Numbers Need Narratives
Numbers Need Narratives
“Do you know the impact of your marketing initiatives on the bottom line? What would a 5 percent increase in customer satisfaction mean for your income statement? … A recent McKinsey survey, presented at the Chief Marketing Officer Summit at Wharton, found that CEOs expect marketing leaders to cut costs and increase contributions to growth…”
This blurb could easily serve as the introduction to half the articles tailored to CMOs and other marketing professionals these days. Instead, it's a pitch for a Wharton Business School executive-education course on marketing metrics.
Wharton's curriculum designers understand that there's more than one way to make money in marketing's measurement craze. As they should. My own pedagogical guidance to marketers is this: Measure mindfully and selectively, and recognize your metrics' limits.
When I speak with CMOs this year, I hear so many mentions of KPIs, ROI, dashboards, metrics, and “profitable growth” that I feel like I'm speaking with CFOs, circa 1993 or 2003. Twenty years ago, many finance executives helped their functions make a decade-long leap from transactional score-keepers to strategic business partners. It was not an easy transition, for many of them.
Numbers are important, but they're not everything. In fact, how those numbers are crunched and used—as well as who is doing the number-crunching—is more important. As data gets bigger and business transactions grow more complex, number crunching has become more of an art and less of a black-or-white science. Most accountants have long known that this is the case; they're the ones who must reconcile the surprising expanses of gray area in their treatments with the endless stream of standards and guidance the Financial Accounting Standards Board (FASB) has been churning out since 1973.
Besides number-crunching has its limits. In a thoughtful column on what data analytics can and cannot do, New York Times columnist David Brooks emphasizes that data struggles with context: “Human decisions are not discrete events. They are embedded in sequences and contexts. The human brain has evolved to account for this reality. People are really good at telling stories that weave together multiple causes and multiple contexts. Data analysis is pretty bad at narrative and emergent thinking, and it cannot match the explanatory suppleness of even a mediocre novel.”
This type of cautionary note tends to get drowned out by the flood of stories focusing the benefits of Big Data to marketing, inventory management, planning and forecasting, employee engagement, and many other realms.
Sports and politics, in particular, are enjoying Metric Moments of their own. It's no surprise that writer Michael Lewis, who started his career on during Wall Street's “Liar's Poker” era, understood that the Oakland A's innovative number-crunching could be transformed into a best-selling story (Moneyball). One of the most engaging places to learn about leading-edge data analytics is on sports columnist Bill “Sports Guy” Simmons' Grantland site (and his podcasts). There, metric mavens like Bill Barnwell (football), Zach Lowe (basketball), Jonah Keri (baseball), and Nate Silver (who predicted the outcome of the most recent Presidential elections with eerie accuracy) discuss the latest measurement techniques.
What's absolutely enjoyable, and extremely educational, about these discussions with quant experts is that Simmons himself, while delighting in what the numbers can track and forecast, remains genetically old-school in his own sports predictions and observations.
He's all about narrative. A team's fate hinges, he routinely concludes, on the characters who comprise that team and on a set of narrative templates featuring these characters: the team with an overrated star player will thrive when the star player is traded or hurt; the team whose prospects are dismissed in the media will play above its skill level; the team that gets hot at the end of the year will cruise to the championship.
Marketing professionals have similar narratives about their initiatives and programs. At least they used to.
These qualitative and instinctual hunches and perceptions have been subtracted from too many ROI calculations amidst the function's Measurement Madness. The old corporate-finance saw that “you can't manage what you don't measure” remains as accurate as it's always been, but CMOs cannot—and should not—manage by measurement alone.