I spend over 45 minutes teaching AI Strategy KPIs in my online course. Monetizing data and models is a significant challenge. Tracking the right KPIs is critical for C-level visibility, company-wide buy-in, and removing bottlenecks that prevent initiatives from achieving their business goals.
I have used Time To Value (TTV) for data and AI initiatives for 3 years. It is an aggregate measure that tracks initiative efficiency. Its lower-level metrics create transparency into where bottlenecks are occurring. Time to market can be misleading, so I like TTV’s more complete approach.
Companies struggle with monetization for a few reasons.
Innovators excel at ideation but struggle with delivery.
Technology-first companies can deliver quickly but hit the wall with monetization.
Traditional businesses struggle with ideation and/or delivery but have a firm grasp of monetization.
Early data and AI maturity businesses struggle with getting from idea to production and don’t have much experience with monetization.
The benefit of TTV is the visibility it creates in each phase of the process. Finding and fixing bottlenecks are much simpler when the cycle is tracked from start to finish with a well-defined metric.