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RAND A NATIONAL »tiomct

1948-1998

Measurement of USMC Logistics Processes Creating a Baseline to Support Precision Logistics Implementation

Marc L. Robbins, Patricia M. Boren, Rick Eden, Daniel A. Relies

National Defense Research Institute 19980615 089

DTIG QUALITY II'SPEOTBD 21

DISTRIBUTION STATEMkNT A

Approved for public release; Distribution Unlimited

The research described in this report was sponsored by the United States Marine Corps. The research was conducted in RAND's National Defense Research Institute,

a federally funded research and development center supported by the Office of the

Secretary of Defense, the Joint Staff, the unified commands, and the defense agencies

under contract No. USMC-96-609.1.

ISBN: 0-8330-2613-5

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RAND

Measurement of USMC Logistics Processes Creating a Baseline to Support Precision Logistics Implementation

Marc L. Robbins, Patricia M. Boren, Rick Eden, Daniel A. Relies

Prepared for the United States Marine Corps

National Defense Research Institute

VTIC QUÄLET IHCPECH8B §

Approved for public release; distribution unlimited

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PREFACE

Marine Corps leaders recognize the need to improve support to expeditionary forces. To help explore options for improving logistics, the Marine Corps asked RAND to undertake a two-pronged research

effort. One perspective explores options for improving the Marine

Corps' logistics through a "top-down" analysis of the totality of logistics processes. The second, bottom-up, perspective evaluates

options for improving Marine logistics by helping with the development, measurement, and assessment of specific initiatives. Bottom-up analyses are (1) measuring order and ship and repair cycle times and (2) examining outsourcing options. By analyzing improvement options from two perspectives, the research aims to achieve both a broad and integrated overview and detailed evaluations

of selected initiatives undertaken in the field. Results from the top-down analysis and the outsourcing options

study are being documented elsewhere. This documented briefing provides evidence on Marine Corps logistics process performance. It lays down baseline measurements of Marine repair cycle and order and ship times, the latter including both retail and wholesale support, with calendar year 1996 selected as the baseline from which to judge the benefits of future changes. It shows an initial diagnosis of the reasons for the baseline performance. An earlier version of this briefing was originally presented to the quarterly meeting of the Marine Corps logistics generals, at Camp Lejeune, NC, on November 19, 1996.

This research is sponsored by the Deputy Chief of Staff for Installations and Logistics (I&L). The results of this project, documented herein, are intended to support implementation of Marine Corps logistics improvements. It should be of interest to Marine Corps logisticians and others interested in logistics and performance measurement. Comments may be sent to the principal author by email (Marc_Robbins@rand.org) or to the principal investigators leading this project (Nancy_Moore@rand.org and David_Kassing@rand.org), or by

post at:

-IV-

RAND 1700 Main Street

PO Box 2138 Santa Monica, CA 90407

The research reported here was conducted within the Forces and Resources Policy Center of RAND's National Defense Research Institute, a federally funded research and development center sponsored by the Office of the Secretary of Defense, the Joint Staff, the

Unified Commands, and the defense agencies.

-V-

SUMMARY

This documented briefing provides a baseline measurement of current Marine repair cycle times (RCT) and order and ship times (OST), the latter including both retail and wholesale support. Its primary goal is to provide USMC leaders with the information they

need to evaluate recent Marine logistics response times (LRT) and to assess the need for improvement. A secondary goal is to help the Marine Corps understand the capabilities and limitations of its current data systems. An early version of this briefing was originally presented to the quarterly meeting of the Marine Corps logistics generals, at Camp Lejeune, NC, on November 19, 1996.

To measure logistics response times, it is important to define each logistics process and the subprocesses that comprise it. We measured logistics response times for three processes—on-base repair, order and ship from retail supplies, and order and ship from wholesale supplies. Figure S.l depicts graphically how these processes interrelate.

REPAIR CYCLE TIMES Defining the On-base Repair Process

The repair process includes all actions required to return an inoperative weapon system (principal end item, or PEI) or secondary reparable (secrep) to serviceable status. This includes all repair actions at each maintenance echelon involved and the retrograde of the item between echelons at the retail level, that is, within the Marine

Expeditionary Force (MEF).

Data for Measuring RCT The Marine Corps has a nationally archived database of Marine

Corps Integrated Maintenance Management System (MIMMS) data collected from equipment repair orders (EROs) which, when closed, are transmitted to the Marine Data Analysis Center at MARCORLOGBASE-Albany (MCLB-Albany). This database provided

the data for our analysis of Marine on-base repair cycle times. We

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On-Base Repair Order and Ship Retail

Order and Ship Wholesale

Requisition

Materiel

MRO

^Ai™£™i

Figure S.l—We Measured the Current Performance of Three Interlinked Logistics Processes

obtained data on all EROs that closed in calendar year 1996 for

maintenance echelons 2 through 4.

RCT Performance Figure S.2 illustrates our general finding that RCTs are slow and

variable. It presents the example of "M"-category repairs, those for deadlined MARES-reportable items, that closed in a one-month period at 1 FSSG, Camp Pendleton. The 50th, 75th, and 95th percentiles of the RCTs for these M-category repairs are approximately 20, 40, and 110

days, respectively. By analyzing the status histories of these repairs,1 we gained

insight into possible drivers of long and variable RCTs. We found that the slowest quartile of these repairs took, on average, 17 times as long to

^Obtained through a special data collection. Status histories are not maintained in the archived MIMMS database.

-Vll-

120 T

100..

Days 60--

40..

20

B75-95%

D50-75%

125-50%

DO-25%

Echelon of maintenance 3 Closing status 15 only I MEF EROs with close dates

96130-96160

N = 115

Figure S.2—RCTs for Critical (MARES-Reportable) Systems Are Long and Variable

complete as the fastest quartile. What accounted for that large difference was not wrench-turning, nor was it shortages in space or technician availability. Overwhelmingly, the slowest M-category repairs were driven by unavailability of parts.

ORDER AND SHIP TIMES FROM RETAIL SUPPLY We turn now to the supply of parts, beginning with measurement

of the order and ship (O&S) process for parts actually available on the shelf in retail supply (that is, these measurements do not include backorders). Retail stocks are critical in supporting repair: approximately 70 to 80 percent of parts used in repairs are filled either by the General Account or the Reparable Issue Point, according to

archived supply data.

Defining the Order and Ship Process from Retail Supply The retail O&S process begins with the identification of the repair

part(s) required, its validation and documentation through varying

-Vlll-

levels of authority, and then the formal creation of the requisition itself

in the Asset Tracking for Logistics and Supply System (ATLASS).

Requisitions are passed from ATLASS to the Supported Activities

Supply Support System (SASSY) either directly (e.g., through email)

or through the "sneaker net" (driving or walking requisition-filled

diskettes). At the SASSY Management Unit (SMU), SASSY cycles are

run typically on a daily basis (three to five days a week), part

availability is determined, high-priority requisitions for backordered

items are passed on to wholesale supply, and materiel release orders

(MROs) are cut for local stocks. The MROs are printed and distributed

to warehouses, where items are retrieved from supply bins and readied

for customer pickup or direct delivery. Once received, the item is

either delivered directly to the mechanic or put into the layette (that is,

parts bin for the item in repair) for the carcass in repair. A receipt

acknowledgment is entered into ATLASS, with a D6T being passed to

SASSY to close out the supply record, and the information is passed to

MIMMS and the parts receipt is recorded for the mechanic in the next

daily progress report.

Data for Measuring Retail OST We measured retail OSTs with the same MIMMS database used to

baseline RCTs. The archived MIMMS database maintained at MCLB-

Albany includes abbreviated histories of all parts used in executing a

repair. These records include part used, requisition document

number, date received or canceled, the source of supply, and latest

status of the requisition. For this analysis, we selected only those

requisitions satisfied out of the MEF's Supply Battalion (the General

Account for consumables and the Reparable Issue Point for

repairables). We calculated OSTs for parts received in CY96 and show

end-to-end times. The data do not permit us to measure the time

incurred in subsegments of the retail order and ship process.

OST Performance from Retail Supply

Figure S.3 shows that retail OSTs are slow and variable for each

active MEF—remarkably so, given that these times are for parts that

-IX-

40 ,

35 ■

30 .

25 -

Days20

15 .

10 -

5-

0 ■

-

a 75-95%

a 50-75%

10-50%

I M

EF

II M

EF

III M

EF

Figure S.3—Each MEF Shows Substantial Delays in Filling Orders from Local Stocks

may be no more than a few miles away from the customer. Half take upward of a week to be filled; many take more than two weeks for the entire O&S process, even though backorders are not at issue here. What is not clear from these results is what accounts for the time incurred: the order and ship process has many steps and many actors, any or all of which may cause delays.

ORDER AND SHIP TIMES FROM WHOLESALE SUPPLY

Defining the Wholesale Order and Ship Process The order and ship process for items from wholesale supply has

several branches, not all shown in Figure S.l. Requisitions for wholesale supply can come both from the maintenance shop or from retail supply, from the former if the item is not held (or is in zero balance) at retail supply and the requisition has high enough priority, and for the latter for standard (often automated) replenishment requisitions. Requisitions from the maintenance shop follow the same procedure as described previously until they reach the SMU. If the

-X-

item is not available locally and the requisition has a high priority, it will be reviewed and approved at the Supply Battalion based on a

financial value threshold. All requisitions are then passed via SASSY to the wholesale

system, first entering that system via the Defense Automated Addressing System (DAAS) computer at Dayton, OH. Requisitions are routed via the DAAS system to the appropriate national inventory control point (NICP) where item managers handle requisitions and manage stockage levels for specific groups of items. At the NICP, a materiel release order (MRO) is cut, usually automatically; in certain

circumstances, a requisition will be bounced out of the system for

further review by the inventory manager. MROs will be sourced to a DLA supply depot for processing and

shipping of the materiel. The MRO will be transmitted via the DAAS system and be entered into the depot's computer system where it will be pulled down, typically at midnight, for processing the next day. MROs are prioritized by the depot for picking and packing, and the mode of shipment—determined by the requisition's priority and its required delivery date—will be selected. The package will be offered for shipment and then transported to the installation, often to the Traffic Management Office, unless another address is specified. It is then sent to the Supply Battalion or to other customers, or deposited in a marked bin for pickup by customers. Upon receipt by the customer, such as a maintenance shop, it follows the same procedure as before, with a D6T (acknowledgment of receipt) being posted through ATLASS to SASSY. When the SASSY cycle is run, a D6S is posted to DAAS, which completes the requisition history and closes out the

record.

Data for Measuring Wholesale OST We measured USMC OSTs for wholesale supply using the

archived requisition histories maintained in DLA's Logistics Response Time (LRT) database. The LRT currently tracks most time segments for the services for items managed by DLA and the Navy. For the Marine

-XI-

Corps, this includes over one million requisitions for CY96 alone. As with retail OST, we limit our analysis to non-backordered requisitions.

Because the LRT captures five time-stamps for the wholesale O&S

process, we are able to measure not only overall OST but also four

segments: • on-base processing times until the requisition is received at

the wholesale level; • the processing time at the NICP required to issue an MRO; • the depot handling time, including picking, packing, and

delivering to the shipper; • the time from when the item leaves the depot, is transported

to the installation, and then is distributed to the ultimate customer and the record is closed out.

OST Performance from Wholesale Supply Our measurements revealed that, as with on-base RCT and retail

OST, wholesale OST performance is also slow and variable. Figure S.4

120 T

100

80 ..

Days 60 ..

40 ■■

20 ..

0

□ 75-95% D 50-75%

■ 0-50% :'■'.':. ''.'Sie ...

?.;„>.Ä,»,'.y..

'•i\£-£T"$"- "

'. -j' ■£'.■& \ .*!

iiiiiiiiiiii^

mmmsm&imsmiä&ii !- _: J L_j '. -^-..

Figure S.4—OST from Wholesale Supply for Corps and by MEF

-Xll-

illustrates this finding by displaying wholesale OSTs for each MEF. The differences between CONUS (I and II) and OCONUS (III) active MEFs are clearly driven by the need to transport materiel across the

Pacific; the longer time associated with the Reserve (MARFORRES)

MEF requisitions arises from the interrupted nature of Reserve operations. The LRT data do not provide additional time-stamps to

further analyze the extended OCONUS transit segment. Average Marine OSTs fall far short of current UMMIPS

standards—which themselves tend to be far more lax than current practices in the commercial sector. Figure S.5 illustrates this point with

the example of wholesale OSTs from I MEF. It shows that high-priority

(IPG 1) requisitions took on average about three times the UMMIPS

standard for CONUS of five days. When we analyzed the four segments of wholesale OST (not

shown), we found that OSTs tended to be driven by ship-to-receive times and by requisition processing time on base, both of which were

100 i

90 .

80 .

70 -

60 .

Da}>S 50 .

40 ■

30 .

20 -

10 ■

0 .

lit

Ul (a

JEF average

UIMIPS standard verage) ■~—"mmmm

Wmmm Wßm0

P75-95%

□ 50-75%

■ 0-50% ms ÄBÄS Wmmrn

i

| | 1 1

IPG 1 IPG 2 IPG 3

»•;/ *>.-■■;■'« ....,.,. . ■■ -■ - ■■'■'-■ •■■•' --•■••. —

Figure S.5—OST from Wholesale Supply Falls Short of UMMIPS Standards

-Xlll-

significantly affected by on-base processes. Moreover, requisitions

passed through from repair activities take longer to leave the

installation than lower-priority repairs that are merely needed to

replenish local stocks.

OBSERVATIONS ON LRT PERFORMANCE AND MEASUREMENT

Each of the three processes measured here—repair, retail order and ship, and order and ship from wholesale supply—suffers from delays and high variability. Because these and other processes are interlinked, performance deficits in one can worsen the performance of

others. Some of these negative interactions are depicted in Figure S.6. For example, as the figure suggests, slow repair will reduce the

number of serviceable items at the RIP, slowing up other repairs depending on those items and impacting the stockage allocation for these often expensive components. Poor parts identification and bad requisitioning procedures will fill the pipelines with requisitions for

Processes Immediate problems Ultimate impacts

Repair

Order and ship

Inefficient repair

of needed parts

Increased time awaiting parts t

Slow, variable delivery

Many zero balance, despite deep depth I

Stockage- ■ determination

Wrong stocks in the wrong

places

Decreased mission

readiness

Decreased deployability

Wasted $$

±^ • - - - \Mi .——.-.: ...■■■: :_; ^-i --^ ii.J i. .-. ! - V . > : -—:-•-

Figure S.6—Poorly Performing Processes Have Many Bad Effects

-XIV-

unneeded parts, both at the retail and wholesale level, and will absorb

space and resources better used by more critical items. Slow OSTs from wholesale supply will impact RCTs and drive up the level of stockage requirements at the retail level, while narrowing the breadth of items that can be carried. Finally, slow and variable retail OSTs will

have a direct link to slow and variable RCTs.

IMPLICATIONS FOR MARINE LOGISTICS PROCESS IMPROVEMENT

The Marine Corps is aggressively pursuing improvement in its

logistics processes, most recently under the umbrella of the "Precision

Logistics" initiative. These baseline performance measures suggest

several implications and recommendations for these efforts:

• Performance measurement is critical to process improvement strategies; in particular, logisticians need to be sensitive to both the length and high variability of the Corps' logistics

processes. • Diagnostic information is vital for detecting core problems

and directing improvement efforts. • Recurrent performance reporting to persons who can make

changes is vital, especially to determine whether changes are having the desired effect. These reports must also be available to the Marines who do the repair, ordering,

shipping, and receiving. • Many parts of the processes are controlled by the Marines

and can be fixed by Marines; for example, the longest delays in order and ship times from wholesale supply can be found

on the installations themselves. • For parts of the processes outside their control, the Marines

need to form partnerships with suppliers and other customers. Especially in wholesale supply, where much is held and controlled by other organizations and services, the Marine Corps needs to work closely with the Defense Logistics Agency, the General Support Administration, the

-XV-

Military Traffic Management Command, and the other Services to help the Department of Defense build a more

effective logistics system, thus ensuring better support of the

Marine in the field.

A BASELINE FOR MEASURING PROCESS IMPROVEMENT Appendices A, B, and C present a performance baseline, a kind of

"sourcebook," against which to compare later performance. Improvements can only be acknowledged through comparison to some given standard, whether in time or against similar organizations. These

appendices attempt to supply both types of information. They present baseline performance measures for each of the three logistics processes for a selected period in time, calendar year 1996. The appendices also present data on the performance of different organizations, from the MEF down to the individual unit level, for each of the three processes. While comparisons, both across organizations and time, should be done carefully, given frequent incompatibilities, these appendices may serve to some degree as a common yardstick as the Marine Corps proceeds on the challenging path of achieving logistics performance

that is faster, better, and cheaper.

-xvii-

ACKNOWLEDGMENTS

This document represents the fruits of a joint effort between

RAND researchers and a large number of Marine logisticians invested

in performance measurement and committed to process improvement.

We benefited from the strong and continuing support of our

project sponsor, Major General Joe Stewart, Deputy Chief of Staff for

Installations and Logistics. At DC/S I&L we are grateful for the

continuing help we received from Colonel Mark Lott, then-Colonel

Rick Kelly, and from the "Turtles": Major Mark Laviolette, Major Mark

Adams, Major Dave Kunzman, and Captain Steve Pellegrino. This

work could not have been done without the day-to-day supervision

and help we received from another "Turtle," Major George Pointon.

We owe a special debt of gratitude to Laurel Abraham for her

superhuman efforts in acquiring and transmitting to us much of the

data that are central to the analysis and measurement presented here.

At 1 FSSG, Camp Pendleton, we were fortunate to receive expert

advice and constructive criticism of our early analyses. We are

particularly grateful for the strong interest and support this work

received there from then-Brigadier General Gary McKissock and

members of the 1 FSSG, in particular Colonel Dale Town, Lieutenant

Colonel Jerry Calleros, Lieutenant Colonel Mike Kampsen, Lieutenant

Colonel Jim Kessler, and Lieutenant Colonel Steve Dodd. At II MEF,

we wish to acknowledge the strong support and direction we received

from Colonel Ed Dillard, Lieutenant Colonel Roy Truba, and Major

Frank Payne. At III MEF, Colonel Mark Lott, in his new incarnation,

was of great help to us, as was Staff Sergeant Steven Parker.

This data-intensive analysis could not have been executed

without the aid, responsiveness, and enthusiasm of personnel at the

Marine Data Analysis Center, MARCORLOGBASE-Albany. In

particular, we are grateful to Captain Mike Lepson, Fred Day, Mike

Carroll, and Staff Sergeant Morrison. Again, we with to thank these

and all other Marines and Marine civilians who helped make this a

better product.

Preceding Page Blank

-XV111-

To analyze order and ship time from wholesale support, we used

the Logistics Response Time database maintained by the Defense Logistics Agency. We are grateful to Captain (USN) Steve Morris for facilitating our access to this database and sharing his deep expertise; we also wish to thank David Raber for patiently enduring our many

questions on the LRT database. We also wish to acknowledge assistance we received from Jimmy Tucker and Mary Maurer at

DAASC. Lastly, we appreciate the contributions made by our RAND

colleagues to this analysis, in particular John Dumond and our

reviewers Lionel Galway and Ken Girardini. This work has also

benefited from the insights and support of the project leadership, Nancy Moore and David Kassing. We owe a special debt of gratitude to Bari Whitbeck, who managed the production of both briefing and document under severe time constraints, and did so professionally and

with grace and humor.

-xix-

ACRONYMS AND ABBREVIATIONS

ATLASS CONUS CY DAAS DAASC DC/S I&L DLA DRIS ERO EROSL FMF FORSCOM FSSG FY GA GSM ICP IPG LIF LRT LTL MARCORLOGBASE MARDIV MARES MARFORRES MAW MCLB MEF MIMMS

MRO MSC MTM NICP NUN O&S

Asset Tracking for Logistics and Supply System Continental United States Calendar year Defense Automated Addressing System Defense Automated Addressing System Center Deputy Chief of Staff (Installation and Logistics)

Defense Logistics Agency Date Received in Shop Equipment Repair Order Equipment Repair Order Shopping List Fleet Marine Force Forces Command Force Service Support Group Fiscal year General Account General Support Maintenance Inventory Control Point Issue Priority Group Logistics Intelligence File Logistics Response time Less than Truckload Marine Corps Logistics Base Marine Division Marine Automated Readiness Execution System Marine Forces—Reserves Marine Air Wing Marine Corps Logistics Base Marine Expeditionary Force Marine Corps Integrated Maintenance Management System Materiel Release Order Major Supported Command Motor Transport Maintenance National Inventory Control Point National Item Identification Number Order and Ship

-XX-

OCONUS OST PEI RCT RDD RIP RUC SASSY Secrep SMU SSA TAM TAMCN TL UAC UMMIPS

USFK USMC

Outside of Continental United States Order and Ship Time Principal End Item Repair Cycle Time Required Delivery Date Reparable Issue Point Receiving Unit Code Supported Activity Supply System Secondary reparable SASSY Management Unit Supply Support Activity Table of Authorized Materiel Table of Authorized Materiel Control Number

Truckload Unit Activity Code Uniform Military Movement and Issue Priority System United States Forces—Korea United States Marine Corps

-1-

NDRi ^mmmm^mmmm^mm^^ma^^mma^mm^^^mi^^ RAND'

Measurement of USMC Logistics Processes

Creating a Baseline to Support Precision Logistics Implementation

This is an expanded version of a presentation to the US Marine

Corps logistics generals' off-site meeting held at Camp Lejeune, NC,

November 19,1996. The briefing was part of a day-long session on

Marine efforts to begin implementation of "Precision Logistics," a

concept described by USMC DC/S I&L (Deputy Chief of Staff

(Installations and Logistics)) MajGen Joseph Stewart as the gateway by

which the Marine Corps will seek a complete overhaul of the way

logistics is provided at the tactical, operational, and strategic levels.

Although the process cuts across many facets of logistics, it focuses

initially on attacking logistics response times. From improvement in

logistics response times, further benefits should follow, such as higher

materiel readiness, leaner deployment and employment signatures,

lower inventory levels, and reduced costs.

-2-

NDRI

. RAND tasked by DCS l&L to assist USMC Vanguard efforts

- Evaluate and integrate initiatives

- Help improve USMC outsourcing capabilities

- Evaluate and assist logistics process improvements

. Last task has been expanded to help develop performance metrics and performance reporting system

-Assist efforts to implement Precision Logistics

- Leverage off RAND efforts supporting the Army's Velocity Management initiative

The RAND Corporation, through its National Defense Research

Institute, was asked by the DC/S I&L to evaluate ongoing Marine Corps efforts to improve logistics processes and to help build structures and strategies for enhancing their effectiveness. One element of the RAND project has been to evaluate logistics response times, especially repair cycle and order and ship. The intent of this effort was to evaluate and assist initiatives being pursued in the Force Service Support Groups (FSSG) at I and II Marine Expeditionary Forces (MEFs), located at Camps Pendleton and Lejeune, respectively. The project's focus was expanded to help the Marine Corps conduct a Corps-wide baseline measurement of current repair cycle times (RCT) and order and ship times (OST) at the base and wholesale levels. These results may be used to form the basis for an institutionalized Marine Corps logistics response time reporting system, to be used to assist ongoing Precision Logistics efforts. In many ways, this RAND effort is similar to work being done in a related process improvement initiative

pursued by the Army under the name Velocity Management. RAND's efforts are configured, however, to adapt to the different nature,

structure, and practices of the Marine Corps.

-3-

Purposes of Presentation NDRI B^i^m——mma—m—^—mm^mi^^m—^^m RAND

. Illustrate application of "Define-Measure-lmprove" methodology to Marine Corps logistics processes

• Provide basis for creating a set of baseline measures for key logistics processes

• Present preliminary diagnostics of logistics performance

This chart lays out the agenda of the briefing.

This briefing demonstrates measurement capability and provides

a baseline measurement of Marine Corps logistics process

performance.

With the intent of helping the Marine Corps build a permanent

performance reporting system, the briefing attempts to show both the

strengths and weaknesses of existing information systems, suggesting

ways to make performance reporting a more valuable tool to support

continuing process improvement.

■Ar

Precision Logistics Improves Process Performance Using Three Steps

NDFH

Define the process • Determine customers, inputs,

outputs, value-added

• Use walkthrough to achieve common understanding

RAND«

^

Measure process performance • Define metrics and identify data

• Determine baseline performance

• Diagnose performance drivers

• Provide reports and feejJbafili—^

Iterate for continuous improvement

U Improve the process

Establish goals

Develop improved process designs

Implement change

The underlying philosophy of Precision Logistics is that logistics processes can be improved continuously by rigorous application of a simple methodology: the "Define-Measure-Improve" technique. By this method, process improvement teams seek first to define the process they aim to improve; typically, this means "walking" the process of interest to understand, step by step, precisely how a repair or a retrograde is accomplished. It means identifying the customers, inputs, and outputs of the process, and defining the value added at

each step. Next, having created a detailed laydown of the process of interest,

the process improvement team seeks to measure process performance. An obvious measure is time (which this document emphasizes) but the scope need not be limited to that. It could be that the process measure is money used efficiently in a value-adding way, or used for non-value-

adding functions, or it could be flaws in quality of the process, such as high numbers of components with no evidence of failure being sent to

repair, or components that fail well before the mean time between failure coming out of repair. As the chart shows, measurement serves

-5-

three principal functions, each placing different demands on data collection and processing systems. Understanding performance requires a broad-based database, covering all parts of the process and in as seamless a fashion as possible. The diagnostic function requires

highly detailed data on individual parts of the process, such as requisition histories to explain short parts problems or test equipment

availability to explain delays while awaiting shop. The monitoring

function, by which performance measures are reported to the repair facilities in the field, requires a standard format meaningful to all customers of these reports and that is produced in a timely enough fashion to be useful yet also covers enough of the repair histories to

uncover general trends. Finally, the critical part of this methodology, after the first two

steps have prepared the way, is to improve the process. Many of the process improvements will "fall out" of the first steps, or at least should be strongly suggested by them. At the least, the process laydowns and measurements will point out the long poles and low- hanging fruit; they will reduce attention paid to side concerns (which may have been critical to other processes or at another time). The measurement system will capture and provide feedback on the effect of these improvements; then, in an iterative process, the whole cycle will

begin again and repeat indefinitely.

-6-

There Are Three Reasons to Measure Process Performance

NDRI HBi^^MHHHBHHBHBIiiil^a^MMBHHHHHH^^M RAND

. Understand current performance

-For planning

• Diagnose drivers of poor performance

- For targeting improvement efforts

• Monitor improvement

- For providing feedback to implementors

The performance measurements presented

here emphasize the first two reasons.

Performance measurement is a powerful tool for making the processes that support the warfighter operate faster, better, and cheaper. Process improvement without measurement depends on anecdotal evidence for confirmation; quite often, it can lead to a frittering away of effort with little information about whether interventions are valuable or useless.

Performance measurement carries the three benefits captured in the chart above. It is critical simply to understand how your processes are performing (especially against some standard or comparable organization). But performance measurement is limited in value

unless it includes diagnostic measures, which give some sense of the "why" of performance: Is bad performance inherent and unlikely to change? or Is it due to a flawed process that might be easily and quickly improved? Finally, regular reporting of performance is required to show whether interventions have had the desired effect, and to motivate continued improvement.

Because a new initiative like Precision Logistics must begin with an understanding of how the system currently performs, this briefing focuses primarily on baseline measurement.

-7-

Multiple Measures Are Needed to Understand and Diagnose Variable Performance

■ NDRI

14

12

10 J.

% 8 ..

6 ..

4 ..

0 12 3 4 5 6

Median = 7days

Mean = 10 days

1

RAND'

Distribution of retail OSTs at a major USMC base

95% = 26 days;

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0J123456789012345

H'f If I I I I t 2222333333333344 5789012345678901

All EROSLs filled out of GA/RIP for EROS closed in FY96 (BA status only)

Many analytical results in this document are presented in a form that may be unfamiliar to most readers, using "medians," "percentages," and the like. This chart briefly explains this mode of presentation.

Time-based performance metrics for logistics processes are typically reported with a single measure, that being the mean, or average. While means can convey useful information, they offer little insight into the performance of processes that are extremely variable.

The above chart offers an example of this. It presents the distribution of order and ship times at a major Marine installation (one of the active MEFs) for items from local supply being sent to customers on the installation. The horizontal axis represents the order and ship time (from document creation date until the requisition is closed out with a receipt) in days; the vertical axis shows what percentage of all orders were completed in a given number of days. (For example, about 13 percent of all requisitions were filled on the seventh day, and about

4 percent on the ninth day.) The mean, or average, order and ship time is ten days. However,

only about 3 percent of all requisitions were actually filled on the tenth

day; all the rest took more or fewer days. In fact, no single number

adequately describes how long it took to order and deliver these items:

many took just a couple days, while a large percentage took several

weeks.2

Not only the length of process times but also their variability are

particular concerns for an efficient and effective logistics system. The

chart shows that OSTs for these items are quite long—e.g., an average of

ten days for an item on the shelf for a customer no more than a few

miles away. Even worse from the customer's perspective is the

unpredictability of the system. Some items are shipped and received

almost immediately; others, mysteriously, may take several weeks.

Consider the effect on critical repair actions. Typically, more

than one part is required for a repair; quite often, a dozen or more

separate requisitions may be made. Given the distribution of OSTs

above, the order and ship process becomes a lottery. Some number of

items may be delivered quickly, but the distribution suggests that at

least one requisition will take two, three, or four weeks. If all

requisitions are important to the repair, it doesn't matter that some

parts are received quickly; the repair action will depend on the part

that takes the longest to arrive. To better convey both the length and unpredictability of logistics

processes, we use a different form of measurement, expressed in terms

of percentiles. The chart above shows measures for the median, 75th,

and 95th percentiles. The median is the value that is at the midpoint:

half the cases are faster and half slower (thus, one half of all requisitions

were filled in a week or less). The 75th percentile shows how long it

takes to fill three-quarters of all requisitions, and the 95th percentile

shows the time at that level (e.g., in the case above, the slowest

remaining 5 percent of the requisitions took more than 26 days to be

filled). One way of showing these measures graphically is with bar charts.

An example of a bar associated with the distribution is represented at

the bottom of the chart, with shaded coding for the median, the 75th,

2This analysis excluded backordered items.

and the 95th percentile. We adopt this as a standard representation of

logistics response time (though we will tilt the bar to the vertical in the

following pages).

-10-

We Measured the Current Performance of Three Interlinked Logistics Processes

mm NDRI iiiiiiiiiiiiiiin On-Base Repair

RAND

Order and Ship Retail

Order and Ship Wholesale

MRO

Materiel

We look at performance in terms of logistics response times for

three interlinked processes; repair, order and ship from retail supplies,

and order and ship from wholesale supplies.

This chart, which also serves as the roadmap for this briefing,

depicts graphically how these processes interrelate.

The repair cycle includes all actions required to return an

inoperative weapon system (principal end item, or PEI) or secondary

reparable (secrep) to serviceable status. This includes all repair actions

at each maintenance echelon involved and the retrograde of the item

between echelons. Many factors affect the repair process (and several of those will be

discussed later), but availability of repair parts is especially critical.

The nearest potential source for needed repair parts (outside of pre-

expended bin materiel) is retail supply, typically the General Account

(consumables) or the Reparable Issue Point (for reparable items). The

probability of getting repair parts from these sources in a timely

manner depends on several factors, including the accuracy of the

stockage determination process, the consistency with which stocks are

-11-

maintained, and the time taken to create and process parts requisitions,

and to deliver the parts to the customer.3

For those parts not available at the retail level, wholesale supply provides the nearest source. National-level parts stockpiles are maintained in supply depots operated by DoD's Defense Logistics Agency; the parts themselves are managed by inventory managers at national inventory control points. Just as for retail stockage (though in a more complicated fashion), success in getting needed parts to mechanics depends on wholesale stockage policies, the maintaining of stockage levels themselves, and the execution of the order and ship

process. In the remainder of this briefing, we examine the performance of

three important logistics processes: repair cycle, order and ship from retail supply, and order and ship from wholesale supply.4 In each case, we focus on the measurement of logistics response time.

3We did not examine the performance of alternative sources of supply at the local level, such as local purchases, scrounging, etc.

4These are not the only logistics processes we could (or should) focus on. Others include, for example, stockage determination, financial management, and logistics elements of the deployment process.

-12-

Measurement of On-Base Repair Cycle Time

NDRI RAND

On-Base Repair Order and Ship Retail

Order and Ship Wholesale

Requisition

Materiel

MRO

We begin by examining current Marine repair cycle times at the

retail level (that is, repairs within the MEF).

-13-

INDFU

The Repair Process Extends from Fault Identification to Item Pick-up

Identify fault and move item

to repair

Receive PEI or secrep

jnd open ERO

Await inspection

Perform inspection

Await Parts Space Techs

Evacto higher

echelon

Return from higher echelon

1 Pickup by/ delivery to customer

Close out

record

Final inspection

Await final inspection

Repair progresses

gewiMM^^^itei^a &£jkjsato^.*jw..^^....rft.l,>.,.«-^w

To measure logistics response time, it is important to define the underlying process and the subprocesses that comprise it. This can be a complicated task: most logistics processes involve many actors, multiple steps and handoffs, and different branches and forking points.

The chart above presents a simplified breakdown of the repair process. Repair begins with the identification of a fault, whether by the equipment owner or by mechanics at any echelon. The repair cycle also includes retrograde of the broken equipment, whether an end item hauled back to the Motor Transport Maintenance Company, a radio returned to the Electronics Maintenance Company, or an unserviceable component removed from a vehicle and sent back to the General Support Maintenance Company. At the maintenance facility, all steps of the repair process are tracked, including those we can call "value- adding," in which work is actually being done (e.g., initial and final inspections, and actual wrench turning repair time) and those which merely involve waiting and thus are not truly "value-adding." The repair cycle is finally closed when the item is fixed, the paperwork

-14-

closed, the owner identified, and the equipment either picked up or delivered to the ultimate customer.5

5For simplicity, we do not discuss cases when the decision is made not to repair, or the repair cannot be completed, and the item is retrograded to the fifth echelon of repair in the wholesale system.

-15-

Repair Cycle Times Were Measured Using M1MMS Data

NDfa mmi^mmmmmmm^^mm^mm^^l^^ma^m^^m RAND«

• Acquired MIMMS database of all Corps EROs closed in CY96

- Echelons of maintenance 2-4, all MSCs

. Database includes 305K EROs from FMF

. Analysis of RCT is limited - No diagnosis of performance by segment

possible due to stripping of ERO status

The Marine Corps has a nationally archived database of Marine

Corps Integrated Maintenance Management System (MIMMS)

data collected from equipment repair orders (EROs) which, when

closed, are transmitted to the Marine Data Analysis Center at

MARCORLOGBASE Albany (MCLB-Albany). This database provided

the data for our analysis of Marine on-base repair cycle times.

We obtained data on all closed EROs for echelon 2 through 4

work during calendar year 1996. The archived records cover all retail

echelons (1-4) but information on and usefulness of echelon 1 EROs are

limited, so we restrict the analysis to echelons 2 (motor pool level end

item repair), 3 (intermediate level end item repair), and 4 (component

level repair). This analysis looks, insofar as possible, at end-to-end repair time.

For example (as illustrated in the process laydown chart), a 2-echelon

ERO on a vehicle may be opened by the motor pool, followed by the

evacuation of the item to a higher echelon (e.g., Motor Transport

Maintenance Company) which then opens a 3-echelon ERO. After

finishing its work, MTM closes its ERO and the vehicle is picked up by

-16-

the customer, who then finishes 2-echelon work and the final ERO is closed. Our measures capture this complete time and therefore reflect the duration that the vehicle is out of service, and not just the time an

ERO is open. (See App. A for a more extended discussion of this point

as well as more complete presentation of base-year RCT results.) Nonetheless, there is considerably more that can and should be

done. We have not yet developed and analyzed diagnostics of the repair process that would tell, across the Marine Corps for all types of

repairs, how long items stay in short parts status, what the delay is from

receipt in shop until the inspection begins, how long it takes to

evacuate items to higher echelons of repair, and so forth.6

6 It is anticipated that these and other issues will be dealt with in a future

expanded USMC retail repair cycle time report.

-17-

Deadlined System Repairs Can Take Months to Complete

■■ NDR!

200 .

180 .

160 .

140 •

120 .

Daysioo .

80 .

60 .

40 .

20 .

0 .

399

KAINU

mm O 75-95%

O50-75%

■ 0-50%

□

I MEF II MEF III MEF MARFORRES

Repair action time for deadlined systems in CY9 S i»;/

I s

This chart represents the first of many baseline measurements presented in this document. Most of the data for these and following charts can be found in App. A, which also lays out in great detail Marine Corps baseline logistics performance.

This chart presents evidence on Marine Corps performance in principal end item (PEI) repair at the retail level (echelons 2-3). As just described, the measurement captures the time from the first (typically 2-echelon) ERO opened up on a PEI until the last ERO associated with that particular end item is closed. This may include several EROs at either second or third echelon and one or more organizations doing repairs. The EROs in our analysis are linked by TAMCN (Table of Authorized Materiel Control Number) and serial number or bumper number of the PEI. To limit this to only the most important repairs, this chart reports on repair actions for both deadlined MARES-

reportable and non-MARES reportable.7

7MARES stands for Marine Automated Readiness Execution System. It includes all end items whose availability status is tracked to feed measures of FMF readiness to go to war.

-18-

This chart and virtually all that follow use the bar chart format described earlier, showing the distribution of logistics response times

from the median performance level to the figures for the 75th and 95th percentiles. These measures are shown above in vertically overlaid bars. For example, in I MEF repairs, the median value is about 29—that is, half the repairs took up to 29 days to complete. The 75th percentile of 63 means that three-quarters of PEI repairs took up to 63 days to finish; or one-quarter took between 29 and 63 days to finish. We also see, with a 95th percentile of 159 days, that 5 percent of all PEI repairs

took more than five months, from first date received in shop (DRIS)

until final record closeout date.

-19-

Fourth Echelon Repair of Secreps Shows Similar Pattern of Variability

NDRI

Days

Number

1FSSG

5908

RAND

..■i.;.-.i: ^VK;».- . i 160 .

140 .

120 ■

100 .

■■■':"■ j\-'.&*■•

■;/•':.'<■■■/ -ft't. ;.£■». 80 .

60 .

40 -

20 .

0 .

D 75-95%

D 50-75% ■ 0-50%

2FSSG

5352

3FSSG

92

All EROs closed in CY 96 at each MEF FSSG, echelon = 4, close status = 15, maint category = D,F,H#I

Component repairs are simpler in concept. There is no cross- echelon movement (all are fourth echelon) and very few organizations do them. In fact, the large majority are done by the General Support Maintenance Company in the MEF Force Service Support Group. Furthermore, typically only one ERO is used per repair action.

The chart above shows the performance of each MEF (meaning mostly, each GSM company) in performing secrep repairs in the 1996 baseline year. Again, the standard percentile metrics are used.

-20-

RCTs for Critical (MARES-Reportable) Systems Are Long and Variable

NDRI

120 _

100..

Days 60..

40-

20-.

N = 115

RAND'

Echelon of maintenance 3 Closing status 15 only I MEF EROs with close dates

96130-96160

This and the next chart present an illustrative analysis of

M-category RCTs and what tends to drive them, based on a specialized

data collection from 1st FSSG, I MEF.

For this analysis we analyzed a small subset of all M-category

repairs, those executed at the 1 FSSGs, with EROs closing between

96130 and 96160. We wished to examine the delays involved in each

repair action and for technical reasons were limited to this small

population.8

This chart shows RCT for these M-category repairs. Note that

again times tend to be long and highly variable, even for these critical

items: the 50th, 75th, and 95th percentiles are about 20, 40, and 110 days,

8The archived MIMMS database does not retain the detailed status information on an ERO that is entered during the course of the repair and is kept in the local MIMMS system for the duration of the repair. Through the support of the 1 FSSG, we obtained information on all EROs at the 1 FSSG that were open as of 96160. We later obtained the archived database from MDAC for all EROs closing in FY96 (including those from 1 FSSG that were open as of 96160). By combining the two databases, we could get detailed status histories for some EROs, but only those that were within 30 days of closing as of 96160.

-21-

respectively. Note that we also include the 25th percentile time of eight days, signifying that one-quarter of all M-category repairs were

completed in eight days or less.

-22-

Time Spent Awaiting Parts Drives Up RCTs for Critical Items

NDRI

Awtg ins

Ins prgs

Rpr prgs

Sht test

Sht tech

RAND'

Slowest quartile mean = 85 days Fast quartile mean = 5 days

■ Slowest quartile a Fastest quartile

Days

M category repairs at I MEF, Close date 96130-96160

This chart presents some evidence on the drivers of length and variability of RCTs. It does so by focusing on the fastest and slowest of the M-category repairs and examining in particular their status histories. In the above chart, the vertical axis represents the separate status typical repairs go through (awaiting inspection, repair progresses, etc.). The x-axis signifies the time spent in each status on average for two quartiles of M-category repairs: the fastest 25 percent and the slowest 25 percent.

Note that the slowest quartile of repairs takes, on average, 17 times as long to complete as the fastest quartile. What accounts for that large difference? As the chart shows, it is not wrench-turning, or "value- added," time. The difference in "repair progresses" (status code 12) times is about seven days on average, far less than the 80-day difference. Nor do shortages in space or technician availability account for the difference. Overwhelmingly, the slowest M-category repairs are driven

by unavailability of parts.9

9The explanations for length and variability will differ by type of repair and will change over time. We have found in other cases, however, that acquisition of repair parts tends to be a prevalent factor in driving poor RCT performance.

-23-

Measurement of Order and Ship Times from Retail Supply

NDRI RAND

On-Base Repair Order and Ship Retail

Order and Ship Wholesale

MRO

Materiel

In the next section of the briefing we turn to the retail order and ship process, that is, the steps required to requisition and receive parts

available from local supplies. In this analysis, we look at the order and ship (O&S) process for

parts actually available on the shelf (that is, we do not examine backorders). The vital, but separate, logistics process of stock determination is responsible for stocking and maintaining parts on the shelf. In future research, we plan to expand our measurements to include the quality of the stockage determination process.

-24-

The Retail Order and Ship Process Extends From Identification to Receipt of a Needed Item

I NDRI RAND

Identify and verify part needed by shop section NCOIC, etc.

Enter requisition into ATLASS

Cut diskette or email to SASSY

< F

SASSY cycle Create Materiel Release Order

" Storage section

pulls/stages

Gear loaded on truck

Gear shipped

Customer signs receipt D6T posted

As in the measurement of the repair process, we begin with a

simplified laydown to define the retail O&S process. The process

begins with the identification of the repair part(s) required, its

validation and documentation through varying levels of authority, and

then the formal creation of the requisition itself in the Asset Tracking

for Logistics and Supply System (ATLASS). Requisitions are passed

from ATLASS to the Supported Activities Supply Support System

(SASSY) either directly (e.g., through email) or through the "sneaker

net" (driving or walking requisition-filled diskettes) on a scheduled

basis. At the SASSY Management Unit (SMU), SASSY cycles are run

typically on a daily basis (three to five days a week), part availability is

determined, high-priority requisitions for backordered items are

passed to wholesale supply, and materiel release orders (MROs) are cut

for local stocks.

The MROs are printed and distributed to warehouses, where

items are retrieved from supply bins and readied for customer pickup

or direct delivery. Once received, the item is either delivered directly

to the mechanic or put into the layette for the carcass in repair. A

-25-

receipt acknowledgment is entered into ATLASS, with a D6T being passed to SASSY to close out the supply record, and the information is passed to MIMMS and the parts receipt is recorded for the mechanic in

the next daily progress report.

-26-

MIMMS Data Permit Measurement of OST for Orders Filled from Retail Stocks

NDRI IIHHIiiMHIiMHBHHHBHHMBBHi^HHBHHil^MMi RAND ■

• Retail OST information derived from EROSLs of closed ERO database

• all EROSLs filled in CY96 from EROs closed in that year

• Eliminate backordered items, local purchase, scrounge

• 188K requisitions filled out of stock on shelf at SMU

. Track OST from creation of requisition document to closeout in MIMMS

- does not capture part identification to document creation time or actual time mechanic receives part

We measured retail OSTs using the same MIMMS database used to baseline RCTs. The archived MIMMS database maintained at MCLB-Albany includes abbreviated histories of all parts used in executing a repair. These records include part used requisition document number, date received or canceled, the source of supply,

and latest status of the requisition. For this analysis, we selected only those requisitions satisfied out

of the MEF's Supply Battalion (the General Account for consumables and the Reparable Issue Point for repairables). We excluded all parts that were received via local purchase and scrounge (as well as those obtained from wholesale supply). To focus on the O&S process itself (as opposed to the stockage determination process), we attempted to limit the analysis to items immediately available on the shelf by selecting only requisitions with a "BA" status.10

10At the time this analysis was originally performed, archived MIMMS data allowed separation of immediate issue from backordered items. The MIMMS trailer records, which capture snapshot EROSL (ERO shopping list, or parts requisition) histories, show the final status appending to a requisition. A "BA" status signifies immediate issue; an "M8" supply status indicates a backordered item now available

-27-

The following charts present examples of order and ship time

performance for each MEF in the baseline year (1996). A more complete presentation of OSTs can be found in App. B. In all cases, we

present one number: the overall order and ship time. In these data, order and ship time is measured from the document date (created in

ATLASS) to the date received as posted in MIMMS (the D6T, also

created in ATLASS).

for release. Using these supply statuses, we were able to limit the results presented to non-backordered items only. Some time after this, MIMMS data became unusable for such measurement due to change in procedures by several of the MEF SMUs. Instead of posting a final supply status (BA or M8), the SMU would include a shipping status (AS1 or AS2) that would overwrite the BA or M8 and so eliminate the backorder indicator from the archived MIMMS records.

-28-

On-Base OST is Important Because Most EROSLs Are Filled Locally

NDRI

CO

E

■o

(0 _J CO O tr UJ

100 _

90 ..

80 -■

70 ..

60 ■-

50 -■

40 •-

30 ..

20 -•

10 --

0 4-

HBIB«

»:1

RAND'

u. UJ £

u. UJ

EROSLs filled in CY96 (excludes PEB, scrounge, local purchase)

This chart gives some indication of the importance of retail stockage in supporting repair. It shows, by MEF, the percentage of ERO shopping lists (EROSLs) that were filled either by the General Account or the Reparable Issue Point. As the chart shows, this ranges from almost 70 percent to over 80 percent.11 Clearly, retail stocks as "the first line of defense" are vitally important in supporting repair. To the extent that retail O&S is flawed and filled with delays, RCTs can be expected to be substantially affected.

nThis chart shows fill rates, i.e., the percentage of all requisitions (minus scrounge, local purchase, or those satisfied out of shop stocks (previously expended bin, or PEB)) that were filled by the SMU.

-29-

Each MEF Shows Substantial Delays in Filling Orders from Local Stocks

NDRI ■!■

40 _

35 --

30 ■-

25 ..

Days 20..

15 ..

10 ■-

5 ■-

0

n75-95% n50-75% ■0-50%

RAND'

This chart shows aggregate retail OSTs for each active MEF. As one can see, despite some variation across the MEFs, a standard conclusion emerges: retail OSTs—for parts that may be more than a few miles away from the customer—are long and variable. Half take upward of a week to be filled, and many take more than two weeks for the entire O&S process, even though backorders are not included here. It is not clear from these results what accounts for the time incurred; as shown previously, the order and ship process has many steps and many actors, any one of which may be a source of delay; the data available for baseline performance measurement (the MIMMS archives) do not permit more than end-to-end measurement of the O&S process.

-30-

Units from the Same MSC and Installation Have Widely Differing Retail OSTs: 1 MARDIV

I NDRI

60

50

I RAND

■ 75-95%

n 50-75% |0-50%

1 MARDIV unit located aboard Camp Pendleton Non-backordered issues from SMU, CY 1996

That there is high variability in the order and ship process is demonstrated by this chart. It shows retail OST for major elements of 1 Marine Division located at Camp Pendleton itself (i.e., no units located outside Pendleton are included). Although distances from the source of supply may differ, they typically do not exceed a few miles.

Order and ship times range all over the map for these combat units even though all are close to the supply warehouses. Median times range from 4 to 13 days and 75th percentiles range as well, from 5 to over 20. Assuming that the Supply Battalion does not discriminate levels of service among these units, then sources of delay may need to be sought in unit processes themselves, including requisition validation, processing, and transmission, pickup or delivery, and the

close-out process.

-31-

Units from the Same MSC and Installation Have Widely Differing Retail OSTs: 2 MARD1V

RAND« na B 75-95%

0 50-75%

■ 0-50%

p B C\-'

te MS

^"•J.

k.V.

ra H — {S3

['■' 1 — — __

— Ü

2 MARDIV units located aboard Camp Lejeune Non-backordered issues from SMU, CY 1996

,q^.0spZM:'A%4?Z&®>Z'l-ii^ mstzzMs. msm

This chart repeats the example of the previous one, using 2 Marine Division units located at Camp Lejeune itself. It demonstrates the same delays and high variability across units that were just seen in the Camp Pendleton case. (More complete results for all MSCs in each of the three active MEFs can be found in App. B.)

-32-

Measurement of Order and Ship Times From Wholesale Supply

■B NDRI IHHHa

On-Base Repair Order and Ship Retail

Order and Ship Wholesale

gas ^tm^. Requisition

Materiel

In this section of the briefing, we investigate order and ship time performance for items requisitioned from the wholesale supply system.

-33-

The USMC Wholesale Report Measures OST End-to-End and in Four Segments

NDRI

5 Pass requisitions tolCP

ICP processes requisition, cuts MRO, selects depot

Depot pulls down MRO, selects shipping mode

I

Depot picks and packs materiel offers for shipment

Shipper moves Materiel sent materiel to TMO to final customer or TAC-2 address and record customer closed out

RAND"

Enter requisition into ATLASS

Cut diskette or email to SASSY SASSY cycle

Hold for edit, review, await replen for low

priority

Pass hi-pri maintenance

requisitions an replens to DAAi

The above chart presents a highly simplified view of the order and ship process for items from wholesale supply.

Several branches are not shown here. Requisitions to wholesale supply can come from the maintenance shop if the item is not stocked and, for high priority requisitions if the item is in zero-balance, and from retail supply for standard (often automated) replenishment requisitions. Requisitions from a maintenance shop follow the same procedure described previously until they reach the SMU. If the item is not available locally (and meets the criteria above), it will be reviewed and approved at the Supply Battalion (based on a financial value threshold) and then be reassigned a new document indicator

code (typically as an A3_, or passing action). All requisitions are then passed via SASSY to the wholesale

system, first entering it via the Defense Automated Addressing System (DAAS) computer at Dayton, OH. Requisitions are routed via the DAAS system and made available to the appropriate national inventory control point (NICP) where item managers handle requisitions and manage stockage levels for specific groups of items.

-34-

At the NICP, a materiel release order (MRO) is cut, usually

automatically; in certain circumstances, a requisition will be delayed

for review by the inventory manager.

MROs are then sourced to a DLA supply depot for processing

and shipping of the materiel. The MRO will be transmitted via the

DAAS system and be entered into the depot's computer system where

it will be pulled down,, typically at midnight, for processing the next

day. Priorities for picking and packing at the depot and the mode of

shipment are both largely determined by the requisition's priority and

required delivery date. The package will be offered for shipment and

then transported to the installation, often to the Traffic Management

Office, unless another address is specified. It is then sent to the Supply

Battalion or to other customers, or deposited in a marked bin for

pickup by customers. When a customer, such as a maintenance shop,

receives the package, the same procedure is followed, with a D6T

(acknowledgment of receipt) being posted through ATLASS to SASSY.

When the SASSY cycle is run, a D6S is posted to DAAS, which

completes the requisition history and closes out the record.

-35-

The Logistics Response Time Database Permits Measurement of Wholesale OST

NDRI ■■■■■■■■■■■■■■^l««^^^^^^^""^^«^^« RAND*

. Maintained by DLA's LRT Process Action Team

• Ali Marine requisitions of DLA and Navy managed items

• Approximately 1 million requisitions opened in CY96

• Captures many, but not all, major steps of O&S process

- missing initial receipt on base, intermediate shipment points OCONUS

• Accuracy/validity can be calibrated using MIMMS

• Analysis focuses on non-backordered requisitions

USMC OSTs for wholesale supply were measured using the archived requisition histories maintained in DLA's Logistics Response Time (LRT) database. This relatively new effort is expanding its coverage of requisition tracking for all managed items of all the Services. In the baseline year, it tracked most time segments for items managed by DLA and the Navy. For the Marine Corps, this includes over one million closed requisitions for CY96 alone.

The LRT database effectively captures major parts of the O&S process, if not all; this will be discussed on the next page. While it is the sole source for detailed information on USMC requisitions on the wholesale system, it is not the only source; the MIMMS database includes limited but relevant information on wholesale OSTs, as will be discussed presently.

Finally, we again limit our analysis to non-backordered

requisitions, as our aim at this stage of the analysis is to understand the performance of the order and ship process, i.e., for items available for immediate issue. In later stages of the research, we intend to measure the performance of the stockage determination process.

-36-

LRT Data Allow Us to Measure Elapsed Time for Four Segments and Overall OST

i NDRI msmamaam Installation/Retail 1. Document

Date

ma—RAND Wholesale

2. DAAS Establishment

3. MRO Cut

Requisition

MRO

\\@«—o XZ— r

5. Customer I Receipt | Materiel

This chart illustrates which segments of the wholesale OST can be

measured with the LRT database. That database has five time stamps

that yield four time segments, as well as an overall measure of OST.

The five dates are:

• the document date (when the requisition was first created),

which is extracted from the document number;

• the document establishment (or "birth") date, which is the

date the requisition first enters the DAAS system (typically,

with an A0_ or A3_ document identifier code);

• the MRO date, when the NICP issues permission to the depot

to release the item and that information is transmitted to the

appropriate DLA supply depot;

• the depot ship date, at which time the item is picked up by

the contracted shipper and leaves the depot; and

• the D6S date, when the received item is posted to the supply

account acknowledging receipt by the ultimate customer and

the record is closed out.

-37-

This then yields four time segments, as well as the overall OST:

• docdate to establish: on-base processing times until the requisition is received at the wholesale level;

• establish to MRO: the processing time at the NICP required

to issue an MRO; • MRO to depot ship time: the depot handling time, including

picking, packing, and making available to the shipper; • depot ship to receipt time: the time from when the item

leaves the depot, is transported to the installation, and then is distributed to the ultimate customer and the record is closed

out. • docdate to receipt time: the overall order and ship time of

the requisition.

Some time stamps are not yet included in the LRT database of Marine requisition histories. The TK_ acknowledging initial receipt at an installation (say, at TMO) is not yet included, making it difficult to separate transit time from on-base receipt takeup time. Few measurements are captured in the overseas segments of the ship process, such as receipt at the port of embarkation, receipt at the port of debarkation, or intra-theater distribution to units.

-38-

Overall OST from Wholesale Supply and Segment Times

Days

90 _

80 ..

70 ■-

60 ..

50 ..

40 ..

30 ..

20 •-

10 |

0

D75-95% n50-75% ■0-50%

O DC

O

w UI

^^&%%%<i&MM$l:^ tMä^&rP¥¥&tiz£U

This chart presents overall wholesale OST performance for the USMC as a whole, including all four MEFs. Data are from the LRT and include all requisitions closed in CY96, for all classes of supply managed by DLA and the Navy (again, backorders are excluded). The first bar shows the percentile breakdown for the overall OST, with a median just over 20 days, the 75th percentile at around 40, and the 95th at 85 days. The other bars show similar breakdowns for each of the four segments captured in the LRT. Note that the longest segment by far is the final one, including transit and receipt takeup time. Detailed base year performance statistics for wholesale OST can be found in App. C.

-39-

OST from Wholesale Supply for Corps and by MEF

Days

D 75-95% U 50-75%

■ 0-50%

§ .ijj

This chart breaks out aggregate OSTs by MEF. Note the differences between CONUS (I and II) and OCONUS (III) MEFs, the latter's long times clearly driven by the need to transport materiel across the Pacific, and also the longer time associated with the Reserve MEF (MARFORRES) requisitions. Note as well the nearly identical OSTs for I and II MEFs: each has a median of 16-18 days, a 75th percentile of just under 25, and a 95th percentile between 50 and 57

days.

-40-

OST from Wholesale Supply and Segment Times: I MEF

90 _

80 ..

70 --

60 ..

Days50 ■■

40 ..

30 ..

20 ■-

10 ..

0

075-95% n50-75%

■0-50%

O C 2 o

In the next four charts, we present OST breakouts for each MEF. This chart shows the performance of I MEF. The first bar repeats end- to-end performance. The four bars to the right break down OSTs by process segment. Again, we see that ship-to-receive time dominates OST, with requisition processing time on base (doc to est time) as the next driver. Relatively speaking, time spent at the ICP and time in the

depot itself are minor contributors to OST.

-41-

OST from Wholesale Supply and Segment Times: II MEF

NDR1

Days

60 _

50 ..

40

30

20 ..

10 ..

u © UJ o

o Q

O DC

O

RAND'

U75-95%

D50-75%

■0-50%

!;«:Vf-

mms

This chart shows equivalent results for II MEF, at Camp Lejeune, NC. The pattern, and most measures, are very similar to I MEF. The front and back end of the process—which to a considerable extent take place on base—are again the biggest contributors to order and ship time length and variability.

-42-

OST from Wholesale Supply and Segment Times: III MEF

NDRI

90 ^

80

70 ■-

60 ..

Days"

103

■■»pi

RAND'

n75-95% Q50-75% ■ 0-50%

This chart presents similar results for III MEF. The obvious difference from the previous charts for II MEF is the final segment. Clearly, transportation time dominates OSTs for items going to OCONUS forces. Nonetheless, on-base requisition processing time is

still a significant driver of OST, somewhat more so than for the other

active MEFs.

-43-

OST from Wholesale Supply and Segment Times: MARFORRES

NDRI

Days

90 _

80 ..

70 ■-

60 ..

50 ..

40 ..

30 ..

20 ■■

10 j.

0

RAND*

113 B75-95% D50-75% ■0-50%

HJ[ftHjjH(|

Hi ^^

I^SS^s^SJ

Finally, we see the same pattern, with more length and variability, reported for the reserve MEF, the MARFORRES. Times are much longer, even than for the OCONUS III MEF, and the amount of variability is much greater (in part due to the interrupted nature of Reserve rotations). Note as well the even greater time required to establish requisitions, in part due to the dispersed nature of Reserve units and, again, the separation of rotations.

In the next series of charts, we take a more analytical view of the O&S process from wholesale supply, in an attempt to understand some

of the drivers of long and variable performance.

-44-

OST from Wholesale Supply Falls Short of UMMIPS Standards:

I MEF Requisitions NDRI

Days

100 j

90 ..

80 ..

70 ..

60 ..

50 ..

40 ..

30 ..

20 ..

10 .-

0

RAND"

I MEF average

UMMIPS standard (average)

■75-95%

■50-75%

■0-50%

Our diagnostic analysis begins with an examination of the effect of

priority on OST. This chart breaks out overall OST, for I MEF

requisitions, by issue priority group (IPG). The bars show the OST

performance for each IPG. The light line higher on the bar shows

current average performance for each IPG. The darker line lower on

the bar shows current UMMIPS standards (as of 1993), expressed again

in averages. Next, the chart makes clear that average Marine OSTs fall far short

of current UMMIPS standards, which themselves tend to be far more

lax than current practices in the commercial sector. For example, high-

priority (IPG 1) requisitions take on average about three times the

UMMIPS standard of five days.

Note that there is little difference between IPG 1 and IPG 2 (even

though UMMIPS standards do call for faster support of IPG 1 than IPG

2, with respective goals of five and nine days). The average OSTs and

each percentile are virtually the same.

In the next series of charts, we take a diagnostic look at the

separate O&S segments in sequence.

-45-

NDRI ■ 10 T

Source of Requisition Affects On-Post Processing Time

RAND

a 75-95% D 50-75% ■ 0-50%

1 AOA requisitions A3A requisitions

(mainly replenishment) (mainly maintenance pass-through) Document date to Establish date for 1 FSSG requisitions

Earlier charts showed that OSTs tended to be driven by ship-to- receive times and by requisition processing time on base, both of which are significantly affected by on-base processes. In this chart, we briefly examine the first segment of the O&S process, the time spent for on- base requisition processing, from the time of document creation through all subsequent reviews and edits, until the requisition is transmitted by SASSY to DAAS.

This chart shows the document creation to DAAS establish time for two types of requisitions: AOAs (or straightforward requisitions) and A3 As (or passing actions on original requisitions). These results are drawn from requisitions issued out of 1 FSSG; similar results would be seen from other organizations as well. AOAs are predominantly issued from the Supply Battalion and are typically used for acquiring replenishment stocks for materiel held in Supply Battalion warehouses. A3As come overwhelmingly from maintenance

activities and represent pass-throughs for zero-balanced or non-stocked

items for parts needed on specific repairs. As we discussed earlier, A3As tend to be higher-priority requisitions for which the decision was

-46-

made not to hold up the requisition until the zero-balance could be

filled via replenishment. The bars show that the time for A3As to be processed on-base is

roughly twice that for AOAs; at the 95th percentile, in fact, it's two and a

half times as long.12 Some preliminary analysis suggests that reviews account for this large difference. AOAs for replenishments are mostly automated; A3As pass through various reviews and stoppages, such as

approvals at the maintenance activity and then "sneaker net" transmission to the SMU; at the SMU, documents are often delayed to

permit the review of high dollar requisitions. These measurements reveal that the most important requisitions—

those directly impacting critical repairs—take longer to leave the installation than lower-priority repairs that are merely needed to fill

thinning shelves.

12The 95th percentile for AOAs is the same as the 75th percentile value.

-47-

Modest Role for Major Depots as Supply Sources across the MEFs

NDRI

70 ,.

60 ..

RAND»

New Cumberland/Mechanicsburg nSharpe/Tracy

| Preferred source]

IMEF IIMEF IIIMEF

:.- . —' :..._;—i M^MMsM^äM^^MMi^^Mff^^Ki^iMääM. ; ._iij

We next move to the depot processing segment.13

One important factor influencing depot processing and shipping time is which depot the requisition is sourced to. Ideally, better service will tend to come from large, fully modernized depots that are located near the customer. This chart shows how the largest depots are servicing Marine customers.

It shows for requisitions in CY96 the percentage of requisitions filled by each of the major DLA supply depots, broken out by MEF. The chart shows the two "West Coast" (I and III MEFs) and the East Coast (II MEF).

The two major DLA depot complexes, New Cumberland/ Mechanicsburg (in Pennsylvania) and Sharpe/Tracy (in central

California) dominate the workload. Of the two, however, New Cumberland/Mechanicsburg accounts for more of the filled

13We skip the ICP processing segment. As shown before, processing times in that segment for non-backordered items are exceedingly short. Overall, 89 percent of Marine requisitions were not backordered. For the 11 percent that were backordered, the percentile ICP processing times were 35, 82, and 182 (median, 75th, and 95th percentiles).

-48-

requisitions. II MEF has about 50 percent of its requisitions filled from this nearby major depot, while I and III MEFs receive less than 40 percent of their materiel from the closest major depot (Sharpe/Tracy, in central California). I and II MEFs receive a substantial level of support from the Pennsylvania depot, whereas relatively little is sent

from California to North Carolina and II MEF.

-49-

Small Package Shipment-Air and Ground- Dominate Depot Shipping Modes

[ NDRI

15 * sü ® £ c

E £ 3 U Ü Jj

IMEF IIMEF

RAND

■I B Air Small Package ■ Comm Air Freight DLess than truckload 0 Truckload ■ Surface Small Pkg ■ Others

^^W^^0f^M!^M^MPM\

Geographical proximity of major suppliers is important because of the transportation efficiencies it allows, as will be discussed shortly. In the baseline year of 1996, a set of inefficient and expensive methods for shipping supplies were being used, as this chart illustrates.

Part of the depot processing segment involves deciding the requisite shipping mode to the customer. This decision typically is a function of the priority and the required delivery date. High-priority requisitions (IPG 1 and 2) that have a valid RDD (999, 777, NMCS or expected NMCS and the requested days until delivery) typically are assigned faster shipping modes, such as air small package delivery (i.e., FedEx-like service). Lower-priority repairs (IPG 1 and 2 without a valid RDD or IPG 3) are treated as routine and typically delivered through slower modes, such as small package ground (e.g., UPS Ground-Trak), less than truckload (LTL), and unscheduled truckload

(TL). The chart above suggests how much expedited, high-priority

shipping service the Marine Corps receives. It shows the distribution of shipping modes to I and II MEF for the two major depots serving

-50-

them, as introduced in the previous chart.14 I and II MEFs get roughly half of their shipments sent expedited (FedEx-like service) and another third small package ground. Obviously the expedited shipments, with one-day transportation, spend much less time in transit than the small package ground, even though all parts may be needed to complete a

repair.

14We exclude III MEF from this part of the presentation because shipping mode information is incomplete. The available data only describe how the item leaves the depot, and not how it arrives at the customer.

-51-

Ship to Receipt (D6S) Times, Controlling for Depot and Ship Mode

NDRI

Days,

RAND

Air small package only

2 1 FSSG 2FSSG 1 MARDIV : 2 MARDIV

While choice of shipping mode will make a substantial difference

in times for this segment of the O&S process, further delays may be experienced once the shipment has reached the installation. Unfortunately, the LRT database does not allow us to separate these two segments of the shipping/receipt takeup process. However, we can infer the length of the on-base takeup portion as this chart illustrates. It concentrates solely on high-priority, air small package deliveries (FedEx-type service) which typically have one to two business-day guaranteed delivery.

The chart shows ship-to-receipt times for air small package shipments by major subordinate command and selected depots. Several points are noteworthy. First, shipping and receipt takeup times are remarkably uniform for a given major subordinate command, even across depots (since these are using FedEx-like delivery, this may not be surprising). The second notable aspect is the large variation across major subordinate commands. While median times are roughly

similar, there are substantial differences in the 75th and 95th percentiles. The third notable point is the absolute value of times for

-52-

this segment. Even in the best case, half the shipping and receipt takeup times exceed five days—sometimes by a lot more. Given guaranteed delivery of one to two days, and even accounting for weekends and holidays, the inferred delays in receipt takeup times once the item has been received on the installation seem quite long.

-53-

Frequency of D6S Reporting Varies Considerably by Organization

39% of requisitions shipped had a D6S posted by 9/30/96 MSC Records with D6S date as % of shipped reqs

1 FSSG 83 1 MARDIV 60 3 MAW 12

2 FSSG 2 MARDIV 2 MAW

86 31

3

3 FSSG 3 MARDIV 1 MAW

77 39

8

4 FSSG 4 MARDIV 4 MAW

35 46 35

MEU (I MEF) MEU (I! MEF) MEU {II! MEF)

42 27

MCB PEN MCB LEJ MCB BUTLER

8 55 69 »»

Performance measurement relies on the quality and comprehensiveness of the data. As the next three charts suggest, there are some serious issues regarding data quality that the Marine Corps may wish to address.

Order and ship time in the LRT database is calculated from beginning to end times, from the document date (in the document itself) and the date the D6S (acknowledging customer receipt) is posted to DAAS. Quite often, however, the D6S is never posted to DAAS and the record is not closed out with a customer acknowledgment. In fact, less than 40 percent of Marine requisitions are ever officially closed out this way in the LRT. The chart above shows how D6S use varies across major USMC organizations. The lines separate the MEFs, with the base operations and MEUs listed below. Some organizations, such as the active Force Service Support Groups, close out most requisitions; Marine divisions, on the other hand, vary substantially in their reporting rate. The air wings, however, barely vary at all: they post

-54-

few record closeouts.15 In some cases, different policies may be in effect; for example there are striking differences in reporting among the

three base operations.

15MAW requisition histories apply only to ground support units, those whose requisitions begin with "M."

-55-

Requisitions Often Closed Out in MIMMS Long Before D6S Posted to DAAS

NDRI ■ 100

90

80

70

60

50

40

30

20

10

Cum. %

£Lfi£ S - MIMMS DRC for All Matches RAND'

.*■ 7

«A*

' '

i /

/ <'

<0 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 >50

DLA and Navy RICs only; matched documents with differing RICs deleted «. mmm

Another concern about data quality regarding D6S posting is when the record closure makes it to DAAS. This chart shows that the D6S is often posted long after the customer has received the needed

part. To measure this discrepancy, we "calibrated" the LRT database

by comparing it to wholesale requisition data resident in the MIMMS requisition histories. In particular, we used the MIMMS records to evaluate the quality of D6S posting. For matched requisitions, we compared the receipt date in MIMMS to the D6S date in the LRT. The figure above shows the difference between the D6S date and the

MIMMS date.16

16In certain cases, the MIMMS may show an earlier receipt date if the required part is acquired through some other means, as might happen if delays occur in the receipt of the item from wholesale or if it remained backordered. In those cases, procedures call for changing the source of supply in MIMMS. In a small percentage of the cases of matched requisitions, we noted that indeed the MIMMS record showed a local source of supply for a requisition that also appeared in the LRT. We excluded these cases from our analysis.

-56-

The chart gives substantial evidence of discrepancies between when the mechanic apparently received the required part and when that fact was recorded in the LRT. In about 4 percent of the cases, the

D6S date actually precedes the MIMMS date. In another 24 percent of the cases, the D6S and MIMMS dates were the same, and in 20 percent

of the cases, the D6S followed one day after the MIMMS receipt. However, in many cases, the D6S date occurs well after the MIMMS

date. In fact, in 10 percent of the cases, the D6S date is posted three

weeks or more later than the MIMMS date.

-57-

MEFs Differ in D6S-DRC Discrepancy Rates:

LRT D6S - MIMMS DRC for All Matches ■ NDRI 1

100

90

80

70

60

Cum.%50

40

30

20

10

0

<0 1 3 5 7 9 11 13 15 1719 21 23 25 2729 31 33 35 3739 41 43 45 47 49 >50

DLA and Navy RICs only; matched documents with differing RICs deleted

SP «Ki te Mi l^u Fi U>AJ y rt* L"t vtü bü w^fi»

/f JU^

. ' p

ft ' . .'

0'* *

I I»

I RAND

- Corps IMEF

II MEF —III MEF —-MARFORRES

This chart repeats the result for the entire Marine Corps we saw on the preceding chart and adds cumulative percentage curves for each of the MEFs. We see that most D6S-MIMMS discrepancies are found in the reserve MEF; indeed, one-third of all cases have at least a 14-day difference; 10 percent of the cases for this MEF show a 45+ day difference. While not as extreme, discrepancies occur for the active MEFs as well. Ten percent of those cases show at least an 11-day difference between LRT closeout and MIMMS receipt date. These discrepancies indicate that in many cases OSTs shown in the LRT do not necessarily reflect the time it actually takes for Marines to receive

the parts they need.

-58-

USMC OSTs Differ from Army Mostly In Ship to Receipt Takeup Time

NDRI ■

60 _

Days,

FORSCOM: MIRP from LIF Jun-Dec96

l+ll MEF: D6S from LRT Jun-Dec96

No backorders

Docdate to Receive

Docdate to Establish

Establish to MRO

MROto Depot Ship

RAND« a 75-95% Q 50-75% ■ 0-50%

Depot Ship to Receive

For more than a year the Army has been aggressively pursuing improving its O&S process from wholesale supply. Since Army operations are in many ways similar to those in the Marine Corps (apart from obvious exceptions, such as the deployed Marine Expeditionary Units), it may be instructive to compare OSTs between the Army and the Marine Corps.

Army performance data are pulled from a database called the Logistics Intelligence File (LIF), similar in many ways to the LRT. The LIF is maintained at the Army's Logistics Support Activity in Huntsville, AL.17 Some differences exist in the data elements contained in the two databases; of most relevance for our concerns is that the Army data cut off both the front end and back end of the order and ship process. The Army data include only time from the supply support activity (SSA, roughly equivalent to the SASSY Management Unit, or SMU) to the wholesale system and ending back at the SSA. For

17Army data cover the period June-December 1996 to match wholesale OST data available for the Marine Corps. We have been calling this period in which data were available "calendar year 1996."

-59-

non-replenishment requisitions Marine OSTs count time from the final customer, through the SMU, to the wholesale system and then finally

back to the ultimate customer. The chart above compares OSTs both overall and by segment for

comparable parts of the Marines and the Army: I and II MEF combined

versus Forces Command (FORSCOM) Army units stationed in

CONUS. The chart reveals somewhat longer OSTs for the MEFs compared to the Army (exaggerated by the incompatible process measurements discussed above), slightly longer on-base requisition processing time for the Marines, no significant differences in the wholesale segments of the process (ICP and depot processing),18 and fairly substantial differences between the Army and the Marines in the ship to receipt segment.

18The shorter processing time for Marine requisitions at the depot may be accounted for by higher priorities used by the Marines or more consistent use of valid RDDs than the Army used in this time period.

-60-

NDRI

Marine/Army Comparison in Depot Sourcing

RAND»

nSharpe/Tracy

■New Cumb/M

Source: Armv-LIF: USMC-LRT: 4QFY96. DLA/Naw ICPs only

This chart shows how some major Army locations and the active

Marine Corps MEFs compare in choice of depots serving their

customers. It presents results from 4Q FY96 for the active MEFs and

comparable Army installations. It shows the percentage of all

requisitions filled for a location by the two major DLA depot

complexes of Sharpe/Tracy (California) and New Cumberland/

Mechanicsburg (Pennsylvania). As argued before, concentrating

support of a customer at a nearby large depot can lead to overall

process efficiencies (as shown on the next chart). To a significant extent

back in mid-1996, the Marines and the Army often were not routinely

supported by local major depots.

I MEF and the Army's Ft. Irwin, near Barstow, CA, received

roughly comparable service, with I MEF receiving slightly more

support from its nearby major depot, Sharpe/Tracy. Ill MEF and US

Army's forces in Korea (USFK) tended to get similar levels of support

from Sharpe/Tracy; USFK tended to get more shipments from the East

Coast depot at New Cumberland/Mechanicsburg.

-61-

The most distinctive difference between the Marine and Army

experience is shown in the middle set of bars, comparing Ft. Bragg, NC, and II MEF at Camp Lejeune, NC. Ft. Bragg received considerably- more support from the closest major depot, New Cumberland/ Mechanicsburg, while II MEF less from the East Coast and more from the West Coast than did its nearby Army neighbor.

-62-

Shipping Mode Comparison: I, II MEF and Selected Army Installations

NDRI I RAND»

■SurParcPost □Truckload □Local Del □ LTL ■Others □Surface small pkg ■Air small pkg

USMC: Requisitions filled by DLA supply depot, 9/95-8/96 Army: Requisitions filled by DLA supply depot, 7/95-6/96

This chart compares shipping modes used to send materiel to Marine and Army customers. It shows the distribution of modes used during FY96 for the two active CONUS MEFs and three selected Army installations. Two things stand out. One is that the Marines benefit from a higher use of the premium shipping mode, air small package,

relative to the Army.19

The other notable point relates again to Ft. Bragg. The previous chart showed that Ft. Bragg got unusually high levels of service from a single major depot. This chart shows that Ft. Bragg, while getting little air small package service, received a large portion of materiel by

truckload. The two are related. Ft. Bragg has aggressively worked with DLA

to improve the level of service it receives. One result of this effort has

19This may indicate more consistent use of RDDs on Marine Corps requisitioners. RAND research for the Army has revealed that many in the Army do not know about or understand the role of RDDs in securing higher-priority treatment of requisitions; many believe the use of the priority designator alone is sufficient. Furthermore, in some cases, Army information systems do not support the propagation of RDDs.

-63-

been scheduled truck deliveries from the New Cumberland/ Mechanicsburg complex. This innovation has both reduced the costs

for DLA (by avoiding the use of expensive services like small package

carriers) and made deliveries to Ft. Bragg more dependable and faster overall: trucks arrived at an agreed-upon scheduled time and all materiel—not just high-priority items—receive the same fast

shipment.20

20Since the time period of the data analyzed here, scheduled trucking arrangements have become extensive for most major Army customers of DLA. Partly as a consequence of Precision Logistics implementation, more Marine customers have started to benefit from scheduled trucking as well.

-64-

Okinawa Ship-to-Receive Times Are Significantly Longer than USFK Times

NDRI

Days

RAND"

D75-95%

D50-75%

■0-50%

in Z3

III MEF: Depot ship to D6S USFK: Depot ship to MIRP; source: Army LIF, 7/95-6/96, all ICPs

The final comparison between the Army and the Marines examines the long ship-to-receive times we saw for III MEF. Those times are compared to US Army Forces in Korea (USFK). The chart shows a dramatic difference in the overall time.21 The difference in support for these two OCONUS locations is so striking as to demand further exploration and explanation. At this time, we can offer no accounting for the difference, but aim to pursue the issue in follow-on

research. Finally, we close the briefing with some observations.

21 Although again it should be noted that Army OST ends at the supply support activity and Marine OST ends, sometimes, at maintenance shop receipt.

-65-

Observations on the Current Performance of Repair and Order & Ship Processes

I NDRI ^■■■■■■■■■■■^■■■■■■■■■^^^^■■■■■■^^ RAND1"

• Cycle times for all three processes are long and extremely variable

- RCTs tend to be driven by "waiting" steps and non- value-added activities

- Retail OST long and highly variable across units

- Wholesale OSTs tend to be driven by on-base processes

• Because these three processes are linked, performance deficits in one can hurt others

The constant refrain of this analysis is that LRTs are long and variable, as observed in the above chart. Each of the three processes measured here—repair, retail order and ship, and order and ship from wholesale supply—suffered from delays and high variability. While there will always be inherent variability in logistics processes (e.g., overhauling an engine will typically take longer than replacing a cracked rearview mirror), much of the length and variability arises from "non-value-added" activities, or processes that are not well controlled. We see this, for example, in the widely varying retail OSTs among the units of 1 MARDIV and the different receipt takeup times for air small package deliveries across the major subordinate

commands.

-66-

Poorly Performing Processes Have Many Bad Effects

NDRI mmmH^mmmmmmmmmm^mi^mmi^^mm^mm^^ RAND™

Processes Immediate problems Ultimate impacts Inefficient

Repair ► rePair

of needed parts

Increased time awaiting parts t

Order and fe. S!ow> variable ship delivery

Many zero balance, despite deep depth I

Stockage- _^. Wrong stocks determination in {he wrong

places /

Decreased mission

readiness

Decreased deployability

Wasted $S

As shown in the above chart, and as we indicated at the beginning of this document, logistics processes are highly interlinked. Repair depends on the supply of parts coming mostly from retail stocks; sometimes it depends on the availability of repairable items whose availability itself depends on quality of the repair process. That availability follows from stockage determination policies and practices which dictate what should be and is held in stocks, and on the O&S process from wholesale supply, which determines how quickly replenishment stocks can be received (and also influences the depth

and breadth of stockage at the retail level). If any one of these processes performs poorly, the other processes

will be affected. Slow repair will reduce the number of serviceable items at the RIP, slowing up other repairs depending on those items and impacting the stockage allocation for these often expensive components. Poor parts identification and bad requisitioning procedures will fill the pipelines with requisitions for unneeded parts, both at the retail and wholesale level, and will absorb space and resources better used by more critical items. Slow OSTs from

-67-

wholesale supply will impact RCTs and drive up the level of stockage requirements at the retail level, while narrowing the breadth of items that can be carried. Finally, slow and variable retail OSTs will have a

direct link to slow and variable RCTs. In short, it is important not to look at these critical logistics

processes in isolation. They depend on and are linked to each other. An effective logistics response time reduction effort must target all of

these processes (and others as well) to achieve the goals the Marine

Corps strives for: better, faster, cheaper logistics in support of the

warfighter.

-68-

Better Performance Measurement/Reporting Is One Key to Precision Logistics

■ NOT jf^mmi^mi^mmi^^m^mm^^mm^mm^mi^^^m RANDBM

. Multiple metrics (50/75/95) are needed to understand the variable performance of the processes

- Means alone not very useful as metric . Baseline measurement critical to create reference point

for future improvements . Continued measurement valuable for monitoring and

reporting performance - requirement for enhanced reporting systems and

more detailed and informative databases

In summary, as emphasized in the above chart and throughout

this briefing, both the length and the variability of LRTs are important

to understand. We believe that single metrics, like averages, hide as

much as they reveal and that true understanding of processes and what

drives them requires multiple metrics. In this briefing we offered

medians, and 75th and 95th percentiles as a way of capturing the full

distribution of OST performance.

Another observation is that while much can be done with current

information systems, more could be done with more capable systems to

help diagnose the reasons for poor performance. Some of these systems

are in the control of the Marine Corps; others are not. MIMMS in

particular might be modified to make it a more powerful tool for

measuring and analyzing RCT performance. Useful information such

as repair statuses, entered painstakingly by Marines, is stripped off

before archiving. The archival policy should be modified to permit

retention of status histories for each ERO.

The LRT database is continually evolving and its capabilities will

expand as all Service-managed items are brought into it. The LRT

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database will be a more powerful tool for supporting process improvement if it includes more segments of the O&S process. These

include (but are not limited to) receipt of materiel at the installation (TK_), and receipt at the port of embarkation and port of debarkation.

LRT performance measurement and diagnostics are critical parts

of a process improvement initiative like Precision Logistics. High-

quality and comprehensive databases are needed to support measurement. To answer this need the Marine Corps should strive to

collect detailed data on the performance of logistics processes and to

make sure that data being entered are correct and complete.

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APPENDICES. BASELINE CYCLE TIME MEASURES

This document makes the argument that measurement is one

critical part of a logistics process improvement strategy, along with detailed knowledge of process characteristics and a straightforward

mechanism to seek improvement and try out new techniques and ideas. To tell that improvements are real, feedback is critical, and the more quantitative the better. But for that feedback to have meaning, there

needs to be some benchmark—a baseline—to refer back to and compare the implemented change to.

The main text of this document has laid out in graphical form some elements of a logistics process performance baseline. The following three appendices attempt to present a performance baseline more rigorously, formally, and comprehensively.

Currently, Precision Logistics seeks to improve three critical logistics processes: retail (echelons 2-4) repair cycle, retail order and ship, and order and ship from wholesale supply. Three overarching metrics are needed to assess performance: time, quality, and cost. The initial focus is on the time metric: how long do each of these processes

take? The following three appendices lay out baseline performance in

cycle time for each of the three processes. In each case, unless otherwise noted, the base year is calendar year (CY) 1996. Appendix A presents results for retail repair cycle time (RCT); App. B does so for retail (SMU-supplied) order and ship time (OST); App. C does so for wholesale OST. Each appendix begins with a short description of the methodology used, some of the constraints involved, and implications for future performance measurement. Each then presents baseline performance results in tabular form. The tables are organized, insofar as possible, in generally hierarchical form, beginning at the grossest

level and then moving to smaller units (e.g., to maintenance shops) or to more diagnostic slices (e.g., time for segments of the process).

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APPENDIX A. RETAIL REPAIR CYCLE TIME

DATA SELECTION The data source for the retail repair cycle time baseline is

MIMMS, extracted from the Headquarters MIMMS archive, maintained

by MARCORLOGBASE-Albany. While all MIMMS records in that

database were obtained by RAND, the following conditions, or

parameters, applied:

• Close dates for repair actions (for definition, see below) in

CY96 • Echelon of maintenance 2, 3, and 4 • Close status of repair action (see below) = 15 (completed

repair) • Maintenance categories used:

- Deadlined MARES-reportable PEI - Deadlined non-MARES-reportable PEI - Maintenance categories D, F, and H for secreps

• For echelon of maintenance 4 (secreps) only repairs done in the Force Service Support Group of the MEF

• TAM (Table of Authorized Materiel) groups (first character of the TAM control number): - A: Communications/electronic - B: Engineering - D: Motor transport - E: Ordnance.

The baseline report is in two parts: PEI repair and secrep repair. PEI repair actions are limited to those for critical maintenance, i.e., returning a deadlined end item to usable status. There is a separate report for each MEF, and no overall USMC report. Only FMF results are reported here. The logic of the report (if not the format of

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presentation) generally follows that of the USMC retail RCT report first

issued November 1997.1

REPORT LOGIC The logic of the first report (for PEIs) needs some explanation, for

it differs from the way RCT is usually thought of in the Marine Corps.

Process performance measurement in Precision Logistics has two

aims in aiding performance improvement. One is to capture an end-to-

end action; the other is to provide information at the right level and in

the right form to the organizations and individuals who own the

relevant part of the process. The retail RCT report attempts to meet

both those aims. Toward the first aim, the retail RCT report focuses on repair

actions, instead of ERO time. That is, to the extent possible, it focuses

on the time from when a piece of equipment is known to be faulty until

it is repaired and available to the user again (or as close as we can get to

those beginning and end points). We call this time—from identification

until final repair complete—a "repair action." A repair action may be

totally contained within a single ERO (in fact, for secreps, we treat

EROs and repair actions as the same). However, a repair action can,

and often does, stretch over two or more EROs. The repair action time

in such cases begins with the date received in shop (DRIS) for the first

ERO and ends with the close-date (with close status 15) of the last ERO.

For multiple-ERO repair actions, the linking mechanism is obviously

critical; we link EROs in a repair action when there is a match by

TAMCN, NUN, serial number of the PEI, and time overlap among the

EROs. Consider the following real case, drawn from the MIMMS

archive:

^or differences in methodology between the baseline measures reported here and the recurrent USMC retail RCT report, see below.

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Repair Action Time Can Be Greater Than Individual EROs

i

2,M

VTO415 ^^^^9§^^S§9mX^mS^ 2,M

WU582

. 20 40 60

Days

Start date 96061, end date 96150, AAVP7A1, S/N 522498

The chart above shows two EROs—both echelon 2, category M—for the same PEI (AAVP7A1, with bumper number 522498) overlapped in time. While the first ERO was open for 41 days and the second (which opened up 27 days into the first one) was open for 21 days, we calculate the repair action time as 48 days, which is the time from the first DRIS to the final close date. Also, for counting the number of repair actions, we count the above two EROs as one repair action: only one item was repaired.

The second consideration in a repair action is how much time to assign to a particular unit, especially if more than one unit is involved in a repair action (e.g., a second echelon repair unit in the MARDIV evacuates a PEI to the FSSG for third echelon repair). The following

chart demonstrates another real world case.

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"ERO" Time Is Apportioned by How Long A Unit Actually Has the Gear

ERO

03

20 40 0

1b

3,M

2,M

Start date 95318, end date 96065 M813A1 TRK, S/N 514576

60

Days

80 100 120

We argue that repair time should only be assigned to a unit for

the time when it actually has control over the non-operable equipment.

For example, in the case illustrated above, the repair action time for this

truck was 112 days, divided between a second echelon (maintenance

category M) ERO and a third echelon (category M) ERO. The third

echelon repair facility held the truck for 75 days (segment 2), and, while

the second echelon ERO was open for the full 112 days, the time it had

the truck, independent of third echelon repair, was instead 37 days (15

days at the beginning and 22 days at the end—segments la and lb). The

"ERO times" for the two units then are 37 days and 75 days, while the

repair action time for the vehicle is 112 days.

What we report, then, is "repair action time" where feasible, and

for units doing the repairs we report their "ERO time" as illustrated

above. In practical terms, what this means is that at the MEF level we

will report repair action times, whereas at any level below MEF (MSC

or unit) we report aggregated ERO time, because a repair action can

cut across MSCs or units, but not across MEFs.

-77-

DEFINING CRITICAL REPAIR ACTIONS The baseline PEI repair action times are intended to cover only

critical repairs, that is, those maintenance actions that bring a deadlined

system back into operation. Other maintenance action—on degraded systems, or for general non-critical work—should be excluded.

Unfortunately, there is no simple way to determine what repair action time is on a deadlined system and what time is spent in less critical repair. The problem exists in current USMC MIMMS data and is even worse for the data used to build this 1996 baseline report.

All EROs in the MIMMS system contain maintenance category

codes ("catcodes") describing the type of maintenance (e.g., M is for

deadlined MARES-reportable systems). However, while the catcode can be changed at any time while the ERO is open, only the final catcode is kept in the MIMMS archive. Thus, an ERO with catcode of M may have included work on a deadlined system for only part of the time the ERO was open.

In the official USMC retail RCT report, developed by RAND, this problem was solved in part by combining catcode information with two other data fields: "catmdays" and "deadlined date." The former captures how long a MARES-reportable system was in deadlined status. The latter, used for both MARES and non-MARES systems, shows the date the PEI became deadlined. This allowed a fairly good approximation of which repair actions were on deadlined PEIs:

• if catmdays was equal to or greater than 90 percent of the repair action time (first DRIS to last close date);

• if the time between deadlined date and final close date was at least 90 percent of the time between first DRIS and final close date, and the catcode associated with that final close date was P or M (i.e., the PEI ended its repair in deadlined status).

MARES-reportable PEIs tend to include catmday values but not deadlined dates (though sometimes they do) and non-MARES- reportable PEI repair actions, while obviously not showing values for catmdays, typically will show a value for deadlined date. The 90 percent value (the deadline time should be at least 90 percent of the

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repair action time) was chosen arbitrarily to exclude repairs where a

significant time was spent in non-critical work. While this logic works well for the existing USMC retail RCT

report, it does not apply as well to the baseline measures reported here. The former is drawn from MISCO MIMMS data resident at each MEF, data that are purged on a recurrent basis. The baseline measures are based on archived MIMMS data held at MARCORLOGBASE-Albany.

Unfortunately, the catmday field is not retained in the archived

database, while the deadlined date is. That is, the logic for non-MARES

PEI repair actions can be duplicated, but the MARES-reportable PEI

repair actions are only consistent across the two methodologies if a

deadlined date appears, which it does frequently but not universally.

Fortunately, the use of catmdays, while useful, does not appear to be absolutely critical. To measure the impact of not using catmdays we compared MARES repairs for I MEF for the period July-September

1997. It turns out that the difference is minor:

Category Number Average

RCT

Median 75th

percentile

95th

percentile

Catmdays

used

2679 33.3 19 40 112

Catmdays

not used

2590 34.0 20 42 112

The first row uses the logic laid out above. The second logic includes all repair actions where the final catcode is M. Apparently, not having catmdays available does not greatly bias our estimate of

MARES-reportable PEI repair actions. The same is not true for non-MARES-reportable PEI repair

actions if we pay no attention to deadlined date:

-79-

Category Number Average RCT

Median 75th percentile

95th

percentile

Deadlined

date used

1281 30.0 21 38 94

Deadlined

date not used

2534 36.8 22 49 105

Including all repairs with final catcode P, irrespective of the deadlined date, greatly inflates the number of repair actions and the RCT. Clearly, using the deadlined date, as described above, is important for identifying critical non-MARES-reportable PEI repairs.

This baseline report, then, uses the standard method for calculating non-MARES-reportable RCTs and for MARES-reportables

includes all repair actions that have a final catcode of M.

REPORT STRUCTURE There are reports for each MEF divided into PEI and secrep

repair, presented in tabular form. Each table uses generally the same format. Results are presented in terms of numbers in each case (e.g., number of repairs for the MEF), average repair cycle time for this case, and percentiles to show the distribution of repair times: median, 75th percentile, and 95th percentile. The records of the table are organized generally in a descending hierarchy.

PEI Report The PEI report first shows overall MEF repair action times for the

baseline period, then reports at the MEF level for each TAM group, then by maintenance category (M or P). After that it shows ERO time at the MEF level by echelon of maintenance (note that this is "ERO time" and not "repair action time" because a repair action can and often does cross echelons of maintenance but never crosses MEFs, TAM, or maintenance category as we have selected them).

-80-

Next the table reports at a finer level of disaggregation.2 Here

"ERO times" are being reported instead of repair action times, as a

repair action may go across MSCs (e.g., a repair started in the division

may end in the FSSG). The same structure is used here as for the MEF:

• MSC

• MSC and TAM group

• MSC and maintenance category

• MSC and echelon of maintenance

Finally, ERO times are shown by individual unit performing the

repair (shown by UAC and unit name). No further disaggregation is

done at this level.

Secrep Report Secrep repair is reported only at echelon of maintenance 4 and at

the FSSG, most typically at the General Support Maintenance

Company. While secrep repairs are sometimes reported using echelon

3 and another MSC, this report will be limited to that echelon and

MSC; also, only maintenance categories D, F, and H are considered.

Since repairs for secreps are typically accomplished on a single

ERO (and in any case, secreps are not generally tracked by serial

number, making linking across EROs impossible), the logic of secrep

repair action time is simple: it is the same as ERO time, with each

secrep/echelon 4 ERO being treated as a single unique repair. Repair

times are broken out in this report as follows:

Overall FSSG RCT

RCT by maintenance category

RCT by unit

RCT by unit and maintenance category

RCT by unit and shop

RCT by unit, shop, and subshop.

2 In this case, and in all cases, a level is reported if there are at least 50 cases in the reporting period that meet the criteria.

-81-

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APPENDIX B. RETAIL ORDER AND SHIP TIME

DATA SELECTION Data for the retail order and ship time report come from

headquarters MIMMS archives held at MARCORLOGBASE-Albany. Archived MIMMS records (i.e., for EROs that have closed)

contain two types of records. The "header" record contains information about the repair itself, such as item fixed, DRIS, close date, etc. (the header records provided the information for the retail RCT

report in App. A). The second, or "trailer," record includes

information about the parts required (the EROSLs, or ERO shopping

lists) associated with the ERO. Each EROSL record contains, among other things, the requisition document number, the source of supply,

the final status, and the date received. This was the source for the

baseline retail order and ship time report.1

The retail OST report is based on the following data selection:

• EROSLs with a date received in CY96 • Items issued out of local stock (routing identifier code

beginning with "M": for I MEF, MCI and MC3; for II MEF, ML1 and ML3; for III MEF, MK1 or MK3, MR1 or MR3—none for MARFORRES, which does not have retail stocks)

• non-backordered requisitions, i.e., those with supply status

BA.

REPORT LOGIC The logic for the retail OST baseline report is exceedingly simple.

Only one time is calculated—the end-to-end order and ship time, defined as the date received-document date. The document date is

lrrhe MIMMS database, however, will not be the source for the recurrent USMC retail OST report scheduled to be issued quarterly by MDAC. For reasons discussed earlier in the text, it is impossible to separate back-ordered and non-back- ordered requisitions in the EROSL archive of MIMMS, making any measurement of non-backordered OST impossible. Instead, an alternative has been developed to build an archive of SASSY requisition histories, based in the SASSY HDIS file. While that archive is currently being filled, it was not started until well after the baseline year was over.

-107-

extracted from the document number and represents the draft ATLASS

date.

REPORT STRUCTURE The retail OST report structure is similar to the retail RCT report,

i.e., it tends to follow a descending hierarchy. Results are presented below in tabular form for each MEF; there again is no overall USMC

report. The sections of the report include OST reported by:

• Overall MEF • MSC • UAC/unit, arranged by MSC.

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APPENDIX C. ORDER AND SHIP TIME FROM WHOLESALE SUPPLY

DATA SELECTION Data for the USMC wholesale OST report come from the Logistics

Response Time database, under the control of the Defense Logistics Agency (DLA) and maintained by the Defense Automated Addressing

System Center (DAASC) at Dayton, OH. The LRT includes requisition

histories for all the Services for most items they requisition. The database is evolving (and the coverage changed over the course of data

collection) as it seeks to include more and more of the order and ship

process. The baseline year measurements include all Marine Corps requisition history data sent to RAND from DAASC for requisitions closing with a D6S in CY 1996. However, there are several things to keep in mind. Very few LRT data were available before April 1996, and "normal" numbers of cases only started entering the database in June 1996. Furthermore, until February 1997, only items managed by DLA and the Navy were included in the database (in 1997, coverage extended to all items except those managed by the Air Force). Thus, the "1996" database isn't precisely a year's worth of data; however, it is the best source of data available. We will continue to refer to the baseline "year" of 1996 as a kind of shorthand. The other thing to note is that not all Marine requisitions are included (beyond the issue of DLA and Navy managed items). Only ground force and other non- aviation Marine requisitions are included (i.e., those documents beginning with "M" as opposed to "R" and "V" for Marine air). Logistics for Marine aviation is a separate process, supported and managed by the Navy; it lies outside the scope of this project.

In creating the baseline report, the following conditions were

applied:

• Requisitions closed out with D6S date in CY 1996 • Non-back-ordered issues from DLA supply depots

(corp_fill_type = A) for overall OSTs and for the ICP processing segment; otherwise, all issues are included

-117-

• FMF ground customers only

REPORT LOGIC This report also has a simple logic. Order and ship times are

calculated as end-to-end measures defined as the document date to the

D6S date (extracted from the document number and representing the

ATLASS draft date). Internal segments of the O&S process are

calculated similarly, i.e.:

• Document date to DAAS establish date: time to move the

requisition off the base • DAAS establish date to MRO date: ICP processing time for

non-back-ordered requisitions • MRO date to depot ship date: depot processing time • Depot ship date to D6S date: transit and receipt take-up time

REPORT STRUCTURE The following baseline year OST report has two major parts. The

first part reports overall OSTs; the second part provides finer detail, reporting segment times for those segments the Marine Corps has most direct influence over—moving the requisition off the base and transit/receipt take-up time. As in the previous reports, we follow a

descending hierarchy: Overall OSTs: • overall FMF • by MEF • by MEF and MSC • by MEF, MSC, and RUC/unit

Segment times: Docdate to DAAS establish by

• overall FMF • MEF • MEF and MSC • MEF, MSC, and RUC/unit

-118-

Depot ship date to D6S date by: • overall FMF • MEF • MEF and MSC • MEF, MSC, and RUC/unit.

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