Data Analytics has captured the attention of businesses worldwide from large corporations to small establishments. It is often mistaken as just a technical process of data collection. However, it requires combining skills and tools to extract useful insights for informed decision-making.

To kick off Season 8 of In Reality: Lessons from Leaders and Entrepreneurs podcast, host John Rebecchi (M.B.A. ’83), Ph.D., is joined by Josh Nafman, Vice President of Data and Operations for Diageo. Diageo is a global leader in high-quality beverages with a portfolio of 200+ brands spanning in various categories, including well-known names like Johnnie Walker, Smirnoff, and Guinness. In this role, Nafman leverages data, technology, AI, e-commerce, media and content to enhance business decision-making. Prior to joining Diageo, Nafman contributed to marketing, digital, and design initiatives for Pepsi, Kind, Hello, Apple, and Starbucks.

Nafman breaks down data analytics as a process of collecting and sorting data, identifying patterns and relationships within that data, interpreting results, and most importantly, presenting the data that are both exciting and inspiring to drive better decision-making. He also highlighted its different aspects including descriptive to understand, prescription to recommend actions, predictive to anticipate future events, and his favorite which is adaptive for continuous learning.

Before starting a project, Nafman begins by categorizing his data analytics projects into three categories including reactive, recurring, and research. He explains that a reactive project involves seeking data quickly to support a specific cause, such as a spreadsheet analysis. Second is a recurring project which includes consistently generating reports to track trends and inform future actions, such as quarterly or half-yearly business reviews. Lastly is a research project which involves in asking deeper questions and establishing scientific processes to prove or disprove hypotheses.

Nafman’s approach to data presentation involves drafting comprehensive explanations before simplifying them into simpler forms. He then uses metaphors to place emphasis on the storytelling element of data presentation.

While Nafman acknowledges that his viewpoint may be controversial, he is not fond of data visualization. He recognizes the preference for graphs and KPIs, but ultimately believes most people prioritize seeking answers over engaging in discussions. He explained, “For me, and for this reason my main tool is PowerPoint.” He added, “I’ve worked across Tableau, Power BI, Datorama and ThoughtSpot. They all have some interesting spots on them, but a lot of data analysis focuses on visualization, not on the story the visuals are trying to tell.” 

To thrive as a leader new to data analysis, Nafman advises being clear about the problem you want to solve and identify what success looks like. He explains, “Data can quickly become overwhelming and try to boil the ocean.” Instead, start with the basics and work up to more advanced outcomes.

Listen to the full episode: Podbean, Apple Podcast, YouTube Podcast, Spotify.

By Patthara Chandaragga