Making Supply Meet

Making Supply Meet

Demand in an

Uncertain World

by Marshall L. Fisher, Janice H. Hammond,

Walter R. Obermeyer, and Ananth Raman

Reprint 94302

Harvard Business Review

M.L. FISHER, J.H. HAMMOND, MAKING SUPPLY MEET DEMAND 94302

W.R. OBERMEYER, AND A. RAMAN IN AN UNCERTAIN WORLD

CHRISTOPHER MEYER HOW THE RIGHT MEASURES HELP TEAMS EXCEL 94305

CRAIG SMITH THE NEW CORPORATE PHILANTHROPY 94309

TODD B. CARVER ALTERNATIVE DISPUTE RESOLUTION: 94301

AND ALBERT A. VONDRA WHY IT DOESN’T WORK AND WHY IT DOES

BRUCE G. POSNER REINVENTING THE BUSINESS OF GOVERNMENT: 94306

AND LAWRENCE R. ROTHSTEIN AN INTERVIEW WITH CHANGE CATALYST DAVID OSBORNE

HBR CASE STUDY

JULIA LIEBLICH MANAGING A MANIC-DEPRESSIVE 94303

PERSPECTIVES

THE RUSSIAN INVESTMENT DILEMMA 94307

NOAH WALLEY IN QUESTION

AND BRADLEY WHITEHEAD IT’S NOT EASY BEING GREEN 94310

WORLD VIEW

KEVIN R. MCDONALD RUSSIAN RAW MATERIALS: 94304

CONVERTING THREAT INTO OPPORTUNITY

FIRST PERSON CLASSIC

ROBERT SCHRANK TWO WOMEN, THREE MEN ON A RAFT 94308

MAY-JUNE 1994

HarvardBusinessReview

DRAWING BY TERRY WIDENER Copyright © 1994 by the President and Fellows of Harvard College. All rights reserved.

Thanks to global competition, faster product development,

and increasingly flexible manufacturing

systems, an unprecedented number and variety

of products are competing in markets ranging from

apparel and toys to power tools and computers. Despite

the benefits to consumers, this phenomenon

is making it more difficult for manufacturers and

retailers to predict which of their goods will sell

and to plan production and orders accordingly.

As a result, inaccurate forecasts are increasing,

and along with them the costs of those errors. Manufacturers

and retailers alike are ending up with

more unwanted goods that must be marked down –

perhaps even sold at a loss – even as they lose potential

sales because other articles are no longer in

stock. In industries with highly volatile demand,

like fashion apparel, the costs of such “stockouts”

and markdowns can actually exceed the total cost

of manufacturing.1

To address the problem of inaccurate forecasts,

many managers have turned to one or another popular

production-scheduling system. But quick-response

programs, just-in-time (JIT) inventory systems,

manufacturing resource planning, and the

like are simply not up to the task. With a tool like

manufacturing resource planning, for example, a

manufacturer can rapidly change the production

schedule stored in its computer when its original

forecast and plan prove incorrect. Creating a new

schedule doesn’t help, though, if the supply chain

has already been filled based on the old one.

by Marshall L. Fisher,

Janice H. Hammond, Walter R. Obermeyer, and Ananth Raman

Marshall L. Fisher is the Stephen J. Heyman Professor

and codirector of the Manufacturing and Logistics Research

Center at the University of Pennsylvania’s Wharton

School in Philadelphia. Janice H. Hammond is associate

professor at the Harvard Business School and

cofounder of the Harvard University Center for Textile

and Apparel Research in Boston, Massachusetts. Walter

R. Obermeyer is a principal of Sport Obermeyer,

Ltd., in Aspen, Colorado, and a graduate of the Harvard

Business School. Ananth Raman is assistant professor at

the Harvard Business School.

HBR M A Y - J U N E 1 9 9 4

MAKING SUPPLY MEET DEMAND

IN AN UNCERTAIN WORLD

84 PHOTOS BY BRUCE T. MARTIN

Similarly, quick response and JIT address only

part of the overall picture. A manufacturer might

hope to be fast enough to produce in direct response

to demand, virtually eliminating the need for a forecast.

But in many industries, sales of volatile products

tend to occur in a concentrated season, which

means that a manufacturer would need an unjustifiably

large capacity to be able to make goods in response

to actual demand. Using quick response or

JIT also may not be feasible if a company is dependent

on an unresponsive supplier for key components.

For example, Dell Computer Corporation

developed the capability to assemble personal computers

quickly in response to customers’ orders but

found that ability constrained by component suppliers’

long lead times.

We think that manufacturers and retailers alike

can greatly reduce the cost of forecasting errors by

embracing accurate response, a new approach to

the entire forecasting, planning, and production

process. We believe that companies can improve

their forecasts and simultaneously redesign their

planning processes to minimize the impact of inaccurate

forecasts. Accurate response provides a way

to do both. It entails figuring out what forecasters

can and cannot predict well, and then making the

supply chain fast and flexible so that managers can

postpone decisions about their

most unpredictable items until

they have some market signals,

such as early-season sales results,

to help correctly match supply

with demand.

This approach incorporates two

basic elements that other forecasting

and scheduling systems

either totally or partially lack.

First, it takes into account missed

sales opportunities. Forecasting

errors result in too little or too

much inventory. Accurate response

measures the costs per

unit of stockouts and markdowns,

and factors them into the planning

process. Most companies do

not even measure how many sales

they have lost, let alone consider

those costs when they commit to

production.

Second, accurate response distinguishes

those products for

which demand is relatively predictable

from those for which demand

is relatively unpredictable.

It does this by using a blend of historical

data and expert judgment.

Those two elements help companies rethink and

overhaul not only every important aspect of their

supply chains – including the configuration of their

supplier networks, schedules for producing and delivering

unfinished materials, transportation, and

the number and location of warehouses – but also

the designs of their products. Armed with the

knowledge of which products have predictable demand

and which do not, they can then take different

approaches to manufacturing each class of product.

Those in the relatively predictable category

should be made the furthest in advance in order to

reserve greater manufacturing capacity for making

unpredictable items closer to the selling season.

Such a strategy enables companies to make smaller

quantities of the unpredictable products in advance,

see how well the different goods fare early in

the selling period, and then use that information to

determine which products to make more of.

Accurate response thus enables companies to use

the power of flexible manufacturing and shorter cycle

times much more effectively. And the capability

to do a better job of matching supply and demand

produces savings that drop straight to the bottom

line. One supplier in the fashion-ski-apparel business,

Aspen, Colorado-based Sport Obermeyer,

Accurate

response

helps retailers

improve forecasts

and

redesign planning

processes

to minimize

the impact of

inaccurate

forecasts.

LOCATION COURTESY OF VERONA, NEWBURY STREET, BOSTON 85

SUPPLY AND DEMAND

Ltd., has slashed its mismatch costs in half by using

accurate response.

By dramatically reducing mismatch costs, this

approach also gives companies the option of taking

a further action: lowering prices. Currently, suppliers,

distributors, and retailers alike build mismatch

costs into their prices. In other words, they try to

make consumers pay more to cover the cost of inaccurate

forecasts.

Clearly, companies that make or sell products

with long lifetimes and steady sales do not need to

make such changes to their forecasting and planning

systems. Forecasts for those products are likely

to be consistently close to the mark, and in any

case, the long lifetimes of such products greatly reduce

the cost of any forecast inaccuracy. But for

companies that deal with products that are new or

highly seasonal, or have short lifetimes, the accurate

response approach is essential. Any manufacturer

whose capacity is constrained during peak

production periods can benefit from making better

use of its off-peak capacity. And any retailer that

has difficulty predicting demand can likewise benefit

by learning which products to order in bulk before

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