Framing and problem definition

Demystifying Decision Science

Howard Friedman

Adjunct Professor at Columbia University

The first step - framing the problem

  • First and most critical step
    • Guides data collection, analysis, and decision-making

Building without a blueprint:

  • Without a clear problem definition, projects become disorganized and ineffective

Without a well-defined problem:

  • Wasted resources
  • Misdirected analyses
  • Failing solutions

 

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Demystifying Decision Science

5 Whys:

  • Repeatedly ask "why" to uncover the root cause
  • Example: Declining sales -> Poor service -> Ineffective marketing

Fishbone Diagrams:

  • Visual tool that categorizes potential causes
  • Common categories: people, process, technology

SMART Goals:

  • Frame problems using Specific, Measurable, Achievable, Relevant, and Time-bound criteria
  • Helps set clear direction and define success

SMART goals best practices:

  • Clearly define your target audience or subject
  • Establish measurable criteria for success (e.g., KPIs, specific outcomes)
Demystifying Decision Science

Context is crucial

  • Business objective:

    • Define the specific goal the decision aims to achieve
    • Examples: increase revenue, reduce costs, improve satisfaction, speed up service

  • Constraints:

    • Identify limitations that may impact solutions
    • Examples: budget, timeline, staffing, IT infrastructure, ethical concerns
  • Stakeholders:
    • Recognize who is affected or involved
    • Examples: decision-makers, data owners, end users

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Demystifying Decision Science

Let's practice!

Demystifying Decision Science

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