chapter three

3 How to frame the right AI opportunity every time

 

This chapter covers

  • Starting on the right foot with a clear, complete idea statement
  • Making sure you tackle the right decision, creatively
  • Establishing baselines and benchmarks for early impact assessment
  • Assessing the organization’s analytics maturity

Roll up your sleeves—this is where the real work begins. In this chapter, we enter the most critical phase of the AI Road Test: the investigation. Many AI initiatives fail because they do not address a business-relevant problem or cannot be sustained due to insufficient organizational maturity. This chapter aims to prevent those failures by helping you frame an AI opportunity that is clear, actionable, and grounded in reality.

Building on Chapter 1’s why and Chapter 2’s what, we now focus on the how: how to move from an initial AI idea to a detailed and validated one. This is the point where intuition gives way to structured analysis, and enthusiasm is tested against operational reality. You will learn how to ensure your AI effort targets the right decision, for the right users, and in service of the right outcome.

3.1 An apparent opportunity that turned out to be secondary

3.1.1 Finding the keys to unlock growth

3.1.2 Lessons from the LuminaEsencia case

3.2 Clarify the idea first

3.2.1 What do we mean by a problem?

3.2.2 Define your idea loosely and broadly before starting the AI Road Test

3.2.3 Make sure you tackle the right decision, creatively

3.2.4 Master the issue tree for unbiased decision making

3.3 Set baseline, benchmarks and analogy

3.3.1 Set the baseline

3.3.2 Choose the right benchmark

3.3.3 How baselines, benchmarks, and targets work together

3.4 Assess analytics maturity

3.4.1 Practical analytics maturity assessment

3.4.2 The case for objective maturity assessment

3.4.3 Visualize the maturity assessment

3.5 Summary