An outcome-focused approach to analytics and AI

I recently had the opportunity to discuss the current state of #data collection, analytics, and AI in an interview with @CIODive.

As technology advances, businesses can collect and analyse more data than ever before. However, most of that information ends up languishing, seldom being used or even catalogued. Recent research suggests that partly, this happens because businesses are unaware of what data they store or don’t know how to get actionable insights out of it.

This lack of visibility into data stores affects organisations’ readiness to apply artificial intelligence (AI) and machine learning (ML): advanced analytics require data to be properly managed and organised.

At Experian, we believe in taking an outcome-focused approach to analytics and AI as we look at activating the power of our data AI outcomes. We work backwards, from high-impact client and consumer outcomes, and bringing to bear the analytics, AI and data to achieve them. This way, we can assess more accurately what effort across data collection and analytics is required to achieve an outcome. Executed effectively this can avoid an enormous amount of investment in people, time, data.

If you’re interested in this topic, I’d recommend you to read the article in full: http://bit.ly/AImlShri_CIODive