Building Data-driven Businesses

Building a data-driven business is clearly on most board agendas. We have all spent time looking at the data infrastructure and technology foundations for it. I enjoyed a recent conversation with Murli Buluswar , who heads analytics and data science at Citibank, as he leaned in on the other two equally critical drivers of success here – strategy and culture.

On strategy, Murli defined a practical framework built on three axes. First, is a portfolio approach to data science work with resource and capital allocation tied in. The goal is to build relevance in the short, medium and long term - tackling a set of short-term problems, while ensuring a step change in intelligence in the medium-term, and more fundamentally transforming for the long term. Second, its critical to put yourself in the shoes of key stakeholders. One way to institutionalize this approach is picking the right metrics, ideally linked to the P&L and balance sheet. Some examples Murli talked me through across both alpha and beta projects - financials realized, financials identified but not yet realized and new frontiers of innovation. Third, Data science needs to function not just vertically but also horizontally and across end-to-end processes with a structured operating model – it’s not enough to just come out with super useful insights, the goal is to deliver financial outcomes and breadth and speed of decision-making.

Equally on culture, Murli’s real-world experience and insights in leading large teams through change are compelling - he thinks in terms of a follow-partner-lead operating model. This requires fundamental transformation of the culture from a data science function to a decision science approach - the team no longer wakes up thinking about delivering analytics or insights, instead delivering clarity on options and decisions being made, coming up with the questions that need to be asked and answered, and partnering with the business to drive outcomes. All this requires change management and showing the team that they are part of something much bigger that they can truly contribute to and learn from. Murli has some great nuggets on how to best do this - incorporating a growth mindset, developing an approach around zooming in and out to view a situation through different lenses, and the connector role between data sciences and the business.

In the end, Murli reminded me it’s all about making the complex simple.?And that is so true in our personal lives as it is in the business world. I hope you get a chance to see the video below and add to this conversation!