Organizations as Evolutionary Systems Daniel Levinthal Wharton School, University of Pennsylvania.

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Organizations as Evolutionary Systems Daniel Levinthal Wharton School, University of Pennsylvania

Transcript of Organizations as Evolutionary Systems Daniel Levinthal Wharton School, University of Pennsylvania.

Organizations as Evolutionary Systems

Daniel Levinthal

Wharton School, University of Pennsylvania

Sustained Competitive Advantage

S&P 500 in 1957

74 firms

1997 Only 12 outperformedS&P 500

Owning just survivors would have yielded a 20% lower return than owning the S&P

Foster and Kaplan (2001)

Challenge for Strategic Management

• What is the problem? What are our expectations?– Immortality – Sustained competitive advantage

time

Competitive advantage

Competitive advantage

time

“It’s not the strongest of the species that survive, not the

most intelligent , but the one that is most responsive to change.” Charles Darwin

The ability to learn faster than your competitors may be the only sustainable competitive advantage

Ray State (CEO Analog Devices)Arie De Geus (Head of Strategic Planning Royal Dutch Shell)Peter Senge (author of the 5th Discipline)

OODA loop (observe, orient, decide, and act)John Boyd (USAF Strategist)

Exploration - Exploitation• Fundamental tension for evolving

entity– Adaptation in Natural and Artificial

Systems (Holland, 1975)– Need to survive in the present and adapt

in ways that enhance survival in the future

• Why the need for adaptation for the future?– Opportunity to improve via search over

complex problem/opportunity space– Changes in the problem/competitive

context itself

Nested Levels of Selection

EnvironmentNichesSelection criteriaSelection pressure

Org A Org B

Nested Levels of Selection

EnvironmentNichesSelection criteriaSelection pressure

Org A Org B

a1 a2 a3 a4 a5

Selection of projects and routines within the organization

Three Challenges to the Problem of Organizational Evolution

• Problem of interim selection

• Problem of selection criteria– Diversity

• From “Dynamic Capabilities” to Dynamic Organizations

QGTsSelection Environment

Problem of Interim Selection: Evolutionary Dynamics

Genotype versus Phenotype

• Fixed genetic structure need not imply fixed form– Adaptation at the individual level– Developmental expression of genotype

Unpacking Construct of Routine-based Action(Levinthal and Marino, 2012)

• Gene– Carrier of inheritable traits across time

• Phenotype– Expression of the “form”– Some degree of loose coupling to gene

• Plasticity– Unique re-enactment of “routine” based behavior

• Feldman (2000), Birnholtz, Cohen, & Hoch (2007), Cohen, Levinthal, and Warglien (2012)

– Selection operates directly on phenotype (and only indirectly on the gene)

• Myopia of selection (Levinthal and Posen, 2007)

QGTsSelection Environment

Products Product markets

Market share

Patents & new products

Financialmarkets

Explicitly myopic

Forward-looking but conditionalon current outcomes

Time

Per

form

ance

Selection

What does it mean to be a good “type”?• High profits conditional on survival

Implicit criteria of business press accounts• Higher probability of survival

Implicit criteria of population ecologists• Highest average (across a particular strategy) for all organizations

Implicit criteria for learning theorists

Unfolding of alternativesearch strategies

Intermediate SelectionLevinthal and Posen (2007) “Myopia of Selection”, ASQ

• When is this most critical?– Early in an organization’s life

• Most vulnerable to selection forces• Most plastic with respect to developmental processes

• Importance of considering in detail both the nature of developmental paths and the nature of selection– Search strategies, resource endowments & temporary buffering from

selection

• Selectability: Informativeness of current fitness for future fitness

Challenge of Intermediate Selection: Valuation of Stage-Setting Moves

• Learning in the absence of [immediate] feedback (Fang, Denrell, and Levinthal, 2004, Fang and Levinthal, 2009)– Samuels (1958): machine learning for checkers

• Reward ‘stage-setting’ moves as opposed to full paths or ultimate outcomes

– Need for mental models for evaluation of intermediate states

– Learning in labyrinths versus t-mazes• Emergence of routines as a mechanism to address inter-temporal

dependencies

Real Options• Initial “stage-setting” investments may give the firm

privileged access to subsequent follow-on investments– New product development– Initial plant in an emerging market– Rights to distribute a new movie

State-setting Investment

Realization of Uncertainty

Stage 2 Investment

Intermediate Selection & Real Options

• Real options as panacea for innovation strategy in an uncertain world

• Problems of selection and real options (Adner and Levinthal, AMR 2004)

– Challenge of updating and evaluation – Impossibility of proving failure– Costs of imposing sufficient constraint to make

innovative efforts conform to a real option

Challenges of Experimentation: Problems of Variety

• Variety of ideas & initiatives – “let a thousand flowers bloom” Rosabeth Moss Kanter

• Challenge of sustaining hetereogentiy of selection criteria– Organizations have sufficient resources to make multiple bets but struggle

to act with multiple minds• Does size matter? (Posen, Martignoni, Levinthal, 2012)• Iron law of hierarchy (Michels, 1911)

Internal Ecology(Levinthal and Marino, 2012)

• Organizational adaptation as aggregate property– Plasticity of individual routines may or may not be

adaptive for the aggregate entity• Flexibility • Reliability • Selectability

– Degree/intensity of internal selection forces

• Plasticity Dynamic capabilities?

Grand Synthesis: Link Intelligent Design and Emergence

• Engineering of evolutionary processes– Balancing exploration and exploitation

• Holland (1976) and March (1991)

– Nested levels of selection• Natural and artificial selection environments • Within group versus across group selection

• Choice processes in evolutionary theories – Proteins versus people climbing fitness landscapes

• Cognition: Gavetti and Levinthal (2000)• Social/population learning processes: Bandura (1977), Miner and

Haunschild (1995)

– Incentives and self-interest• Landscape design: Levinthal and Warglien (1999)

Return to Darwin & Mendel• Our thinking about growth and decay is dominated by

the image of a single lifespan, animal or vegetable. Seedling, full flower and death. “The flower that once has bloomed forever dies.” But for an ever-renewing society the appropriate image is a total garden, a balanced aquarium or other ecological system. Some things are being born, other things are flourishing, still other things are dying --- but the system lives on John Gardner (1972) – Silicon Valley– Internal ecology of organizations

Small Steps on a Long Journey