Agriculture & Food Chemistry

Katya Vladislavleva is CEO and chief data scientist at Data Stories International NV, a premium predictive analytics company headquartered in Turnhout, Belgium. At work Katya is developing and deploying big data analytics solutions in new products R&D and continuous improvement in manufacturing, does government consulting, scientific advice and gives invited talks on big data, advanced analytics, supply chain optimization and entrepreneurship. She holds a PhD in data driven modeling from Tilburg University, Netherlands. She is a Professional Doctorate in engineering from Eindhoven University of Technology and a MSc in intelligent systems from Lomonosov Moscow State University Russia.

Advanced predictive analytics is gaining importance and proven impact in R&D environments. Surprisingly, the data science universe and the research and development universe co-exist with insufficient overlap in sharing the innovative value creating solutions. We claim that data driven solutions will see a greater success in a formulation discovery process 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 is 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 datadriven transformation incomplete. Interestingly, the technology exists to turn all of these data into immediate actions without epic efforts and with existing human capital.