Using System Dynamics to Understand Disruption: A ...cfp.mit.edu/events/10Apr/Chintan Vaishnav-CFP...

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Using System Dynamics to Understand Disruption: A General Model for Technology and Industry Disruption

Chintan Vaishnav MIT

© 2010 Chintan Vaishnav, MIT

Steps in the System Dynamics Modeling Process

  Problem Articulation   What is the problem?   Key Variables   Time Horizon

  Formulating Dynamic Hypotheses   Formulation of a Simulation Model

  Causal Loops, Stocks and Flows   Estimation

  Testing and Validation   Consistency with the purpose and boundaries   Comparison with Expected Behavior   Robustness of the Model   Sensitivities and other tests

  Policy Evaluations

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© 2010 Chintan Vaishnav, MIT 3

Problem/Research Question

How can we improve decision making amidst technology and industry disruption?


Model Formulation, Testing, and Validation


Model: Philosophy and Principles

Regulatory

Policy

Dynamics

Technology

Dynamics

Corporate Strategy

Dynamics

Industry

Structure

Dynamics Customer

Preference

Dynamics

Telecommunications System

Technology

Dynamics

Regulatory

Policy

Dynamics

Corporate

Strategy

Dynamics

Industry

Structure

Dynamics

Customer

Preference

Dynamics

Subsystems Subsystem-level behavior

Analysis

Emergent (system-level) behavior

Synthesis

Innovation and competition emerge from the interaction of five gears…

Ref: Gear Model, Charles Fine

Model formulations rest upon: 1.  Theories of adoption, tech strategy, and innovation 2.  Unstructured interviews with stakeholders


Example: Model based on Theory

Firm Price Primary Performance (Quality)

Ancillary Performance (Innovation)

Incumbent (e.g. AT&T)

High High Low

Entrant (e.g. Skype) Low Low High

Christensen’s Conditions for Disruptive Technology (Christensen 1997)

Customer

Preference

Dynamics

Assumptions: •  2 Firms – Incumbent, Entrant •  Each firm represents a typical firm in their industry


Example: Model based on Unstructured Interviews

Corporate Strategy

Dynamics

Customer

Preference

Dynamics

Assumption: •  Features of each service are separable into (identifiable as) primary performance (quality) and ancillary performance (innovation)


Example: Model based on Unstructured Interviews (Contd.) (making Firm’s Strategy endogenous)

Corporate Strategy

Dynamics

Customer

Preference

Dynamics

Assumption: Both firms endowed with equal total attention (resources)

Price

Product Attractiveness

Adopters +

+ -

Firm's Market Share +

Maximum Ancillary

Performance

Time to Acquire Ancillary

Performance

Resources to Ancillary

Performance

+ - Ancillary

Performance

Primary Performance

-

+

Resources to Primary

Performance -

+

+ +

Time to Acquire Primary

Performance Maximum Primary

Performance + -

R1 Network Effect

innovation

quality

B4 Effect of Competitive

Pressure on Innovation

R5 Effect of Competitive Pressure on Quality

Effect of Firm's Expected Market Share on Resources

to Ancillary Performance

“The only strategy was that of a monopolist. Incumbent A did not care what other features you want!” Director, CTO Organization, Incumbent A

-


Example: Model based on Unstructured Interviews (Contd.) (making Firm’s Strategy endogenous)

Corporate Strategy

Dynamics

Customer

Preference

Dynamics

“Incumbent cares about ancillary performance only with: the entry of the non-traditional competitor, and the growth of its market share.” Director, CTO Organization, Incumbent A

Assumption: Both firms endowed with equal total attention (resources)

Price

Product Attractiveness

Adopters +

+ -

Firm's Market Share +

Maximum Ancillary

Performance

Time to Acquire Ancillary

Performance

Resources to Ancillary

Performance

+ - Ancillary

Performance

Primary Performance

-

+

Resources to Primary

Performance -

+

+ +

Time to Acquire Primary

Performance Maximum Primary

Performance + -

R1 Network Effect

innovation

quality

B4 Effect of Competitive

Pressure on Innovation

R5 Effect of Competitive Pressure on Quality

Effect of Firm's Expected Market Share on Resources

to Ancillary Performance

Competitor's Market Share

+ Effect of Competitor's

Market Share on Resources to Ancillary Performance

-


Example: Model based on Unstructured Interviews (Contd.)

“First [when the entrant enters] the question is whether this is a price game or a performance game. Then, you realize that the future is ancillary.” Chief Strategist and Architect, Incumbent B

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9

1

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Competitor’s Expected Market Share

Firm’s Attention to Innovation (Ancillary Performance)

As competitor gains market share

more risk aversion

Effect of Competitor’s Market Share on Resources to Innovation


Model Testing and Analysis

Model Verification, Validation

1.  Calibration with real-world trends 2.  Expert Opinion: Regulators (FCC, MIAC-Japan), Industry Architects

and Strategy Experts (Motorola, BT, Nokia, Cisco, Comcast, Verizon), Academics (Primary Sources)

Testing 1.  Sensitivity of each exogenous parameter (including those that were

made endogenous later) 2.  Analysis of a unit model to understand structural forces and incentives 3.  Analysis of calibrated model to understand timing and magnitude of

the forces 4.  Industry Structure Scenarios

  Integrated Incumbent Remains Dominant   Niche Entrant, modular in technology and industry structure, displaces the

Incumbent   Erstwhile Entrant (new Incumbent in the modular structure) remains

dominant with a new modular entrant present


Model Validation

100

75

50

25

0

1935 1943 1951 1959 1967 1975 1983 1991 1999 2007 Time (Year)

% Households

PSTN Penetration : Model

PSTN Penetration : Data Source: FCC NECA & USAC Data (2008)

Through calibration with data, agreement with shared mental models of stakeholders, and expert opinion

PSTN Calibration


Results

© 2010 Chintan Vaishnav, MIT

Base Case Behavior Passive Base Case - Incumbent does not respond to threat Active Base Case - Incumbent responds to threat

Adopters 200 M

150 M

100 M

50 M

0 3 3 3

3

3 3 3 3 3 3

1

1 1

1

1 1 1 1 1 1

0 24 48 72 96 120 144 168 192 216 240 Time (Month)

Adopters[Incumbent] : Passive Base Case 1 1 1 1 1 Adopters[Entrants] : Passive Base Case 3 3 3 3 3

4 4 4

4

4 4

4 4 4

2

2 2 2

2 2

2 2 2 2

Adopters[Incumbent] : Active Base Case 2 2 2 2 2 Adopters[Entrants] : Active Base Case 4 4 4 4 4 4


Market Uncertainty: Network Effect Phase Plot

0

10

20

30

40

50

60

70

80

90

100

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2 2.4 2.8

Strength of Network Effect Sensitivity of Attractiveness to Compatibility (εn)

Max. Market Share

(Entrant)

No Network Effect (Services Interoperate)

Network Effect Helps Entrants Network Effect Helps Incumbents

Winner Takes All (WTA) outcome less probable Winner Takes All (WTA) outcome more probable


Market Uncertainty: Switching Cost Phase Plot

0

2

4

6

8

10

12

14

4% 3% 2% 1% Same -1% -2% -3% -4%

% of Incumbent's Consumers Considering Switching Relative to % of Entrant's Consumers

Time of Disruption (Years)

Time at which Entrant’s Market Share Crosses Incumbent’s Market Share

γ1 < γ2 γ1 > γ2


Market Uncertainty: Consumer Choice Phase Plot

0

10

20

30

40

50

60

70

80

90

100

0 1 2 3

Sensitivity of Attractiveness of Attribute under Consideration

Max. Market Share

(Entrant)

Sensitivity of Attractiveness of Any Other Attribute

Consumers Value the Attribute as much as

Other Attributes

Consumers Value the Attribute Twice

as much as the Other Attributes Consumers Value the

Attribute Thrice As much as

the Other Attributes

Consumers Do Not Value the Attribute

εn

εi

εq

εp


Limits to Technology and Industry Disruption

Technology Disruption

No Technology Disruption

Industry Disruption

No Industry Disruption

•  Weak Network Effect •  Consumer highly price sensitive and willing to risk adopting innovative service with low quality and compatibility

Quadrant Not Studied •  General double helix dynamics without technology disruption

•  Strong Network Effect •  Consumer value quality and compatibility over innovation and low price

•  Incumbents can affect switching behavior heavily •  Incumbents innovate while maintaining quality •  Entrants struggle to offer quality due to lack of functional control or market power


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