Here’s a different way of viewing your responsibilities as a corporate board member: pretend for a moment you work in the front office of a mid-market Major League Baseball team—and you want your team to be competitive against the Major League’s Goliaths. How do you do that?
Consider this: Among the five American League teams currently in contention for the MLB Playoffs, only two of them are considered Goliaths: The Boston Red Sox and the New York Yankees. The other teams, Cleveland, Houston and Oakland, are considered “mid-market teams.” Davids. Without getting too far into what defines “major vs. mid-market” (market size, total revenues and how much you can spend), the mid-market guys are more than holding their own. Why?
Consider this: the Houston Astros were a major league doormat until just a few years ago. From 2011-13 they lost almost twice as many games as they won. But in 2014 they started using data analytics to predict what talent to draft and what high-priced talent to let go.
The rebuilt, analytics-driven team started winning games. The Astros continued using analytics to build a championship team—six guys on the 2017 World Series winning team were draft picks. Nine more came via trades—again, the front office used analytics helping to choose those guys. Of the remaining group, only five came from more expensive free agent signings—with one, Jose Altuve, being an international free agent who signed for $15,000.
But data analytics did more than help the Astros pick talent.
It helped deploy players on the field in “defensive shifts.” It helped identify players’ strengths and weaknesses. It helped set batting orders. It helped hitters learn what pitches to swing at and at what “launch angles.” It helped set a starting pitching rotation. And it helped identify which pitcher should be called into the game in relief situations. Bottom line? The Astros went from worst to first in four years. And today virtually all 30 Major League Baseball teams, large and small, use data analytics.
What does that have to do with being a board member? More than you think.
For example, it’s well-known that many of the largest banks—$50B in assets and above—use data analytics for everything, from fraud detection, compliance and cybersecurity to hiring, marketing and outreach. Has it helped them grow? Have you seen their earnings lately?
More important, many of them are now aggressively going after the community banking market.
And why not? The Financial Brand recently reported that only about nine percent of institutions with assets less than $1B have invested in advanced analytics, compared with about half of banks with more than $50 billion in assets.
The lesson is clear: Keep up with the competition or else. Where do you think the Astros would be if they hadn’t invested in analytics?
The Astros deployed analytics in all phases of their game, from player selection to player improvement to offensive and defensive decisions, based on past success and probability.
That’s not unlike using analytics to determine how much of your company’s tech budget should be deployed on fraud detection, how much on compliance, how much on overall efficiency and the ability to react quickly to any situation. Quickly is the operative word. Just as quickly as a baseball game can change on a single pitch so too, a company’s fortunes can change when fraud goes undetected.
The Punjab National Bank (PNB) scandal began with a single LOU (“letter of undertaking”) for a relatively small amount. When that—and other LOUs—went unpaid and the fraud went unchecked, the amount escalated until PNB wound up covering six years of fraudulent transactions at a cost of about $2 billion.
It’s true that PNB is the second largest bank in India. But as the Astros proved, you don’t need to be a Goliath to make data analytics save the day for you. Analytics employed by small-to-mid-sized organizations have more than paid for themselves in terms of fraud prevented, compliance achieved and efficiencies gained. One organization realized an ROI of 702 percent including recovery of $2.9 million in vendor overpayments, prevention of $250,000 in purchase card fraud and more than $360,000 savings in labor costs from improved vendor reporting.
As a board member, you have a chance to persuade your company to invest in data analytics. As the Astros demonstrated, it’s something any organization should do if it’s worried about winning and its bottom line. All it takes is a commitment, an “all-in” effort and a willingness to trust the process no matter where it takes you.