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Organizational Learning and Distributed Innovation Planning Edward Anderson University of Texas McCombs School www.EdAnderson.org Nitin Joglekar Boston.

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Presentation on theme: "Organizational Learning and Distributed Innovation Planning Edward Anderson University of Texas McCombs School www.EdAnderson.org Nitin Joglekar Boston."— Presentation transcript:

1 Organizational Learning and Distributed Innovation Planning Edward Anderson University of Texas McCombs School Nitin Joglekar Boston University School of Management INFORMS 2006

2 2 © Anderson & Joglekar 2006 Motivation Distributed Innovation Planning P Portfolio Elements L Locations, M Skills Q Projects S 1 S 2 S p L 1 J 1 L 1 J 2 L 2 J 1 L n J m I 1 T 1 I 1 T 2 I 2 T 1 I 2 T 3 I Q 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!

3 3 © Anderson & Joglekar 2006 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)

4 4 © Anderson & Joglekar 2006 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?

5 5 © Anderson & Joglekar 2006 Capability Dynamics Evolution of Benefits & Risks Product Development is a Complex System, Literally. Performance Gap Desired Product Performance Product Performance Capabilities Investment O Legislative Shocks O Market Wants R DELAY Market Shocks Technology Shocks Project Execution Shocks & Uncertainties Target Setting Uncertainties & Biases MARKET CO-EVOLUTION R CAPABILITY DEVELOPMENT B PRODUCT PORTFOLIO IMPROVEMENT

6 6 © Anderson & Joglekar 2006 Capability Dynamics Three 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. Performance Gap Desired Product Performance Product Performance Capabilities Investment O Market Wants R DELAY MARKET CO-EVOLUTION R CAPABILITY DEVELOPMENT B PRODUCT PORTFOLIO IMPROVEMENT Effects of random shocks suppressed for clarity

7 7 © Anderson & Joglekar 2006 Evolution of R&D Capability* * Source: Miranda 2003

8 8 © Anderson & Joglekar 2006 Market … Wants Market 3 Wants Market 2 Wants Performance of Product … Performance of Product 3 Performance of Product 2 Capability… Capability 3 Capability 2 Multi Dimensional Dynamics With 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! Performance Gap Desired Product Performance Performance of Product 1 Capability 1 Investment O Market 1 Wants R DELAY MARKET CO-EVOLUTION R CAPABILITY DEVELOPMENT B PRODUCT PORTFOLIO IMPROVEMENT

9 9 © Anderson & Joglekar 2006 Consequences of Complexity Two Metaphors for Product Development 1.All pool players act indirectly upon their playing environment 2.Good pool players plan ahead for contingencies while modularizing risk or CAPABILITIES POTENTIAL PRODUCTS MARKET SPACE

10 10 © Anderson & Joglekar 2006 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

11 11 © Anderson & Joglekar 2006 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

12 12 © Anderson & Joglekar 2006 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

13 13 © Anderson & Joglekar 2006 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

14 14 © Anderson & Joglekar 2006 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

15 15 © Anderson & Joglekar 2006 Questions? We welcome your feedback …

16 Backup Slides

17 17 © Anderson & Joglekar 2006 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?

18 18 © Anderson & Joglekar 2006 Backup Graphics Three Modes of Organization Learning

19 19 © Anderson & Joglekar 2006 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).


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