View
226
Download
3
Category
Tags:
Preview:
Citation preview
Slide 1 © Carliss Y. Baldwin 2007
Design Theory and Methods
Carliss Y. BaldwinHarvard Business School
MiniConference with the Professors and Students from L’Ecole des MinesOctober 16, 2007
Slide 2 © 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 projects
Slide 3 © Carliss Y. Baldwin 2007
In the economy, value acts like a force operating on and through designs
Value = money or the promise of money
Consider the computer industry…
Why we study designs…
Slide 4 © Carliss Y. Baldwin 2007
The changing structure of the computer industry
Andy Grove described a vertical-to-horizontal transition in the computer industry:
1995-“Modular Cluster”
1980-“Vertical Silos”
Slide 5 © 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 “Top N” Companies each year
Slide 33 © Carliss Y. Baldwin 2007
The End of the Verticals
Value forced the industry to a new shape/structure
Does this always happen?
Slide 56 © Carliss Y. Baldwin 2007
The industry turned over, but most value stayed in the OEM layer…
Slide 58 © Carliss Y. Baldwin 2007
What Causes One Industry to Break Apart and Another to Integrate and Consolidate?
Design Structure + Option Value
Slide 59 © Carliss Y. Baldwin 2007
Design Structure + Option Value
Verticals HorizontalsHigh Will Dominate; Will Dominate;
High Turnover High Turnover
Option Value
Verticals HorizontalsWill Dominate; Will Dominate;
Low Low Turnover Low Turnover
Integral ModularDesign Structure
Slide 60 © 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 task-
and-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 61 © 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 62 © 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 63 © Carliss Y. Baldwin 2007
Our Direct Predecessors
Herbert Simon Christopher Alexander Fred Brooks David Parnas John Holland
Our theory builds on theirs
Slide 64 © Carliss Y. Baldwin 2007
Herbert Simon
Sciences of the Artificial Fundamental insight:
Design is a decision-making process (under constraints of physics, logic and cognition)
Rational and reductionist
Slide 65 © 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: user-centered adaptive design; non-hierarchical complexity; unfolding designs; patterns
Mystic and visionary (frustrating to scientists)
Slide 66 © 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 67 © 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 68 © 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 69 © 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 70 © 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 71 © 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 72 © Carliss Y. Baldwin 2007
Designs are the instructions, based on knowledge, that turn resources into things people use and value.
Designs (noun)
Slide 73 © 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 74 © Carliss Y. Baldwin 2007
Is the process of filling in the set of instructions Designing occurs in 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!
The Process of Designing
Design Process
Start CompleteTime
Slide 75 © Carliss Y. Baldwin 2007
Completing a Design—for a Mug
Mug= Cap Handle Shape Material Decoration100110 xxxxx xxxxx xxxx xxxxxx xxxxxx
Complete design of a Mug100110 100010001 1100100100 1001110100 1010001010 100010001 …
All parameters have been selected and encoded
Partial design of a Mug100110 100010001 xxxxxx xxxxxxx xxxxxxx 100010001 …
Slide 76 © Carliss Y. Baldwin 2007
There are Many Different Names for Partial Designs
Design Process
Start CompleteTime
Slide 77 © 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 XXXX
Handle
XXXX
Logo
XXXX
Material
Slide 78 © Carliss Y. Baldwin 2007
Decision-Information Hierarchies
If no cap—Decisions contingent on “cap” disappear
List of instructions becomes shorter
MUG
No Cap
XXXX
Handle
XXXX
Logo
XXXX
Material
Slide 79 © Carliss Y. Baldwin 2007
Decision-making design hierarchy (Marple, ducts and valves, 1961)
Slide 80 © 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 83 © Carliss Y. Baldwin 2007
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 84 © 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.mathworks.com/contest/sudoku/evolution.html
Slide 85 © 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)
Mozilla Before Redesign (RAD) Mozilla After Redesign (Targeted)
Two Architectures, same functions, different states of knowledge
© Alan MacCormack, Johh Rusnak and Carliss Baldwin, 2006
Mirroring Hypothesis: Integral architectures require integral design teams
Mozilla BEFORE refactoring Linux of similar size
Coord. Cost = 30,537,703Change Cost = 17.35%
Coord. Cost = 15,814,993Change Cost = 6.65%
One Firm, Tight-knit Team, Rich communication
Distributed Open Source Development
© Alan MacCormack, Johh Rusnak and Carliss Baldwin, 2006
Slide 88 © Carliss Y. Baldwin 2007
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 89 © 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 90 © Carliss Y. Baldwin 2007
Global Design Rules v.1
Version 1.0Version 1.2
Version 1.5Version 1.8
Low Medium Zero High
Option Potential () Determines value of optional substitution Successive, improving versions are evidence of
option potential () being realized over time—after the fact
Slide 92 © Carliss Y. Baldwin 2007
/Option potential is like dark matter in the universe
We can measure its effects but we can’t measure “it”
“Architects” can perceive /option potential– But architects often don’t talk to scientists!
Thus we lack ways to measure /option valuescientifically– It is a “research frontier”
Slide 93 © Carliss Y. Baldwin 2007
Sources of /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 94 © 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 95 © Carliss Y. Baldwin 2007
Current Projects & Collaborations
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
Recommended