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ISLD Forum April 11, 2005

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CPG Industry. Pam Stegemen - VP Supply Chain and Technology ... Apparel. Data Included. No Data Included. Cereal, Pasta. Detergent, Paper Products ... – PowerPoint PPT presentation

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Title: ISLD Forum April 11, 2005


1
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

2
Workshop Objectives
  • Discuss rationale for conducting the study
  • Review key findings and implications
  • Discuss recommended action plans

Answer any open questions about the study
3
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
  • Dont 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

EDI
GDS
4
The Goal Better supply and demand visibility
Better Product Visibility
Requires
Technical
Process
People
  • 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

5
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
6
Scope of Analysis
  • Manufacturer Companies
  • 24 NA business cases - 90 companies with sales
    gt2 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 Matls Pkg. Suppliers
Manufacturer
Retailer
Door to Floor
Mfr. DC
Retailer RDC
Store Back Room
Store Shelf
Factory
Factory
Key
Included
Excluded
7
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 -gt 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

8
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

9
Category Definitions Data Points Available
Dry Goods (food)
Dry Goods (non-food)
Cereal, Pasta
Health, Beauty Cosmetics
Frozen / Chilled
Detergent, Paper Products
Carbonated Drinks Snacks
Fresh Produce
Pharmacy
Shampoo, Lotion, Cold Medicine
Cigarettes Tobacco
Alcoholic Beverages
Frozen Dinners, Ice Cream, Juice
News Stationery
Toys
Consumer Electronics
Soda, Potato Chips, Pretzels
Music, Video Games
Apparel
Data Included
No Data Included
10
Benefits Many Benefit Opportunities, but Four
Consistently Ranked as Primary Areas
  • Reduced retailer claims (overages, shortages)
  • Reduced DC/Plant labor
  • Reduced returns labor

Increase Operating Income
Reduce Operating Costs
Increase Capital Efficiency
Reduce Working Capital
  • Reduced inventory (safety stock)
  • Reduction in write-offs due to returns/unsale-able
    s

Increase ShareholderValue
Increase Market Share
  • Improved on shelf availability
  • Reduced Counterfeiting
  • Reduced Diversion

Increase Revenue
  • Improved promotional planning and execution
  • Improved shrink management

Increase Volume
11
Benefits Vary Significantly across Product
Categories
Manufacturer Benefits Overview
Legend
Other DC labor Credits/claims Inventory
reduction Out of stock
DSD CSD, snacks
Grocery - food
Grocery non-food
Grocery frozen
HBC/OTC
All benefits are Averages, as of total 10-year
NPV benefits varied significantly by company
Note Percentages are averages and of total
over a 10-year horizon Source IBM and A.T.
Kearney business case studies
12
Out-of Stocks Still a Challenge for DC DSD
Based Product Categories
Company Analysis Example
Average OOS Rate for Selected DC-Based Categories
  • Avg. Overall OOS Rate 7.9
  • Avg. DSD OOS Rate 6.8

Average OOS Rate for Selected DSD-Based
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
13
Out of Stocks Impact Varies by Category,
Consumer Behavior Trading Partner Not all OOS
Lead to Lost Sales
Company Analysis Example
Average Consumer Response to OOS Situation
Retailer Impact (43)
  • Average net lost sales due to OOS
  • Overall CPG Basket 2.5
  • DSD-Based Categories 2.1

Manufacturer Impact (31)
- Excluded from analysis although industry
research indicates incremental loss in revenue to
both manufacturer and retailer due to switching
to smaller or cheaper substitutes
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
14
Out-of Stocks RFID has the Potential to Help
Improve Store Level Execution and Upstream
Efficiencies
Impact to manufacturer and retailer will vary
based upon brand loyalty of the product
DC-Based Example
OOS at Retail Shelf (average 8)
Upstream Issues (5-30)
Retail Store Issues (70-95)
Primary Area of Benefit
Receiving Accuracy
Backroom Visibility
Replen. from Backroom
Data Accuracy
Product Availability- Forecasting
Planogram Comp.
Cycle Count
Physical Inv.
Retailer DC Execution
Mfg. DC Execution
POS Accuracy
Replen. Algorithms
Primary level of impact
- Case level impact
- Item level impact
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
15
Most of the Benefits will Require Coordination
with Trading Partners
Source IBM Business Consulting Services
16
Costs Vary by distribution method (DC vs. DSD),
with tag costs, infrastructure/integration as
key drivers
DC Supply Chain Costs
DSD Supply Chain Costs
Higher Percentage
25 higher in total costs due to number of
facilities
All costs are averages, and are expressed as of
total cost based on a 10-year NPV horizon
17
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

18
Business Case Results Vary by Category
Analysis of Manufacturer Business Cases (Pallet
and Case Level Tagging) - Range of NPV Results
by Product Category Using Constant Tag Costs
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
19
Even if we double the projected out of stock
benefit, we do not achieve a positive NPV for all
categories
Out-of-stock 100
Tag costs
.25
.15
.05
20
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

21
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 ofout-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

22
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 data EPC network
cannot work with use of data
23
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

24
Questions?
  • Pam StegemanVice President, Supply Chain and
    Technologypstegeman_at_gmabrands.com
  • Sean CampbellPartner, IBM Business Consulting
    Servicessean.campbell_at_us.ibm.com
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