We know that data’s important. But what can we really do with it, and how much does it affect people who aren’t data analysts on the front lines? It might be overwhelming to consider from afar — yet it’s far from dismissible. 

Here, Darden experts offer some examples of varied workplace functions on which data analytics can have massive impact. It serves, drives and can lead to wild (though methodically so) success in multiple and varied areas of an organization. 


Firms today have an unprecedented ability to analyze every aspect of marketing campaigns, comparing types of advertisements and messages to see which resonate most with consumers, and tracking their follow-through rates to gauge which are most effective in leading to sales. No one knows this better than Rajkumar Venkatesan, Ronald Trzcinski Professor of Business Administration, who co-wrote the book The AI Marketing Canvas, which provides CMOs with actionable advice on how to work data science and artificial intelligence into their marketing toolkits. Venkatesan leads the Digital Marketing Innovation Executive Education program at Darden.

In a case study, Ventkatesan examined Compare.com, an insurance comparison site by the Admiral Group. After lackluster results with TV and Google Ad Words advertisements, the company experimented with email marketing, optimizing its message by varying the language, subject lines and cadence of its messages.

Next, it focused on the website itself. Noting that customers who completed a questionnaire for an insurance quote were more likely to purchase, it tested a banner ad with customers’ estimated premiums to motivate them to finish the form. The ad worked, increasing completion and click-through rates by 4 and 6 percent, respectively.


Much of running a successful operation relies on being able to predict what’s going to happen next. That’s the expertise of Yael Grushka-Cockayne, Altec Styslinger Foundation Bicentennial Chair in Business Administration and senior associate dean for professional degree programs, who specializes in decision analysis and forecasting using data science and artificial intelligence. Among her recent accomplishments is helping to optimize passenger transfer between flights at Heathrow Airport.

In other work, Grushka-Cockayne has analyzed how supermarkets can better plan for stocking shelves. Years ago, stockers would walk the shelves, noting what items to request from the warehouse, she says; now, an ongoing camera feed provides up-to-the-minute information. “They can tell you in real time what items are missing, and may even generate an order automatically,” she says.

Similar techniques are being implemented in retail stores and banking, in which tellers are fed information about customers to predict the financial product they might need next. “As managers and operation leads, we need to have a vision for the future,” she says. “Data scientists have the ability to communicate between various groups, to look at the data they have and to see how we can use that data to solve business problems.”


“Analysis is essential to business strategy,” says Michael Lenox. An expert in innovation, technology strategy, and the interface between business strategy and public policy, Lenox serves as Tayloe Murphy Professor of Business Administration and senior associate dean and chief strategy officer at Darden. “Analytics helps harness data to improve efficiency, driving down costs and creating novel value for customers, driving higher willingness to pay,” Lenox says. “Data and analytics are becoming a key component of competitive advantage.”  

In a case study on a publicly traded biotechnology company, Lenox analyzed innovation-driven growth and how C-suite leaders could formulate a strategy by analyzing and balancing multiple factors: R&D spend, debt, equity, potentials for acquisition or liquidation, low morale/high turnover, competitors’ attempts to steal market share through PR manipulation, and time constraints in product education with sales teams, customers and the research community.  

“I think you would be hard-pressed to find an industry not being impacted by data science,” says Lenox. “From music subscription services to autonomous vehicles to online retail, data provides the means to create novel value for customers, improve operations and ultimately enhance profitability,” he says.  

Analysis can show the quickest path to profitability — as well as drive long-term value.


Ethical issues are inexorably part of data collection and analysis, and business leaders need to be prepared to consider their companies’ practices not only in terms of data integrity, but also in terms of human integrity. Bobby Parmar, an expert in decision-making and ambiguity, business ethics, and leadership and stakeholder management, serves as Shannon Smith Emerging Scholar Associate Professor of Business Administration at Darden. Businesses have a responsibility, he says, to be transparent about the way data is gathered, what personal data is collected and how it will be used.

Though the competitive market can feel like a race to reach consumers, Parmar emphasizes the importance of thoughtful decision-making in determining how to use the vast amounts of data businesses may have at their virtual fingertips. “You have to learn about the impacts on stakeholders and empathize with them,” he says. And this applies to multiple stakeholders — not only existing customers or target markets for potential business, but employees, too.

Further, data use can be about more than avoiding questionable methods: It can also be used to make decisions that actively express an organization’s values. Parmar notes Airbnb as an example; though the heart of the business is a platform facilitating exchanges between groups — travelers looking for a space and homeowners willing to rent one out — to what extent should the organization intervene when the numbers showed that hosts accepted fewer guests with “distinctly African-American names”? The company responded by banning certain hosts and reviewing its own practices, in keeping with its community commitment to “accept people regardless of their race, religion, national origin, ethnicity, disability, sex, gender identity, sexual orientation or age.”

Certificate in Data Science for Business Strategy