Crossing the Analytics Chasm with Nanoeconomics

"I love it when a plan comes together" – John (Hannibal) Smith, The A Team One of the biggest challenges that I continue to see are organizations struggling to cross the Analytics Chasm; to transition their use of data and analytics from retrospective Business Intelligence that monitors what has happened to AI/ML-driven analytics that predict what is likely to happen and prescribe preventative, corrective or monetization actions. I wrote about the challenges to crossing the Analytics Chasm in the blog "Crossing the Big Data / Data Science Analytics Chasm" and in further detail in my just released book "The Economics of Data, Analytics, and Digital Transformation". The Analytics Chasm prevents organizations from leveraging AI / ML analytics to uncover the customer, product, and operational insights (propensities) buried in the data, that then can be used to optimize the organization's business and operational use cases (see Figure 1). Then on my early morning jog, it became clear to me what organizations specifically need to do to cross the analytics chasm. And the key to successfully crossing the analytics chasm is found in my favorite and maybe my most powerful concept – the Big Data Business Model Maturity Index (see Figure 2).