Transcript NFRS Seminar - HBS People Space

Design Theory and Methods
Carliss Y. Baldwin
Harvard Business School
MiniConference with the Professors and Students from
L’Ecole des Mines
October 16, 2007
Slide 1
© Carliss Y. Baldwin 2007
Overview of my presentation
 Why
we study designs: Their impact on
industry structure
– Computers vs. Autos
 Design
Structure + Option Value =>
Industry Structure and Evolution
 Our concept of design theory
– Our Lineage
– Our Definitions
 Current
Slide 2
projects
© Carliss Y. Baldwin 2007
Why we study designs…
In the economy, value acts like a
force operating on and through
designs
Value = money or the promise of money
Consider the computer industry…
Slide 3
© Carliss Y. Baldwin 2007
The changing structure of the
computer industry

Andy Grove described a vertical-to-horizontal transition in
the computer industry:
1980-“Vertical Silos”
1995-“Modular Cluster”
Slide 4
© Carliss Y. Baldwin 2007
Grove’s Layer Map with Data
 Take
a sector, and consider the basic SIC / NAISC
codes
– 4 to 6 digit codes to compose the entire “ecosystem” as it
evolves
– Work with industry experts to construct the sectors’ list
 Tabulate
the results in terms of “verticals” and
“horizontals”
– Objective: see how profit shifts from vertical to horizontal
layers
– …and how much “churn” there is within layers
 Map
Slide 5
“Top N” Companies each year
© Carliss Y. Baldwin 2007
How the map works
Slide 6
© Carliss Y. Baldwin 2007
What a map looks like… Computers, 1979
Slide 7
© Carliss Y. Baldwin 2007
The End of the Verticals
Value forced the industry to a new
shape/structure
Does this always happen?
Slide 33
© Carliss Y. Baldwin 2007
Look at the auto industry
Slide 34
© Carliss Y. Baldwin 2007
In the beginning (1984)
The industry turned over, but
most value stayed in the OEM
layer…
Slide 56
© Carliss Y. Baldwin 2007
Telecomm is yet another story…
Slide 57
© Carliss Y. Baldwin 2007
What Causes One Industry to
Break Apart and Another to
Integrate and Consolidate?
Design Structure + Option Value
Slide 58
© Carliss Y. Baldwin 2007
Design Structure + Option Value
High
Verticals
Will Dominate;
High Turnov er
Horizontals
Will Dominate;
High Turnov er
Verticals
Will Dominate;
Low Turnov er
Horizontals
Will Dominate;
Low Turnov er
Option Value
Low
Integral
Modular
Design Structure
Slide 59
© Carliss Y. Baldwin 2007
In other words…

Design structure/Modularity (of products and processes)
determines industry structure
– Because module boundaries are “thin crossing points” in the taskand-design network
– Transaction costs are low at module boundaries
– Every thin crossing point/module boundary is a potential place to
put a transaction, i.e., bring in a different firm

Option value of designs determines rate of change/industry
evolution
– Option value makes design experiments worthwhile
– Experiments yield new designs (of products and processes)…
– Better new designs replace or augment the older ones!
Slide 60
© Carliss Y. Baldwin 2007
Thus design theory holds the key
to understanding the structure
and dynamics of the economy
But what is design theory?
Slide 61
© Carliss Y. Baldwin 2007
Influential Design Theorists







Bell and Newell, computer hardware: Computer Structures
Hennessy and Patterson, computer hardware-software
interface: Computer Architecture
Mead and Conway, semiconductors: Intro to VLSI
Nevins and Whitney, manufacturing: Concurrent Engineering
Nam Suh, mechanical engineering: The Principles of Design
German design theorists (Hubka, Pahl and Beitz) in
mechanical engineering: The Theory of Technical Systems;
Engineering Design: A Systematic Approach
March, Thompson, Galbraith, organizations: Organizations;
Organizations in Action; Organizational Design
Slide 62
© Carliss Y. Baldwin 2007
Our Direct Predecessors
 Herbert
Simon
 Christopher Alexander
 Fred Brooks
 David Parnas
 John Holland
Our theory builds on theirs
Slide 63
© Carliss Y. Baldwin 2007
Herbert Simon
 Sciences
of the Artificial
 Fundamental insight:
Design is a decisionmaking process (under
constraints of physics, logic
and cognition)
 Rational and reductionist
Slide 64
© Carliss Y. Baldwin 2007
Christopher Alexander
Notes on the Synthesis of
Form; A Pattern Language; A
City is not a Tree; The Nature
of Order
 Fundamental insights: usercentered adaptive design; nonhierarchical complexity;
unfolding designs; patterns
 Mystic and visionary
(frustrating to scientists)

Slide 65
© Carliss Y. Baldwin 2007
Frederick Brooks



The Mythical Man Month; No
Silver Bullet; Computer
Architecture
Fundamental insights: the
complexity catastrophe lurking in
large designs; limits on the division
of knowledge and labor; group
inter-communication formula
Architect of System/360
Slide 66
© Carliss Y. Baldwin 2007
David Parnas
On the Criteria to be Used in
Decomposing Systems into
Modules; Software
Fundamentals
 Fundamental insights:
Information-hiding
modularity; Abstraction;
Interface; Modules are task
assignments
 Software designer

Slide 67
© Carliss Y. Baldwin 2007
John Holland
Hidden Order; Adaptation in
Natural and Artificial Systems;
Emergence
 Fundamental insights: Formal
dynamics of complex adaptive
systems; unified theory of
natural and artificial evolution;
operators
 Our best link to complexity
sciences (better than
Kauffman)

Slide 68
© Carliss Y. Baldwin 2007
Baldwin and Clark


Design Rules: The Power of
Modularity; Modularity,
Transactions and the Boundaries of
Firms
Most important ideas:
– designs are lodged in the larger
economy;
– financial value is a force driving design
evolution;
– designs are options;
– modules are units of optional
substitution;
– uncertainty is valuable;
– new firms attach at module boundaries
Slide 69
© Carliss Y. Baldwin 2007
That is our view of Design
Theory
We are eager to learn yours…
But, first, for the sake of
understanding, our definitions
Slide 70
© Carliss Y. Baldwin 2007
Our Definitions

Design (noun)
– Design (verb)—Process of Designing
– Partial vs. Complete Designs
Design Hierarchy
 Design Space
 Value Landscape of a Design Space
 Design Structure/Modularity (Alan)

– Mirroring Hypothesis

Options and Option Value (Carliss)
Slide 71
© Carliss Y. Baldwin 2007
Designs (noun)
Designs are the instructions,
based on knowledge, that turn
resources into things people use
and value.
Slide 72
© Carliss Y. Baldwin 2007
Implications of the definition
 Designs
are not “the thing itself”, they are
the instructions for making it
– In software: source code = design
– Compiled, running code = the thing itself
 Designs
are information
 Designs are part of human knowledge
– But not all knowledge is design
– Designs make knowledge useful
Slide 73
© Carliss Y. Baldwin 2007
The Process of Designing


Is the process of filling in the set of instructions
Designing occurs in time
Design Process
Start


Complete
Time
When design is complete, the design process is over,
“production” can begin
Along the way, you have partial designs
– A source of huge amounts of confusion!
Slide 74
© Carliss Y. Baldwin 2007
Completing a Design—for a Mug
M ug=
C ap
1 0 0 1 1 0xxxxx
H andle
xxxxx
Shape
xxxx
M aterial
xxxxxx
D ec oration
xxxxxx
C omplete des ign of a M ug
1 0 0 1 1 0 1 0 0 0 1 0 0 0 11 1 0 0 1 0 0 1 0 01 0 0 1 1 1 0 1 0 01 0 1 0 0 0 1 0 1 0 1 0 0 0 1 0 0 0…
1
A ll parameters have been s elec ted and enc oded
P artial des ign of a M ug
1 0 0 1 1 0 1 0 0 0 1 0 0 0xxxxxx
1
Slide 75
xxxxxxx
xxxxxxx
1 0 0 0 1 0 0 0…
1
© Carliss Y. Baldwin 2007
There are Many Different Names for
Partial Designs
Design Process
Start
Slide 76
Complete
Time
© Carliss Y. Baldwin 2007
Decision-Information Hierarchies
 Process
of design is a decision-making
process
 Some design decisions create the need for
subsequent decisions
MUG
Cap?
XXXX
Slide 77
Handle
XXXX
Logo
XXXX
Material
XXXX
© Carliss Y. Baldwin 2007
Decision-Information Hierarchies
 If
no cap—Decisions contingent on “cap”
disappear
 List of instructions becomes shorter
MUG
No Cap
Handle
XXXX
Slide 78
Logo
XXXX
Material
XXXX
© Carliss Y. Baldwin 2007
Decision-making design hierarchy
(Marple, ducts and valves, 1961)
Slide 79
© Carliss Y. Baldwin 2007
Design Space
 A design
space comprises the set of all
possible variants of a set of designs
 Design spaces are bounded by prior design
decisions
– Mug … w/ cap
– Pentium chip … w/ out-of-order, superscalar
microarchitecture
 Can
be mapped, unmapped, partially
mapped
Slide 80
© Carliss Y. Baldwin 2007
All these—and many more— are in
the design space of “bicycles”
Slide 81
© Carliss Y. Baldwin 2007
The newer the artifact, the less we know, the
more exploration of the design space is
valuable…
Value Landscape
Maps points in design space to value
 In biology, value=fitness
 Fitness landscape for designs of eyes

Created by Mike
Land. Height
represents optical
quality and the
ground plane
evolutionary
distance.
From Dawkins R:
Climbing Mount
Improbable. New
York, Norton,
1996.
Slide 83
© Carliss Y. Baldwin 2007
Value Landscape and Search History
of a computer program
Scored results of
submissions to
the Mathworks
“Sudoku”
programming
contest. Red path
shows trajectory
of best design
over time.
http://www.math
works.com/contes
t/sudoku/evolutio
n.html
Slide 84
© Carliss Y. Baldwin 2007
Design Structure/Architecture
 The
degree and pattern of interdependence among
the elements of a design
 Establishes dependencies between design spaces,
hence their scope/complexity
 Some key architectural types
– Integral (all interdependent)
– Layered (X depends on Y; Y does not depend on X)
– Modular (independent blocks, all depending on design
rules—combination of integral and layered)
 Architectures
are somewhat under the control of
designers (subject to constraints of knowledge)
Slide 85
© Carliss Y. Baldwin 2007
Two Architectures, same functions,
different states of knowledge
Mozilla Before Redesign (RAD)
Mozilla After Redesign (Targeted)
© Alan MacCormack, Johh Rusnak and Carliss Baldwin, 2006
Mirroring Hypothesis:
Integral architectures require integral design teams
Mozilla BEFORE refactoring
One Firm,
Tight-knit
Team, Rich
communication
Coord. Cost = 30,537,703
Change Cost = 17.35%
Linux of similar size
Distributed
Open Source
Development
Coord. Cost = 15,814,993
Change Cost = 6.65%
© Alan MacCormack, Johh Rusnak and Carliss Baldwin, 2006
Alan and John will tell you more
about our findings…
But we have one more set of critical
concepts—
Options
Optional substitution
Option potential
Slide 88
© Carliss Y. Baldwin 2007
Options, Optional Substitution

The right but not the obligation to take an action
– Action = Use a new design
– If new is better than old, use new;
– Otherwise, keep the old (“optional substitution”)
Designs have the property of optional substitution
 Unit of optional substitution is a module (that
which can be changed without changing
something else)
 Thus option value resides in modules

Slide 89
© Carliss Y. Baldwin 2007
Option Potential (s)
 Determines
value of optional substitution
 Successive, improving versions are evidence of
option potential (s) being realized over time—
after the fact
Global Design Rules v.1
Version 1.0
Version 1.2
Version 1.5
Version 1.8
s = Low
Slide 90
Medium
Zero
High
© Carliss Y. Baldwin 2007
Optional substitution at work—
Evolution of a computer program
Slide 91
© Carliss Y. Baldwin 2007
s /Option potential is like dark matter
in the universe
 We
can measure its effects but we can’t
measure “it”
 “Architects” can perceive s /option
potential
– But architects often don’t talk to scientists!
we lack ways to measure s /option
value scientifically
 Thus
– It is a “research frontier”
Slide 92
© Carliss Y. Baldwin 2007
Sources of s /option potential
 Physics—
– Moore’s Law—dynamics of miniaturization in electronic
circuits (Mead and Conway)
– Power and heat systems vs. logic systems (Dan Whitney)
 Users—
– Users experiment to discover their own needs/tastes
– New features, techniques, and applications=> new
willingness to pay
– Exaptations (designed for one thing, does another)
 Architecture
—
– Isolate sources of uncertainty, variability, and bottlenecks
– Support new compositions & combinations (e.g.
YouTube=movie+PC+Internet+Library)
Slide 93
© Carliss Y. Baldwin 2007
When options are present,
variability in outcomes is
valuable…
When is this true?
Which industries, which NPD
processes? Why?
How does one obtain variability in
outcomes?
Slide 94
© Carliss Y. Baldwin 2007
Current Projects & Collaborations

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Dividing up the economic system—modularity and
transactions
Design structure in software (Alan and John)
Price competition in modular clusters (J. Woodard)
Design theory and user innovation (E. von Hippel)
Strategic variability (M. Szigety)
The value of modular production systems (V.
Kuppaswamy)
Transparency vs. modularity (L. Colfer)
Modularity and intellectual property rights (J. Henkel)
Layer Maps and Industry Evolution (M. Jacobides)
‘Selfish’ Designs—the institutional structure of innovation
Slide 95
© Carliss Y. Baldwin 2007
Thank you!
Slide 96
© Carliss Y. Baldwin 2007