Yesterday I had the pleasure of speaking at the Chief Data & Analytics Officer (CDAO) Winter event in Miami. If you’ve ever been to CDAO, you know it is quite a gathering of some of the smartest minds in analytics. Everyone I met had great stories to tell about the innovative work being done with analytics, artificial intelligence (AI) and machine learning (ML).
My keynote was focused on using AI, ML and prescriptive analytics to improve business impact and drive optimal outcomes. In partnering with FICO clients, I have found that combining ML with prescriptive analytics solutions delivers the best results when the strategic business outcomes are at the center and are the foundation that influences execution moving forward. Defining a business outcome seems simple enough, but the more prescriptive you can be about what you want to achieve, the more positive impact the solution will have on the business.
As part of my presentation I shared best practices, a road map if you will, on putting this into action. For those of you who weren’t in Miami, I’ll share the key take-aways:
#1 Outcomes should always be in the hands of the business owner; meaningful action from data and analytics is based on business involvement.
#2 The power of machine learning and artificial intelligence must be unlocked, but also understood. The business objective and the output needs to be understood by the business user.
#3 Don’t let operational trade-offs limit the predictive elements of the analytics decision.
#4 Extend beyond human limits to find the optimal. The combination prescriptive analytics, AI and ML, when applied to a real and desired business outcome, are able to extend way beyond human initiated capabilities. I call this the intersection of AI and HI.
I encourage analytics and operation professionals to attend the next CDAO this spring in San Francisco. There are so many people all focused on data analytics all in one place, it’s a great investment of time!
