Principal Research Scientist for MIT Sloan Center for Information Systems Research (CISR) Barbara Wixom is an academic dynamo and a data veteran. For more than two decades, she has been behind important studies on big data, business analytics, data warehousing, and business intelligence. Holding a crucial role within MIT Sloan’s CISR, a nonprofit research center that helps companies best put technology to use, she has been lending her expertise to efforts focused on the challenges senior-level executives face and directing studies that promote a deeper understanding about how firms create and deliver business value from enterprise data capabilities.
She is also a beloved and familiar face around UVA. Before joining MIT Sloan in June 2013, Wixom was a fixture at McIntire as a tenured professor for more than 15 years, and served as the M.S. in MIT Director in Northern Virginia between 2005 and 2011. During that period teaching data management, business analytics, and IT strategy courses, Wixom was recognized for her inspirational and motivational contributions as a faculty member and twice received UVA’s esteemed All-University Teaching Award for her excellence in 2002 and 2010.
McIntire’s Center for the Management of Information Technology (CMIT) is thrilled to welcome Wixom back to Grounds May 10 for the 2019 Digital Innovation edition of the Center’s annual Knowledge Continuum event. [Note: registration for this cutting-edge, one-day executive program closes May 1. Register here.]
We had the chance to speak to her in advance of her appearance as a featured panelist at the event, learning about the various ways companies are benefiting from rethinking how they use their information and analytics.
How have you seen your research position leaders to get the most value from their data? What success stories have you witnessed firsthand?
Leaders turn data into dollars when they purposely commit to generating specific economic returns (e.g., operational efficiencies, product sales lift, new revenue streams)—and then put the right data monetization capabilities and accountabilities in place to drive results. My research helps companies appreciate what monetization choices they have—and what the different choices require.
Since 2015, I have been fortunate to research BBVA, a 130,000-employee bank headquartered in Madrid and operating in 30 countries. BBVA’s data monetization activities have been fascinating to follow. One of BBVA’s many interesting actions was establishing a data science center of excellence as a separate legal entity, charged with 1) generating new revenue streams from information solutions, 2) building innovative, enterprise-wide data science capabilities for BBVA, and 3) leading data-driven culture change. The center of excellence helped BBVA develop some key analytics-based features, such as a personal finance budget categorizer and a transaction forecaster. Forrester recognized BBVA for best mobile banking in 2017 and 2018.
What trends are emerging among companies who have been effectively monetizing their information assets through data wrapping? What’s surprised you recently?
Last year I surveyed over 500 product managers to learn how and why they are using data and analytics to create product features and experiences (a phenomenon we term “data wrapping”)—and to learn how they are generating economic returns. Companies that are great at wrapping have product organizations with analytics-savvy employees who work well with their company’s IT and data organizations. These companies have established an accurate, historical, 360-view of their customers that employees can access using internal APIs. And they create valued features by co-creating them with customers or by involving customer-facing employees in product development. Most importantly, companies that are great at data wrapping have clear policies in place regarding acceptable data use; their employees know how to safely innovate without fear of deploying to customers analytics that are wrong…or creepy.
I’m surprised by the growing importance of artificial intelligence in data wrapping—and the positive impact AI is having on data wrapping effectiveness. Our research identified that wraps deployed within the past two years are more likely to draw on AI for capabilities as compared to wraps that have been in the marketplace for a longer period of time. And, product features and experiences that leverages AI tend to generate greater returns and are harder for competitors to replicate.
What are the most widespread challenges that remain for organizations that have been slow implementing a strategy to transform their business into the digital realm and monetizing their data? Does anyone still need convincing?
I think business leaders “get” that data matters these days. The question is really how big and in what way should my company pursue data opportunities?
The biggest data-related challenges companies face are the ones we have always grappled with: getting top management and boards to appreciate what it means to treat data like a strategic asset, engaging employees in evidence-based decision making, changing culture from decisions made by gut to decisions backed by information, and understanding how data reshapes the company’s profit formula (what new costs, risks and benefits does data drive). Data is a journey where companies learn over time—so the best time to start, whatever state you are in, is now.
Where can we find out more about your research?
My research specifically helps company succeed with data—and the research is available at no charge on the CISR website at cisr.mit.edu (simply register for free to download briefings and working papers from the publication search page). I do hope the research offers value to members of the McIntire community.