The Secrets of AI Value Creation

6Creating Actionable Insights

The goal is to turn data into information and information into insight.

—Carly Fiorina (former CEO of HP)

Years of experience in data‐driven decision‐making have made it clear to us that simply pursuing a data‐driven approach will not lead to business opportunity creation. Despite today's technology offering numerous ways to leverage data for business operations, and the promise of consultancies, data, and analytics initiatives to deliver insights that bolster the bottom line, only 26% of organisations have experienced success (Bean 2022). But what is the key to success?

Crafting ‘actionable insights’ from data holds the key to business opportunity creation. Although the phrase actionable insights has become popular, its application to guide the design and development of analytics and AI solutions is not widely adopted. Despite AI practitioners often prioritising metrics such as accuracy, recall, precision, sensitivity, and specificity to optimise algorithms, the aspect of actionability is typically overlooked in their evaluation (for an overview of commonly used evaluation metrics; see Blagec et al. 2019).

However, what are effective examples of actionable insights? In the marketing arena, they could assist in determining a budget allocation, selecting a creative campaign, or setting a product's price – each aimed at driving sales. In the context of customer relationship management, actionable insights might involve assigning a customer success ...