“Analyse this dataset and come back with any insights you find.”

This was one of the first requests I ever received as a data scientist, and to be perfectly honest, I didn’t quite understand what it meant.

Sure, I understood the “analyse the dataset” part, but at the time, I had no idea what my stakeholder meant when she spoke of “insights”.

I interpreted the word as a synonym for “interesting facts”. And that’s exactly how she politely responded when I returned with my findings.

“That’s interesting.”

Unsurprisingly, my work didn’t drive any change. In fact, I suspect it just got shoved in a drawer, never to be seen again, as soon as I left the room.

In the years that followed, I found myself frequently reflecting on that experience and wondering what I did wrong. The answer didn’t come until I eventually read Effective Data Storytelling by Brent Dykes.

In it, Brent argues that interesting observations and genuine insights are not the same thing - and the ones that truly matter are those that offer a tangible promise of value, such as increased revenue, cost savings or reduced risk.

In the latest episode of Value Driven Data Science, Brent joins me to share the frameworks behind identifying and communicating insights that actually move organisations to act.

In this episode, you’ll discover:

1. What makes an insight an insight and why only 5% of findings qualify [03:42]
2. The four dimensions that focus your analysis before you touch the data [11:25]
3. The six criteria for a truly actionable insight [15:06]
4. Why narrative outperforms an executive summary every time [19:14]

If your work keeps ending up in a drawer, this episode will show you where to begin.

Listen now on Apple Podcasts or Spotify, or click the link below:

​Episode 103: The Art of the Actionable Insight​

Talk again soon,

Dr Genevieve Hayes