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TRANSCRIPT
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
EDIEDI
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
ust
ome
rs
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 [email protected]
• Sean CampbellPartner, IBM Business Consulting [email protected]