USPS-T-25
BEFORE THE
POSTAL RATE COMMISSION
WASHINGTON, D.C. 20268-0001
POSTAL RATE AND FEE CHANGES, 2000
I
DIRECT TESTIMONY
OF
DAVID G. YACOBUCCI
ON BEHALF OF
UNITED STATES POSTAL SERVICE
Docket No. R2000-1
-,
USPS-T-25
Page i
TABLE
AUTOBIOGRAPHICAL
I. PURPOSE
OF CONTENTS
SKETCH . . .. . .. .. . . .. . .. . .. .. . .. . . .. .. . . .. . .. . . .. . .. . .. . . .. .. . .. . .. . .. . .. . .. . .. . . iii
AND SCOPE OF TESTIMONY
II. SUMMARY
. .. . .. . . .. .. . .. . .. . . .. . . .. . .. . . .. .. . .. . .. . .. . .. . .. . .. . . 1
OF RESULTS . .. .. . .. . .. . .. .. . .. . .. . . .. .. . .. . . .. .. . .. . .. . . .. . .. . . .. . .. . .. .. . .. . . .. . .. .. . .. . . 2
Ill. SUPPORTING
MATERIALS
IV. COST DEVELOPMENT
.. . .. . . .. .. .. . . .. . .. .. . .. . . .. .. . .. . .. . . .. . . .. . .. . .. . .. . .. . .. . .. . .. . .. . .. . .. 6
. .. . . .. .. . .. . .. . .. .. . .. . . .. .. . .. . .. . .. . .. . .. . .. . . .. . .. . . .. . .. . .. .. . .. . . .. . .. .. . .. . 8
A.
OVERVIEW
. .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
B.
METHODOLOGY
. . .. . .. . .. . .. . .. . .. .. . .. . .. . .. . .. . .. . .. . .. . .. .. . . .. . .. . . .. . . .. . .. .. . .. . .. . .. . .. . .. . .. . 8
C.
ENHANCEMENTS
. .. . .. . .. . .. .. . . .. .. . .. . .. . .. . .. . .. . .. . .. .. . . .. .. . . . .. . .. . .. . .. . .. . .. . .. . .. . .. . .. . . 11
D.
MAILFLOW
MODEL DESIGN . .. .. . . .. . .. . .. .. . . .. . .. .. . .. . . .. . .. . . .. . .. . .. . .. .. . . .. . .. . .. . .. . . 13
E.
VOLUMES
.. . .. . .. . . .. .. . .. . . .. .. . . .. .. . .. .. . .. . . .. .. . .. . . .. .. . .. . .. . .. . . .. . . .. .. . . .. . .. .. . .. . . .. . .. . .. .. 13
F.
CRA-ADJUSTED
G.
MODEL INPUTS .. .. . .. . . .. . .. . .. .. . .. . .. . .. . .. . .. . .. . .. . .. .. . . .. .. . . . .. . .. . .. . .. . .. . .. .. . . .. . .. . .. . .. 14
H.
MODEL WORKSHEETS
I.
MODEL MISCELLANY
V. WEIGHTED-AVERAGE
VI. ISOLATED
APPENDIX
A
COSTS . .. . .. . .. .. . .. . .. . .. . .. . .. . .. . .. . .. . .. . . .. . .. . .. . . .. . .. .. . .. . . .. .. . .. . .. 14
. .. . .. . .. .. . .. . .. . .. . .. . .. . . .. .. . .. . .. . . .. . .. . . .. . .. . .. .. . .. . . .. . .. .. . .. . 19
. .. . .. . .. . .. .. .. . . .. . .. . .. . .. . . .. .. . .. . .. . . .. . .. . .. . . .. . .. .. . .. . .. . . .. .. . .. . 23
COSTS BY RATE CATEGORY . .. . .. . . .. .. . .. . .. . .. . .. . .. . .. . 26
BARCODE-RELATED
COST SAVINGS . . . .. . .. . .. . . .. .. . .. .. . . .. . .. . .. . .. . 27
USPS-T-25
Page ii
LIST OF TABLES
II-1
FIRST-CLASS
UNIT VOLUME VARIABLE
II-2
PERIODICALS REGULAR
PROCESSING COSTS
II-3
PERIODICALS NONPROFIT
PROCESSING COSTS
UNIT VOLUME VARIABLE
II-5
STANDARD MAIL (A) NONPROFIT
PROCESSING COSTS
‘SCENARIO
IV-2
REJECT FLOW
MAIL PROCESSING
UNIT VOLUME VARIABLE
II-4
STANDARD MAIL (A) REGULAR
PROCESSING COSTS
IV-l
1
DATA’ EXAMPLES
COSTS
MAIL
MAIL
UNIT VOLUME VARIABLE
UNIT VOLUME VARIABLE
MAIL
MAIL
USPS-T-25
Page iii
DIRECT TESTIMONY
1
OF DAVID G. YACOBUCCI
AUTOBIOGRAPHICAL
2
3
SKETCH
4
My name is David G. Yacobucci.
5
1997 as an Economist in the Special Studies office. Prior to joining the Postal
6
Service, I worked as a consultant at Price Waterhouse.
7
responsibilities
8
services based upon quantitative
9
and sample design, linear programming,
10
I have worked for the Postal Service since
included directing and performing
techniques.
At Price Waterhouse,
management
Such techniques
forecasting,
regression,
my
consulting
included survey
data mining,
and data warehousing.
11
12
At the Postal Service, I have visited field offices including air mail facilities, bulk
13
mail centers, processing
14
transportation,
and distribution
mail processing,
centers, and delivery units.
and delivery operations
I observed
during these visits.
15
16
I earned Master of Engineering
and Bachelor of Science degrees in Operations
17
Research and Industrial Engineering
18
respectively.
from Cornell University in 1993 and 1992,
USPS-T-25
Page 1
1
2
I. PURPOSE
3
The purpose of my testimony
4
mail processing
5
calculate weighted-average
6
calculate isolated barcode-related
AND SCOPE OF TESTIMONY
is to compute test year (TY) unit volume variable
costs for flat-shaped
mail. This testimony
mail processing
uses these costs to
costs by rate category and to
cost savings.
7
8
To develop these costs and savings, the testimony
9
combinations
10
machinability.’
11
proposed
12
(USPS-T-35)
13
Mail (A) Regular, and Standard Mail (A) Nonprofit flats.
of container
presortation,
models distinct mailflows for
bundle presortation,
barcoding,
These costs support the presort and automation
by witnesses
Fronk (USPS-T-33),
for First-Class,
Periodicals
discounts
Taufique (USPS-T-38),
Regular, Periodicals
and piece
and Moeller
Nonprofit, Standard
’ This testimony uses the following terms interchangeably:
“bundle” and
“package,” “barcoded” and “automation,” and “nonbarcoded” and
“nonautomation.”
USPS-T-25
Page 2
1
2
3
II. SUMMARY
OF RESULTS
This testimony
uses unit volume variable mail processing
4
averages-actual’
5
shaped mail. Cost averages-actual
6
by rate category.
7
holding automationlnonautomation
8
related mail processing
9
savings are normalized weighted-average
mail processing
10
barcode-related
of these cost averages when holding
11
the presort category constant are the isolated barcode-related
12
V and VI of this testimony discuss each method in greater detail.
and “cost averages-normalized
Subtracting
savings.
auto-related
are weighted-average
one weighted-average
characteristics
cost differences.
The differences
costs to calculate “cost
savings” for flat-
mail processing
cost from another when
constant yields presortation-
Cost averages-normalized
auto-related
costs that isolate
savings.
13
14
costs
Tables II-1 through II-5 present the results provided for pricing purposes.
Sections
USPS-T-25
Page 3
UNIT VOLUME
Method
Cost Averages-Actual
TABLE 11-I: FIRST-CLASS
VARIABLE MAIL PROCESSING
COSTS
Rate Category
Cost (cents)
Basic,
Basic,
3-Digit,
5-Digit,
Nonautomation
Automation
Automation
Automation
40.594
47.754
43.872
30.006
Basic,
Basic,
3-Digit,
5-Digit,
Nonautomation
Automation
Automation
Automation
55.041
49.940
40.659
30.036
Cost Averages-Normalized
Auto-Related Savings
USPS-T-25
Page 4
TABLE 11-2: PERIODICALS REGULAR
UNIT VOLUME VARIABLE MAIL PROCESSING
Method
Cost Averages-Actual
Rate Category
COSTS
Cost (cents)
Basic, Nonautomation
Basic, Automation
3-Digit, Nonautomation
3-Digit, Automation
5-Digit, Nonautomation
5-Digit, Automation
Carrier Route
22.781
21.493
18.332
17.898
13.133
13.572
8.640
Basic, Nonautomation
Basic, Automation
3-Digit, Nonautomation
3-Digit, Automation
5-Digit, Nonautomation
5-Digit, Automation
24.115
21.992
19.269
17.755
13.720
13.465
Cost Averages-Normalized
Auto-Related Savings
TABLE
UNIT VOLUME
Method
Cost Averages-Actual
11-3: PERIODICALS NONPROFIT
VARIABLE MAIL PROCESSING COSTS
Rate Category
Basic,
Basic,
3-Digit,
3-Digit,
5-Digit,
5-Digit,
Carrier
Cost (cents)
Nonautomation
Automation
Nonautomation
Automation
Nonautomation
Automation
Route
14.157
11.989
11.438
10.523
7.956
8.039
5.008
Basic, Nonautomation
Basic, Automation
3-Digit, Nonautomation
3-Digit, Automation
5-Digit, Nonautomation
5-Digit, Automation
14.399
13.092
11.733
10.694
8.141
7.958
Cost Averages-Normalized
tuto-Related Savings
USPS-T-25
Page 5
TABLE H-4: STANDARD MAIL (A) REGULAR
UNIT VOLUME VARIABLE MAIL PROCESSING COSTS
Method
Cost Averages-Actual
Rate Category
Cost (cents)
Basic, Nonautomation
Basic, Automation
3/5-Digit, Nonautomation
3IBDigit. Automation
17.765
17.459
12.152
11.664
Basic, Nonautomation
Basic, Automation
3/5-Digit, Nonautomation
3/5-Digit, Automation
19.825
17.915
12.004
11.457
Cost Averages-Normalized
Auto-Related Savings
TABLE 11-5: STANDARD MAIL (A) NONPROFIT
UNIT VOLUME VARlABLE,MAIL
PROCESSING COSTS
Method
Cost Averages-Actual
Rate Category
Cost (cents)
Basic, Nonautomation
Basic, Automation
3/5-Digit, Nonautomation
3/5-Digit, Automation
17.009
17.016
10.098
11.528
Basic, Nonautomation
Basic, Automation
315Digit, Nonautomation
3/5-Digit, Automation
19.334
17.487
10.848
10.370
Cost Averages-Normalized
Auto-Related Savings
USPS-T-25
Page 6
1
2
Ill. SUPPORTING
MATERIALS
3
This section briefly discusses the supporting
4
this testimony.
materials that are associated
with
5
6
A. USPS LR-I-90, FLATS MAIL PROCESSING
COST MODEL.
7
Library reference USPS LR-I-90 presents the electronic spreadsheet
8
testimony used to develop the unit volume variable costs presented
9
The spreadsheet
10
that this
in section II.
presents the data inputs, performs the cost calculations,
and
specifies citations and notes.
11
12
A review of the structure and of section IV, part H, provides a better
13
understanding
14
only presents the electronic version and selected worksheet
of the model.
Due to the size of the model’s printouts, LR-I-90
printouts.
15
-
16
B. USPS LR-I-87, PERIODICALS
MAIL CHARACTERISTICS
17
Library reference USPS LR-I-87 presents the Periodicals
18
mail characteristics
19
and preparation
20
uses these data to determine volume-based
21
weighted-average
survey.
of flat-shaped
Regular and Nonprofit
This survey provides information
Periodicals.
on mail make-up
The flats mail processing
costs and weighted-average
SURVEY
cost model
weights in order to calculate
barcode-related
savings.
22
23
Data come from electronic manifests of Periodicals
mailings and from a national
24
survey of Periodicals
25
Detached Mail Units for randomly selected finance numbers.
26
collected data from June 1999 to July 1999.
mailings sampled through Bulk Mail Entry Units and
The survey
27
28
-~
C. USPS LR-I-89, COVERAGE
29
Library reference
30
analysis allocates originating
31
specific flat sorting machines.
FACTORS
FOR FLATS.
USPS LR-I-89 presents the coverage factor analysis.
and destinating
This
volumes to facilities that employ
The results are the percentages
of mail volume
USPS-T-25
Page 7
1
that originate or destinate to facilities that have equipment.
2
processing
The flats mail
cost model uses these data to model the mail flow of flats.
3
4
D. USPS LR-I-88, FLATS BUNDLE STUDY.
5
Library reference
6
and analyzed data pertaining to bundle handling activities.
7
included mechanized
8
downflow densities,
9
flats mail processing
USPS LR-I-88 presents the bundle study. This study collected
sorting productivities,
and percentages
Study results
manual sorting productivities,
of mechanized
and manual handlings.
cost model uses these data to calculate unit volume
10
variable mail processing
11
1998 and December
costs. The study collected data between September
1998.
The
USPS-T-25
Page 8
.-
1
2
IV. COST DEVELOPMENT
A. OVERVIEW
3
4
This testimony develops unit volume variable mail processing
5
based on particular cost-driving
6
characteristics
7
below.
8
bundle and piece distribution
9
processing
IO
USPS-T-IO.
as worksharing
characteristics.
costs for flats
This testimony
refers to these
attributes and elements and discusses
them
It develops the costs by modeling flats’ mailflows across prospective
operations
activities.
These activities represent TY 2001 mail
for flats. Witness Kingsley discusses these operations
in
11
12
The analysis combines the costs using volume-based
13
by rate category.
14
holding all other factors constant.
weights to develop costs
The analysis also isolates barcode-related
cost savings,
15
16
The barcode-related
cost savings are the mail processing
17
with barcodes and those same flats without barcodes.
18
mail processing
cost differences
of flats
The net results are the
costs avoided due to the barcode.
19
20
B. METHODOLOGY
21
This testimony employs the following methodological
22
Excel 97 software.
23
methodology
The general methodology
in Docket No. R97-1, USPS-T-26
approach
using Microsoft
is based upon witness Seckar’s
and USPS LR-H-134.
24
25
This approach
26
elements in developing
27
productivities,
28
approach assumes that the barcoded worksharing
influences
30
considers
downflow
mail processing
differences
costs. Mail processing
due to variable worksharing
differences
densities, and coverage factors.
mail processing
piece, the worksharing-related
include differences
For example, this
element is an activity that
and, hence, mail processing
costs.
savings reflect mail processing
For a barcoded
differences
in
USPS-T-25
Page 9
1
between a barcoded flat and a nonbarcoded
2
elements constant.
flat, holding all other worksharing
3
4
For the first step of this approach,
5
that cause flats to either avoid or incur mail processing
6
which sufficient modeling data exist:
7
.
Barcoding
8
.
Bundle Presortation
9
l
Container
IO
.
Piece Machinability
I identified the following worksharing
attributes
activity costs and for
Presortation
11
12
I did not include Container Type* as a worksharing
13
necessary
14
productivities,
15
breakdowns
attribute due to the lack of
and sufficient modeling data. Such data include container
the type of container breakdowns,
and the frequency
breakdown
of container
by container type.
16
17
For the second step, I identified the following elements of the worksharing
18
attributes:
19
.
Barcoding
20
l
Bundle Presortation
21
22
Distribution
.
Attribute: Carrier Route3, 5-Digit, 3-Digit, Area
Center (ADC), or Mixed Area Distribution
Presortation
Center (MADC)
Attribute: Carrier Route3, 5-Digit, 3-Digit, ADC, or
MADC4
23
24
Container
Attribute: Barcoded or Nonbarcoded
l
Piece Machinability
Attribute: Machinable
or Nonmachinable
25
* Sacks and pallets are examples of container types.
3 For Periodicals only.
4 This testimony combined Sectional Center Facility (SCF) containers with 3-Digit
containers.
5 I defined machinable flats as flats eligible for Flat Sorting Machine 881 (FSM
881) and Automated Flat Sorting Machine 100 (AFSM 100) processing. Such
USPS-T-25
Page 10
.*
1
For the third step, I identified the following mail processing
2
with respect to the elements of the worksharing
activities that vary
attributes:
3
Bundle Sortation:
MADC Container, ADC Container,
4
Container
5
FSM 881 BCR/OCR
6
Primary (IP), or Incoming Secondary
7
FSM 881 Keying Sortation: OP, ADC, IP, or IS
8
AFSM 100 BCR/OCRIVCS7
9
FSM 1000 BCR Sortation: OP. ADC, IP, or IS
3D Container,
or 5D
Sortation: Outgoing Primary (OP)6, ADC, Incoming
(IS)
Sortation: OP, ADC, IP, or IS
10
FSM 1000 Keying Sortation: OP, ADC, IP, or IS
11
Manual Sortation: OP, ADC, IP, or IS
12
-~
13
For the fourth step, I developed the modeled unit volume variable cost of each
14
appropriate
15
the mail processing
16
and Standard Mail (A) Nonprofit, I modeled 40 distinct mailflows.
17
Regular and Periodicals
combination
of elements by modeling the distinct mailflows across
activities.
For First-Class Mail, Standard
Mail (A) Regular,
For Periodicals
Nonprofit, I modeled 47 distinct mailflows.
18
19
For the fifth step, I adjusted the modeled unit volume variable cost using
20
worksharing-related
21
(CRA) costs.
and not worksharing-related
Cost and Revenue Analysis
22
23
For the sixth step, I weighted the CRA-adjusted
24
volumes to develop weighted-average
unit volume variable costs using
costs by rate category.
25
pieces meet the FSM 881 processing criteria in DMM 5 C820. Nonmachinable
flats are all other flats and are eligible for FSM 1000 processing.
6 The analysis combined OP with Outgoing Secondary (OS) activities. In
addition, it combined Sectional Center Facility (SCF) with IP activities.
7 VCS is an acronym for Video Coding System.
USPS-T-25
Page 11
1
For the seventh step, I weighted the CRA-adjusted
2
using volumes to develop normalized
3
barcode-related
unit volume variable costs
weighted-average
costs that isolate
savings.
4
5
C. ENHANCEMENTS
6
7
This testimony
8
methodology
makes the following enhancements
and construct in Docket No. R97-I,
to witness Seckar’s model
USPS-T-26.
9
1. Updated Mail Processing
IO
11
The model incorporates
12
100 deployments,
Activities
updated mail processing
activities that include AFSM
FSM 881 OCR retrofits, and FSM 1000 BCR retrofits.
13
2. Integrated
14
Bundle and Piece Handling Model
15
The model integrates the bundle and piece handling components
16
Bundles enter bundle handling activities and subsequently
17
downstream
18
activities.
bundle handling activities or separately
into one model.
flow as bundles to
as pieces to piece handling
19
3. Updated Bundle Handling Model
20
21
The model incorporates
an updated bundle handling model.
22
presortation
which modeled bundle handling activity bundles enter.
23
Then, bundles flow to downstream
24
downflow
determines
Container
bundle handling activities based on bundle
densities or to piece distribution.
25
26
The model uses data that include bundle handling productivities,
number of
27
bundle handling% and piggyback factors to develop modeled bundle distribution
28
costs per piece.
29
-,
USPS-T-25
Page 12
.-
1
4. Updated Periodicals
Carrier Route Costing Methodology
2
The model develops mail processing
3
using an updated methodology.
4
bundle handling activities and, when bundles inadvertently
5
carrier route pieces across piece handling activities.
6
the model flows bundles directly to a container opening activity.
7
assigns costs based on the number of handlings
8
include bundle productivities,
costs for carrier route-presorted
Periodicals
The model flows carrier route bundles across
break, flows separate
For carrier route containers,
The model
per activity and data that
wage rates, and piggyback factors.
9
IO
This updated approach is similar to witness Seckar’s approach in Docket No.
11
R97-I,
12
Exhibit USPS-9G.
13
container opening costs. For non-carrier
14
incorporated
15
sortation costs. The current approach
16
past approach,
17
activities.
USPS-T-26
and USPS LR-H-134 which originated
For carrier route containers,
in Docket No. R90-I,
this past approach
route containers,
incorporated
this past approach
allied labor costs to open and dump the container and bundle
incorporates
such costs but, unlike the
models carrier route mailflows across bundle and piece handling
18
5. Incorporated
19
Bundle Breakage
20
The model incorporates
inadvertent
bundle breakage
21
The model assigns a bundle handling cost to the broken bundle and
22
subsequently
23
bundle handling scheme in which the bundle broke.
flows the pieces to the piece distribution
into the modeled mail flow.
scheme comparable
to the
24
25
6. Incorporated
Capacity/SOP
26
The model incorporates
27
(SOP) factors to reflect operational
28
eligible for and have access to a specific piece distribution
29
other activities due to capacity or SOP constraints.
30
equipment
capacity and standard operating procedure
capacity and SOP constraints.
Flats that are
activity will flow to
USPS-T-25
Page 13
1
7. Enhanced
Costing By Worksharing
2
Combinations
3
The model develops costs for each worksharing
4
combination.
5
worksharing-related
This isolates mail processing
Attribute and Element
attribute and element
costs that enable enhanced
savings analyses.
6
7
8. Updated Input Data
8
The model incorporates
9
productivities,
updated input data. Such data include coverage factors,
accept rates, mail characteristics
volumes, and CPA costs.
IO
11
D. MAILFLOW
MODEL DESIGN
12
13
The mailflow model design integrates bundle and piece handling activities to
14
represent
15
model flows flats across activities.
16
capacity/SOP
17
analysis uses the number of bundle or piece handlings per activity to determine
18
the modeled unit volume variable cost.
mail processing
of flats for costing purposes.
Data determine
how the
Such data include coverage factors,
factors, reject rates, and downflow densities.
The modeled cost
19
20
E. VOLUMES
21
22
The model determines
23
combination
24
from mail characteristics
25
volume shares.
The model uses historical volumes in lieu of forecasted
26
to be consistent
with witness Smith’s (USPS-T-21)
27
costs by shape.
Witness Smith assumes volume shares are constant when
28
moving from the base to test year.
29
volume shares for each modeled worksharing
as percentages
of total volume.
The model combines
surveys and from billing determinants
element
historical data
to calculate the
volumes
analysis of mail processing
--
USPS-T-25
Page 14
--
F. CXA-ADJUSTED
1
COSTS
2
3
The model adjusts the modeled unit volume variable costs to determine
CRA-
4
adjusted unit volume variable costs. This is to allocate all modeled and non-
5
modeled volume variable mail processing
6
inherent in any model.
7
and piece handling costs. Non-modeled
8
costs.
costs and to reconcile variation
Modeled costs include bundle handling, bundle opening,
costs include platform and cancellation
9
IO
CRA costs are mail processing
11
considers each cost pool’s cost as either worksharing-related
12
related.
13
worksharing
14
variable with respect to worksharing
Worksharing-related
activity.
costs divided into cost pools. The model
or not worksharing-
costs are costs that are variable with respect to
Not worksharing-related
costs are costs that are not
activity.
15
rc-.
16
The model determines
a proportional
CRA adjustment
factor by dividing the
17
worksharing-related
18
variable cost. The model adjusts the modeled unit volume variable costs by
19
multiplying
20
the not worksharing-related
21
resulting CRA-adjusted
22
that reflect modeled worksharing
CRA cost by the weighted average modeled unit volume
each by the proportional
CRA adjustment factor and then by adding
CRA cost to the consequent
product.
unit volume variable costs are “deaveraged”
Hence, the
CRA costs
cost relationships.
23
24
G. MODEL INPUTS
25
26
The following list describes data inputs to the model.
27
the data inputs.
28
LR-I-90 cites sources for
USPS-T-25
Page 15
1
I. Labor Rate
2
The labor rate is the average cost per hour for clerks and mailhandlers
3
in processing
4
encoding center clerks’ wages.
involved
flats. Hence, this labor rate excludes window service and remote
5
6
2. Premium Pay Factors
7
Premium pay reflects the marginal cost difference due to service standards
8
between First-Class,
9
amount of night and Sunday premium pay hours incurred for mail processing
IO
Periodicals,
and Standard
Mail (A) mail. Differences
in the
cause the factors to differ.
11
3. Piggyback
12
13
Activity-specific
14
processing
15
supervisors,
16
maintenance,
piggyback
costs.
Factors
factors determine
Indirect mail processing
activity-specific
indirect mail
costs include such cost elements as
rent, custodial, heat, lighting, facility and equipment-related
and equipment
depreciation.
17
4. Number of Bundle Handlings
18
19
The number of bundle handlings is the average number of handlings a bundle
20
receives within each bundle handling activity.
21
5. Percentage
22
of Bundle Handlings
23
The percentage
24
manual bundle handlings.
25
MADC, ADC, and 3D containers
26
This division is due to materially different percentages
27
manual bundle handlings for bundles in 5D containers than for bundles in all
28
other containers.
29
ADC, and 3D containers
30
percentages.
31
of bundle handlings is the percentage
of mechanized
The model uses one set of percentages
versus
for bundles in
and another set for bundles in 5D containers.
of mechanized
The model uses one set of percentages
due to model simplification
and
for bundles in MADC,
and materially similar
USPS-T-25
Page 16
1
The model uses these data to weight mechanized
2
productivities
3
handling activity.
and manual bundle
to develop mean bundle handling productivities
for each bundle
4
6. Bundle Breakage
5
6
Bundle breakage
7
integrity and bundle presortation.
8
the broken bundle and flows the pieces in the former bundle to the piece
9
distribution
10
is the percentage
scheme comparable
of bundles that prematurely
lose bundle
The model assigns a bundle handling cost to
to the bundle handling scheme in which the
bundle broke.
11
7. Pieces per Bundle
12
13
Pieces per bundle is the average number of flats per bundle.
The model uses
14
the data to determine the number of bundles entering bundle distribution.
15
8. IS Machine/Manual
16
Factors
17
Incoming secondary
machine/manual
factors are the percentages
18
machine type that flow to a machine for incoming secondary
19
the machine actually processes.
20
the machine are processed
of flats by
piece handlings that
The remaining flats not actually processed
on
manually.
21
9. Plant/Delivery
22
Unit Manual IS Factor
23
The plant/delivery
unit manual incoming secondary
24
flats within manual incoming secondary
25
plant actually distributes.
26
manual incoming secondary
27
processed
factor is the percentage
piece distribution
operations
The remaining flats not actually distributed
piece distribution
operations
of
that the
through the
at the plant are
manually in the delivery unit.
28
-
29
The application
of IS machine/manual
factors and the plant/delivery
30
IS factor model the practice of plants performing
31
and the delivery unit performing
IS distribution
IS distribution
unit manual
for larger zones
for smaller zones.
USPS-T-25
Page 17
1
10. Coverage
2
Factors
3
Coverage factors are the percentages
of mail volume that originate or destinate
4
to facilities that have flat sorting machines.
5
proportions
That is, coverage factors are the
of mail volume that have access to equipment.
6
7
11. Capacity/SOP
Factors
8
These factors indicate the piece distribution
9
due to capacity or standard operating
activities to which flats volumes flow
procedure
constraints.
The flats volumes
10
must be eligible for and have access to the specific piece distribution
activity.
11
other words, these factors allocate flats to specific piece distribution
activities.
12
Operations
In
estimated these factors.
13
14
For example, the model considers
barcoded,
15
eligible for AFSM 100 and FSM 881 processing.
16
those flats originate in a facility that employs AFSM 100s and FSM 881s. The
17
originating
18
model to allocate 55 percent and 45 percent of the flats to the AFSM 100 and
19
FSM 881 respectively.’
20
factors for Periodicals
21
to the FSM 881. This results in 55 out of 100 flats modeled on the AFSM 100
22
activity and 45 out of 100 flats modeled on the FSM 881 activity.
23
considers standard operating
AFSM 100 barcoded capacity/SOP
Then, the originating
machinable
Periodicals
flats to be
Assume in this example that
factors for Periodicals
direct the
FSM 881 barcoded capacity/SOP
direct the model to allocate 100 percent of the 45 percent
procedures
This allocation
and finite machine capacity.
24
25
The modeling approach
developed
and applied the capacity/SOP
26
independently
27
manual IS factor.
28
testimony
29
will overstate the number of flats allocated to manual piece distribution
of the IS machine/manual
In developing
considered
’ USPS LR-I-90, ‘CapacitySOP
factors and the plant/delivery
the destinating
IP piece distribution
factors
capacity/SOP
unit
factors, the
only. Including IS piece distribution
Factors Worksheet.
activities
USPS-T-25
Page 18
1
when the model applies both the capacity/SOP
2
IS machine/manual
and IS machine/manual
factors.
factors allocate flats to IS manual piece distribution
activities.
3
12. Downflow
4
Densities
5
Bundle downflow
densities are the percentages
of bundles that flow from one
8
bundle handling activity to a downstream
7
distribution.
The model presents bundle downflow
8
presortation
by bundle presortation.
bundle handling activity or to piece
densities by container
9
10
Piece downflow
densities are the percentages
11
scheme to a downstream
12
the same equipment
13
itself.”
sortation scheme.
of flats that flow from one sortation
Flats that require a second sort on
using the same sortation scheme are considered
to “flow to
14
15
The model uses the piece downflow density “flow to itself’ to inflate the number
16
of handlings per piece in the ‘Mailflow Mode/ Cosfs’worksheet.
17
18
13. Productivities
19
Bundle handling and piece distribution
20
of bundles and pieces processed
productivities
are the respective number
per work hour.
21
22
14.Volume
Variability Factors
23
Volume variability factors are the elasticities of cost with respect to volumes for
24
mail processing
25
divided by the percentage
activities.
The factors represent the percentage
changes in cost
changes in volume.
26
27
The model uses volume variability factors to develop marginal productivities.
28
29
15.Accept
Rates
30
Bundle and piece accept rates are the respective
31
and piece volumes successfully
percentages
sorted by an activity.
of bundle volumes
The model presents
USPS-T-25
Page 19
1
bundle accept rates by outgoing and incoming.
2
3
4
rates by piece distribution
5
6
7
8
9
IO
11
12
13
14
15
18
17
18
19
20
21
22
23
The model presents piece accept
activity by piece distribution
scheme.
The model uses the bundle reject rates, that is, the difference of one less the
bundle accept rates, to inflate the number of handlings per bundle in the ‘Mailflow
Mode/ Cosfs’worksheet.
difference
The model uses the piece reject rates, that is, the
of one less the piece accept rates, to flow rejected flats to the
appropriate
processing
activity.
16.CRA Costs
CRA costs are mail processing
costs divided into cost pools.
classifies each cost pool’s cost as either worksharing-related
related.
Worksharing-related
modeled worksharing
activity.
The model
or not worksharing-
costs are costs that are variable with respect to
Not worksharing-related
not variable with respect to modeled worksharing
costs are costs that are
activity.
17.Volumes
Volumes are the number of pieces for each worksharing
The model uses the resulting volume percentages
weighted-average
costs and weighted-average
element combination.
as weights in calculating
barcode-related
savings.
H. MODEL WORKSHEETS
24
The following list describes each worksheet of the Excel model. LR-I-90
25
presents the model and worksheets.
26
27
28
29
30
1. ‘Control Sheet’ Worksheet
This worksheet
information
worksharing
controls the model.
The user selects or enters scenario
to develop scenario costs. A scenario is a distinct combination
elements.
of
Variable inputs located in cells 82 through B7 correspond
USPS-T-25
Page 20
.-
1
to the scenario’s
mail class, mail subclass, volume variability assumption,
2
number of entry pieces, and number.
3
4
This worksheet
houses two macro buttons: ‘Run A// Scenarios’ and ‘RUN All
5
Scenarios
6
When pressed, the former button executes a macro that models the pertinent
7
scenarios for the desired class, subclass, and volume variability assumption.
8
The macro also copies each scenario’s total modeled costs per piece to the
9
‘Scenario Costs worksheet.
- PRINT “Mailflow Model” & “Mailflow Model Costs” Worksheets.’
IO
11
When pressed, the latter button executes a macro that performs the same
12
functions as the former button’s macro, but additionally
13
scenarios’
14
the user to print each and every scenario’s
15
subclass.
‘Mai/flow Mode/‘and
prints the pertinent
‘Mailflow Mode/ Costs’worksheets.
This enables
mailflow for the selected class and
16
17
When entering an individual scenario on the ‘Control Sheet,‘the
18
corresponding
19
worksheet.
user will find the
modeled unit volume variable cost on the ‘Mailflow Model Costs’
20
2. ‘Cost Averaging’worksheet
21
22
This worksheet
calculates weighted-average
23
barcode-related
24
These calculations
25
Co&s’ worksheet.
savings for the specified
costs by rate category and isolated
‘Control Sheet’class
and subclass.
rely upon the unit volume variable costs on the ‘Scenario
26
3. ‘Scenario Costs’ Worksheet
27
28
This worksheet
29
specified
30
modeled unit volume variable costs.
31
develops the CRA-adjusted
unit volume variable costs for the
‘Control Sheet’ input. The aforementioned
macros populate the
USPS-T-25
Page 21
4. ‘Mailflow Model’ Worksheet
1
2
This worksheet
is a graphical
representation
3
bundle and piece handling activities.
of a scenario’s
mailflow across
4
5. ‘Mailflow Model Costs’ Worksheet
5
6
This worksheet
develops a scenario’s total modeled cost per piece that is the
7
sum of the modeled bundle distribution cost per piece and the modeled piece
8
distribution
cost per piece.
9
6. ‘Mailflow Model Costs Footnotes’
IO
11
This worksheet
Worksheet
presents footnotes for the ‘Mailflow Mode/ Cosfs’worksheet.
12
7. ‘Scenario Data’ Worksheet
13
14
This worksheet
performs calculations
upon input data and provides data
15
employed
by the ‘Mailflow Mode/‘worksheet.
16
scenario.
The scenario determines
17
worksheet
data examples.
There is one row of data for every
which data are used. Table IV-l presents
18
.
TABLE IV-l: ‘SCENARIO DATA’ EXAMPLES
Number of bundles entering the MADC container activity.
.
Percentage
of bundles that downflow from the 3D container
activity to piece
distribution.
.
Number of pieces that downflow from the ADC container activity to IP piece
distribution.
.
Percentage
of pieces that downflow from the ADC container
piece distribution
.
that flow to the FSM 881 BCR/OCR
FSM Keying OP).
19
activity.
Number of rejects that flow from the FSM 881 BCR/OCR
Keying OP (calculated
activity to IP
OP to the FSM
as part of the total number of pieces flowing to the
USPS-T-25
Page 22
.-
8. ‘Scenario Data Footnores’ Worksheet
1
2
This worksheet
presents footnotes for the ‘Scenario Data’worksheet.
3
9. ‘Data’ Worksheet
4
5
This worksheet
stores modeling input data.
6
IO. ‘Coverage Facto&Worksheet
7
8
This worksheet
stores originating
and destinating
coverage factors.
9
11. ‘CapacitySOP
10
11
This worksheet
stores originating
Factors’ Worksheet
and destinating
capacity/SOP
factors.
12
12. ‘Downflows - Bundle’ Worksheet
13
14
This worksheet
stores bundle downflow densities.
15
/-
13. ‘Downflows
16
17
This worksheet
- Piece’ Worksheet
stores piece downflow densities.
18
14. ‘Productivifies’
19
20
This worksheet
Worksheet
stores productivities
and volume variability factors.
21
15. ‘Accept Rates’ Worksheet
22
23
This worksheet
stores accept rates.
24
16. ‘CRA Cost Pools’ Worksheet
25
26
This worksheet
stores CRA costs and determines
27
worksharing-related
worksharing-related
and not
C!?A costs.
28
17. ‘Vols-First’ Worksheet
29
_-
30
This worksheet
calculates
31
element combinations.
First-Class Mail volumes by worksharing
attribute and
USPS-T-25
Page 23
1
18. ‘Vols-Per Reg’ Worksheet
2
3
This worksheet
calculates
4
and element combinations.
Periodicals
Regular volumes by worksharing
attribute
5
19. ‘Vols-Per Non’ Worksheet
6
7
This worksheet
calculates
8
and~element combinations.
Periodicals
Nonprofit volumes by worksharing
attribute
9
20. ‘Vols-Std (A) Reg’ Worksheet
10
11
This worksheet
calculates
Standard Mail (A) Regular volumes by worksharing
12
attribute and element combinations.
13
21. ‘Vols-Std (A) Non’ Worksheet
14
15
This worksheet
calculates
Standard Mail (A) Nonprofit volumes by worksharing
16
attribute and element combinations.
17
18
I.
MODEL MISCELLANY
19
20
The following list describes various modeling considerations.
21
22
23
1. The model flows rejects according to table IV-2. These flows are estimates
from Operations.
24
25
26
2. The model does not apply coverage or capacity/SOP
factors to rejects.
This
is due to model simplification.
27
28
29
30
3. The model does not model costs for carrier route flats on MADC containers.
This is due to model simplification
and an expected immaterial
cost impact.
USPS-T-25
Page 24
TABLE N-2: REJECT FLOW
.
AFSM 100 barcoded
rejects + 50% FSM 1000 keying, 50% manual
.
AFSM 100 nonbarcoded
l
FSM 881 barcoded
.
FSM 881 nonbarcoded
rejects + 50% FSM 1000 keying, 50% manual
rejects + 50% FSM 881 keying, 50% FSM 1000 keying
rejects + 50% FSM 881 keying, 50% FSM 1000
keying
.
FSM 881 keying rejects + 100% FSM 1000 keying
.
FSM 1000 barcoded
l
FSM 1000 nonbarcoded
rejects 9 80% FSM 1000 keying, 20% manual
rejects 3 100% manual
1
2
P
4. The model considers
nonbarcoded,
to have representative
carrier route flats on ADC, 3D, and 5D
3
containers
mailflows and costs as the corresponding
4
barcoded
mailstreams.
5
barcoded,
carrier route pieces from bundles that prematurely
6
integrity in a manner similar to nonbarcoded
This is due to mail processing
activities handling
lose bundle
pieces.
7
8
9
IO
5. The model considers all CR containers to have only nonbarcoded,
nonmachinable
flats. This is due to the mail processing
respect to barcoding
cost not varying with
or machinability.
11
12
6. The model does not differentiate
sacks from pallets in determining
13
costs. The analysis does differentiate
14
volumes in order to weight costs into rate category average costs.
modeled
sacked volumes from palletized
15
16
-
7. The model applies coverage and capacity/SOP
factors when flats first enter
17
originating
and destinating
piece handling activities.
Before applying the
18
destinating
coverage and capacity/SOP
19
aggregates
flats from both AFSM 100 and FSM 881 activities and from FSM
20
1000 activities.
21
100 and FSM 881 activities and from FSM 1000 activities to destinating
factors, the model separately
Hence, the model reallocates flats flowing from both AFSM
USPS-T-25
Page 25
1
activities.
2
capacity/SOP
Appendix A illustrates how the model combines
coverage and
-~
factors to allocate flats.
3
4
8. The model uses witness Seckar’s piece downflow densities from USPS LR-H-
5
134 which originated
6
extends to each of the following activities: FSM 881 OCR, FSM 881 keying,
7
AFSM 100 BCRIOCRNCS,
8
The FSM 881 BCR density extends to each of the following
9
881 BCR and FSM 1000 BCR. The manual density extends to manual
IO
in USPS LR-MCR3.
The FSM 881 keying density
AFSM 100 OCR/W&
and FSM 1000 keying.
activities: FSM
activities.
11
12
The AFSM 100 can have 120 bins, 20 bins more than the FSM 881 and FSM
13
1000. The model extends the historical densities, however, to AFSM 100
14
activities due to the lack of necessary
and sufficient AFSM 100 density data.
15
16
9. The model equates mechanized
bundle downflow densities
17
bundle downflow densities.
18
manual bundle downflow density data.
with manual
This is due to the lack of necessary
--.
and sufficient
-,
USPS-T-25
Page 26
1
2
V. WEIGHTED-AVERAGE
COSTS BY RATE CATEGORY
3
This testimony calculates weighted-average
4
designates
5
the average flats that qualify for the rate categories.
6
comparable
7
R97-1.
them “cost averages - actual.”
costs by rate category and
These costs are the average costs of
This approach
is
to witness Seckar’s actual mail makeup method in Docket No.
8
9
These cost averages - actual figures determine the average mail processing
10
volume variable unit cost for a given rate category and the presortation-related
11
cost difference for a given flat. Subtracting
12
another when holding automation
13
presortation-related
one weighted-average
or nonautomation
cost from
constant calculates the
cost difference.
14
-
15
The cost averages - actual do not necessarily
16
related cost savings.
17
4 at 1 I-12)
18
barcoded flats appeared
19
averaging.
enable one to calculate barcode-
In witness Moden’s Docket No. R97-1 testimony
(USPS-T-
he referred to a peculiar output from the flats’ cost models, where
to cost more than nonbarcoded
flats. This is due to
20
21
The average flat of a nonbarcoded
rate category may have different container
22
presortation,
and machinability
23
flat of the corresponding
24
hypothetical
25
ADC sack and a hypothetical
26
nonmachinable
27
weighted-average
costs would consider a cost effect due to variable presortation
28
and machinability.
This accordingly
29
savings and may indeed result in peculiar outputs.
package presortation,
barcoded rate category.
average basic, nonbarcoded
attributes than the average
For example, consider a
flat to be a 3-digit, machinable
flat in an
average basic, barcoded flat to be an ADC,
flat on an ADC pallet. A difference of the basic rate categories’
does not isolate barcode-related
cost
USPS-T-25
Page 27
1
2
VI. ISOLATED
BARCODE-RELATED
3
The model calculates
4
and designates
5
differences
6
are the isolated barcode-related
7
savings by holding container
8
machinability
COST SAVINGS
a second set of weighted-average
them “cost averages - normalized
costs by rate category
auto-related
savings.”
The
of these cost averages when holding the presort category constant
cost savings.
presortation,
This testimony
isolates the
package presortation,
and
constant.
9
10
For example, this approach
contrasts the modeled cost of a nonbarcoded,
11
MADC, machinable
flat in a MADC container to the modeled cost of a barcoded,
12
MADC, machinable
flat in a MADC container.
13
processing
14
calculates
15
presortation,
The resulting difference
costs avoided due to the presence of a barcode.
a difference for most combinations
is the mail
The model
of container presortation,
package
and machinability.
16
17
The model excluded the following combinations:’
18
.
Nonbarcoded,
19
.
Barcoded,
20
.
Nonbarcoded,
21
.
Barcoded,
22
.
Nonbarcoded,
23
.
Barcoded,
3-digit flats in ADC and MADC sacks.
3-digit flats in ADC and MADC sacks.
5-digit flats in ADC and MADC sacks.
5-digit flats in ADC and MADC sacks.
5-digit Periodicals
5-digit Periodicals
in 3-digit sacks.
in 3-digit sacks.
24
25
The model excluded these flats because the analysis isolated barcode-related
26
cost saving relationships
27
corresponding
28
between, for example, the basic, nonautomation
29
automation
automation
between each nonautomation
rate category.
rate category and its
Hence, these relationships
are
rate category and the basic,
rate category.
’ The model also did not consider certain First-Class flats due to the
nonexistence of 3-digit and 5-digit nonautomation rate categories.
USPS-T-25
Page 28
*
1
2
The excluded flats do not have such rate category relationships.
3
nonbarcoded,
4
the basic, nonautomation
5
(A) flats in ADC and MADC sacks qualify for the 3/5-digit, automation
6
rate category relationship
7
rate category and the 3/5-digit, automation
3-digit Standard
For example,
Mail (A) flats in ADC and MADC sacks qualify for
rate. The analogous
barcoded,
3-digit Standard Mail
rate. The
in this example is between the basic, nonautomation
rate category.
8
9
IO
Excluding these flats results in isolated barcode-related
cost savings that can be
used for pricing purposes.
11
12
The model uses both barcoded and nonbarcoded
13
cost averages -normalized
14
approach
15
flats and the potential barcode-related
16
differences
17
costs avoided by barcoded flats due to their barcodes and the costs that would
18
be avoided by nonbarcoded
recognizes
auto-related
volumes in calculating
savings weighted
the expected barcode-related
average.
each
This
cost savings from barcoded
cost savings from nonbarcoded
of the cost averages, therefore, include cost-based
flats. The
signals of the
flats if they had barcodes.
19
20
This approach
also ensures that the differences
21
equal the averages of the differences.”
of the weighted-average
costs
lo There are two obvious approaches to perform the calculations. The first
approach is to calculate the average, barcoded flat cost and the average,
nonbarcoded flat cost and then take the difference. This is the difference of the
weighted-average
costs. The second approach is to calculate the barcode to
nonbarcode cost difference for each combination of container presortation,
package presortation, and machinability. Then, the approach uses the
respective volumes to calculate the weighted-average
cost difference. This is the
average of the differences.
APPLICATION
APPENDIX A
OF COVERAGE AND CAPACITY/SOP
FACTORS
-,
1
The ensuing flow charts illustrate how the cost modeling methodology
combines
2
coverage and capacity/SOP
activities.
3
There is a chart for each of the following:
4
.
nonbarcoded,
5
.
barcoded,
6
.
nonbarcoded,
7
.
barcoded,
factors to allocate flats to mail processing
nonmachinable
nonmachinable
machinable
machinable
flats
flats
flats
flats.
8
9
This testimony
discusses the nonbarcoded,
nonmachinable
nonmachinable
flats flow chart. The
10
square box at the top has 100 nonbarcoded,
flats. The approach
11
first applies the FSM 7000 coverage factor to those 100 flats. 86 of the 100 flats
12
originate or destinate to facilities that have FSM 1000s.
13
originate or destinate to facilities that have FSM 1000s. The chart depicts these
14
figures in oval boxes as having “access” or “no access.”
14 of the 100 flats do not
15
,-~
16
The approach then applies the FSM 7000 nonbarcoded
capacity/SOP
factor to
17
the 86 flats. Of the 86 flats, 43 flow to the FSM 1000 keying activity and 43 flow
18
to manual processing.
19
with rounded edges.
The chart depicts these figures in bolded, square boxes
20
21
Of the 14 flats that do not have FSM 1000 access, all 14 flow to manual
22
processing.
23
edges.
The chart depicts this figure in a bolded, square box with rounded
24
25
The overall approach allocates 43 percent of nonbarcoded.
nonmachinable
26
to the FSM 1000 keying activity and 57 percent to manual processing.
flats
Nonmachinable
FSM 1000 Coverage
Factor
14%
88%
100%
FSM 1000 Nonbarcoded
Capacity/SOP Factor
i
-
Nonmachinable
FSM 1000 Coverage
Factor
FSM 1000 Barcoded
Capacity/SOP Factor
100%
0%)
0%
0
Manual
Processing
14
Nonbarcoded,
Machinable
Flats
100
AFSM 100 Coverage
Factor
72%
28%
I
AFSM 100 Nonbarcoded
Capacity/SOP Factor
881 Nonbarcoded
Capacity/SOP Factor
FSM 881 Coverage Fact
AFSM 100
FSM 1000 Coverage Factor,
no AFSM 100 & FSM 88,
FSM
! Fador
FSM 1000 Nonbarwded
Capacity/SOP Factor
72%
AFSM 100 Coverage
Factor
AFSM 100 Barcoded
Capacity/SOP Factor
I
I
1
60%
&AFSM 1 OOb
BCWOCW
VCS
Processing
<
43
,
FSM 881 Coverage Factor I
AFSM 100
FSM 881 Barcoded
CaoacitvlSOP Factor
I
FSM ,000 Coverage Factor I
._^.. .^^ ^ _^..^^1
&0
D
M=3lUd
Processing
0
00.
Capacity/SOP
Factor
P
c
0%
coverage
.FSM 100
100%
I
no AFSM 100 & FSM 881
FSM ,000 Barcoded