Data Analysis for Decision Making

Over the last two decades, we have witnessed an explosion in the availability of data. Firms routinely collect point of sales transactions, monitor operating performance throughout their supply-chain, mine website traffic, and track customer engagement. Business analytics and data are transforming modern firms, and, in some cases, disrupting entire industries. Importantly, these changes are not limited to the “back-office” or operations; every aspect of the firm -- organizational structure, marketing, product design, and strategic planning – is shifting towards data-driven decision-making. With this shift comes an increased need for “data-savvy” managers; managers who are not necessarily data-science experts, but understand what analytics can and cannot do, how to ask the right questions, and, most importantly, how to interpret data to make better decisions.

The goal of this course is to help you develop your skills as a data-savvy manager. To that end, we will study several basic analytics techniques, focusing on how you, yourself, can apply them in practice, interpret their output, build intuition, and leverage them in decision-making. Specifically, we will focus on:

• KPIs and Dashboarding: How do we convert the ocean of raw data into a manageable insights for decision-making? What are the right data to measure and track? How can we communicate that data most effectively to stakeholders?
• AB Testing: How can we combine data and experimentation to incrementally improve our business model?
• Classification: Can we utilize historical data to make useful predictions?
• Clustering: What hidden structure is in our data? What sorts of insights does that structure give us about our business?