1. Copyright © IRI, 2005. Confidential and proprietary. Consumer-driven Enterprise Management Solutions Consumer-driven Sales Forecasting Solution Overview February, 2005

2. Copyright © IRI, 2005. Confidential and proprietary. What is a Consumer Driven Sales Forecast? Definition:  The strategy and process of aligning an entire enterprise to current and expected consumer actions

3. Copyright © IRI, 2005. Confidential and proprietary. What is a Consumer Driven Sales Forecast? AMR Says:  “The Bottom Line: Consumer products manufacturers must centrally manage all demand signal data, including POS, to create a Demand-Driven Supply Network (DDSN) that improves demand visibility to reduce stockouts by more than half and increase Perfect Order performance”  Reduce stockouts by 50%+  70% faster time to market  Increase perfect order performance by 17% RESULTS

4. Copyright © IRI, 2005. Confidential and proprietary. What is a Consumer Driven Sales Forecast? P&G Says:  “At Procter & Gamble, we're working toward a vision we call "the consumer-driven supply network." That differs from our supply-chain strategy of the past in two significant ways: It puts the consumer first, and it envisions a network rather than a chain. The investment isn't trivial, but neither are the returns ”  Reduced fulfillment times to the retail DC from 38 days to 16 days  In 2004 alone, P&G Inventory Turns improved by 11% RESULTS

5. Copyright © IRI, 2005. Confidential and proprietary.  We applied just these two benefits (AMR’s markdown improvement and P&G’s inventory improvement) to an average composite $2BB US CPG manufacturer  These benefits alone yielded a $165MM Net Present Value or a 5% increase in the value of the company Notes: - Composite $2BB CPG manufacturer financials; Assumes GMA estimate of 7.4% average of stock - 50% reduction in OOS; 11% reduction in inventory $3.51BB $15 MM $150 MM $3.68BB Why Should You Care? MARKET CAP INCREASE 5% Growth in Market Cap!

6. Copyright © IRI, 2005. Confidential and proprietary. What Many CPG Manufacturers Face Today– Non-integrated Planning  Account teams generate customer POS plans to meet financial targets, primarily revenue, with little margin consideration  Supply Chain generates a demand plan, based on shipments, that does not take into account the current year’s retail price and promotion plans  Supply Chain produces and deploys to this forecast TYPICAL CPG PLANNING CYCLE Customer POS Forecast DRIVES Production & Financial Plans Expected Shipment Demand  Sales plans that don’t maximize margin  Operations plans that are not tied to customer activity  Financial plans that try to guess the % expected demand that will be met or actualized RESULTS

7. Copyright © IRI, 2005. Confidential and proprietary. Closing the loop to Consumer-driven planning  Account teams generate price and promotion plans to meet financial targets with margin consideration  Supply Chain produces a demand plan that is driven by current price and promotional plans  Supply Chain tests the feasibility of the plan and suggests changes based on constraints  Account teams iterate promotional and pricing plans to align to the feasibility of the plan  Supply Chain produces to the sales forecast that it helped to influence CONSUMER-DRIVEN PLANNING CYCLE Customer POS Forecast DRIVES Production & Financial Plans Expected Shipment Demand

8. Copyright © IRI, 2005. Confidential and proprietary. Getting started on a road to closed loop planning: Consumer-driven Sales Forecasting NEXT GENERATION SALES FORECASTING REQUIREMENTS Capture a true demand signal Few organizations systematically drive their business based on the demand signal, instead relying on shipments; IRI has unique access and understanding of POS demand data. 1 Continuously monitor performance Most CPG sales forecasting processes are generated monthly – or less frequently. This allows for weekly market impacts to build up and catch planners by surprise. IRI can support a weekly monitoring process if required and will support daily monitoring over time. 4 Use consistent methodologies & discipline The use of a single forecast tool and method, as well as the use of causal factors give your team the ability to have a consistent forecast across brands, channels and territories. IRI embeds a structured and consistent approach that eliminates variability among accounts. 5 Collaborate for input and output Systematic collaboration across functional groups to gain input on the forecast is a key step of a consensus forecast. IRI’s Web-based front end enables multi- functional collaboration. 6 Use the best available causal model The use of causal factors is critical to systematically include the impact of trade promotions and pricing. IRI delivers an efficient and proprietary causal model capability based on our 20 years of experience. 2 Forecast at the granular levels Forecasts generated within the organization must be done at a granular-enough level of the business to translate easily. IRI’s Analytic Server has the ability to support interactive SKU and Account Level forecast simulations. 3

9. Copyright © IRI, 2005. Confidential and proprietary. 1. Sales Forecasting Challenge: Beyond sell-in data  Operations and Supply Chain Planning has traditionally focused on “shipments out” or “sell in” as the primary demand signal  “Sell in” –based planning systems typically fail in their ability to integrate recent shifts in retail POS activity which have a significant effect on business operations:  promotional activities that temporarily increase sales  forward buying practices that front-load sales and reduce future sales  competitive pricing that can decrease sales  The result is a significant disconnect between the sell-in forecast and what is truly going on at the account Traditional Demand Planning Focus Demand signal: Shipments Out/Sell-in PROCUREMENTOPERATIONSCONSUMERS SALES MARKETING Supply Sources Production Distribution Centers Distributor Retail Distribution Retail Sales IRI POS/ Retailer POS

10. Copyright © IRI, 2005. Confidential and proprietary. 1. Consumer-driven Sales Forecasting Response: POS-driven supply chain Benefits:  More rapid planning for consumer trends  Forecast built on current promotional plan  More efficient production planning  More accurate financial planning Consumer-driven Demand Planning Focus Demand signal: Retail Consumption PROCUREMENTOPERATIONSCONSUMERS SALES MARKETING Supply Sources Production Distribution Centers Distributor Retail Distribution Retail Sales IRI POS/ Retailer POS

11. Copyright © IRI, 2005. Confidential and proprietary. BASE DEMAND  More forecastable pattern  Incorporates trend, seasonality but excludes promotional effects INCREMENTAL DEMAND  Includes only estimated effects of promotional volumes only  Estimate using events calendar 2. Use the best available causal model Causal modeling allows manufacturers and retailers to separate the base demand from incremental demand, thereby enabling a more accurate forecast that includes promotional activities.  Difficult to forecast  High peaks  Little statistical pattern TOTAL DEMAND

12. Copyright © IRI, 2005. Confidential and proprietary. 2. Use the best available causal model By utilizing causal modeling and separating base volume from promoted/incremental volume, a Midwestern Retailer was able to generate a more accurate forecast for its gelatin products.

13. Copyright © IRI, 2005. Confidential and proprietary. 3. Forecast at the granular level By forecasting at a relatively granular level, other functions that use or interact with the consumption forecast can easily translate consumption into a forecast that meets their implied requirements, thereby increasing the probability of reaching a “one number” forecast. Consumption Forecast: Recommendation GEOGRAPHY: Market TIME: Weekly PRODUCT: Promoted Product Group ACCOUNT: Key Account Financial GEOGRAPHY: Total U.S. TIME: Quarterly PRODUCT: Category ACCOUNT: All Sales/Marketing GEOGRAPHY: Total U.S. TIME: Monthly PRODUCT: Brand or PPG ACCOUNT: Key Account Operations GEOGRAPHY: Region TIME: Weekly/Daily PRODUCT: SKU ACCOUNT: All AGGREGATION AGGREGATION + ALLOCATION TO SKU

14. Copyright © IRI, 2005. Confidential and proprietary. 4. Continuously monitor performance Best practices in Performance Management dictate that continuously monitoring of forecast accuracy and actual results at all levels of the organization creates the greatest odds of meeting and exceeding product, group and division targets. EXECUTIVE ANALYST

15. Copyright © IRI, 2005. Confidential and proprietary. 5. Use Consistent Methodologies Implementing a solution that incorporates causal modeling, due to analysis and other standard methods and approaches, lowers the risk of differences in results.  Some deeply experienced sales team members can intuit the impact of promotional activities on consumption  Other team members, perhaps due to a recent transfer or rotation in brand or account have less imbedded intuition on the impact of promotions  The use of causal modeling and due to’s eliminates the uncertainty and levels the playing field for a more standard approach to the forecast

16. Copyright © IRI, 2005. Confidential and proprietary. 6. Collaborate for inputs and ouputs Putting together a systematic plan for gathering input to the forecast is a critical step in the achievement of a one-number forecast. Just as important, is planning for the outputs of the forecast in a way that encourages the entire business to utilize the consumption forecast. Processes Impacted  Quarterly/annual business plan  Account planning  Brand planning  Supply Chain planning Processes Impacted  Quarterly/annual business plan  Account planning  Brand planning  Supply Chain planning Consumption Driven Sales Forecast SalesFinanceExecs Operations Marketing

17. Copyright © IRI, 2005. Confidential and proprietary. 1.Determine causal drivers of sales (every 6 -12 months) Sales Forecasting Solution Capabilities 2. Analyze the forecast results and causes (weekly/monthly) 4.Translate the forecast into functional views (weekly/monthly) 3.Simulate and execute the forecast (weekly/monthly)

18. Copyright © IRI, 2005. Confidential and proprietary. Outstanding Results 40%+ for DC/Item for one customer 36% for RMA/PPG for another customer IRI FORECAST ERROR (MAPE)OTHER’S FORECAST ERROR Regional grocery (regional/SKU is often the best metric for supply chain)  9.3% across Region-SKU-weeks  7.9% across Region-PPG-weeks  7.0% across Region-SKU-quads  5.8% across Region-PPG-quads RMA (RMA/PPG is often the best metric for sales)  24.8% across RMA-UPC-weeks  22.3% across RMA-PPG-weeks  21.1% across RMA-UPC-quads  19.0% across RMA-PPG-quads

19. Copyright © IRI, 2005. Confidential and proprietary. Existing Forecasting Customers Dow Jones (Wall Street Journal and Barron’s) is implementing the integration capabilities and analytic engine of the BPM solution to drive the monthly circulation forecasting of the entire U.S. business. The forecast is based on the weekly consumer transaction data, from both direct sales and channel sales and allows for collaboration and input from the marketing managers driving various monthly promotional campaigns. The platform integrates data from multiple legacy systems and provides forecasting analysts with the ability to run rapid forecasting “what if” scenarios – calculating a 12 month forecast for the entire business in less than 5 minutes, allowing for an interactive sales forecasting process. Polaroid is leveraging the flexibility and scalability of the BPM solution to provide a consistent "system of record" for demand and supply planning across the entire organization. The weekly sales forecast generated by the solution is passed to SAP each Friday night, driving the production and MRP processes. The solution is driving down planning cycle times and improving the effectiveness and efficiencies of the planning teams, thus enabling better and faster decision making. Inventory, customer service, forecasting accuracy, and asset utilization are all metrics that are being improved.