ISLD ForumApril 11, 2005

A Balanced Perspective:EPC/RFID Implementation in the

CPG Industry

Pam Stegemen - VP Supply Chain and Technology Sean Campbell - Partner, IBM Business Consulting Services

Workshop Objectives

• Discuss rationale for conducting the study

• Review key findings and implications

• Discuss recommended action plans

Answer any open questions about the study

Lessons Learned - History of e-collaboration tools

• It should not be about “The Technology”– More emphasis on process change and improving

product visibility and enhancing consumer value• Set business oriented goals and measure results• Be realistic about costs and savings

– Don’t amplify the hype cycle• Communications must be increased

– Top level message must be consistent• Maintain flexibility and technology options

– Manage the pace of implementation• Ensure there is a positive consumer point of view

EDEDII

GDSGDS

The Goal: Better supply and demand visibility

Better Product Visibility

Technical Process People

Requires

Product location / movement data

Automated data capture

Links with GDS

End-to-end processes

Process standardization

Industry infrastructure

Collaboration

Goal and incentive alignment

Measurement and feedback

Why GMA conducted the study

Many manufacturers have EPC initiatives in progress to explore potential benefits and to pilot the technology. These early adopters share a need to address common challenges:

●Believing in the long term EPC vision, but not having a clear migration path to anticipated benefits

●Balancing the need of solving business problems across the value chain vs. the current focus around the technology of RFID tags and EPC itself ●Understanding distribution of investments and benefits among the value chain participants

GMA engaged both IBM and A.T. Kearney to conduct the study

Scope of Analysis

Manufacturer Companies • 24 NA business cases - 90%

companies with sales >$2 billion• All business cases represented

companies with relatively efficient operations (e.g. use WMS )

• Benefits identified are incremental to other current operational improvement initiatives

Analysis Areas• Pallet and case level tagging

(no inner packs or eaches)• Processes covered those from point

of finished goods production thru receipt and storage in the retail backroom and movement to the sales floor

• Source tagging not addressed

Raw Mat’ls & Pkg. Suppliers

Manufacturer Retailer

Mfr. DCRetailer

RDC Store Back

Room Store ShelfFactory Factory

Door to Floor

Key Included Excluded

Manufacturer Business Case Data

• Business Case Data– 10 yr. time phased cash flows– Includes est. retail adoption rates– Includes company specific

tagging strategies (slap & ship -> tag in mfg)

– Any “anomalies” were investigated and reviewed with company for clarification

• Assumptions, data, timing of investments and delivery of benefits came from individual participant companies and have NOT been changed (except tag costs)

• Business cases have been presented internally to respective management teams and represent a current, point in time, corporate view

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

1 2 3 4 5 6 7 8 9 10

83%

71%

55%

Year

% s

ale

s to

RF

ID c

usto

mer

s

LEGEND

HBC/OTC

DC (except for HBC/OTC)

DSD soft drinks, snacks

Sample Retailer Adoption Curve

10 Year End Point

Modelling Adjustments

• We normalized volumes and associated costs and benefit projections to eliminate any distortions caused by size

• We used constant tag cost estimates (with sensitivity analysis) as opposed to maintaining variety of existing company projections– High level of variability across companies– Ability to compare impact of tag prices across companies– Provides direction around target or break-even tag prices– Eliminates debate around starting, ending and rate of

decreasing cost estimates

• We recalculated net present value analysis based on these modifications

Category Definitions & Data Points Available

Pharmacy

Fresh Produce

Cigarettes & Tobacco

Alcoholic Beverages

News & Stationery

Toys

Consumer Electronics

Music, Video & Games

Apparel

Data Included No Data Included

Cereal, Pasta

Detergent, Paper Products

Frozen Dinners, Ice Cream, Juice

Shampoo, Lotion, Cold Medicine

Soda, Potato Chips, Pretzels

Carbonated Drinks & Snacks

Dry Goods (food)

Dry Goods (non-food)

Frozen / Chilled

Health, Beauty & Cosmetics

Benefits – Many Benefit Opportunities, but Four Consistently Ranked as Primary Areas

Reduced retailer claims (overages, shortages)

Reduced DC/Plant labor

Reduced returns labor

Reduced inventory (safety stock)

Reduction in write-offs due to returns/unsale-ables

Improved promotional planning and execution

Improved shrink management

Improved on shelf availability

Reduced Counterfeiting

Reduced Diversion

Increase Operating

Income

Increase Capital

Efficiency

Increase Revenue

Increase Shareholder

Value

Reduce Operating Costs

Reduce Working Capital

Increase Market Share

Increase Volume

Benefits – Vary Significantly across Product Categories

Manufacturer Benefits Overview

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

All benefits are Averages, as % of total 10-year NPV; benefits varied significantly by company

Other

DC labor

Credits/claims

Inventory reduction

Out of stock

Grocery - food

Grocery – non-food

Grocery – frozen

DSD – CSD, snacks

HBC/OTC

Note: Percentages are averages and % of total over a 10-year horizonSource: IBM and A.T. Kearney business case studies

Legend

7.1

10.2

12.0

15.6

6.6

6.8

7.0

7.7

9.816.0

0 5 10 15 20

Toilet Tissue

Feminine Care

Diapers

Laundry Detergent

Hair Care

Average High

Average OOS Rate for Selected DC-Based Categories

11.2

11.3

20.6

14.2

13.9

10.5

24.7

3.2

5

6

6

6.1

10.5

9.7

0 5 10 15 20 25 30

Milk

Beer

Cookies & Crackers

Salty Snacks

Soft Drinks

Frozen Pizza

Prepackaged Bread

All Promoted

Average OOS Rate for Selected DSD-Based Categories

Out-of Stocks – Still a Challenge for DC & DSD Based Product Categories

Source: Retail Out-of-Stocks: A Worldwide Examination of Extent, Causes and Consumer Responses; Full-Shelf Satisfaction – Reducing Out-Of-Stocks In the Grocery Channel: An In-Depth Look at DSD Categories

• Avg. Overall OOS Rate = ~7.9%

• Avg. DSD OOS Rate = ~6.8%

Company Analysis Example

Out of Stocks – Impact Varies by Category, Consumer Behavior & Trading Partner; Not all OOS Lead to Lost Sales

* - Excluded from analysis although industry research indicates incremental loss in revenue to both manufacturer and retailer due to switching to smaller or cheaper substitutes

Average Consumer Response to OOS Situation

Average net lost sales due to OOS

● Overall CPG Basket = 2.5%

● DSD-Based Categories = 2.1%

Retailer Impact (43%)

Manufacturer Impact (31%)

Source: Retail Out-of-Stocks: A Worldwide Examination of Extent, Causes and Consumer Responses; Full-Shelf Satisfaction – Reducing Out-Of-Stocks In the Grocery Channel: An In-Depth Look at DSD Categories

100%

17%

32%

11%

20%

20%

Total BoughtLater -SameStore

Bought atAnotherStore

Did notBuy

SubstituteotherBrand

SubstitutewithinBrand*

Company Analysis Example

Out-of Stocks – RFID has the Potential to Help Improve Store Level Execution and Upstream Efficiencies

The majority of anticipated benefits from the reduction of out of stocks in a DC environment is predicated on enhanced retail store execution

Source: Retail Out-of-Stocks: A Worldwide Examination of Extent, Causes and Consumer Responses; IBM Business Consulting Services analysis

Primary Area of Benefit

OOS at Retail Shelf

(average 8%)

Impact to manufacturer and retailer will vary based upon brand loyalty of

the product

Primary level of impact:

- Case level impact

- Item level impact

Upstream Issues

(5-30%)

Data Accuracy

Retailer DC Execution

Retail Store Issues

(70-95%)

Receiving Accuracy

Backroom Visibility

Replen. from Backroom

Planogram Comp.

Cycle Count Physical Inv.

POS Accuracy

Replen. Algorithms

Mfg. DC Execution

DC-Based Example

Product Availability- Forecasting

HighLow

Key:

Most of the Benefits will Require Coordination with Trading Partners

MediumReduced DC/Plant Labor

MediumReduced Credit/Claims

HighImproved Promotional Planning and Execution

MediumReduced Diversion

LowReduced DC Returns Labor

HighImproved Inventory Management

HighReduced Out of Stocks

Reliance on Trading Partners

Relative Value Potential

Selected Benefit Categories

Source: IBM Business Consulting Services

DC Supply Chain Cost Breakdown

Tags

Maintenence

SoftwareIntegration

Infrastructure

Readers

Other

DSD Supply Chain Cost Breakdown

Readers

Infrastructure

Software Integration

MaintenanceTags

Other

DC Supply Chain Costs DSD Supply Chain Costs

Higher Percentage

All costs are averages, and are expressed as % of total cost based on a 10-year NPV horizon

~25% higher in total costs due to

number of facilities

Costs – Vary by distribution method (DC vs. DSD),

with tag costs, infrastructure/integration as key drivers

0.3% to 29.9%10.3%Other

49.6% to 88.9%66.5%Tags

2.8% to 17.6%9.1%Maintenance

0.6% to 5.4%2.6%Software Integration

2.2% to 10.6%6.0%Infrastructure

1.1% to 10.6%5.5%Readers

RangeAverageCost Category

6.9% to 28.1%17.6%Other

28.1% to 50.8%39.5%Tags

12.3% to 14.3%13.3%Maintenance

4.4% to 5.7%5.1%Software

Integration

9.9% to 12.0%11.0%Infrastructure

9.9% to 17.4%13.7%Readers

RangeAverageCost Category

“Other” Cost Category

• Corporate Overhead– Extra Labor required to manage and administer EPC/RFID

related infrastructure and data

• Incremental Short Term Costs– Carrying Dual Inventory– Additional Warehouse costs– Labor expenses related to tagging subset of pallets and

cases

Business Case Results Vary by Category

NPV

++

0

--

Grocery –dry goods -food

Grocery –dry goods –non-food

Grocery –frozen, refrigerated

DSD – CSD, snacks

HBC/OTC

$.25 tag cost$.20 tag cost$.15 tag cost$.10 tag cost$.05 tag cost$.02 tag cost$.00 tag cost($.05) tag cost

Analysis of Manufacturer Business Cases (Pallet and Case Level Tagging) - Range of NPV Results by Product Category Using Constant Tag Costs

Business cases show positive NPV if tag prices are $0.05 – $0.10

Business cases indicate that $0.00 tags do not generate a positive NPV for all

Tag costs

Even if we double the projected out of stock benefit, we do not achieve a positive NPV for all categories

Out-of-stock +100%NPV

++

0

--

Grocery –dry goods -food

Grocery –dry goods –non-food

Grocery –frozen, refrigerated

DSD – soft drinks

HBC/OTC

Source: Normalized IBM and ATK business case studies, based on 10-year horizon

$.25

$.15

$.05

Tag costs

Overview of Study Findings

• Benefit and cost estimates vary significantly by company and product category -these differences should be considered in any roll-out plan

• Trading partners must be capable of sharing “clean” data, via GDS, to gain maximum benefits from EPC

• Manufacturers’ business cases are heavily contingent upon retailers improving operations (and sharing new data)

• While the vision for EPC/RFID is compelling, the economics for manufacturers are currently tempering adoption – Even optimistic estimates for tag prices are insufficient to

generate a positive returns for many manufacturers – Need to find new ways to increase the value potential, build

more confidence in benefits and decrease overall costs

Benefits appear to differ by category attributes(Manufacturer View)

• High value, low volume• Significant out-of-stocks,

shrinkage, and unsaleables• High level of counterfeit, illegal

diverting• Significant use of mixed pallets

and eaches• Low use of bar code technology

in supply chain

• Examples : Pharma, OTC, consumer electronics, high fashion, cosmetics, some HBC and non-food

• Low value, high volume• Limited shrinkage• Lower levels or value of

out-of-stocks • Low risk of counterfeit, illegal

diverting• Significant use of full pallet, full

truck ordering• Sophisticated use of bar code

technology, WMS, etc.

• Example: Dry foods, perishables, beverages, frozen goods, DSD distribution

Recommended Industry Actions

Understand Category Dynamics

Rollout categories most able to gain return on EPC investment in the short term

Define process changes and demonstrate benefits

Collaborate with trading partners to develop plan for solving business issues Using EPC and process changes

Share data freely, openly and in a standardized way

All business cases assumed complete, free access to product movement dataEPC network cannot work with use of data

Managing the Transition 2005 – 2008

• Complete data synchronization efforts. Without correct data – limited benefits will be realized

• Understand the benefit drivers, especially those requiring collaboration

• Adapt business processes to take advantage of new supply chain data

• Expect to manage parallel systems for several years. Ensure management systems are agile

• Leverage the invested infrastructure – encourage broader retail involvement and consider other EPC applications

• Plan as an investment

Questions?

• Pam StegemanVice President, Supply Chain and Technologypstegeman@gmabrands.com

• Sean CampbellPartner, IBM Business Consulting Servicessean.campbell@us.ibm.com