© 2004 Chintan Vaishnav, Engineering Systems Division, Massachusetts Institute of Technology
Does Technology Disruption Always MeanIndustry Disruption?
Chintan [email protected]
Engineering Systems DivisionMassachusetts Institute of Technology
July 23, 2008 Plenary PresentationThe International Conference of System Dynamics
Athens, Greece
2© 2008 Chintan Vaishnav, Engineering Systems Division, Massachusetts Institute of Technology
Christensen’s Conditions for Disruptive Technology
Example Cases:Mini millsDisc Drives
Ref: The Innovator’s Dilemma,Clayton Christensen (1997)
HighLowLowEntrantLowHighHighIncumbent
AncillaryPerformance(AdditionalFeatures)
PrimaryPerformance
(Basic Features)
PriceFirm
Time/Engineering Effort
Prod
uct P
erfo
rman
ce
First (incumbent) Technology
Second (entrant)Technology
Question: Are Christensen Conditions necessary and sufficientfor industry disruption?
3© 2008 Chintan Vaishnav, Engineering Systems Division, Massachusetts Institute of Technology
Technologies in Computer and Communications Industries
Have they displaced the existing industrial order?
Potentially Disruptive Technology
Price ComparedTo Incumbent
Primary PerformanceComparedTo Incumbent
Ancillary PerformanceComparedTo Incumbent
LOWOften free
LOWLow initialreliability andease of use
HIGH- Quick bug fixing- Code customization
MeetsChristensenConditions
LOWCheaper tobuild and operate
LOWLow mobility
HIGH- Higher speed- Wireless-Wired interconnection
MeetsChristensenConditions
LOWOften free
LOWLow reliability
HIGH-Voice, Text, Video convergence
MeetsChristensenConditions
Open SourceSoftware[OperatingSystems]
WiFi MeshNetworks[WirelessOperators]
P2P ServiceProviders[Long DistanceCall Providers]
Do they meet Christensen Conditions?
4© 2008 Chintan Vaishnav, Engineering Systems Division, Massachusetts Institute of Technology
Industry Structure in Computer and CommunicationsIndustries
What factors influence such variation in outcome?
Potentially Disruptive Technology
IndustryStructure(2000)
IndustryStructure(2007) Key Observations
Open SourceSoftware[OperatingSystems]
WiFi MeshNetworks[WirelessOperators]
P2P ServiceProviders[Long DistanceCall Providers]
1. Microsoft2. IBM3. CSI4. Oracle5. HP
Microsoft still has90% of the OS market
No IndustryDisruption
1. Microsoft2. IBM3. Oracle4. SAP5. Symantec
1. Verizon2. SBC3. AT&T WL4. Sprint PCS5. Nextel
1. AT&T2. Verizon3. Sprint-Nextel4. T-mobile5. Alltel
1. AT&T2. WorldCom3. Others4. Sprint
1. AT&T2. Verizon3. Comcast4. Time Warner5. Charter
MajorIndustryChanges
-Broadband providersown parts of accessmarket -P2P Service big inKorea and Japan
-AT&T and T-Mobile own 1/3 US hotspots-Nokia, Samsung, lead Wireless-WiFI handset market
No IndustryDisruption
5© 2008 Chintan Vaishnav, Engineering Systems Division, Massachusetts Institute of Technology
Model Setup and Assumptions
• A behavioral model (akin to behavioral game theory model)• 2 Firms – Incumbent, Entrant• 20 year period (think technology paradigms…)• Incumbent enters at Year 0• Entrant enters at Year 6 (when incumbent is mature)• Firms initialized with Christensen’s conditions…– Entrant has half Cost base than Incumbent– Entrant has half Initial Primary Performance than Incumbent– Entrant has double the Initial Ancillary Performance than Incumbent
• Both firms endowed with a total attention (resources) = 1• Each firm allocates resources to Primary and Ancillary Performance only• Consumers are homogenous in their preferences
6© 2008 Chintan Vaishnav, Engineering Systems Division, Massachusetts Institute of Technology
Adopters
Switching
Fractiona l Net
Population Growth
Rate
+
Potential
Adopte rsAdoption
Pote ntial
MarketNet Population
Growth Rate
Adoption from
AdvertizingAdoption from
WOM
+ +
Advertizing
EffectivenessContact
RateAdoption
Fraction
++
+
++
<Market Entry
Switch>
Industry De ma nd
Refere nce Price
<PotentialMarket>
De mand Curve
Slope
Refe rence
Popula tion
Reference Industry
Demand Ela sticity
Lowest Price
<Price>
Adoption and Industry Demand
7© 2008 Chintan Vaishnav, Engineering Systems Division, Massachusetts Institute of Technology
Consumer Preference and Behavior
Product
Attractiveness
Attractiveness from
Primary Performance
+
Attractiveness from
Ancillary Performance
+
Price
-
8© 2008 Chintan Vaishnav, Engineering Systems Division, Massachusetts Institute of Technology
Consumer Preference and Behavior
Adopters
Attractiveness from
Installed Base
Product
Attractiveness
Market Share of
Product
Attractiveness
Total Product
Attractiveness
+
+
+
+
+
-
Attractiveness from
Primary Performance
+
Attractiveness from
Ancillary Performance
+
Price
-
R1
Network Effect
B1
Market Saturation
9© 2008 Chintan Vaishnav, Engineering Systems Division, Massachusetts Institute of Technology
Consumer Preference and Behavior
Adopters
Attractiveness from
Installed Base
Product
Attractiveness
Market Share of
Product
Attractiveness
Total Product
Attractiveness
+
+
+
+
+
-
Switching to
Competitor
-
-
Attractiveness from
Primary Performance
+
Attractiveness from
Ancillary Performance
+
Price
-
R1
Network Effect
B1
Market Saturation
B2
Switching Behavior
10© 2008 Chintan Vaishnav, Engineering Systems Division, Massachusetts Institute of Technology
Corporate Strategy: Incumbent’s Initial Focus
Adopters
Attractiveness from
Installed Base
Product
Attractiveness
Market Share of
Product
Attractiveness
Total Product
Attractiveness
+
+
+
+
+
-
Switching to
Competitor
-
-
Attractiveness from
Primary Performance
Primary
Performance
Resources to
Primary
Performance
Market Share+
+
+
+
+
Attractiveness from
Ancillary Performance
+
Price
-
R1
Network Effect
R2
Primary
Performance
Effect
B1
Market Saturation
B2
Switching Behavior
“The only strategy was that of a monopolist. Incumbent A did not care what Other features you want!” Director, CTO Organization, Incumbent A
• Based on 4 Interviews– 2 Incumbents, 2 Entrants
11© 2008 Chintan Vaishnav, Engineering Systems Division, Massachusetts Institute of Technology
Adopters
Attractiveness from
Installed Base
Product
Attractiveness
Market Share of
Product
Attractiveness
Total Product
Attractiveness
+
+
+
+
+
-
Switching to
Competitor
-
-
Attractiveness from
Primary Performance
Primary
Performance
Resources to
Primary
Performance
Market Share+
+
+
+
+
Entrant's Expected
Market Share
Attention to
Ancillary
Performance
Effect of Entran'sMarket Share on
Attention to AncillaryPerformance
Resources to
Ancillary
Performance
Ancillary
Performance
Attractiveness from
Ancillary Performance
+
+
+
+
+
Price
-
-
-
R1
Network Effect
R2
Primary
Performance
Effect
B1
Market Saturation
B2
Switching Behavior
B3
Diversification into
Ancillary Performance
R3
Resource
Conservation
ResourceReorientation
Delay
Corporate Strategy: Incumbent’s Response to Entrant
“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
12© 2008 Chintan Vaishnav, Engineering Systems Division, Massachusetts Institute of Technology
Effect of Entrant’s Market Share on Attention toAncillary Performance
Entrant’s Expected Market Share
Incu
mbe
nt’s
Atte
ntio
n to
A
ncill
ary
Perf
orm
ance
“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
13© 2008 Chintan Vaishnav, Engineering Systems Division, Massachusetts Institute of Technology
Resource Diversification
1 – Resources toAncillary Performance
0.8Entrant
1 – Resources toAncillary Performance
SMOOTH(Attention to AncillaryPerformance,Resource Reorientation Delay)
Incumbent
Resources to PrimaryPerformance
Resources to AncillaryPerformance
“First you have to write a report, then convince the leadership, and then the people who will work on it.” Director, CTO Organization, Incumbent A
Resource Reorientation Delay
Entrant’s Resources“After the prototype phase, 80% attention is on developing new features (ancillary performance) and 20% on scale and reliability (primary performance).” CTO, Entrant A
“New features is our forte. We are not going after the incumbent. The primary performance will come as a byproduct.” CEO, Entrant B.
14© 2008 Chintan Vaishnav, Engineering Systems Division, Massachusetts Institute of Technology
Base Case BehaviorPassive Base Case - Incumbent does not respond to threatActive Base Case - Incumbent responds to threat
Adopters200 M
150 M
100 M
50 M
0 3 3 3
3
33 3 3 3 3
1
1
11
1
1 1 1 1 10 24 48 72 96 120 144 168 192 216 240
Time (Month)
Uni
t
Adopters[Incumbent] : Passive Base Case 1 1 1 1 1
Adopters[Entrants] : Passive Base Case 3 3 3 3 3
4 4 4
4
44
4 4 4
2
22 2
22
22 2 2
Adopters[Incumbent] : Active Base Case 2 2 2 2 2
Adopters[Entrants] : Active Base Case 4 4 4 4 4 4
Note: We have created the basic reference mode
15© 2008 Chintan Vaishnav, Engineering Systems Division, Massachusetts Institute of Technology
Technological Uncertainty:Primary Performance Acquisition Delay
Technological uncertainty can help either the incumbent or the entrant
Adopters200 M
150 M
100 M
50 M
0 1
1
1
11
1 1
0 24 48 72 96 120 144 168 192 216 240Time (Month)
Uni
t
Adopters[Incumbent] : Active Base Case 1 1 1 1 1
4 4
4
4
4 4
Adopters[Entrants] : Active Base Case4 4 4 4 4 4
5 5
5 55 5
2
2
2
22
2 2
Adopters[Incumbent] : Primary Performance Ack Short 2 2 2 2
Adopters[Entrants] : Primary Performance Ack Short 5 5 5 5
6 6
66
6 63
33
3
33 3
Adopters[Incumbent] : Primary Performance Ack Long 3 3 3 3
Adopters[Entrants] : Primary Performance Ack Long 6 6 6 6
16© 2008 Chintan Vaishnav, Engineering Systems Division, Massachusetts Institute of Technology
Market Uncertainty: Network Effect
Adopters200 M
150 M
100 M
50 M
0 4 4
4
4
4 4
1
1
1
11
1 1
0 24 48 72 96 120 144 168 192 216 240Time (Month)
Uni
t
Adopters[Incumbent] : Active Base Case 1 1 1 1 1
Adopters[Entrants] : Active Base Case4 4 4 4 4 4
5 5
5
5 5 5
2
2
2
22 2 2
Adopters[Incumbent] : Network Effect Lo 2 2 2 2 2
Adopters[Entrants] : Network Effect Lo5 5 5 5 5
Adopters[Incumbent] : Network Effect Hi 3 3 3 3 3
3
3
3 3 3 3 3
6 6 6 6 6 6
Adopters[Entrants] : Network Effect Hi 6 6 6 6 6
With network effects the equilibrium can be winner take all (WTA). The strength of network effect determines the winner
17© 2008 Chintan Vaishnav, Engineering Systems Division, Massachusetts Institute of Technology
Market Uncertainty: Switching Costs
Higher the switching costs the longer the incumbent retains the market.Longer retention buys time to reorient resources.
Adopters200 M
150 M
100 M
50 M
0 4 4
4
4
4 4
1
1
1
11
1 1
0 24 48 72 96 120 144 168 192 216 240Time (Month)
Uni
t
Adopters[Incumbent] : Active Base Case 1 1 1 1 1
Adopters[Entrants] : Active Base Case4 4 4 4 4 4
5 5
5 55 5
2
22
22 2 2
Adopters[Incumbent] : Switching Cost Exogenous Lo 2 2 2 2
Adopters[Entrants] : Switching Cost Exogenous Lo 5 5 5 5
6 6
6
66
6
3
33
33
33
Adopters[Incumbent] : Switching Cost Exogenous Hi3 3 3 3 3
Adopters[Entrants] : Switching Cost Exogenous Hi 6 6 6 6
18© 2008 Chintan Vaishnav, Engineering Systems Division, Massachusetts Institute of Technology
Organizational Uncertainty: Resource Reorientation Delay
50% 75% 95% 100%Adopters[Incumbent]200 M
150 M
100 M
50 M
00 60 120 180 240
Time (Month)
The nature of technology and market matter more than firm’s agility. This is for future work…
19© 2008 Chintan Vaishnav, Engineering Systems Division, Massachusetts Institute of Technology
Conclusion
Technology Disruption Does Not Always Mean IndustryDisruption!
Technology disruption may not change the existing industrialorder despite meeting Christensen’s Conditions when…
•The incumbent can maintaining the lead in Primary Performancewhile improving their Ancillary Performance
• Strong Network Effects are present
• The incumbent can influence the Switching Behavior
Our research argues for broadening the research agendaaround understanding industry disruption
© 2004 Chintan Vaishnav, Engineering Systems Division, Massachusetts Institute of Technology
Thank You!
Chintan [email protected] Systems DivisionMassachusetts Institute of Technology