A guide to demand forecasting within the grocery industry

September 2000

Background

• Collaboration between trading partners is rare

• Demand drivers are generally not known or understood

• Forecasts are often done only monthly

• Forecasts are often different for sales and operations

• Forecast performance is not measured routinely

Objectives

• An industry guide to demand forecasting

• Easy to use

• Applicable across a variety of trading environments:– manufacturers, retailers and wholesalers

– large and small enterprises

– all grocery categories

Process

Research- Local- Global

Nov1999

Dec Jan Feb Mar Apr2000

Case studies- Sanitarium- P&G / Franklins

Content development

Industry workshops

Project Team

• Paul Middleton - AFGC / Proctor & Gamble

• Daniel Kochanowicz - Woolworths

• Mark McMahon - Unilever

• Bob Boucher - Colgate Palmolive

• Gary Thomas - Parke-Davis Warner Lambert

• Peter Lord - Proctor & gamble

• Bill Barbour - Reckitt & Coleman

• Justin Golding - SC Johnson

Project Team

• Sally Menzies - Carter Holt Harvey

• Steve Newton - Davids

• Stephen Viles - CCA

• Michael LaRoche - PWC

• Justin Greig - PWC

• Simon Coates - Franklins

• Peter Ryrie - Kimberly-Clark

The guide

• Why should you use this guide?

• A framework for demand forecasting

• Improving the forecasting process

• Developing the organisational capability

• Acquiring the right information technology

• Building collaborative partnerships

• Getting started

Partnerships

ProcessesTechnology

People

Increasing benefitsIncreasing benefits

Inc

rea

sin

g b

en

efi

tsIn

cre

as

ing

be

ne

fits

Collaborative

Extended

Shared

Aligne

d

Inte

grat

edSkil

led

Spread sheet

Specialist solution

eBusiness

Basic

Causa

lBal

ance

d

The “levers of change”

Supplier benefits

Cu

sto

mer

ben

efit

s

Fundamental

AdvancedC

ollaborative

The maturity profile

Economic value

Dem

and

varia

bilit

y

H

L

C B A

Volatile: Sophisticated techniques; frequent reviews

Unimportant: Unsophisticated techniques; infrequent reviews

Stable: Less sophisticated techniques; less frequent reviews

Segmentation

Improving the process

• Supply chain management activities and time horizons

• Demand and demand drivers

• Demand forecasting units (DFUs)

• Forecasting methods

• Business and decision rules

• Performance measures

Developing the capability

• Roles and responsibilities

• Structure

• Skills

• Incentives

Acquiring the right IT

• Technology options– spreadsheets

– general statistical packages

– specialist forecasting packages

– enterprise resource planning packages (ERP)

– advanced planning and scheduling packages (APS)

• Data integrity and standards

• Evaluating options– the top 10 questions to ask

CommitmentControl

Compatibility

Capability

Collaborativepartnership

The 4Cs of collaboration

Recommendations

• Segment products to determine forecasting processes

• Develop forecasts collaboratively

• Suspend practices that obscure consumer demand signals

• Improve the integrity of data and use common data standards

• Develop processes, people and technology

• Use “The Guide” for improvement every step of the way!