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

Copyright © IRI, 2005. Confidential and proprietary.Consumer-driven Enterprise Management Solutions

Consumer-driven Sales Forecasting

Solution Overview

February, 2005

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



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



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


$0 $15 $149.73

$3,000

$3,100

$3,200

$3,300

$3,400

$3,500

$3,600

$3,700

$3,800

$3,900

$4,000

Beginning MarketValue

InventoryImprovement Impact

StockoutImprovement Impact

Ending Market Value

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!


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

CustomerPOS

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


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

CustomerPOS

Forecast

DRIVES

Production & Financial

Plans

Expected Shipment Demand


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


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

PROCUREMENT OPERATIONS CONSUMERSSALES MARKETING

SupplySources

ProductionDistribution

CentersDistributor

Retail Distribution

RetailSales IRI POS/

Retailer POS


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

PROCUREMENT OPERATIONS CONSUMERSSALES MARKETING

SupplySources

ProductionDistribution

CentersDistributor

Retail Distribution

RetailSales IRI POS/

Retailer POS


BASE DEMAND

More forecastable pattern Incorporates trend, seasonality but

excludes promotional effects

INCREMENTAL DEMAND

Includes only estimated effects ofpromotional 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


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.

0

500

1000

1500

2000

2500

3000

3500

1 11 21 31 41 51 61 71 81 91 101 111 121

Base Incremental

0

500

1000

1500

2000

2500

3000

3500

1 11 21 31 41 51 61 71 81 91 101 111 121

Actual Fit/ForecastFitted values Forecasts


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 AGGREGATION + ALLOCATION TO SKU


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.

Volume to Date

PPG: All April May JuneEast Actuals 10000 -

Forecast 10000 12000 10000Plan 10000 12000 10000

Central Actuals 11000 -Forecast 12000 12000 10000

Plan 12000 12000 10000West Actuals 14000 -

Forecast 14000 12000 10000Plan 14000 12000 10000

EXECUTIVE

ANALYST

Month to Date Analysis Absolute Percent Error

Month To Date Volume Month To Date %PPG 346 Actuals 3500 78% PPG APE Alert

Forecast 4500 100% 346 98 NoPlan 4500 100% 347 97 No

PPG 347 Actuals 2900 104% 348 88 YesForecast 2800 100% 349 96 NoPlan 2800 100% 350 95 No

PPG 348 Actuals 2600 93% 351 96 NoForecast 2800 100% 352 98 NoPlan 2800 100% 353 97 No


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


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

OperationsMarketing


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)


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


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.

Documents

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