partment, said final CL-.nils of
a contract agreement lor the
last half of 1974 are expected
to be worked out \Vt cbesday
in city hall when the union
meets with City Manager
Paul Royster.
Contract talks have been
stymied by uncertainty over
the trash collection plan
which would go into effect
during the last half of the
year.
-93
-------
APPENDIX 9,14 NEWSPAPER CITIZEN NOTIFICATION PRIOR TO CHANGE OVER
The Kentucky P«f, Saturday, August 3, 1974
| /l^l^^^M^t \\
At//' Mfnfnr^-'V^fe—i=-^L_=J^:3 psr,lr,; 1 \\v
Pjli||s|^5r
MfeBJjIsteW^H^-i
?
ALL CITIZENS OF COVINGTON
TRASH COLLECTION SCHEDULE
RESIDENTIAL PICKUP
EFFECTIVE MONDAY, AUGUST 5, 1974
MONDAY AND TKUHSDAY PICKUP
All residences which lie WE5T of the LAN RR track, and NORTH of 13th Street.
HfiV
EAST of the L8.N RR tracks and ABOVE 18th Street, but not including 18th Street,
will be collected on Monday and Thursday.
TUESDAY A-ND FRIDAY PICKUP
All residences which lie WEST of the, L8.N RR tracks and SOUTH of 13th Street,
but not including 13th Street.
AND
all residences which lie EAST of the L&N RR tracks and on or below I8th Street.
will be cc'lccrer:; en Tv^jdv or
-------
APPENDIX 9,15 SUMMARY OF TEAM ASSIGNMENTS
CITY OF COVINGTON
DEPARTMENT OF PUBLIC WORKS
WASTE COLLECTION
Foreman:
Team Drivers:
Heavy User Drivers
TEAM I
Johnson
Craddock
Hitch
Klein
Powers
Raper
Stanley
England
TEAM II
Miller
Cain
Findley
Halbert
Harris
Harris
Sturgeon
McQueen
Results of Team Assignments:
Choices:
Cain
Craddock
England
Find^ey
Fischer
Halbert
Harris
Hitch
Klein
McQueen
Powers
Raper
Stanley
Sturgeon
4/4
2/4
3/4
3/4
2/4
3/4
3/4
1/4
3/4
3/4
3/4
2/4
4/4
3/4
3/4
3/4
2/4
3/4
3/4
3/4
4/4
Shupe/Sbell
7/29/74
195
-------
APPENDIX 9,16
CITY OF COVIflGTON
DEPT, OF PUBLIC WORKS
WASTE COLLECTION
DRIVER GUIDELINES!;
1) In case of breakdown, illness, or accident,
call the Assistant Superintendent's Office
immediately (292-2293, 292-2294).
2) Position truck close to setout.
3) Collect only one side of street per pass
unless street is narrow (3 car widths or
less) and little traffic.
4) Load packer as full as possible.
5) During trip to landfill, shift laborer to
another truck in your team.
6) Help load at heavy setouts except where
unsafe to leave cab.
7) Refuel truck at end of day.
8) ._
9) .
10)
196
-------
APPENDIX 9,17
CITY OF COVINGTON
DEPT, OF PUBLIC WORKS
WASTE COLLECTION
FOREMEN'S ACTIVITIES
The foreman is a key person in the successful
operation of the team initiative system.
Each team is responsible for a collection area on
a given day under the direction of its foreman. The
team member crews share the work load until the job
is completed. No one leaves work until the team area
is totally collected, unless permitted by the foreman.
The foreman's major activities include:
1) Assigning individual manpower and trucks
within the team collection area, and
requesting from the Assistant Superintendent
substitute personnel as required.
2) Maintaining field contact with his truck
crews through out the working day.
3) Coordinating field operations with the
Public Works Office and the Assistant
Superintendent.
4) Responding to citizen complaints originating
within his team's collection crews.
5) Inspecting solid waste containers set out
for collection.
6) Condemning containers that are in violation
of City Ordinance.
7) Initiating action on litter violations
resulting from solid waste setout.
197
-------
APTEJ? TWO
STupy AND £vAiiwnoN, WE'VE N|glf
CONCLUDED; VftU SURE 6OTTA Itf^^
The Kentucky Post, May 15, 1974.
------- |