Winning the Hardware Software Game book Winning the Hardware-Software Game

Using Game Theory to Optimize the Pace of New Technology Adoption

Innovators of new technology systems requiring users to combine both hardware and software components often face delays in adoption of their new systems.  Users will not buy the hardware until enough software or content is available, while at the same time software providers will not provide content until enough users have adopted the new system.  This book examines the dynamics of this adoption process and provides methods for optimizing the pace of adoption of new technology systems.     Read more...

Why is network anatomy so important to characterize? Because structure always affects function.

– Steven H. Strogatz

Networks that seek commercial success must develop and maintain the ability not only to change in the face of highly competitive environments, they must also be able to adapt in ways that influence that environment.

– Robert Rycroft

“Everyday inventors don’t let themselves be limited like the rest of us do. They open their minds to the possibilities.”

– Rini Paiva, US National Inventors Hall of Fame

Yet the secret of evolution is the continual emergence of complexity. Simplicity brings a spareness, a grit; it cuts the fat. Yet complexity makes organisms like us possible in the first place.

– W. Brian Arthur

Natural selection may explain the survival of the fittest, but it can not explain the arrival of the fittest.

– Hugo De Vries

External vs. Internal

rulers


External vs. Internal Measurements of IC
  1. External Measurements of IC
    • Measure the value of IC in financial terms at the organization level;
    • Describe the company so that it may be assessed by stakeholders, customers, and creditors;
    • Describe company changes, flows, and risk;
    • Assess how effectively managers utilize IC.
  2. Internal Measurements of IC
    • Entail component-by-component evaluations;
    • Enable management to monitor company progress and to take corrective action where and when needed;
    • Emphasize flows, trends, and changes;
    • Should be mutually consistent; that is, they must be aligned to reflect common purposes and directions for the company as a whole;
    • Have different relevance and usefulness at different levels in the company.

Accounting vs. Economic

Accounting v. Economic Information

Accounting information is collected and maintained by all companies, as per SEC and IRS requirements.   Accounting terms and procedures are carefully defined by GAAP so as to be uniformly applied, and thus uniformly interpreted across companies.   Furthermore, companies may strategically choose their methods so as to achieve a given accounting goal, such as the minimization of tax burdens.   Thus, a given set of company needs and/or information will not necessarily yield the same accounting results.

Economic information is not required to be reported by companies, and so it may or may not be collected and/or maintained by companies.   Economic information is much more conceptual, where accounting tends to be literal.   As a result, economic information is much less conducive to being manipulated than is accounting information.   However, its lack of standardization tends to make economic data more difficult to analyze.

The various characteristics of accounting and economic data thus yield tradeoffs when being used in analysis:
  • Standardization:   Accounting information is relatively standardized across companies, to the extent that it complies with GAAP terms and procedures.   Economic information, on the other hand, tends to be much more idiosyncratic across companies.

  • Accessibility:   Since the SEC and/or IRS require both public and private companies to report their financial information, these data tend to be easily accessible.   To the extent that economic information may be maintained by the company, they tend to be scattered throughout departments, and are thus much less accessible than accounting information.

  • Level of detail:   Accounting data tend to be summarized and aggregated on financial statements.   When available, economic information tends to be maintained at a disaggregated level.   Economic information is thus generally more conducive to detailed analysis.

  • Accuracy:   While accounting information is GAAP-compliant, it may have little correlation with economic information.   However, it is economic information upon which companies should be acting to manage and optimize company value.   Economic information is thus generally more accurate than accounting data for purposes of IC management analyses.

Measurement Approaches

IC Measurement Approaches
  1. Market Capitalization Approach (MC)
    • Defines the value of a company's IC as the difference between the company's market capitalization and its book value;
    • Includes such measures as:
      • Tobin's q [Stewart (1997), Bontis (1999)]
      • Market-to-Book Value [Stewart (1997), Luthy (1998)]
  2. Return on Assets Approach (ROA)
    • Defines a company's IC as the excess return on its tangible assets
    • Includes such measures as:
      • Economic Value Added (EVA(TM)) [Stewart (1997)]
      • Calculated Intangible Value [Stewart (1997), Luthy (1998)]
      • Knowledge Capital Earnings [Lev (1999)]
      • Value Added Intellectual Coefficient (VAIC(TM)) [Pulic (1997)]
  3. Direct Intellectual Capital Approach (DIC)
    • Estimates the value of specific individual IA
    • Includes such measures as:
      • Technology Broker [Brooking (1996)]
      • Citation-Weighted Patents [Bontis (1996)]
      • Inclusive Valuation Methodology (IVM) [McPherson (1998)]
      • The Value Explorer(TM) [Andriessen & Tiessen (2000)]
      • IA Valuation [Sullivan (2000)]
      • Total Value Creation, TVC(TM) [Anderson & McLean (2000)]
      • Accounting for the Future (AFTF) [Nash (1998)]
  4. Scorecard Approach (SC)
    • Generates indicators and indices for identified IA and reports them in scorecards or graphs
    • Includes such measures as:
      • Skandia Navigator(TM) [Edvinsson & Malone (1997)]
      • Value Chain Scoreboard(TM) [Lev (2002)]
      • IC-Index(TM) [Roos, Roos, Dragonetti & Edvinsson (1997)]
      • Intangible Asset Monitor [Sveiby (1997)]
      • Balanced Score Card [Kaplan & Norton (1992)