organizational learning and distributed innovation planning edward anderson university of texas...

Organizational Learning and

Distributed Innovation Planning

Edward AndersonUniversity of Texas McCombs Schoolwww.EdAnderson.org

Nitin JoglekarBoston University School of Managementhttp://people.bu.edu/joglekar/

INFORMS 2006

© Anderson & Joglekar 2006 2

Motivation Distributed Innovation Planning

P Portfolio Elements

L Locations, M Skills

Q Projects

S 1 S 2 S p

L1 J 1 L1 J 2 L2 J 1Ln J m

I1 T 1 I1 T 2 I2 T 1 I2 T 3 I2 T 3 IQ T 1

• Multiple linkages and uncertainties • Network analysis (NP Hard Problem): Must use heuristics, business rules/IS

Modular Choices

Modular learning lies is at the heart this planning problem!


Distributed Innovation Literature Sourcing Decisions

Socio-political issues Hidden costs of coordination/vertical integration

Chaos & Emergence Risks Adaptive behaviors (Brown & Eisenhardt) Modularity is touted as a solution (Baldwin & Clark, Sosa et al, Ethiraj & Levinthal)

Organizational Learning Explore or Exploit (March, Katila & Ahuja) Integration (Anderson & Parker) Ex-post selections (Sommer & Loch)


Research Questions What implications does distributed

product development have for organizational learning and vice-versa?

How can the risk inherent in distributed product development be managed through modularization of capabilities?

What risks does modularizing capabilities pose for organizational learning and distributed innovation?


Capability DynamicsEvolution of Benefits & Risks

Product Development is a Complex System, Literally.

PerformanceGap

Desired ProductPerformance

ProductPerformance

Capabilities

Investment

O

LegislativeShocks

O

Market Wants

R

DELAY

DELAY

DELAY

Market Shocks

TechnologyShocks

Project ExecutionShocks &

Uncertainties

Target SettingUncertainties &

Biases

MARKETCO-EVOLUTION

R

CAPABILITYDEVELOPMENT

B

PRODUCTPORTFOLIO

IMPROVEMENT


Capability DynamicsThree Modes of Learning to Create & manage Complexity

1. Market develops its preferences through experience with the product, sometimes in unpredictable ways (Market Co-Evolution).

2. Firm improves its product portfolio by learning about the market.3. Firm improves its capability portfolio by developing products.

PerformanceGap


ProductPerformance

Capabilities

Investment

O

Market Wants

R

DELAY

DELAY

DELAY

MARKETCO-EVOLUTION

R


B

PRODUCTPORTFOLIO

IMPROVEMENT

Effects of random shocks suppressed for clarity


Evolution of R&D Capability*

* Source: Miranda 2003


Market … WantsMarket 3 Wants

Market 2 Wants

Performance ofProduct …

Performance ofProduct 3


Capability…Capability 3

Capability 2

Multi Dimensional DynamicsWith multiple capabilities,many products, and detached markets

Capabilities, Products and Markets are multi-dimensional and have many-to-many interconnections, with goal setting processes and delays!

PerformanceGap



Capability 1

Investment

O

Market 1 Wants

R

DELAY

DELAY

DELAY

MARKETCO-EVOLUTION

R


B

PRODUCTPORTFOLIO

IMPROVEMENT


Consequences of ComplexityTwo Metaphors for Product Development

1. All pool players act indirectly upon their playing environment2. Good pool players plan ahead for contingencies while modularizing risk

or

CAPABILITIES

POTENTIAL PRODUCTS

MARKETSPACE


Playing Pool within the Distributed Innovation Space?

Roadmap planning for product portfolios with contingencies (resources) with three modes of learning

Invest in capabilities to support the portfolio using a real options approach

Modularize your capabilities to support contingencies Using the six modular operators* to deal with

randomness, co-evolution, & tipping points

* Split/exclude/substitute/augment/invert/port


Capability Interactions Resources

Separate projects require same capability; potential domino effect

One capability dependent upon another• Complementarity if dependence is mutual

Communication Interaction with other capabilities within projects (defined by

architecture) • Overall product integration

Bundled or complementary products Piggybacking: Two projects utilizes the same capability to

develop a common modular component Knowledge

Later projects require information (tacit knowledge, education, prior projects or diffusion) from capabilities developed during earlier projects


Capability Modularization Strategems

Time and resource buffering By e.g. sacrificial functionality Isolate inter-capability risks (e.g. Intel’s operations strategy)

Modular, uniform architecture & common business processes Encapsulates capability Provides “plug and play” personnel from each capability Enables off-the-shelf components

Fungible skill-sets Substitute capabilities Fungible capabilities (perhaps through cross-training)

“A, B, C” Capability Map Insourcing, partial insourcing/in-house experts, complete

outsourcing (Linked to real options approach) Utilize in combination with a ring-of-defense personnel strategy


Risks to Organizational Learning Capabilities are tacit knowledge

Vulnerable to turnover Requires intra and inter-capability knowledge diffusion

Common architecture and business processes promote “core rigidities” Tendency to ignore scouting except by integrative

personnel and executives, reducing absorptive capacity Excessive overhead for mature industries

Starves investment in current capabilities


Recap Product development is a complex system amenable to

scenario planning using a real-options approach Complexity created and managed by three learning loops: capability,

product portfolio, and market Capability planning is a high leverage activity

Modular risk management Risks to organizational learning

Managerial Implications In non-mature industries, use of scenario planning, with three modes

of learning, to determine a long-term capability strategy is key Modularizing capability risk must be seen as a necessary hedge to

enable long-term viability Research Implications

Examine capability modularity in a manner analogous to study of component modularity

Formal specification and testing of three modes of learning


Questions?

We welcome your feedback …

[email protected]

www.EdAnderson.org

Backup Slides


How Do We Play Pool with Distributed Innovation Product development is not predictable, but may be amenable to scenario planning Hence, you can plan for developing capabilities using a real-options approach, but

you may need to these recombine these capabilities quickly. This is only reinforced by the need to launch multiple test product probes to promote product

learning to match market’s evolution of tastes (of course these coevolve, so you do get a Red Queen effect)

One way to do this is to modularize your capabilities (by encapsulating business units with standard business processes), then capabilities (i.e. people) can be inserted and removed as necessary from a product’s development. Of course each product’s organization will need to be modularized as well.

Also recommends test products, both to probe the shape of market demand and also to provide development of capabilities.

Suggests a decentralized, modular architecture for capabilities, whose carriers of tacit knowledge are people.

Created by splitting, inversion, and porting through encapsulation. Advantages: speed of reaction to market, allows augmentation, substitution, exclusion, Disadvantages: Opportunism and other bad behavior, overhead from encapsulation (learning

standard business processes), and threats to organizational learning. How does this modular organization of technical capabilities diminish or create risk,

and what threats do these make to organizational learning?


Backup Graphics

Three Modes of Organization Learning

PerformanceGapDesired Product

Performance

ProductPerformance

Capabilities

Investment

O

LegislativeShocks

O

Market Wants

R

DELAY

DELAYDELAY

Market Shocks

TechologyShocks

Project ExecutionShocks &

Uncertainties

Target SettingUncertainties &

Biases

MARKETDIVERGENCE

R


B

PRODUCTIMPROVEMENT


Marginally shuffled Nutshell Argument (NRJ) Market, product, and capability learning create a complex system

Some researchers assume that the planning landscape is given, and call for scenario planning (with ex-post selectionism and learning) with provisions for contingencies, both foreseen and unforseen (unk-unks)

We argue that the landscape is not entirely random because there are basins of attraction. Furthermore, there is feedback between the market, your products, and your capabilities, so you may be able to shape your future (cars with safety features) in a modular manner. But tipping points all over, and even these modular actions are unpredictable.

Research Questions: How does one modularize capability risk? And, what are the downsides to modularizing capability risk for organizational learning, esp. innovation?

• Carriers of tacit knowledge (capabilities) are people• Interactions between capabilities• Potential remedies

Hypotheses: • Three modes of learning for managing this risk!• Best dealt with by roadmap to develop capabilities through product introductions (which

also improve market learning).

organizational learning and distributed innovation planning edward anderson university of texas...

Documents

capability capability

capability portfolio

anderson joglekar

capability dependent

product portfolios

evolution of rd capability

intercapability risks

multiple capabilities