From Data Science to Data Stories: Automating Advanced Analytics for R&D and Manufacturing
From Data Science to Data Stories: Automating Advanced Analytics for R&D and Manufacturing


Advanced Predictive analytics is gaining importance and proven impact in many areas despite some of the hype. Surprisingly, the data science universe and the business universe keep co-existing without too much overlap. We claim that data-driven solutions will see a greater success in business and industry only when they are understood and internalized by domain experts (not just data scientists), and when domain experts take ownership of the solutions. This can only happen if predictive analytics outcomes are communicated to domain experts in human language with a narrative; otherwise they have little chance to be sustainably deployed.

Data-driven strategy are proven to increase EBITs, but are assumed to require epic efforts in terms of upfront investment and unique talent acquisition. Budgets are almost always spent on collecting the data with little to no plans on what to do with it later, which makes the transformation incomplete. Interestingly, the technology exists to turn all of these data into immediate actions with minimal effort and with existing human capital. Our claim is that turning data science into data stories is the missing ingredient in competing the data-driven transformation, and making it an enjoyable and natural next step to make.


Guido Smits has worked in the field of computational intelligence for 31 years. Prior to joining DataStories as a CSO, Guido was a principal research scientist at Core R&D dept. of Dow Chemical for 25 years. His expertise spans quantum physics, chemistry, statistical learning theory, machine learning and high performance computing. He spent his entire career applying AI to industrial challenges on product design and process optimization.

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