Creating a new generation of data to solve social problems.
It has been almost 10 years since Michael Lewis wrote Moneyball: The Art of Winning an Unfair Game, igniting an already smoldering debate in the baseball community about the relative merits of choosing players based on scouting versus straight statistical analysis. Over the last decade, this burgeoning analytics movement has exploded: When a book about baseball data is turned into a movie featuring Brad Pitt, you know the topic has hit the mainstream.
This shift toward “stats” can be seen in the nonprofit world as well, as organizations increasingly look to measurement as a way to improve their programs and raise more money.
But in some nonprofits, the analysts, researchers, evaluators, and others doing the “stats” are having trouble making themselves heard. Just as in baseball, there is a disconnect between the people with the stats and the decision makers.
I recently attended a panel featuring Mr. Lewis, outspoken entrepreneur Mark Cuban, and data wunderkind Nate Silver at the MIT Sloan Sports Analytics Conference held in Boston, where current and future sports decision makers looked to analytics to get their next edge. Though my attendance was supposed to be a gift to my inner baseball-stats nerd, I could not help but notice the parallels with the work of measuring nonprofit programs.
The panel, titled “Revenge of the Nerds,” discussed whether there could be any room for traditional decision making in this new age of data analytics. But while the high-profile panelists eagerly agreed that analytics would play an increasingly vital role in successful organizations, the rest of the conference struck a notably different tone. Session after session included awkward moments of analysts discussing their struggle to make their voice heard at the decision-making tables of even the most data-friendly organizations. Where it matters most, the movement is stalling. Something is missing–and it’s not data.
Ultimately, it comes down to a simple fact. Analysts too often fail to provide decision makers with what they really need: insights, not just numbers.
So, analysts, here are three lessons from the conference to help you turn your data into meaningful insights that can help drive better strategy and ultimately have more impact.
Answer the Right Questions. When we have a lot of data, it can be tempting to chase answers to all sorts of interesting questions. But after all that analysis, if you answer questions that nobody else is in your organization is asking, your findings will wither on the vine. Either focus on the questions that matter to decision makers or, better yet, understand that your first job is to help people ask better questions.
Speak Their Language. We love our data. We value its robustness, its nuance, its elegance. Nobody else cares. Yes, be rigorous. But if you want to be heard, you need to translate your findings into the language that your target audience speaks. If you have to interpret, you’ve already lost your chance to influence. Lead with the answer to the “so what?” question rather than with your methodology. Use visualizations to bring the data to life. And whatever you do, don’t fill a PowerPoint slide with a giant data table.
Be Humble. Data geeks (this author included) sometimes fall in to the trap of thinking our data are reality. We’ve cut them 100 ways and come up with a solid, fascinating, controversial conclusion. So far, so good. Our instinct is to run to the nearest decision maker and say, “Look at this! You need to change!” Don’t. It’s very possible (maybe even likely) that you don’t have the complete picture. One or two false alarms can undermine your credibility. Instead of “You need to change!” try “What am I missing?” You’ll either uncover a flaw in your thinking before embarrassing yourself or you’ll have made your case to a decision-maker while showing that person you appreciate his or her expertise. It’s a win-win.
Moneyball heralded a new era of data-driven decision making in sports. But it’s time for the nerds to stop seeking revenge, whether in the front office of a baseball team or at the table of a nonprofit boardroom. Collecting and analyzing data is easy. Coming up with real insights is hard. Communicating those insights effectively? That’s where the real money is.
Originally published in The Chronicle of Philanthropy.