1

The Dynamics of Product Variety

Karl UlrichThe Wharton School

University of Pennsylvania547 Huntsman Hall

Philadelphia, PA 19104 USA

ulrich@wharton.upenn.edu

http://opim.wharton.upenn.edu/~ulrich

Joint work with Taylor Randall and Karthik Balasubramaniam.

Funding for this research has been provided by the Mack Center for Technological Innovation, Emerging Technologies Management Research Progam

Ulrich 2

“Product variety has been increasing steadily in recent years.”

- paraphrasing of many researchers motivating work on management of product variety

Definitional Issues: “Variety”• The number of different products available in a market.• Distinct SKUs; or the theoretical number of “orderable” variants for make-to-order products.• Fundamental vs. peripheral variety.• Variety w.r.t. attributes vs. number of combinations of attributes.

Expected story: Variety has increased because customer needs are increasingly heterogeneous and production systems/supply chains are increasingly flexible.

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Example Data from DataSources

CTX International 22 12 12 24 10 1 7CTXT Systems 2 2 2 2Cube Computer 1Customer Design Technology 1 1 1Cypress Com;puter 11 22DAP Electronics Canada 1 1 2 2 2Darius Technology 1 1Data Bank Computer 2Data General Corp. 1 1 3 3 3 2 2 2 1 1 3 1 1 1 1Datalux 6 2 2 1 1Dataport 1 1 1Datavue 1 1 5 3 4 2 2 1Dataworld 2 3 11 15Datec 1Dauphin International Trade Center 1 2 2 11 15 8 1DEC Direct/Digital PC 7Dee One Systems 15Dell Computer 1 4 8 9 6 15 7 6 10 20 20 43Delta Data Systems Corp. 1 2 3 3 1Delta Phase International 3DFI 15 1 15 11 11DFM Systems 1 1 1Diamond Technologies 2 2 1Digital Distributing 6Digital Equipment 3 10 14 10 9 16

Notebook computers: number of SKUs by company and year 1981-2001

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Desktop PCs

0.0

0.2

0.4

0.6

0.8

1.0

1980 1985 1990 1995 2000

Fra

cti

on

of

Ma

xim

um

Val

ue

SKUs

5.25in Disk Drives

0.0

0.2

0.4

0.6

0.8

1.0

1980 1985 1990 1995 2000

Fra

ctio

n o

f M

axim

um

Val

ue

SKUs

Voiceband Modems

0.0

0.2

0.4

0.6

0.8

1.0

1980 1985 1990 1995 2000

Fra

cti

on

of

Ma

xim

um

Va

lue SKUs

Bicycles (>$200)

0.0

0.2

0.4

0.6

0.8

1.0

1980 1985 1990 1995 2000

Fra

cti

on

of

Ma

xim

um

Va

lue

SKUs

Laser Printers

0.0

0.2

0.4

0.6

0.8

1.0

1980 1985 1990 1995 2000

Fra

ctio

n o

f M

axim

um

Val

ue

SKUs

Dot Matrix Printers

0.0

0.2

0.4

0.6

0.8

1.0

1980 1985 1990 1995 2000

Fra

ctio

n o

f M

axim

um

Val

ue

SKUs

Automobiles

0.0

0.2

0.4

0.6

0.8

1.0

1970 1975 1980 1985 1990 1995 2000

Fra

cti

on

of

Ma

xim

um

Va

lue

SKUs

Notebook Computers

0.0

0.2

0.4

0.6

0.8

1.0

1980 1985 1990 1995 2000

Fra

ctio

n o

f M

axim

um

Val

ue SKUs

3372 SKUs

342 SKUs1563 SKUs

529 SKUs1249 SKUs928 SKUs

1201 SKUs1104 SKUs

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Desktop PCs

0.0

0.2

0.4

0.6

0.8

1.0

1980 1985 1990 1995 2000

Fra

cti

on

of

Ma

xim

um

Va

lue

units

SKUs

SKU density (SKUs/unit volume)

Laser Printers

0.0

0.2

0.4

0.6

0.8

1.0

1980 1985 1990 1995 2000

Fra

ctio

n o

f M

axim

um

Val

ue

units

SKUsSKU density(SKUs/units)

If customer needs are increasingly heterogeneous and processes are increasingly flexible, we would expect SKU Density (1/niche-width) to be increasing…

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Laser Printers

0.0

0.2

0.4

0.6

0.8

1.0

1980 1985 1990 1995 2000

Fra

ctio

n o

f M

axim

um

Val

ue

units

SKU density

Notebook Computers

0.0

0.2

0.4

0.6

0.8

1.0

1980 1985 1990 1995 2000

Fra

ctio

n o

f M

axim

um

Val

ue

SKU density units

Voiceband Modems

0.0

0.2

0.4

0.6

0.8

1.0

1980 1985 1990 1995 2000

Fra

cti

on

of

Ma

xim

um

Va

lue

SKU density

sales

Desktop PCs

0.0

0.2

0.4

0.6

0.8

1.0

1980 1985 1990 1995 2000

Fra

cti

on

of

Ma

xim

um

Va

lue

unitsSKU density

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Desktop PCs

0.0

0.2

0.4

0.6

0.8

1.0

1980 1985 1990 1995 2000

Fra

ctio

n o

f Max

imu

m V

alu

e

units

SKUs

5.25in Disk Drives

0.0

0.2

0.4

0.6

0.8

1.0

1980 1985 1990 1995 2000

Fra

ctio

n o

f M

axim

um

Val

ue

units

SKUs

Voiceband Modems

0.0

0.2

0.4

0.6

0.8

1.0

1980 1985 1990 1995 2000

Fra

cti

on

of

Ma

xim

um

Va

lue SKUs

sales

Bicycles (>$200)

0.0

0.2

0.4

0.6

0.8

1.0

1980 1985 1990 1995 2000

Fra

cti

on

of

Ma

xim

um

Va

lue

salesSKUs

Notebook Computers

0.0

0.2

0.4

0.6

0.8

1.0

1980 1985 1990 1995 2000

Fra

ctio

n o

f M

axim

um

Val

ue SKUs

units

Laser Printers

0.0

0.2

0.4

0.6

0.8

1.0

1980 1985 1990 1995 2000

Fra

ctio

n o

f M

axim

um

Val

ue

units

SKUs

Dot Matrix Printers

0.0

0.2

0.4

0.6

0.8

1.0

1980 1985 1990 1995 2000

Fra

ctio

n o

f M

axim

um

Val

ue

units

SKUs

Automobiles

0.0

0.2

0.4

0.6

0.8

1.0

1970 1975 1980 1985 1990 1995 2000

Fra

cti

on

of

Ma

xim

um

Va

lue

unitsSKUs

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Observed Regularity (?)

SKU Densityskus/unit

Market Size, units

time

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Plausible Explanations for Dynamics of Product Variety

1. Product variety is strongly related to the portfolios of individual firms. The dynamics of the number of firms in the industry is an important driver of the dynamics of variety.

2. Product portfolios are realizations of plans and strategies crafted 2-5 years in the past. Thus, product variety will exhibit stickiness and the over/undershoot typical of dynamic systems with information delays.

3. There are economies of variety. The “optimal” level of variety is a concave function of market size, assuming some “fixed costs” per variant.

4. And many more: Variety shifts from vertical to horizontal because of changes in supply/demand of

fundamental product performance. Industries “figure out” platforms and architectures to lower the cost of variety. Early phase of industry development is characterized by a lot of experimentation and

associated higher variety (Sorenson, SMJ, 2000). (your theories here…)

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Laser Printers

0.0

0.2

0.4

0.6

0.8

1.0

1980 1985 1990 1995 2000

Fra

ctio

n o

f M

axim

um

Val

ue

units

SKUs

firms

Desktop PCs

0.0

0.2

0.4

0.6

0.8

1.0

1980 1985 1990 1995 2000

Frac

tion

of M

axim

um V

alue units

firms

SKUs

Automobiles

0.0

0.2

0.4

0.6

0.8

1.0

1970 1975 1980 1985 1990 1995 2000

Fra

ctio

n o

f Max

imu

m V

alu

e

unitsSKUs

firms

Bicycles (>$200)

0.0

0.2

0.4

0.6

0.8

1.0

1980 1985 1990 1995 2000

Fra

cti

on

of

Ma

xim

um

Va

lue

salesSKUs

firms

Post shakeout… No shakeout (inherently fragmented?)…

Effect of shakeout…

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Laser Printers

0.0

0.2

0.4

0.6

0.8

1.0

1980 1985 1990 1995 2000

Fra

cti

on

of

Ma

xim

um

Va

lue

SKUs/unit

firms units/firm

Desktop PCs

0.0

0.2

0.4

0.6

0.8

1.0

1980 1985 1990 1995 2000

Fra

ctio

n o

f M

axim

um

Val

ue

firms

unit volume/firm

SKU density (SKUs/unit volume)

Bicycles (>$200)

0.0

0.2

0.4

0.6

0.8

1.0

1980 1985 1990 1995 2000

Fra

cti

on

of

Ma

xim

um

Va

lue

sales/firmfirms

SKU density(SKUs/units)

Automobiles

0.0

0.2

0.4

0.6

0.8

1.0

1970 1975 1980 1985 1990 1995 2000

Fra

cti

on

of

Ma

xim

um

Va

lue

SKUs/unit

firms

units/firm

Post shakeout… No shakeout (inherently fragmented?)…

Effect of shakeout…

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1. Industry Dynamics, Product Variety, and Hotelling’s Street

full featured

Exp

ect

atio

ns

of

dis

trib

utio

n o

f p

ote

ntia

l cu

sto

me

rs

lightweight

Example: notebook computers

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1. Industry Dynamics, Product Variety, and Hotelling’s Street

full featured

Exp

ect

atio

ns

of

dis

trib

utio

n o

f p

ote

ntia

l cu

sto

me

rs

lightweight

Example: notebook computers

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1. Industry Dynamics, Product Variety, and Hotelling’s Street

full featured

Exp

ect

atio

ns

of

dis

trib

utio

n o

f p

ote

ntia

l cu

sto

me

rs

lightweight

Example: notebook computers

Ulrich 15

5.25in Disk Drives

0.0

0.2

0.4

0.6

0.8

1.0

1980 1985 1990 1995 2000

Frac

tion

of M

axim

um V

alue

units

firms

SKUs

Dot Matrix Printers

0.0

0.2

0.4

0.6

0.8

1.0

1980 1985 1990 1995 2000

Frac

tion

of M

axim

um V

alue

SKUs/unit

firms

units/firm

5.25in Disk Drives

0.0

0.2

0.4

0.6

0.8

1.0

1980 1985 1990 1995 2000

Frac

tion

of M

axim

um V

alue

unit volume/firm

SKU density (SKUs/unit volume)

firms

Dot Matrix Printers

0.0

0.2

0.4

0.6

0.8

1.0

1980 1985 1990 1995 2000

Frac

tion

of M

axim

um V

alue

units

SKUs

firms

Unexpected demand spike

Precipitous erosion of market

2. Product Portfolios are Sticky… firms are stuck with too much or too little.

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3. Economies of Variety – static model

attributed

en

sit

ymarket width

de Groote (Int. J. of Prod. Econ. 1994)

N* = market-width * market-density^1/3 * (1/fixed-costs)^1/3 * “pickiness”^2/3

p'

p

= d*a/2

a/2 a

p + d ( x – a/2)

Market Width

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3. Economies of VarietyHow does optimal variety change as market width and depth change?

attribute

de

ns

ity

attribute

de

ns

ity

As density of market increases,variety increases, but at a decreasing rate.

attribute

As the breadth of a market increases, variety increases proportionally.

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3. Economies of Variety – Dynamic forces

price

de

ns

ity

of

po

ten

tia

l m

ark

et

industry evolution allows product lines to be extended in this direction

19801981198219831984

full featuredlightweight

Conjecture:Markets growth patterns over time shift from expansion of breadth to expansion of depth.

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First Cut Model – For a monopolist in a growing market category, would a decrease in SKU density be expected?

Normalised N* and Mkt Volume for Monopolist(t=[0,20] a'>b';t=[21,40] a'<b')

0.0000

0.1000

0.2000

0.3000

0.4000

0.5000

0.6000

0.7000

0.8000

0.9000

1.0000

5 10 15 20 25 30 35 40

Total Market Units

SKU Density,Variants/Units

Optimal Number of SKUs

Assumes constant “set up” or fixed costs per variant over product lifecycle.

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Integrated Explanation of Dynamics

Firm dynamics and Industry shakeout

• Excess variety is created in initial phases of industry growth. Experimentation Expectations of future market size Niche saturation

• Firm shake out is associated with elimination of product redundancy. Market growth shifts from width to density

• Learning, scale efficiencies lead to lower costs, which leads to deeper markets.

• Optimal to have less variety “per customer” as markets get more dense Flexibility, reduction in costs of providing variety

• Architectural stability

• Component industry develops

• Combinatoric variety

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Other Interesting Ideas Related to Variety Dynamics

Sequential vs. simultaneous population of market spaces.

• R&D capacity decisions

• Value of learning from iterations Diminishing returns to investments in fundamental product performance (e.g., S-curve

behavior) gives rise to transition to investments in peripheral variety (e.g., fashion, color, style).

Establishment of platform and industry standards allows combinatorial variety at relatively low cost. (But, this is generally in the “wrong direction” w.r.t. empirical evidence.)

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Some Next Steps

Deeper examination of causal structure within two product categories

• Notebook computers and Laser Printers

• Is there evidence of substantial redundancy and overlap in product lines before the “shakeout.”

• Do we in fact observe a shift in market growth from “breadth” to “depth” of product lines. Analytic model, particularly of “Story 3: Economies of Variety”

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So What?

Product portfolio decisions are important problems in managerial decision making. An understanding of the fundamental drivers of product variety at an industry level informs a

firm acting within that industry. Conjectures:

• Managerial decision making with respect to product variety is typically reactive and incremental, without a clear understanding of how product lifecycles and the evolution of markets impact variety strategy.

• One of the root causes of the shake out of firms in industry lifecycles is a failure to gain efficient scale, which may be the result of the pursuit of too much product variety.