Forecast Pro Multiple Level

Considerations for Effectively Forecasting a Product Hierarchy

Presented byEric StellwagenVice President & CofounderBusiness Forecast Systems, [email protected]

Business Forecast Systems, Inc.68 Leonard StreetBelmont, MA 02478 USA(617) 484-5050www.forecastpro.com

© 2010, Business Forecast Systems, Inc. www.forecastpro.com

Eric Stellwagen

Vice President, CEO & Cofounder ofBusiness Forecast Systems, Inc.

Coauthor of Forecast Pro product line.

Over 25 years in forecasting.

Currently serving on the board of directors of the International Institute of Forecasters and on the practitioner advisory board of Foresight: The International Journal of Applied Forecasting.


What We’ll Cover

Introductions

Basic Concepts

Constructing the Hierarchy

Examples

Q&A

Reconciliation Techniques

Summary


A Sample Hierarchy

Total Sales

Brand A

Retail

Cans

6-Pack 12-Pack

Bottles

Commercial

Brand B Brand C

Corporations typically deal with multiple levels of aggregation and require consistent forecasts at all levels.

Item Level

Group Levels


What Are the Forecasts Used For?

Item-level forecasts

Drive production, purchasing and inventory control

Short horizons are important

Intermediate-level forecasts

Drive marketing and revenue planning

Medium horizons are important

Upper-level forecasts

Guide “big picture” decision making

Medium to long horizons are important


Should You Strive for One-Number Forecasts?

Depends on the environment.

The larger the company, the harder this is to achieve.

Communication between the different functional groups is very important. This is a primary goal of an S&OP process.


A Very Simple Hierarchy

Total Cans

6-Pack 12-Pack


Common Reconciliation Techniques

Bottom-Up

Create model-based forecasts at the lower level. Construct upper-level forecasts by summing nested lower-level forecasts.

Top-Down

First, create a model-based forecast at the top level by forecasting the aggregated history. Then, create model-based forecasts at the lower levels. Finally, apply proportionality factors to lower-level forecasts so that the forecasts sum to the top-level forecast.

Proportional Allocation

Disaggregate higher-level forecasts by applying proportionality factors. This method would be appropriate when proportions are constant and known.


Reconciliation Techniques Example

Total Cans

6-Pack 12-Pack

In a hierarchy with 3 or more levels, combinations of top-down and bottom-up approaches can be applied (i.e., middle-out).

Model-Based

6-Pack 7012-Pack 30Total Cans 120

Proportions(50-50)6060120

Top-Down

8436120

Bottom-Up

7030100


Choosing a Reconciliation Approach

Group-level data is higher volume and often exhibits more structure than lower-level data—this argues for top-down.

If two items exhibit distinctly different behaviors, then a single model is unlikely to perform well—this argues for bottom-up.

If relationships between levels are not changing in time, then forecasting based on history does not add value—this argues for proportional allocation.


Hierarchical Data

Total Sales

Brand A

Retail

Cans

6-Pack 12-Pack

Bottles

Commercial

½ Kegs Full Kegs

Brand B Brand C


Choosing a Reconciliation Approach

Start by determining if proportional allocation should be used.

Try to think like your consumers – how do they view the items?

At times, lack of structure at the lower levels may force you to use top-down approaches.

Measuring empirical performance is always an option.

Most multiple-level forecasts should combine top-down and bottom-up approaches.


Setting up the Hierarchy

The units of measure need to be comparable.

The hierarchy should be as simple as possible.

Discontinued items may need to be included to ensure group totals are correct.

The structure of the hierarchy should be selected for forecasting, NOT for reporting.


Two Alternative Hierarchies

Total

State 1

Business

Main Other

Residential

Basic Addline Other

Public

Coin Access

State 2 Etc.

Total

Business

Main

State 1 State 2 Etc.

Other

State 1 State 2 Etc.

Residential Public


Example


Summary

Many organizations forecast hierarchical data and require forecasts that are consistent across levels.

Defining the hierarchy to facilitate accurate forecasting is important.

Selection of an appropriate reconciliation strategy is also important and directly impacts forecast accuracy.


Business Forecasting Seminar

September 20-22, 2010 – Boston, USAOctober 18-20, 2010 – London, UK

This three-day comprehensive course covers techniques, uses real-world examples and includes computer workshops using your data.Register at www.forecastpro.com


Forecast Pro

Examples from today’s Webinar used Forecast Pro.

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Questions?


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Forecast Pro Multiple Level