I am a believer that the pathway to innovation must end with putting a product or service into the market that provides economic value to customers, economics the branch of knowledge concerned with the production, consumption, and transfer of wealth. Innovation is about economics and economics is about value creation. Products or services that never reach the market may have been great ideas, but you can't pay the mortgage or buy your Venti Chai Latte with great ideas. Yes, I believe for something to truly be an innovation, it must achieve market success; it must deliver economic value. I know that probably buts me in conflict with some traditional innovation thinkers, but that's what makes my role as Chief Innovation Office at Hitachi Vantara so…interesting (see Figure 1).

I hate it when I hear senior executives state that they want to become data-driven, as if somehow having data is value in of itself. Now, one can hardly blame the unenlightened executive whose only perspectives on data are associated with statements like "Data is really the new oil" (Wall Street Journal) or "The world's most valuable resource is no longer oil, but data" (The Economist). The infatuation with "data-driven" versus "value-driven" can be confirmed from Google Trends (Figure 1). However, this is where the value determination of data and oil diverge. Oil has value as determined by Generally Accepted Accounting Principles (GAAP).

I hate it when I hear senior executives state that they want to become data-driven, as if somehow having data is value in of itself. Now, one can hardly blame the unenlightened executive whose only perspectives on data are associated with statements like "Data is really the new oil" (Wall Street Journal) or "The world's most valuable resource is no longer oil, but data" (The Economist). The infatuation with "data-driven" versus "value-driven" can be confirmed from Google Trends (Figure 1). However, this is where the value determination of data and oil diverge. Oil has value as determined by General Acceptable Accounting Principles (GAAP).

What does Google know that the other 99.99% of organizations don't? I don't roam the hallowed hallways of Google or have access to any insider secrets as to their business plans and future business models, but it sure does make one contemplate why they would give away the very engine that fuels their obscenely-lucrative search business. You see, Google uses Machine Learning and Deep Learning to fuel its Personal Photo App (it auto-magically groups your photos into storyboards or collages), recognize spoken words (natural language processing), translate foreign languages (handy for me as I frequently travel internationally), and serve as the basis for its search engine. Arguably, Machine Learning and Deep Learning are the foundation for everything that makes Google money, and TensorFlow is the foundation for those Machine Learning and Deep Learning efforts. So why would Google open source TensorFlow and make it accessible to everyone – researchers, scientists, machine learning experts, students, and even its competitors?