Fisher Marco Island Talk

How do you decide what to How do you decide what to produce when you don’t know produce when you don’t know what your customers will buy?what your customers will buy?

Marshall FisherUPS Professor, The Wharton

SchoolCofounder and Chairman, 4R

Systems

ISC/SCLC SPRING 2006 MEETINGHilton Marco Island APRIL 29, 2006

© 2006 Marshall L. Fisher

Cost of lost sale

Risk of obsolescence

Forecast accuracy

Product variety

Product life cycle

High

Low

Low

Low

High

High

High

Low

ShortLong

Functional Innovative

Products differ


And supply strategies differ

Factory focus

Inventory Strategy

Lead-time focus

Supplier selection

Product-design strategy

Low cost trumps short lead-time

High utilization

High turns

Low cost

Maintain buffer capacity

Significant buffer stocks of components and FGs

Speed & flexibility

Aggressively shorten lead-time

Modular to enable postponed differentiation

Integral for max performance at min cost

Physically efficient

Market responsive


match

matchmismatch

mismatch

Life cycle > 2 yearsGross Margin < 35%Low Product Variety

Functional Products

Life cycle < 1 yearGross Margin > 35%High Product Variety

Innovative ProductsR

espo

nsiv

e Su

pply

Cha

inEf

ficie

nt

Supp

ly C

hain

Supply predictable demand efficiently at lowest cost

Respond quickly to unpredictable demand to minimize stockouts, markdowns, and obsolete inventory

Need to match supply strategy with product type


So as to minimize total of two types of costs

• Physical Production/Distribution Costs

– Production Costs– Transportation Costs– Facility Utilization rates– Inventory carrying cost on pipeline and cycle stocks

• Supply/Demand Mismatch Costs

– Lost revenue and profit margin when supply is less than demand– Product and parts scrapped or sold at a loss when supply

exceeds demand– Inventory carrying cost on safety stocks

Raw Materials

ComponentSuppliers

Manufacturer

Retailers Consumers


Dell reaps benefits from supply chain innovation

“Supply chain management is what it’s all about“ Tom Meredith, Chief Financial

Officer of Dell

Source: Open manufacturing Online, July 28, 1998

Dell

S&P 500


P & G has grown earnings faster than sales by cutting supply chain costs

0

5000

10000

15000

20000

25000

30000

35000

40000

1990

1991

1992

1993

1994

1995

1996

1997

1998

010002000300040005000600070008000900010000

Net S

ales

($M

)

Net E

arni

ngs (

$M)

trendline

Source: Company 10K reportsNote: 1993-94 accounting change makes series

discontinuous.

During 94-98Net Sales grew 22.3%

Net Earnings grew 71%

P&G Net Sales and Net Earnings 1990-98


A page from Sport Obermeyer’s product catalog


Next year’s catalog


Obermeyer’s styles are fashion-forward and change every year


Factories in China

DC in Denver

800 Ski Retailers

The Obermeyer supply chain stretches from Asia to Aspen

Obermeyer’s planning calendar is driven by when it snows


Which parka family sold best?

Black Voodoo sold 4000

Sold 4


Initial forecasts are highly inaccurate

Black Voodoo


Measuring the cost of over and under supply

Orders 4000 4Production 2000 2000Lost sales 2000 Excess 1996Full price = $200 Markdown price = 130 Variable cost = 150

Lost sales cost $50 x 2000 = $100,000

Excess cost $20 x 1996 = $39,920

Initial forecasts are highly inaccurate …

but improve dramatically with just a little sales data


Early write

• Bring 25 (out of 800) largest retailers to Aspen in February. Accounts for 20% of sales.

• Put them up at the Ritz Carlton

• They ski with Klaus Obermeyer, an industry icon

• They get an advance preview of the line

• They order early

Lead time reduction

• Fabric dyer lead time of several months was a problem for Obermeyer• Dyer has long lead time on greige goods and needed to keep their

capacity utilized year round but can change colors overnight• Obermeyer can predict total annual sales and sales of basic colors,

but can’t predict fashion colors

Solution • Offer dyer one year commitment on greige goods and capacity• Dye basic colors early in year and fashion colors late in

season on few days notice

Fabric Producer

Fabric Dyer

Cut/Sew Factory

Denver Warehouse

Retailer

undyed greige goods Sport Obermeyer

Asia

Consumer


Revised planning calendar


Sample buying committee projections

Which product is more predictable?

PandoraParka

EnticeShell

Carolyn

Laura Tom Kenny Wally Wendy Average

Std. Dev.

1200

1500

1150 1250 1300 1100 1200 1200 65

700 1200 300 2075 1425 1200 572


0

200

400

600

800

1000

1200

1400

0 110 220 330

Standard Deviation of the IndividualForecasts of a Six Person Committee

Forecast Error

HighError

LowError

High Agreement Low Agreement

AverageError =155 units

AverageError =252 units

The committee process allowed us to forecast forecast accuracy


STYLE COLOR Wholesale COMM COMM# # Price LK CO SS CB JD WS WRO TT GW AM AVE STD DEV

MEN'S PARKAS6220 77.5

64 479 700 500 400 475 600 414 300 600 340 481 12545 650 200 500 200 560 800 614 300 840 340 500 23378 50 300 200 100 475 300 895 300 600 510 373 2539 180 300 200 100 390 290 876 400 360 510 361 217

TOTAL: 1359 1500 1400 800 1900 1990 2799 1300 2400 1700 1715 581

6221 94.5 64 350 700 500 600 400 275 465 200 420 300 421 15245 600 200 400 400 500 575 542 300 516 375 441 12878 350 300 300 100 385 400 310 175 432 600 335 13876 500 400 400 400 320 150 233 175 72 225 288 137

TOTAL: 1800 1600 1600 1500 1605 1400 1550 850 1440 1500 1485 2496222 9.5

64 700 700 400 1100 350 550 771 400 400 600 597 23245 200 200 400 400 250 375 135 100 672 300 303 1689 750 500 500 200 350 725 539 500 400 800 526 189

49 450 600 500 300 150 150 275 300 200 300 323 150TOTAL: 2100 2000 1800 2000 1100 1800 1720 1300 1672 2000 1749 324

9 930 800 700 300 740 1015 1415 900 760 1310 887 316

45 1450 600 1300 1000 1310 1750 1291 700 2028 1015 1244 44049 450 600 500 300 150 150 275 300 200 300 323 15064 1529 2100 1400 2100 1225 1425 1650 900 1420 1240 1499 37576 500 400 400 400 320 150 233 175 72 225 288 13778 350 300 300 100 385 400 310 175 432 600 335 138

Obermeyer Committee Forecasts

Color forecasts


Historical Distribution of Forecast Errors Follows the Normal Bell-Shaped Curve


The Normal Distribution Accurately Models Demand Uncertainty at Obermeyer

Probability Distribution for Sales of PandoraMean = 1200 Standard Deviation = 230


Pandora Parka

1200 1430 1660970740

33%33%15% 15%

2%2%

Cost of Under and Over Production

Pandora Parka Wholesale Price Less Supplier charges Sales Commission Inventory carrying/Delivery

Profit Margin

Markdown Price Less Supplier charges Inventory carrying/delivery

Loss

$ 200

100 30 25 _____ $ 45 Cost of Under Production

$ 120 100 35 _____ ($15) Cost of Over Production


Probabilistic Break Even AnalysisProduce to the point whereProbability we sell x Gain if we sell = Probability we don’t sell x Loss if we don’t sell

.25 x 45 = .75 x 15

Pandora Parka

1200 1430

Probability = .25

Gain if we sell Loss if we don’t sell


Production Decision if we can only buy once

Accurate Response Optimization Model

• Demand Distributions• Cost of Stockouts & Excess Inventory• Production Capacity and Minimum Constraints

Minimize Expected Costof Stockouts

& Excess Inventory

• Risk Adjusted Production Commitments by Style/Color• Can be used as Simulation Model to measure the impact

of better information or increased supply chain flexibility


Desk top tool run by user

Factories in China

DC in Denver

800 Ski Retailers

Product Sketches

Forecast Committee

Forecasts

Order 50% in

November

Order 50% in April

Retailers order in

Feb & April

Results of a parallel test show profit increase equal to 1.8% of sales

Optimization Model

Decisions

Legacy Process

Decisions

Total Production (Units) 124,805 121,432Demand 103,831 103,,831Over-Production (Units) 22,036 25,094Under-Production (Units) 792 7,493Over-Production Cost (% of Sales) 1.30% 1.74%Under-Production Cost (% of Sales) 0.18% 1.56%Total Cost (% of Sales) 1.48% 3.30%


Retailers Loved the New Program!


Obermeyer process at World, a major Japanese retailer


Right Buy: Commercial Implementation of the Obermeyer concept

Elements of the Obermeyer process Which of these would be useful in your company?• Early orders are highly predictive

• Early write -> bring 25 largest retailers to Aspen to order early

• Cut lead times on expensive, long lead time component – dyed fabric

• Use committee forecast process to forecast forecast errors

• Risk based production sequencing– Replace point forecast by probability distribution– Make predictable volume early.– Set production volumes based on likely forecast

accuracy and cost of over and under production.

How to think about supply chain improvementProduct

Availability

Responsive Supply Chain

Inventory

Accurate Forecasts

How does product availability drive revenue?

Optimize cost of lost margin, carrying and obsolescence

Track & improve the accuracy of forecasts that drive decisions e.g. parts lead time demand


Create a framework for inventory efficiency e.g. common parts, short lead times, efficient small lot production

Documents

Fisher Marco Island Talk