Leadership has a lot to do with ideologies and culture than just technical know-how. In conversation with Susan Wilson, VP Global Data Governance and Privacy Segment Leader, Informatica, Sandip Sahota, Enterprise Chief Data and Analytics Officer, BMO Financial Group, talks about his leadership principles and the organization’s approach to measuring the impact of data analytics.

Sharing his experiences and observations from his journey as a data analytics leader, Sahota says, “There’s no secret sauce here. It’s about just honing your particular culture in your organization and honing your view and your core principles. I would say, be practical and pragmatic.”

He points out that there is a fair amount of conversation that can be ideological in nature during transformation journeys, and it demands pragmatism and practicality. While leaders have to be very outcome-driven, they also need to rely on common principles to drive the outcomes.

“As I reflect on my journey, there were many robust dialogues, a lot of debate about where we wanted to be, and we sometimes lost the focus on the actual outcome that we were trying to achieve. So, if you use some common principles to get agreement, use those principles to get a real line of sight on how you’re going to achieve the outcomes. And at the end of the day, operate with a very practical and pragmatic perspective. I think those are conditions that help, but every culture is unique,” Sahota says.

He then sheds light on BMO’s approach to measuring and communicating the value of data and analytics and progressing toward a desired outcome. “We have a relentless focus on our customers, their experience, and how they operate with the bank, and it extends to our employees. So, the equation in our mind is sort of this relentless focus on customers, employees, and measuring the impact, and then on ways to sustain that focus over time.”

He notes that there are several ways of measuring outcomes, like economic variables used to set the strategy and targets. Sahota says that while the team has considered economic variables, it can also ask the organization’s businesses, “If we weren’t here helping you with this outcome, what would you have done? What was the speed to a decision being made, speed to execution? And what’s the value that we can take back to the organization and say that experience has some stickiness which delivered some outcome? And now let’s price the relationship of what we’re doing relative to that. And is there a way to factor that into the overall equation?”

Sharing examples, Sahota points toward a couple of initiatives taken by the organization in the RPA (robotic process automation )space. BMO introduced BMO CashTrack, which leverages AI to drive the understanding of predictive cash flows for its customers. And for this, the team built objective and subjective measures. 

“Objectively saying, ‘How has this shifted our business?’. And then we’ve taken that to our business partners to say, ‘We want you to be part of the dialogue to tell us exactly where that value came from.’ And then subjectively, we’ve refined it to show various ways that the organization rallied around this capability and we’ve extended it to new thinking,” he explains. “So, it isn’t the same product, but the thinking around product ‘A’ led to the discussion around several other products, which are now being iterated and brought to market.”

He concludes by emphasizing that BMO Financial thinks seriously about the development in terms of the ‘dry powder’ invested in data analytics by the organization, asking “So, how many dollars of value do we have to actually bring back to the BMO organization through the investment that’s being made in us?”