Sullivan said it’s difficult to show ROI on data science capabilities in the first year. Companies should think of that first data science year as a bootstrapped effort where you’re discovering the unknown unknowns, curating data and tagging it so it can later be linked to a business outcome. “It’s about small wins at first,” Sullivan said. Another key point from Zutavern: No company has perfect data ontology and categorization so you shouldn’t put off an analytics effort in hopes of perfection. Every company has data gaps and the information is likely to be messy.
"Human behavior is hard to predict," Sullivan explained. "For instance, in fraud it’s hard to analyze a human who is doing everything to defeat you and avoid detection."