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The Art and Science of Decision-Making: Strategies for Effective Choices

Explore the art and science of decision-making, from credibility to emotional positioning and using data to enhance decision-makers' understanding. Examine types of decisions, errors to avoid, and the importance of facts in framing recommendations.

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The Art and Science of Decision-Making: Strategies for Effective Choices

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  1. The Art and Science of Decision-Making May 6, 2013 Robert S. Duboff Tony Gallo Jason Robins

  2. Persuasion (per Aristotle) • Credibility • Rational • Emotional

  3. Positioning the Professional Service Firm Back Room Added Value Front Room Added Value “Pharmacy” “Nursing Ward” Procedure = Execution Grey Hair = Experience “Psychotherapy” “Surgery” Brains = Expertise Source: 1985 David H. Maister

  4. Choices • Commodity vs. flourishing? One time or systematic? • Mindset vs. math? • Mystery vs. puzzle? • Art vs. science?

  5. The Scientific Approach • Decision Tree • Or • B. • Bayes • Put odds around consequences • Revised odds as you progress • PLUS…. • BIG DATA • a b • a b • a b • a b c • a b c

  6. BIG DATA Pros Cons • “Know” what to do • Commodity decisions • When environment is stable • Quantity • Don’t know why • Can develop wrong correlations • People are NOT continuous • Quality

  7. How Facts/Data Can Add Value to Decision-Makers • Information • Ideas • Recommendations • Options/Alternatives • Framing/Models • Trends

  8. Anticipated Use in Decision Use of Market Research Lamp post Shed light/insight Art View of Market Research Science

  9. Types of Decisions • Fully automated (e.g., yield management systems in hotels, airlines, or insurance underwriting systems in financial services). • Automated with overrides (e.g., insurance companies often invoke human experts when insurance policies are too large or complex). • Assisted (e.g., physician will first consider an automatic recommendation, but then make up his or her own mind about how to treat the patient). • Provides rich set of relevant information and analysis • May provide simulation of process flow and results for decision-makers to use • More Ad hoc independent models are maintained, improved and reused Source: Davenport, Harris & Morison, Analytics at Work, p. 125.

  10. Types of Decisions and Fundamental Approaches Source: Davenport, Harris & Morison, Analytics at Work, p. 125.

  11. Typical Decision-Making Errors – Process Errors • Careless mistakes • Not considering analyses and/or new insights in the decision-making process • Not considering the alternatives • Using incorrect or insufficient decision-making criteria • Gathering data and computing analyses occurring too late in the process to be of any use • Postponing decisions because of dissatisfaction with the data found and the analyses done Source: Davenport, Harris & Morison, Analytics at Work, p. 13.

  12. “If you can measure it, it can also be measured incorrectly.” • - Samuel Arbesman • “Once you have missed the first button hole, you’ll never manage to button up.” • - Goethe • “ ‘Facts’ may not always be facts, but feeling will always be feelings.” • “ Do you want to know what to do or why you should do it?”

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