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Business Chess (Istvan, 1984)
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The Case for Using Probabilistic Knowledge in a Computer Chess Program (John L. Jerz)
Resilience in Man and Machine

This short article appeared in 1984 and quotes are from the reprint found in The Boston Consulting Group on Strategy by Stern and Deimler, 2006

p.361 Profound parallels exist between business and chess. Both are complex forms of competition. Both have been studied for centuries, and both depend on strategy.
 
p.361-362 sophisticated chess computers depend on rules of thumb and experienced-based policies and procedures to develop strategies and direct tactics.
  These rules to simplify a complex world are the parallels to the mental maps successful managers develop to determine a corporation's strategy and tactics... Making maps explicit and continually reflective of reality separates grand masters from computer programs
 
p.364 Direct lessons from chess are applicable in business... One device is recognizing patterns. This is the art of making useful abstractions... Patterns filter extraneous information, reduce complexity, focus on the essential. Only key patterns of competitive behavior are evaluated... The other device is guidelines, rules of thumb. Rules of thumb are guiding principles that, while never strictly true because of oversimplification, point reliably to the probable direction of action. Experience builds rules by remembered results of trial and error.
 
p.365 All good chess programs depend on rules of thumb to simplify calculations... The effort to create successful chess programs parallels the effort of top management to form successful business organizations. Strategic success requires:
  • Appropriate pattern recognition. The organization must seek out all relevant information but not be overwhelmed by trivial detail.
  • Appropriate rules of thumb. Decision rules reflect competitive reality at several levels of complexity. Too simple, and decisions will be erroneous; too elaborate, and they will be made late or never.
  • Learning. No intelligence networks, reporting systems, filters, or decision rules can be appropriate always, everywhere. Learning when rules do not apply, and when exceptions justify new ones, is the essence of adaptive strategy.

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