USPS-T-25
BEFORE THE
POSTAL RATE COMMISSION
WASHINGTON, D.C. 20268-0001
POSTAL RATE AND FEE CHANGES, 2000
Docket No. R2000-1
DIRECT TESTIMONY
OF
DAVID G. YACOBUCCI
ON BEHALF OF
UNITED STATES POSTAL SERVICE
USPS-T-25
Page i
TABLE OF CONTENTS
AUTOBIOGRAPHICAL SKETCH......................................................................... iii
I. PURPOSE AND SCOPE OF TESTIMONY ....................................................... 1
II. SUMMARY OF RESULTS ................................................................................ 2
III. SUPPORTING MATERIALS ............................................................................ 6
IV. COST DEVELOPMENT .................................................................................. 8
A.
OVERVIEW ................................................................................................ 8
B.
METHODOLOGY ....................................................................................... 8
C. ENHANCEMENTS ................................................................................... 11
D. MAILFLOW MODEL DESIGN .................................................................. 13
E.
VOLUMES................................................................................................ 13
F.
CRA-ADJUSTED COSTS ........................................................................ 14
G. MODEL INPUTS ...................................................................................... 14
H. MODEL WORKSHEETS .......................................................................... 19
I.
MODEL MISCELLANY ............................................................................. 23
V. WEIGHTED-AVERAGE COSTS BY RATE CATEGORY ............................... 26
VI. ISOLATED BARCODE-RELATED COST SAVINGS ..................................... 27
APPENDIX A
USPS-T-25
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LIST OF TABLES
II-1
FIRST-CLASS UNIT VOLUME VARIABLE MAIL PROCESSING COSTS
II-2
PERIODICALS REGULAR UNIT VOLUME VARIABLE MAIL
PROCESSING COSTS
II-3
PERIODICALS NONPROFIT UNIT VOLUME VARIABLE MAIL
PROCESSING COSTS
II-4
STANDARD MAIL (A) REGULAR UNIT VOLUME VARIABLE MAIL
PROCESSING COSTS
II-5
STANDARD MAIL (A) NONPROFIT UNIT VOLUME VARIABLE MAIL
PROCESSING COSTS
IV-1
‘SCENARIO DATA’ EXAMPLES
IV-2
REJECT FLOW
USPS-T-25
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1
DIRECT TESTIMONY OF DAVID G. YACOBUCCI
2
3
AUTOBIOGRAPHICAL SKETCH
4
My name is David G. Yacobucci. I have worked for the Postal Service since
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. At Price Waterhouse, my
7
responsibilities included directing and performing management consulting
8
services based upon quantitative techniques. Such techniques included survey
9
and sample design, linear programming, forecasting, regression, data mining,
10
and data warehousing.
11
12
At the Postal Service, I have visited field offices including air mail facilities, bulk
13
mail centers, processing and distribution centers, and delivery units. I observed
14
transportation, mail processing, and delivery operations during these visits.
15
16
I earned Master of Engineering and Bachelor of Science degrees in Operations
17
Research and Industrial Engineering from Cornell University in 1993 and 1992,
18
respectively.
USPS-T-25
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2
I. PURPOSE AND SCOPE OF TESTIMONY
3
The purpose of my testimony is to compute test year (TY) unit volume variable
4
mail processing costs for flat-shaped mail. This testimony uses these costs to
5
calculate weighted-average mail processing costs by rate category and to
6
calculate isolated barcode-related cost savings.
7
8
To develop these costs and savings, the testimony models distinct mailflows for
9
combinations of container presortation, bundle presortation, barcoding, and piece
10
machinability.1 These costs support the presort and automation discounts
11
proposed by witnesses Fronk (USPS-T-33), Taufique (USPS-T-38), and Moeller
12
(USPS-T-35) for First-Class, Periodicals Regular, Periodicals Nonprofit, Standard
13
Mail (A) Regular, and Standard Mail (A) Nonprofit flats.
14
This testimony uses the following terms interchangeably: “bundle” and
“package,” “barcoded” and “automation,” and “nonbarcoded” and
“nonautomation.”
1
USPS-T-25
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2
3
II. SUMMARY OF RESULTS
4
averages-actual” and “cost averages-normalized auto-related savings” for flat-
5
shaped mail. Cost averages-actual are weighted-average mail processing costs
6
by rate category. Subtracting one weighted-average cost from another when
7
holding automation/nonautomation characteristics constant yields presortation-
8
related mail processing cost differences. Cost averages-normalized auto-related
9
savings are normalized weighted-average mail processing costs that isolate
This testimony uses unit volume variable mail processing costs to calculate “cost
10
barcode-related savings. The differences of these cost averages when holding
11
the presort category constant are the isolated barcode-related savings. Sections
12
V and VI of this testimony discuss each method in greater detail.
13
14
15
Tables II-1 through II-5 present the results provided for pricing purposes.
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TABLE II-1: FIRST-CLASS
UNIT VOLUME VARIABLE MAIL PROCESSING COSTS
Method
Cost Averages-Actual
Rate Category
Cost (cents)
Basic, Nonautomation
Basic, Automation
3-Digit, Automation
5-Digit, Automation
40.594
47.754
43.872
30.006
Basic, Nonautomation
Basic, Automation
3-Digit, Automation
5-Digit, Automation
55.041
49.940
40.659
30.036
Cost Averages-Normalized
Auto-Related Savings
USPS-T-25
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TABLE II-2: PERIODICALS REGULAR
UNIT VOLUME VARIABLE MAIL PROCESSING COSTS
Method
Cost Averages-Actual
Rate Category
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 II-3: PERIODICALS NONPROFIT
UNIT VOLUME VARIABLE MAIL PROCESSING COSTS
Method
Cost Averages-Actual
Rate Category
Cost (cents)
Basic, Nonautomation
Basic, Automation
3-Digit, Nonautomation
3-Digit, Automation
5-Digit, Nonautomation
5-Digit, Automation
Carrier 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
Auto-Related Savings
USPS-T-25
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TABLE II-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
3/5-Digit, 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 II-5: STANDARD MAIL (A) NONPROFIT
UNIT VOLUME VARIABLE 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
3/5-Digit, Nonautomation
3/5-Digit, Automation
19.334
17.487
10.848
10.370
Cost Averages-Normalized
Auto-Related Savings
USPS-T-25
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1
2
III. SUPPORTING MATERIALS
3
This section briefly discusses the supporting materials that are associated with
4
this testimony.
5
6
A. USPS LR-I-90, FLATS MAIL PROCESSING COST MODEL.
7
Library reference USPS LR-I-90 presents the electronic spreadsheet that this
8
testimony used to develop the unit volume variable costs presented in section II.
9
The spreadsheet presents the data inputs, performs the cost calculations, and
10
specifies citations and notes.
11
12
A review of the structure and of section IV, part H, provides a better
13
understanding of the model. Due to the size of the model’s printouts, LR-I-90
14
only presents the electronic version and selected worksheet printouts.
15
16
B. USPS LR-I-87, PERIODICALS MAIL CHARACTERISTICS SURVEY
17
Library reference USPS LR-I-87 presents the Periodicals Regular and Nonprofit
18
mail characteristics survey. This survey provides information on mail make-up
19
and preparation of flat-shaped Periodicals. The flats mail processing cost model
20
uses these data to determine volume-based weights in order to calculate
21
weighted-average costs and weighted-average barcode-related savings.
22
23
Data come from electronic manifests of Periodicals mailings and from a national
24
survey of Periodicals mailings sampled through Bulk Mail Entry Units and
25
Detached Mail Units for randomly selected finance numbers. The survey
26
collected data from June 1999 to July 1999.
27
28
C. USPS LR-I-89, COVERAGE FACTORS FOR FLATS.
29
Library reference USPS LR-I-89 presents the coverage factor analysis. This
30
analysis allocates originating and destinating volumes to facilities that employ
31
specific flat sorting machines. The results are the percentages of mail volume
USPS-T-25
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1
that originate or destinate to facilities that have equipment. The flats mail
2
processing 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 USPS LR-I-88 presents the bundle study. This study collected
6
and analyzed data pertaining to bundle handling activities. Study results
7
included mechanized sorting productivities, manual sorting productivities,
8
downflow densities, and percentages of mechanized and manual handlings. The
9
flats mail processing cost model uses these data to calculate unit volume
10
variable mail processing costs. The study collected data between September
11
1998 and December 1998.
12
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2
3
IV. COST DEVELOPMENT
A. OVERVIEW
4
This testimony develops unit volume variable mail processing costs for flats
5
based on particular cost-driving characteristics. This testimony refers to these
6
characteristics as worksharing attributes and elements and discusses them
7
below. It develops the costs by modeling flats’ mailflows across prospective
8
bundle and piece distribution activities. These activities represent TY 2001 mail
9
processing operations for flats. Witness Kingsley discusses these operations in
10
USPS-T-10.
11
12
The analysis combines the costs using volume-based weights to develop costs
13
by rate category. The analysis also isolates barcode-related cost savings,
14
holding all other factors constant.
15
16
The barcode-related cost savings are the mail processing cost differences of flats
17
with barcodes and those same flats without barcodes. The net results are the
18
mail processing costs avoided due to the barcode.
19
20
B. METHODOLOGY
21
This testimony employs the following methodological approach using Microsoft
22
Excel 97 software. The general methodology is based upon witness Seckar’s
23
methodology in Docket No. R97-1, USPS-T-26 and USPS LR-H-134.
24
25
This approach considers mail processing differences due to variable worksharing
26
elements in developing costs. Mail processing differences include differences in
27
productivities, downflow densities, and coverage factors. For example, this
28
approach assumes that the barcoded worksharing element is an activity that
29
influences mail processing and, hence, mail processing costs. For a barcoded
30
piece, the worksharing-related savings reflect mail processing differences
USPS-T-25
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1
between a barcoded flat and a nonbarcoded flat, holding all other worksharing
2
elements constant.
3
4
For the first step of this approach, I identified the following worksharing attributes
5
that cause flats to either avoid or incur mail processing activity costs and for
6
which sufficient modeling data exist:
7

Barcoding
8

Bundle Presortation
9

Container Presortation
10

Piece Machinability
11
12
I did not include Container Type2 as a worksharing attribute due to the lack of
13
necessary and sufficient modeling data. Such data include container breakdown
14
productivities, the type of container breakdowns, and the frequency of container
15
breakdowns by container type.
16
17
For the second step, I identified the following elements of the worksharing
18
attributes:
19

Barcoding Attribute: Barcoded or Nonbarcoded
20

Bundle Presortation Attribute: Carrier Route3, 5-Digit, 3-Digit, Area
21
Distribution Center (ADC), or Mixed Area Distribution Center (MADC)

22
Container Presortation Attribute: Carrier Route3, 5-Digit, 3-Digit, ADC, or
MADC4
23

24
Piece Machinability Attribute: Machinable or Nonmachinable5
25
2
Sacks and pallets are examples of container types.
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
3
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For the third step, I identified the following mail processing activities that vary
2
with respect to the elements of the worksharing attributes:
3

4
5
Bundle Sortation: MADC Container, ADC Container, 3D Container, or 5D
Container

6
FSM 881 BCR/OCR Sortation: Outgoing Primary (OP)6, ADC, Incoming
Primary (IP), or Incoming Secondary (IS)
7

FSM 881 Keying Sortation: OP, ADC, IP, or IS
8

AFSM 100 BCR/OCR/VCS7 Sortation: OP, ADC, IP, or IS
9

FSM 1000 BCR 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 combination of elements by modeling the distinct mailflows across
15
the mail processing activities. For First-Class Mail, Standard Mail (A) Regular,
16
and Standard Mail (A) Nonprofit, I modeled 40 distinct mailflows. For Periodicals
17
Regular and 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 and not worksharing-related Cost and Revenue Analysis
21
(CRA) costs.
22
23
For the sixth step, I weighted the CRA-adjusted unit volume variable costs using
24
volumes to develop weighted-average costs by rate category.
25
pieces meet the FSM 881 processing criteria in DMM § 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.
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1
For the seventh step, I weighted the CRA-adjusted unit volume variable costs
2
using volumes to develop normalized weighted-average costs that isolate
3
barcode-related savings.
4
5
C. ENHANCEMENTS
6
7
This testimony makes the following enhancements to witness Seckar’s model
8
methodology and construct in Docket No. R97-1, USPS-T-26.
9
10
1. Updated Mail Processing Activities
11
The model incorporates updated mail processing activities that include AFSM
12
100 deployments, FSM 881 OCR retrofits, and FSM 1000 BCR retrofits.
13
14
2. Integrated Bundle and Piece Handling Model
15
The model integrates the bundle and piece handling components into one model.
16
Bundles enter bundle handling activities and subsequently flow as bundles to
17
downstream bundle handling activities or separately as pieces to piece handling
18
activities.
19
20
3. Updated Bundle Handling Model
21
The model incorporates an updated bundle handling model. Container
22
presortation determines which modeled bundle handling activity bundles enter.
23
Then, bundles flow to downstream bundle handling activities based on bundle
24
downflow densities or to piece distribution.
25
26
The model uses data that include bundle handling productivities, number of
27
bundle handlings, and piggyback factors to develop modeled bundle distribution
28
costs per piece.
29
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4. Updated Periodicals Carrier Route Costing Methodology
2
The model develops mail processing costs for carrier route-presorted Periodicals
3
using an updated methodology. The model flows carrier route bundles across
4
bundle handling activities and, when bundles inadvertently break, flows separate
5
carrier route pieces across piece handling activities. For carrier route containers,
6
the model flows bundles directly to a container opening activity. The model
7
assigns costs based on the number of handlings per activity and data that
8
include bundle productivities, wage rates, and piggyback factors.
9
10
This updated approach is similar to witness Seckar’s approach in Docket No.
11
R97-1, USPS-T-26 and USPS LR-H-134 which originated in Docket No. R90-1,
12
Exhibit USPS-9G. For carrier route containers, this past approach incorporated
13
container opening costs. For non-carrier route containers, this past approach
14
incorporated allied labor costs to open and dump the container and bundle
15
sortation costs. The current approach incorporates such costs but, unlike the
16
past approach, models carrier route mailflows across bundle and piece handling
17
activities.
18
19
5. Incorporated Bundle Breakage
20
The model incorporates inadvertent bundle breakage into the modeled mail flow.
21
The model assigns a bundle handling cost to the broken bundle and
22
subsequently flows the pieces to the piece distribution scheme comparable to the
23
bundle handling scheme in which the bundle broke.
24
25
6. Incorporated Capacity/SOP
26
The model incorporates equipment capacity and standard operating procedure
27
(SOP) factors to reflect operational capacity and SOP constraints. Flats that are
28
eligible for and have access to a specific piece distribution activity will flow to
29
other activities due to capacity or SOP constraints.
30
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2
7. Enhanced Costing By Worksharing Attribute and Element
Combinations
3
The model develops costs for each worksharing attribute and element
4
combination. This isolates mail processing costs that enable enhanced
5
worksharing-related savings analyses.
6
7
8. Updated Input Data
8
The model incorporates updated input data. Such data include coverage factors,
9
productivities, accept rates, mail characteristics volumes, and CRA costs.
10
11
D. MAILFLOW MODEL DESIGN
12
13
The mailflow model design integrates bundle and piece handling activities to
14
represent mail processing of flats for costing purposes. Data determine how the
15
model flows flats across activities. Such data include coverage factors,
16
capacity/SOP factors, reject rates, and downflow densities. The modeled cost
17
analysis uses the number of bundle or piece handlings per activity to determine
18
the modeled unit volume variable cost.
19
20
E. VOLUMES
21
22
The model determines volume shares for each modeled worksharing element
23
combination as percentages of total volume. The model combines historical data
24
from mail characteristics surveys and from billing determinants to calculate the
25
volume shares. The model uses historical volumes in lieu of forecasted volumes
26
to be consistent with witness Smith’s (USPS-T-21) analysis of mail processing
27
costs by shape. Witness Smith assumes volume shares are constant when
28
moving from the base to test year.
29
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F. CRA-ADJUSTED 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 costs and to reconcile variation
6
inherent in any model. Modeled costs include bundle handling, bundle opening,
7
and piece handling costs. Non-modeled costs include platform and cancellation
8
costs.
9
10
CRA costs are mail processing costs divided into cost pools. The model
11
considers each cost pool’s cost as either worksharing-related or not worksharing-
12
related. Worksharing-related costs are costs that are variable with respect to
13
worksharing activity. Not worksharing-related costs are costs that are not
14
variable with respect to worksharing activity.
15
16
The model determines a proportional CRA adjustment factor by dividing the
17
worksharing-related CRA cost by the weighted average modeled unit volume
18
variable cost. The model adjusts the modeled unit volume variable costs by
19
multiplying each by the proportional CRA adjustment factor and then by adding
20
the not worksharing-related CRA cost to the consequent product. Hence, the
21
resulting CRA-adjusted unit volume variable costs are “deaveraged” CRA costs
22
that reflect modeled worksharing cost relationships.
23
24
G. MODEL INPUTS
25
26
The following list describes data inputs to the model. LR-I-90 cites sources for
27
the data inputs.
28
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1. Labor Rate
2
The labor rate is the average cost per hour for clerks and mailhandlers involved
3
in processing flats. Hence, this labor rate excludes window service and remote
4
encoding center clerks’ wages.
5
6
2. Premium Pay Factors
7
Premium pay reflects the marginal cost difference due to service standards
8
between First-Class, Periodicals, and Standard Mail (A) mail. Differences in the
9
amount of night and Sunday premium pay hours incurred for mail processing
10
cause the factors to differ.
11
12
3. Piggyback Factors
13
Activity-specific piggyback factors determine activity-specific indirect mail
14
processing costs. Indirect mail processing costs include such cost elements as
15
supervisors, rent, custodial, heat, lighting, facility and equipment-related
16
maintenance, and equipment depreciation.
17
18
4. Number of Bundle Handlings
19
The number of bundle handlings is the average number of handlings a bundle
20
receives within each bundle handling activity.
21
22
5. Percentage of Bundle Handlings
23
The percentage of bundle handlings is the percentage of mechanized versus
24
manual bundle handlings. The model uses one set of percentages for bundles in
25
MADC, ADC, and 3D containers and another set for bundles in 5D containers.
26
This division is due to materially different percentages of mechanized and
27
manual bundle handlings for bundles in 5D containers than for bundles in all
28
other containers. The model uses one set of percentages for bundles in MADC,
29
ADC, and 3D containers due to model simplification and materially similar
30
percentages.
31
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The model uses these data to weight mechanized and manual bundle
2
productivities to develop mean bundle handling productivities for each bundle
3
handling activity.
4
5
6. Bundle Breakage
6
Bundle breakage is the percentage of bundles that prematurely lose bundle
7
integrity and bundle presortation. The model assigns a bundle handling cost to
8
the broken bundle and flows the pieces in the former bundle to the piece
9
distribution scheme comparable to the bundle handling scheme in which the
10
bundle broke.
11
12
7. Pieces per Bundle
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
16
8. IS Machine/Manual Factors
17
Incoming secondary machine/manual factors are the percentages of flats by
18
machine type that flow to a machine for incoming secondary piece handlings that
19
the machine actually processes. The remaining flats not actually processed on
20
the machine are processed manually.
21
22
9. Plant/Delivery Unit Manual IS Factor
23
The plant/delivery unit manual incoming secondary factor is the percentage of
24
flats within manual incoming secondary piece distribution operations that the
25
plant actually distributes. The remaining flats not actually distributed through the
26
manual incoming secondary piece distribution operations at the plant are
27
processed manually in the delivery unit.
28
29
The application of IS machine/manual factors and the plant/delivery unit manual
30
IS factor model the practice of plants performing IS distribution for larger zones
31
and the delivery unit performing IS distribution for smaller zones.
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1
2
10. Coverage Factors
3
Coverage factors are the percentages of mail volume that originate or destinate
4
to facilities that have flat sorting machines. That is, coverage factors are the
5
proportions of mail volume that have access to equipment.
6
7
11. Capacity/SOP Factors
8
These factors indicate the piece distribution activities to which flats volumes flow
9
due to capacity or standard operating procedure constraints. The flats volumes
10
must be eligible for and have access to the specific piece distribution activity. In
11
other words, these factors allocate flats to specific piece distribution activities.
12
Operations estimated these factors.
13
14
For example, the model considers barcoded, machinable Periodicals flats to be
15
eligible for AFSM 100 and FSM 881 processing. Assume in this example that
16
those flats originate in a facility that employs AFSM 100s and FSM 881s. The
17
originating AFSM 100 barcoded capacity/SOP factors for Periodicals direct the
18
model to allocate 55 percent and 45 percent of the flats to the AFSM 100 and
19
FSM 881 respectively.8 Then, the originating FSM 881 barcoded capacity/SOP
20
factors for Periodicals direct the model to allocate 100 percent of the 45 percent
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. This allocation
23
considers standard operating procedures and finite machine capacity.
24
25
The modeling approach developed and applied the capacity/SOP factors
26
independently of the IS machine/manual factors and the plant/delivery unit
27
manual IS factor. In developing the destinating capacity/SOP factors, the
28
testimony considered IP piece distribution only. Including IS piece distribution
29
will overstate the number of flats allocated to manual piece distribution activities
8
USPS LR-I-90, ‘CapacitySOP’ Factors Worksheet.
USPS-T-25
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1
when the model applies both the capacity/SOP and IS machine/manual factors.
2
IS machine/manual factors allocate flats to IS manual piece distribution activities.
3
4
12. Downflow Densities
5
Bundle downflow densities are the percentages of bundles that flow from one
6
bundle handling activity to a downstream bundle handling activity or to piece
7
distribution. The model presents bundle downflow densities by container
8
presortation by bundle presortation.
9
10
Piece downflow densities are the percentages of flats that flow from one sortation
11
scheme to a downstream sortation scheme. Flats that require a second sort on
12
the same equipment using the same sortation scheme are considered to “flow to
13
itself.”
14
15
The model uses the piece downflow density “flow to itself” to inflate the number
16
of handlings per piece in the ‘Mailflow Model Costs’ worksheet.
17
18
13. Productivities
19
Bundle handling and piece distribution productivities are the respective number
20
of bundles and pieces processed 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 activities. The factors represent the percentage changes in cost
25
divided by the percentage 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 percentages of bundle volumes
31
and piece volumes successfully sorted by an activity. The model presents
USPS-T-25
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1
bundle accept rates by outgoing and incoming. The model presents piece accept
2
rates by piece distribution activity by piece distribution scheme.
3
4
The model uses the bundle reject rates, that is, the difference of one less the
5
bundle accept rates, to inflate the number of handlings per bundle in the ‘Mailflow
6
Model Costs’ worksheet. The model uses the piece reject rates, that is, the
7
difference of one less the piece accept rates, to flow rejected flats to the
8
appropriate processing activity.
9
10
16. CRA Costs
11
CRA costs are mail processing costs divided into cost pools. The model
12
classifies each cost pool’s cost as either worksharing-related or not worksharing-
13
related. Worksharing-related costs are costs that are variable with respect to
14
modeled worksharing activity. Not worksharing-related costs are costs that are
15
not variable with respect to modeled worksharing activity.
16
17
17. Volumes
18
Volumes are the number of pieces for each worksharing element combination.
19
The model uses the resulting volume percentages as weights in calculating
20
weighted-average costs and weighted-average barcode-related savings.
21
22
H. MODEL WORKSHEETS
23
24
The following list describes each worksheet of the Excel model. LR-I-90
25
presents the model and worksheets.
26
27
1. ‘Control Sheet’ Worksheet
28
This worksheet controls the model. The user selects or enters scenario
29
information to develop scenario costs. A scenario is a distinct combination of
30
worksharing elements. Variable inputs located in cells B2 through B7 correspond
USPS-T-25
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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 All Scenarios’ and ‘RUN All
5
Scenarios – PRINT “Mailflow Model” & “Mailflow Model Costs” Worksheets.’
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.
10
11
When pressed, the latter button executes a macro that performs the same
12
functions as the former button’s macro, but additionally prints the pertinent
13
scenarios’ ‘Mailflow Model’ and ‘Mailflow Model Costs’ worksheets. This enables
14
the user to print each and every scenario’s mailflow for the selected class and
15
subclass.
16
17
When entering an individual scenario on the ‘Control Sheet,’ the user will find the
18
corresponding modeled unit volume variable cost on the ‘Mailflow Model Costs’
19
worksheet.
20
21
2. ‘Cost Averaging’ Worksheet
22
This worksheet calculates weighted-average costs by rate category and isolated
23
barcode-related savings for the specified ‘Control Sheet’ class and subclass.
24
These calculations rely upon the unit volume variable costs on the ‘Scenario
25
Costs’ worksheet.
26
27
3. ‘Scenario Costs’ Worksheet
28
This worksheet develops the CRA-adjusted unit volume variable costs for the
29
specified ‘Control Sheet’ input. The aforementioned macros populate the
30
modeled unit volume variable costs.
31
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Page 21
4. ‘Mailflow Model’ Worksheet
1
2
This worksheet is a graphical representation of a scenario’s mailflow across
3
bundle and piece handling activities.
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
10
6. ‘Mailflow Model Costs Footnotes’ Worksheet
11
This worksheet presents footnotes for the ‘Mailflow Model Costs’ worksheet.
12
7. ‘Scenario Data’ Worksheet
13
14
This worksheet performs calculations upon input data and provides data
15
employed by the ‘Mailflow Model’ worksheet. There is one row of data for every
16
scenario. The scenario determines which data are used. Table IV-1 presents
17
worksheet data examples.
18

TABLE IV-1: ‘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 activity to IP
piece distribution that flow to the FSM 881 BCR/OCR activity.

Number of rejects that flow from the FSM 881 BCR/OCR OP to the FSM
Keying OP (calculated as part of the total number of pieces flowing to the
FSM Keying OP).
19
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1
8. ‘Scenario Data Footnotes’ Worksheet
2
This worksheet presents footnotes for the ‘Scenario Data’ worksheet.
3
4
5
9. ‘Data’ Worksheet
This worksheet stores modeling input data.
6
7
8
10. ‘Coverage Factors’ Worksheet
This worksheet stores originating and destinating coverage factors.
9
10
11
11. ‘CapacitySOP Factors’ Worksheet
This worksheet stores originating and destinating capacity/SOP factors.
12
13
12. ‘Downflows – Bundle’ Worksheet
14
This worksheet stores bundle downflow densities.
15
16
13. ‘Downflows – Piece’ Worksheet
17
This worksheet stores piece downflow densities.
18
19
20
14. ‘Productivities’ Worksheet
This worksheet stores productivities and volume variability factors.
21
22
23
15. ‘Accept Rates’ Worksheet
This worksheet stores accept rates.
24
25
16. ‘CRA Cost Pools’ Worksheet
26
This worksheet stores CRA costs and determines worksharing-related and not
27
worksharing-related CRA costs.
28
29
17. ‘Vols-First’ Worksheet
30
This worksheet calculates First-Class Mail volumes by worksharing attribute and
31
element combinations.
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1
2
18. ‘Vols-Per Reg’ Worksheet
3
This worksheet calculates Periodicals Regular volumes by worksharing attribute
4
and element combinations.
5
6
19. ‘Vols-Per Non’ Worksheet
7
This worksheet calculates Periodicals Nonprofit volumes by worksharing attribute
8
and element combinations.
9
10
20. ‘Vols-Std (A) Reg’ Worksheet
11
This worksheet calculates Standard Mail (A) Regular volumes by worksharing
12
attribute and element combinations.
13
14
21. ‘Vols-Std (A) Non’ Worksheet
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 IV-2: REJECT FLOW

AFSM 100 barcoded rejects  50% FSM 1000 keying, 50% manual

AFSM 100 nonbarcoded rejects  50% FSM 1000 keying, 50% manual

FSM 881 barcoded rejects  50% FSM 881 keying, 50% FSM 1000 keying

FSM 881 nonbarcoded rejects  50% FSM 881 keying, 50% FSM 1000
keying

FSM 881 keying rejects  100% FSM 1000 keying

FSM 1000 barcoded rejects  80% FSM 1000 keying, 20% manual

FSM 1000 nonbarcoded rejects  100% manual
1
2
4. The model considers nonbarcoded, carrier route flats on ADC, 3D, and 5D
3
containers to have representative mailflows and costs as the corresponding
4
barcoded mailstreams. This is due to mail processing activities handling
5
barcoded, carrier route pieces from bundles that prematurely lose bundle
6
integrity in a manner similar to nonbarcoded pieces.
7
8
9
10
5. The model considers all CR containers to have only nonbarcoded,
nonmachinable flats. This is due to the mail processing cost not varying with
respect to barcoding or machinability.
11
12
6. The model does not differentiate sacks from pallets in determining modeled
13
costs. The analysis does differentiate sacked volumes from palletized
14
volumes in order to weight costs into rate category average costs.
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 factors, the model separately
19
aggregates flats from both AFSM 100 and FSM 881 activities and from FSM
20
1000 activities. Hence, the model reallocates flats flowing from both AFSM
21
100 and FSM 881 activities and from FSM 1000 activities to destinating
USPS-T-25
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1
activities. Appendix A illustrates how the model combines coverage and
2
capacity/SOP factors to allocate flats.
3
4
8. The model uses witness Seckar’s piece downflow densities from USPS LR-H-
5
134 which originated in USPS LR-MCR-3. The FSM 881 keying density
6
extends to each of the following activities: FSM 881 OCR, FSM 881 keying,
7
AFSM 100 BCR/OCR/VCS, AFSM 100 OCR/VCS, and FSM 1000 keying.
8
The FSM 881 BCR density extends to each of the following activities: FSM
9
881 BCR and FSM 1000 BCR. The manual density extends to manual
10
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 with manual
17
bundle downflow densities. This is due to the lack of necessary and sufficient
18
manual bundle downflow density data.
19
USPS-T-25
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1
2
V. WEIGHTED-AVERAGE COSTS BY RATE CATEGORY
3
This testimony calculates weighted-average costs by rate category and
4
designates them “cost averages - actual.” These costs are the average costs of
5
the average flats that qualify for the rate categories. This approach is
6
comparable to witness Seckar’s actual mail makeup method in Docket No.
7
R97-1.
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 one weighted-average cost from
12
another when holding automation or nonautomation constant calculates the
13
presortation-related cost difference.
14
15
The cost averages - actual do not necessarily enable one to calculate barcode-
16
related cost savings. In witness Moden’s Docket No. R97-1 testimony (USPS-T-
17
4 at 11-12), he referred to a peculiar output from the flats’ cost models, where
18
barcoded flats appeared to cost more than nonbarcoded flats. This is due to
19
averaging.
20
21
The average flat of a nonbarcoded rate category may have different container
22
presortation, package presortation, and machinability attributes than the average
23
flat of the corresponding barcoded rate category. For example, consider a
24
hypothetical average basic, nonbarcoded flat to be a 3-digit, machinable flat in an
25
ADC sack and a hypothetical average basic, barcoded flat to be an ADC,
26
nonmachinable flat on an ADC pallet. A difference of the basic rate categories’
27
weighted-average costs would consider a cost effect due to variable presortation
28
and machinability. This accordingly does not isolate barcode-related cost
29
savings and may indeed result in peculiar outputs.
30
USPS-T-25
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1
2
VI. ISOLATED BARCODE-RELATED COST SAVINGS
3
The model calculates a second set of weighted-average costs by rate category
4
and designates them “cost averages - normalized auto-related savings.” The
5
differences of these cost averages when holding the presort category constant
6
are the isolated barcode-related cost savings. This testimony isolates the
7
savings by holding container presortation, package presortation, and
8
machinability 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. The resulting difference is the mail
13
processing costs avoided due to the presence of a barcode. The model
14
calculates a difference for most combinations of container presortation, package
15
presortation, and machinability.
16
17
The model excluded the following combinations:9
18

Nonbarcoded, 3-digit flats in ADC and MADC sacks.
19

Barcoded, 3-digit flats in ADC and MADC sacks.
20

Nonbarcoded, 5-digit flats in ADC and MADC sacks.
21

Barcoded, 5-digit flats in ADC and MADC sacks.
22

Nonbarcoded, 5-digit Periodicals in 3-digit sacks.
23

Barcoded, 5-digit Periodicals in 3-digit sacks.
24
25
The model excluded these flats because the analysis isolated barcode-related
26
cost saving relationships between each nonautomation rate category and its
27
corresponding automation rate category. Hence, these relationships are
28
between, for example, the basic, nonautomation rate category and the basic,
29
automation rate category.
9
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
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1
2
The excluded flats do not have such rate category relationships. For example,
3
nonbarcoded, 3-digit Standard Mail (A) flats in ADC and MADC sacks qualify for
4
the basic, nonautomation rate. The analogous barcoded, 3-digit Standard Mail
5
(A) flats in ADC and MADC sacks qualify for the 3/5-digit, automation rate. The
6
rate category relationship in this example is between the basic, nonautomation
7
rate category and the 3/5-digit, automation rate category.
8
9
10
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 volumes in calculating each
13
cost averages - normalized auto-related savings weighted average. This
14
approach recognizes the expected barcode-related cost savings from barcoded
15
flats and the potential barcode-related cost savings from nonbarcoded flats. The
16
differences of the cost averages, therefore, include cost-based signals of the
17
costs avoided by barcoded flats due to their barcodes and the costs that would
18
be avoided by nonbarcoded flats if they had barcodes.
19
20
This approach also ensures that the differences of the weighted-average costs
21
equal the averages of the differences.10
10
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.
APPENDIX A
APPLICATION OF COVERAGE AND CAPACITY/SOP FACTORS
1
The ensuing flow charts illustrate how the cost modeling methodology combines
2
coverage and capacity/SOP factors to allocate flats to mail processing activities.
3
There is a chart for each of the following:
4

nonbarcoded, nonmachinable flats
5

barcoded, nonmachinable flats
6

nonbarcoded, machinable flats
7

barcoded, machinable flats.
8
9
This testimony discusses the nonbarcoded, nonmachinable flats flow chart. The
10
square box at the top has 100 nonbarcoded, nonmachinable flats. The approach
11
first applies the FSM 1000 coverage factor to those 100 flats. 86 of the 100 flats
12
originate or destinate to facilities that have FSM 1000s. 14 of the 100 flats do not
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.”
15
16
The approach then applies the FSM 1000 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. The chart depicts these figures in bolded, square boxes
19
with rounded edges.
20
21
Of the 14 flats that do not have FSM 1000 access, all 14 flow to manual
22
processing. The chart depicts this figure in a bolded, square box with rounded
23
edges.
24
25
The overall approach allocates 43 percent of nonbarcoded, nonmachinable flats
26
to the FSM 1000 keying activity and 57 percent to manual processing.
Nonbarcoded,
Nonmachinable
Flats
100
86%
FSM 1000 Coverage Factor
FSM 1000 Nonbarcoded
Capacity/SOP Factor
50%
FSM 1000
Keying
Processing
43
14%
FSM 1000
Access
No FSM 1000
Access
86
14
50%
100%
Manual
Processing
Manual
Processing
43
14
Barcoded,
Nonmachinable
Flats
100
86%
FSM 1000 Coverage Factor
FSM 1000 Barcoded
Capacity/SOP Factor
100%
14%
FSM 1000
Access
No FSM 1000
Access
86
14
0%
0%
FSM 1000
BCR
Processing
FSM 1000
Keying
Processing
86
0
100%
Manual
Processing
Manual
Processing
0
14
Nonbarcoded,
Machinable
Flats
100
72%
28%
AFSM 100 Coverage Factor
AFSM 100 Nonbarcoded
Capacity/SOP Factor
40%
72
28
0%
Manual
Processing
FSM 881
Access
29
0
14
26
No FSM
881 Manual
Processing
0
29
0%
FSM 881
OCR
Processing
0
50%
FSM 1000
Keying
Processing
0
0
13
78%
22%
FSM 1000
Access
0
14
0
No FSM
1000 Manual
Processing
0
50%
90%
FSM 1000
Access
0
50%
Manual
Processing
0
FSM 1000
Keying
Processing
0
10%
No FSM
1000 Manual
Processing
0
50%
Manual
Processing
0
FSM 1000 Coverage Factor |
AFSM 100
FSM 881 Nonbarcoded
Capacity/SOP Factor
Manual
Processing
Manual
Processing
35%
50%
Sent to FSM
1000
13
50%
65%
FSM 1000
Access
0%
Sent to FSM
1000
14
FSM 1000 Coverage Factor |
AFSM 100 & FSM 881
FSM 881
OCR
Processing
FSM 881 Coverage Factor |
no AFSM 100
No FSM
881 Manual
Processing
2
50%
0%
50%
7%
Sent to FSM
1000
100%
FSM 881 Nonbarcoded
Capacity/SOP Factor
93%
20%
Sent to FSM
881
FSM 881
Access
FSM 1000 Nonbarcoded
Capacity/SOP Factor
No AFSM 100
Access
40%
AFSM 100
OCR/VCS
Processing
29
FSM 881 Coverage Factor |
AFSM 100
AFSM 100
Access
50%
FSM 1000
Keying
Processing
0
FSM 1000 Coverage Factor |
no AFSM 100 & FSM 881
No FSM
1000 Manual
Processing
0
50%
Manual
Processing
0
FSM 1000 Nonbarcoded
Capacity/SOP Factor
Barcoded,
Machinable
Flats
100
72%
28%
AFSM 100 Coverage Factor
AFSM 100 Barcoded
Capacity/SOP Factor
60%
72
28
0%
Manual
Processing
FSM 881
Access
29
0
0
26
No FSM
881 Manual
Processing
0
29
0%
FSM 881
BCR/OCR
Processing
0
100%
0
0
78%
22%
Manual
Processing
FSM 1000
Access
0
0
0
65%
FSM 1000
Access
Manual
Processing
26
0%
35%
No FSM
1000 Manual
Processing
0
0%
FSM 1000
BCR
Processing
FSM 1000
Keying
Processing
0
0
FSM 1000 Coverage
90%
FSM 1000
Access
0
0%
Manual
Processing
0
100%
10% Factor | AFSM 100
No FSM
1000 Manual
Processing
0
0%
FSM 1000
BCR
Processing
FSM 1000
Keying
Processing
0
0
0%
Manual
Processing
0
100%
FSM 881 Barcoded
Capacity/SOP Factor
0%
Sent to FSM
1000
Sent to FSM
1000
29
FSM 1000 Coverage Factor |
AFSM 100 & FSM 881
0%
FSM 881
BCR/OCR
Processing
FSM 881 Coverage Factor |
no AFSM 100
No FSM
881 Manual
Processing
2
100%
0%
100%
7%
Sent to FSM
1000
100%
FSM 881 Barcoded
Capacity/SOP Factor
93%
0%
Sent to FSM
881
FSM 881
Access
FSM 1000 Barcoded
Capacity/SOP Factor
No AFSM 100
Access
40%
AFSM 100
BCR/OCR/
VCS
Processing
43
FSM 881 Coverage Factor |
AFSM 100
AFSM 100
Access
0%
FSM 1000
BCR
Processing
FSM 1000
Keying
Processing
0
0
FSM 1000 Coverage Factor |
no AFSM 100 & FSM 881
No FSM
1000 Manual
Processing
0
0%
FSM 1000 Barcoded
Capacity/SOP Factor
Manual
Processing
0