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Dr Mark Kennedy, Director of Imperial Business Analytics, highlights new techniques being developed to limit the effects of data-driven disruption

"Data-driven disruption" is a big problem facing UK businesses: it’s the sneak attacks that occur when data-enabled business models beat out established ones. All too often, people don’t realise this is happening until it’s too late to respond. These days, the growing availability of new kinds of information about people and things is making data a huge source of disruption across many industries.

Imperial College Business School is at the centre of innovation on this key trend. In partnership with the Data Science Institute and other collaborators from across Imperial College London, we are analysing many different types of data to identify potentially significant changes sooner and more confidently. Our collaborative work is building models that help decision makers arrive at earlier, more confident calls about when they need to respond to potentially disruptive developments in their fields.

For example, we use words like "crash" or "jolt" to refer to big economic downturns because we are still very bad at seeing when these kinds of storms are brewing. Recently, this is what happened with the dramatic liquidity crisis of 2008 and the years of recession that followed. By analogy, weather catastrophes were once just as much of a surprise, but now we have satellite imagery, radar and all kinds of ways to build models of what is likely to happen.

This is exactly the kind of thing we are doing with data-driven disruptions in markets. This work is not only exciting and challenging – it also holds the promise of providing very valuable insights to leaders in business and government, helping to anticipate these events and prevent large-scale disruption.
 

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Mark Kennedy

About Mark Kennedy

Associate Professor and Director, Imperial Business Analytics
Mark is Associate Professor of Strategy and Organisation at Imperial College Business School, Director of Imperial Business Analytics, a research lab in Imperial College London’s Data Science Institute (DSI) and also a Deputy Director of the DSI. Mark has a long-standing interest in categories and categorization processes for their role in the adoption and diffusion of innovations. Within this broader topic, Mark studies how people collectively determine if and when unfamiliar new things become social realities, a topic that has led him to develop and use text mining methods for analyses of social change. Having previously focused on the dynamics of product markets and changes to organisations and business practice, Mark is currently studying what AI-based innovations will mean for the future of organisations, careers, labour markets, and society writ large. He has PhD and MBA from Northwestern University and its Kellogg School and an AB degree from Stanford in Philosophy and Logic of Formal Systems.