The Big Three: A Methodology to Increase Data Science ROI by Answering the Questions Companies Care About
This provides a practical framework for companies to increase data science ROI by addressing neglected business questions beyond basic descriptive analysis.
The paper addresses the problem that companies achieve only about one-third of potential data science value by proposing a methodology to answer three key business questions (what's happening, why, and what actions to take), with a practical example demonstrating application.
Companies may be achieving only a third of the value they could be getting from data science in industry applications. In this paper, we propose a methodology for categorizing and answering 'The Big Three' questions (what is going on, what is causing it, and what actions can I take that will optimize what I care about) using data science. The applications of data science seem to be nearly endless in today's modern landscape, with each company jockeying for position in the new data and insights economy. Yet, data scientists seem to be solely focused on using classification, regression, and clustering methods to answer the question 'what is going on'. Answering questions about why things are happening or how to take optimal actions to improve metrics are relegated to niche fields of research and generally neglected in industry data science analysis. We survey technical methods to answer these other important questions, describe areas in which some of these methods are being applied, and provide a practical example of how to apply our methodology and selected methods to a real business use case.