Marketing Forecasting at Post Foods division of Ralcorp Holding

Fostering Demand Planning and Forecasting for Nearly 30 Years!

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Marketing Forecast

At Post Foods,

Division of Ralcorp Holdings.

http://www.ralcorp.com/




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Main Topic

The topic of this presentation is forecasting

fast moving consumer goods from a

Marketing point of view.

Examine the business drivers and spending

that impact a brand performance and how

to quantify them into a forecast.


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Agenda• Forecasting at Post Foods

• How We Build the Forecast

• S&OP Consensus Process

• Marketing Forecast Tools– Inputs

• The Drivers– Driver Details

• External Factors

• Forecast Accuracy Measurement & Actions

• Measures of Success

• Challenges and Solutions

• Next Steps and Questions


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Post Foods• Founded by C. W. Post in 1895

• Was part of General Foods and then Kraft Foods until 2008 when Post was acquired by Ralcorp Holdings

• Headquartered in Parsippany, NJ

• Over $1 Billion gross revenue - ~40% of Ralcorp net revenue

• #3 Ready to Eat Cereal, grown by 125% over the last 6 years

• 4 Plants plus several co-packers and 6 warehouses

• 103 SKU’s

• ~8 primary brands

• Customers include major grocery stores, mass merchandisers, club, drug stores and Dollar stores

• David Zatz – Marketing Forecast Planner


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Forecasting at Post Foods

• Scope

• Consumer goods – Ready To Eat Cereal; US Domestic only

• Short term and medium term – current quarter through next fiscal year – this is Tactical S&OP, not Strategic

• Longer range forecasting is done less frequently for capacity analysis and is outside the scope of this presentation

• Focused on Brand but calculated at SKU

• Results drive Production Planning, Deployment and Financial forecast

• Methodology

• Monthly Cycle and monthly buckets

• Strive to arrive at “one number”

• Avoid changing the forecast for next month


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How We Build the Forecast

• Marketing drivers forecast impact vs. year ago by brand

• Sales force bottom up forecast used for the short term one to four month time period, built mostly by customer and geography

• Statistical forecasting at the SKU level used for scheduling and deployment

• All the voices come together in a monthly S&OP process to arrive at one number to drive the business and report up to corporate


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S&OP Consensus Process

Different

•Drivers

•Goals

•Units of

measure

One Number


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S&OP Consensus Process (cont.)

• Risks and Opportunities are discussed but not included in the forecast – our version of a “range” forecast

• Gaps in our numbers are used to alert management to issues which may drive policy decisions to guide us to one number

• This method works for Post Foods and other fast moving consumer goods brands because a large portion of customer sales are driven by trade promotion, and consumer consumption is driven by advertising and promotion. The Marketing Manager is the general manager of the brand. Sales and Marketing report separately to the President.


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Marketing Forecast ToolsThe Marketing Forecast uses several techniques to arrive at the numbers presented during the S&OP meetings.

•Expert opinion and judgmental approach; reliance on the expertise of others

Nielsen syndicated data

Consumer Insights – Marketing Mix Analysis

Sales and Customer behavior

•Time series and trend projections using market changes to predict turning points

•Planned Marketing programs quantified into impact on expected customer shipments

•The use of Nielsen market data to compare drivers to year ago statistics


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Inputs

• Monthly shipment history by SKU

– Customer level history is used to examine

outlier data

• Nielsen syndicated consumption data

• Other Marketing and consumer insights

analysis for each brand


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The Drivers• Equity

– Advertising

– Consumer Promotion

– Base Velocity

• Innovation– New Products

• Price / Merchandising– Merchandising

– Base Price

– Distribution

• Other Channels– Wal-Mart, Club, Dollar

• Other– Trade Inventory

These use a combination of Art and Science


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The Drivers (cont.)

FY 11 FY 11 FY 11 FY 11 FY 11 FY 11 FY 11 FY 11 FY 11 FY 11

10/26/2010 Oct Nov Dec Jan Feb Mar Apr May Jun Jul

2010 Actual 15.6$ 14.5$ 14.6$ 15.0$ 16.7$ 16.3$ 16.1$ 14.3$ 17.6$ 14.0$

2011 $ Prior Call 15.3$ 13.5$ 14.2$ 16.9$ 16.9$ 18.3$ 17.2$ 14.8$ 16.9$ 16.9$

2011 Curr Call 12.3$ 10.7$ 11.3$ 16.9$ 16.9$ 18.4$ 17.5$ 15.0$ 16.9$ 16.9$

$Chg vs. Prior Call (3.0)$ (2.8)$ (2.8)$ -$ -$ 0.1$ 0.3$ 0.2$ (0.0)$ (0.0)$

Bridge Items: -$ -$ -$ -$ -$ -$ -$

WM Growth (2.7)$ (3.0)$ (3.1)$ -$ -$ -$ -$ -$ -$ -$

Club (0.1)$ (1.0)$ 0.4$ 0.1$ 0.1$ 0.4$ 0.1$ 0.1$ 0.1$ 0.0$

Advertising (0.9)$ (0.6)$ (0.1)$ 0.3$ (0.1)$ 2.1$ (0.2)$ (1.3)$ (0.4)$ 1.2$

Merchandising (1.0)$ 0.1$ 0.1$ (1.3)$ (1.7)$ (0.2)$ 0.9$ 0.9$ (0.7)$ 0.8$

New Products (0.1)$ (0.2)$ 0.1$ 1.0$ 0.7$ 0.8$ 1.0$ 1.0$ 0.9$ 0.9$

Consumer Promotions -$ -$ -$ -$ -$ -$ -$ -$ -$ -$

Base Velocity 0.3$ 0.3$ 0.3$ 0.1$ 0.1$ 0.1$ 0.1$ 0.1$ 0.1$ 0.1$

Base Price -$ -$ -$ -$ -$ -$ -$ -$ -$ -$

Distribution (0.1)$ (0.2)$ (0.2)$ (0.1)$ (0.1)$ (0.1)$ (0.1)$ (0.1)$ (0.1)$ (0.1)$

Inventory 1.4$ 0.3$ (0.1)$ 1.0$ (0.4)$ (0.6)$ 0.0$ (0.3)$ 0.4$ (0.4)$

Other (0.2)$ 0.5$ (0.7)$ 0.7$ 1.6$ (0.2)$ (0.3)$ 0.4$ (1.0)$ 0.3$

Sum of the Drivers (3.2)$ (3.8)$ (3.3)$ 1.8$ 0.2$ 2.1$ 1.4$ 0.8$ (0.8)$ 2.9$

2010 Actuals + Drivers 12.3$ 10.7$ 11.3$ 16.9$ 16.9$ 18.4$ 17.5$ 15.0$ 16.9$ 16.9$


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Driver Details

Equity

Advertising and Consumer Promotions are

calculated based on planned spending and packages

sold on consumer promotion. We’re developing a tool

to break that down to flavors and SKU’s.

Innovation

For New Products, we include the first 12 months of

shipments as new products volume and multiply that

by an incrementality factor. Early ships are a

challenge for new products.


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Driver Details (cont.)These drivers are calculated for past months

using Nielsen syndicated data:

Merchandising

Base Velocity

Base Price

Distribution

For Trade Inventory, we compare monthly

customer shipments to a year ago and monthly

consumer consumption to a year ago

Other channels (Wal-Mart, Club, Dollar) are fed

directly from mangers of those businesses.


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External Factors

• We use factors to control the results – Incrementality

– Elasticity

– Velocity Weight Factor

– Competitive Activity

• As the marketplace changes, we use these factors to adjust the drivers

• For example, over the last two years we’ve seen a much greater sensitivity to price changes so we can adjust the elasticity to reflect this market change.


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Forecast Accuracy Measurement & Action

• Every month we measure forecast accuracy at the brand,

top customers and SKU levels and use that to make

adjustments going forward.

• For example, will the missed forecast last month result in

something that will continue for future months or was it a

one-time event that will result in the opposite affect in the

short term?

• When the absolute error is greater than the threshold, both

customer shipments and consumer consumption are

examined closely


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Measures of Success

• Spend our Marketing and Trade Promotion dollars

to maximize returns and drive our business

forward as planned – making revenue and profit

targets

• Maintain inventory levels and customer fill rate

targets while minimizing production disruptions

and costs

• Anticipate the impact of business decisions

• Allow Marketers to focus on Marketing


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Challenges & Solutions

• Forecasting new categories

• Deviating from the focus of forecast

accuracy for other business needs

like inflating the forecast where

capacity is tight

• Getting timely and accurate input

from all systems and people

• Converting the forecast into different

units of measure, levels of product

aggregation, geographies, and

more…

• Use similar products and Bases

• Focus on one number and emphasize

best guess; adjust inventory policy for

tight capacity; better utilize risks and

opportunities

• Develop and adhere to a firm schedule;

get senior management support

• Define the standard conversion rates,

maintain and use them for reporting

and integrating results


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Challenges & Solutions (cont.)

• Nielsen data is split into months of

4-4-5 weeks but shipments and

forecasts are on calendar months

• Determining trade inventory levels

• Expanding complexity into other

grocery categories (different

manufacturing, lead times, etc.)

• Profitability by brand and SKU is

calculated and used to drive

decisions but profitability by

customer is unknown

• Where necessary spread the monthly

shipments into a 4-4-5 pattern for

comparison to consumption

• Combine industry standards with

estimates and past patterns

• Fold other categories into existing

systems

• Develop the calculation for customer

profitability – partner more closely

with customers


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Next Steps

• Deeper analysis for Risks & Opportunities

followed by appropriate action

• Develop Sales tools and expand their role in the

S&OP process

• Expand SKU level bottom up calculation in the

marketing forecast models to include

– Lift

– Distribution changes

– Other channels

– Advertising campaigns and promotional events


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Questions

[email protected]

Marketing Forecasting at Post Foods division of Ralcorp Holding

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