Professor Philippe Baumard

IAE Aix en Provence – Graduate School of Managment

May 2001 - MBA Seminar

Information Technology Seminar IAE Aix en Provence - Tias Business SchoolMay 9, 2001

Knowledge Rents and Knowledge Rents and Competition : Competition : Understanding Understanding

Tomorrow ’s Business ModelsTomorrow ’s Business Models

Research Background & Objectives Field experience in knowledge management in large firms

Large firms undertake extensive expenses for common knowledge

They usually disregard sophisticated and superior knowledge (Wilensky, 1967)

They strategize having access to the same information (Starbuck, 1992)

Research on knowledge management (1991-1997) Insight: Tacit knowledge in organizations is a key resource

when firms face crises and ambiguous situations (Baumard, 1994)

Research question: How to develop a sustainable competitive advantage from knowledge rents and asymmetries ?

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Disturbing Assumptionson Knowledge & Competition

Competitive advantage derives from rich, superior knowledge Knowledge-based view of the firm (after Penrose, 1959)  :

growth is explained by idiosyncratic managerial resources that are superior to competitors’ (Spender, 1989 ; Scribner, 1986 ; etc.)

Structural perspective of strategy (Porter, 1980, etc.) : superior intelligence of competitors’ capacities, moves, intents leads to superior plans

Confusion between scarcity and superiority ; secrecy and value The Cola formula might not be superior knowledge, but it’s

secret ; as Michelin tires  ; DeBeers’ extraction processes  ; etc. When knowledge is scarce, people tend to believe in its

superiority (Wilensky, 1967)  ; i.e. Orange County administrators’ belief in the superiority of derivative products or Indosuez’s hunt for derivative experts  ; readers of confidential newsletters (Baumard, 1994)

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Why Knowledge used in competitionis poor...

Poor as opposed to Elaborate Superficial, driven by beliefs (as opposed to Geertz’ ‘thick

understanding”)  : simple loop learning without impregnation  Poor as opposed to Articulated

Unsystematic, uncodified, unorganized Poor as opposed to Extensive

Learning from samples of one (March, Sproull, Tamuz, 1991) Poor as Conjectural and Purposive

Driven by results rather than the search for truth (i.e cunning, Hollis,1987)

Combined from opportunism and flair, rather than reason and analysis (Détienne & Vernant’s mètis, 1974)

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The strategic objective : building long term competitive advantage on rich knowledge Rich knowledge in ethnographic terms (Geertz, 1983)

Dense, rich descriptions, intensive use of qualitative data, sense-making driven organizations

Rich knowledge in terms of intensity (KIF) Concentration of know-how in minimal teams, intensity of expertise,

renewal of know-how

Rich knowledge in terms of variety (scope) Large scope of knowledge bases, organizational culture that favors

diversity

Downstream & customer designed and derived Expertise and know-how is constantly internalized from lead users

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Developing Knowledge Rents Customer Relational Knowledge

1-to-1 relations : personalization of preferences, interface, knowledge of behavior, preferences (like & do not like)

Communities of customers : Group behavior, pattern recognition, management of groups / clans / communities.

Industry Knowledge License management & preemption : interpersonal knowledge

between negotiators R&D and creative streams : upstream head hunting ; early

preemption of innovations ; downstream co-development (implication of lead users in product design)

Tacit collective knowledge : “style” Patterns of implicit learning valued by the customers

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The Field : The on-line entertainment industry

“What value can be placed on game players ? The ability to manage such a potential customer base will ultimately be very valuable. Online games are moving us from orientation of audiences to capturing and retaining them.” BNP Equities, September 1999

“One group of companies looks particularly interesting to us from the “buy” standpoint. No one knows how to entertain viewers on the small screen better than those who have been successfully doing so for 15 years.” First Boston, February 1999

“[Gaming] communities have the following attributes : “stickiness”, a steady stream of traffic and large existing cutomer base, highly focused communities, a high-degree of user interaction, flexible, rich media advertising and sponsorship opportunities, compelling opportunities to sell merchandise to targeted audiences” Thomas Weisel Partners, February1999

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The on line game industry

20 millions on-line gamers 8.5 M on Microsoft’s Game Zone, 7 millions on Vivendi’s Won

(formerly Cendant Software), 2.2 millions on Battle.Net…

A learning laboratory for large telecommunications & entertainment group

Apprenticeship of real-time multimedia entertainment Technical laboratory for high speed connection and

interoperability

A large source of income From 88 millions $ in 1999, to 2,3 billions $ in 2002.

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Recent strategic moves

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Buyer

CheckOut.com

Eidos

Electronic Arts

CMGI

Lycos

AOL

Vivendi

Target

Gamespy

Maximum

Kesmai

Gamers.com

Gamesville

Electronic Arts

Cendant Soft.

Date

Août 99

Oct. 99

Oct. 99

Oct. 99

Oct. 99

Oct.99

Nov. 99

Strategic objective

The Michael Ovitz entertainment site is taking a major share in a « gaming community » site

Downstream integration : a software publisher builds his own on-line gaming platform

The leader of video games buy out the world pioneer in on-line gaming

The CMGI network acquires a gaming tools website, reaching the largest tools portfolio in the world.

The Lycos platform buys the largest casual gaming community & highly profitable, with 2.2. Millions users

AOL takes a major share in a leading simulation & sports video game producers

Vivendi integrates all Cendant software’s companies into a new entertainment unit, under Havas Interactive. Vivendi becomes the world’s second largest game producer.

Case study : www.goa.com

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Presentation of the company

The French leading on-line gaming platform 650.000 on-line gamers, with more than 239.000 hard-core

gamers (+25h/week). Strong leadership in gaming communities Pioneer in persistent games, massive multiplayer games (MMG)

A key weakness : no upstream integration All 120 games are negotiated through license agreements

A key strength : 50% market share Largest single user market share

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On-line gaming

Casual - per round on line gaming Chess, backgammon, fun games

On line strategy games Limited number of players (2-16) Rounds & contests Limited gameplay (2 to 16 hours)

Massive Multiplayer Games (MMG) No limits in the number of players (generally 20 to 200) Mapping and user’s design (map, skins, scenarios)

Persistent MMG Persistent environments (the game evolves independently from the player)

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The future of on-line gaming Competing with real life

French developer, Kalisto confirmed its first foray into online gaming this week with a game concept that will reportedly marry real life sporting events with Internet gameplay. According to Kalisto, its "Sportners" concept will enable unlimited online gamers to compete against sport professionals, live and in real-time. No word on what specific sport they will focus on first.

Sportners is protected by strong international patents. A software development company, Interactive Online Sports has been created in December 1999 by Kalisto Entertainment and the inventors of the project, Jacques Levasseur and Gérard Benkel.

Sportners utilizes Kalisto’s advanced 3D racing engine to recreate live sports events. The technology is based on the proprietary capture of real-time racing information. It enables players on the Internet to immerse themselves in the race, and compete against actual, real life participants from their personal computers or televisions.

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Grounding virtual experience in real life

Decreasing game life span Software producers have tripled R&D budgets to increase game

play from 15 hrs to 30+ (1998-2000) Budgets of games have jumped to US$5 - 10 Millions Life cycles have shrunk from 8 to 4 months

Growing demand for constant diversity Explosion of the map & scenario phenomena Success of Ultima & Everquest

There is nothing more diverse and surprising than real life Permanent input of independent variables Unpredictable behavior of real life competitors

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Capturing and retaining customers

Building a personal relation Organizational & interpersonal memory

Customers are known by their names or aliases Software engines learn their on-line and off-line behavior so to

adapt the mode of interaction to behaviors (on line text, vocal chat on IP, voice)

Implication Lead users (hard core gamers) are involved in the constant

design of the man-machine interface Creation of GOA-Aids and GOA-Leaders : recognition

Appropriation All users are given Extranet tools to build their own knowledge &

practice sharing space

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Encouraging stickiness

Definition of “stickiness” A high degree of loyalty of customers that leads to long

continuous periods of platform use by a single user, exclusive to other platforms’ use

Adhesion + Appropriation + Involvement Stickiness increases brand adoption, brand equity Stickiness is sine qua none to community marketing

Tools and strategies that increase stickiness Customer’s autonomy : freedom to design and develop Customer’s identity : recognition of inputs and value Their own knowledge & design tools

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Adapting the business model to communities

Community behavior “Word of mouth” / “Word of chat” :

Informal reputation building with informal leadership A strong sense of hierarchy among users :

Demand for acknowledged leadership and authority of a clan, community, squad, group.

Self-assessment & competitive assessment : Demand for tools that rank the clan’s performance, relative to

other gamers and other clans

Allergies to mass-customization & mass media No spamming

Traditional direct marketing techniques have constantly failed Respect of communities’ dissident nature

Alternative ways of addressing customers’ demands

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Discussion : Knowledge and Competition “Valid Learning” vs. Deep Understanding

To believe that firms favor a deep understanding of their environments is an “academic bias” : findings are consistent with Starbuck’s “action generators” (1983) or March, Sproull, Tamuz’s “learning from samples of one” (1991)

Profitability of studied firms does not appear to be linked with their consultants’ expertise

Formal knowledge structures serve as institutional “façades” Observations corroborate Fahey & King’s findings (1977)  : firms

are informal and unsystematic in their interpretation. They favor collateral and transient organizations (Zand, 1981 ; Wilensky, 1967).

Poor knowledge favors determination Aggression is an auto-reinforced process. Excess of knowledge

impedes determination (i.e. success of Branson in the airline industry)

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Limits and Future Research

Limits Knowledge practice relies on accuracy and value for action

Abstractive and cumulative knowledge is not the purpose  ; the same research could be conducted in the professional firms industry (Anderson, Coopers & Lybrand, etc.)

External validity is limited by the fewness of numbers Participant observation may impeded internal validity

Future research Field research on innovation processes : are “valid learning”-

driven firms more innovative than “abstractive/exhaustive learning”-driven firms   ?

The superiority of “double loop learning” in consumer interactions, vs. Single-loop learning ?

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