Fostering Demand Planning and Forecasting for Nearly 30 Years!
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Marketing Forecast
At Post Foods,
Division of Ralcorp Holdings.
Fostering Demand Planning and Forecasting for Nearly 30 Years!
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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.
Fostering Demand Planning and Forecasting for Nearly 30 Years!
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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
Fostering Demand Planning and Forecasting for Nearly 30 Years!
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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
Fostering Demand Planning and Forecasting for Nearly 30 Years!
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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
Fostering Demand Planning and Forecasting for Nearly 30 Years!
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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
Fostering Demand Planning and Forecasting for Nearly 30 Years!
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S&OP Consensus Process
Different
•Drivers
•Goals
•Units of
measure
One Number
Fostering Demand Planning and Forecasting for Nearly 30 Years!
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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.
Fostering Demand Planning and Forecasting for Nearly 30 Years!
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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
Fostering Demand Planning and Forecasting for Nearly 30 Years!
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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
Fostering Demand Planning and Forecasting for Nearly 30 Years!
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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
Fostering Demand Planning and Forecasting for Nearly 30 Years!
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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$
Fostering Demand Planning and Forecasting for Nearly 30 Years!
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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.
Fostering Demand Planning and Forecasting for Nearly 30 Years!
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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.
Fostering Demand Planning and Forecasting for Nearly 30 Years!
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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.
Fostering Demand Planning and Forecasting for Nearly 30 Years!
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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
Fostering Demand Planning and Forecasting for Nearly 30 Years!
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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
Fostering Demand Planning and Forecasting for Nearly 30 Years!
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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
Fostering Demand Planning and Forecasting for Nearly 30 Years!
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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
Fostering Demand Planning and Forecasting for Nearly 30 Years!
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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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