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The Art and Science of Decision-Making

The Art and Science of Decision-Making. May 6, 2013. Robert S. Duboff Tony Gallo Jason Robins. Persuasion (per Aristotle). Credibility Rational Emotional. Positioning the Professional Service Firm. Back Room Added Value. Front Room Added Value. “Pharmacy”. “Nursing Ward”.

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The Art and Science of Decision-Making

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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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