Data seems to be everywhere. Since data can impart crucial knowledge, companies must determine how they will take advantage of this valuable resource. It’s not unusual to see markedly different perspectives on data’s role in business. How data driven a company will be can vary depending upon corporate culture and strategy. So, some organizations are more highly data driven than others.

For example, the May 27-28, 2017 Wall Street Journal presented two sides to the role of data in investment companies. One was “Quants Are Better than Brains” by David Siegel, co-founder and co-chairman of Two Sigma Investments, LP. On the same page, the Wall Street Journal also featured a piece with the opposite viewpoint. It was titled “Brains Are More Reliable than Machines” and its author is John W. Rogers Jr., Chairman and Chief Investment Officer of Aerial Investments LLC.

That said, Siegel’s “Quants Are Better” advocates the scientific method. Acknowledging that there are challenges, he points out that “significant research and expertise in data science, modeling, and related analytical techniques” are required. With the advent of more quantitative analysis and scientific experiments, Siegel says, “The shifts we are seeing in the industry today represent a welcome, if overdue, move in that direction.”

Presenting an opposing view, Rogers’ “Brains Are More Reliable than Machines” says “data alone is not enough” and sees a much greater role for human judgement. According to Rogers, “Those promoting artificial intelligence would lead one to believe it is all about replicating human judgement in a superior manner. The data part may be easy for machines, but the human part isn’t. This is where computers meet their limits and our brains can triumph.” Rogers reminds us that information is not the same as insight, which I’ll point out has long been true for users of data. Rogers’ viewpoint does not mean data is ignored, but it recognizes the value of human judgement.

According to Rogers, “Computers are often right, but they can fail spectacularly, when things reach extremes or new patterns arise.” This really resonates with me since I saw it happen many years ago when I was that era’s version of today’s data scientist. Based upon my experience, computer models can work well in some situations, but they can be very vulnerable when a shift takes place. Since I saw the limitation of data analytics, I have stressed the importance of a broader understanding of the dynamics of the business. And, going well beyond data analytics and modelling, I have devoted much of my life to unearthing patterns behind the strategic choices that lead to Winning Moves for companies. So, I relate to Rogers’ viewpoint because it is consistent with much of what I have been saying in my blog and newsletters posted on my web site.

Nonetheless, some organizations will do quite well with the kind of heavy quantitative emphasis Siegel’s “Quants Are Better than Brains” discusses. And, Siegel makes a very good point when he says, “The availability of massive amounts of data and cutting edge technology only magnifies the power of a scientific approach.” I’d agree that Siegel’s approach can be powerful, but it’s also important to remember Rogers’ view that there can be times when things shift and computers aren’t always right.

Despite their differences, however, both Siegel’s and Rogers’ viewpoints recognize that data can play a valuable role. But, what that role is can vary from one organization to next. An interesting and inspiring example comes from the sports sector.

The Chicago Cubs strategy for winning the World Series illustrates how data, in the quantitative sense, is not enough. The April 1, 2017 issue of Fortune magazine ran a feature “The World’s 50 Greatest Leaders”, which placed Theo Epstein, President, Baseball Operations, Chicago Cubs, in the number one position on the greatest leaders list. Adapted from the book, The Cubs Way, Fortune’s write-up about Epstein explains that, prior to joining the Cubs, he was with the Boston Red Sox, where he used a “data driven analysis that helped teams identify and accumulate players with little-noticed, but crucial strengths.’ His data driven approach successfully took “the team to six playoff appearances and two World Series titles in nine seasons.” “But, character and chemistry were strengths a ‘quant’ approach couldn’t capture.” “The team underwent a late season collapse.” Players egos got in the way, preventing recovery from the adversity.

As Fortune explains, Epstein decided to go beyond analytics with the Cubs and “put their faith, not just in numbers, but also in the type of people they acquired.” Epstein directed Cubs talent scouts to find players who handled adversity well. Epstein wanted “three examples of how that player responded to adversity on the field and three examples of how that player responded to adversity off the field.” Epstein’s scouts were told to talk to everyone who knew the potential recruit. The goal was “to build a team around high character.” And, of course, Epstein’s approach paid off with the Cubs winning the World Series for the first time in 108 years.

As Fortune points out, the Cubs character approach “wasn’t hard measurable data. But, it was information, nonetheless.” As I see it, what Epstein did illustrates key points of those two Wall Street Journal articles about brains versus quants. Epstein’s early success with analytics at the Red Sox is similar to what Seigel describes in “Quants Are Better than Brains”. But, what Epstein did in Chicago resembles what Rogers advocates in “Brains Ate More Reliable than Machines.” Consistent with Rogers’ view, Epstein recognized that computers can be right, but that analytics and data alone are not enough. So, Epstein added valuable human judgement. True, the information Epstein’s scouts gathered was still a form of data about the character of each recruit. But, this kind of data is more deeply rooted in human judgement. As Fortune points out, Epstein’s approach did not rely on a computer or algorithms.

Fortune’s write-up about Epstein includes a brief section “What Business Can Learn from the Cubs’ History-Making Win’, which offers key takeaways. Here, Fortune urges us to “See Data’s Limits”. That resonates with me because I saw the limits of data analytics long ago as that era’s version of a data scientist. And, I have since spent years understanding business dynamics, going beyond mere data and algorithms to get a broader and deeper grasp of what drives success.

That’s why I favor Rogers’ “Brains Are More Reliable than Machines” approach. Computers can be right and data is highly valuable. But, we are not at the point where computers are all knowing. And, there are times when human judgement takes on greater importance. That’s how the Cubs won the World Series. It’s what Rogers advocates in his successful investment firm. And, it’s what I’ve advocated often through my writing here on this website. So, although some situations are amenable to greater amounts of automation than others, the right mix of human judgement and hard data can have great value.