Dataspeak has entered the nonprofit lexicon.  It took awhile—nonprofits historically have lagged behind the business world in using data to inform operations, fund raising and overall strategy.  This seems to be changing, and the new prevalence of terms like “CRM,” “dashboard” and “growth curve” in management and board meetings is one sign.

This is good news and bad news.  The good news is that our sector has long been starved for practical data to inform day-to-day decisions, and the best substitute—intuition—only works some of the time.  Now, data is easier to come by, the technology is better developed and more affordable, and the workforce is more tech-savvy than ever.  The more information we have, the better, right?

Not necessarily.  While having too little information is good, having too much brings its own troubles.  (I’m reminded of the great Hitchcock movie The Man Who Knew Too Much, and the more recent spoof starring Bill Murray, The Man Who Knew Too Little.)  We should be making progress, but are we?

We’re bombarded with information throughout each day.  Some of it is important, some is interesting, and a lot is neither.  Information is only as good as what we get from it.  Unfortunately, a lot of what we get is noise.  The problem is that the more background noise, the harder it is to hear the important idea or the cry for help.

Moneyball and Nonprofits

When I think of data, I often think about baseball.  Box scores, team and league statistics were my introduction to statistics by way of the morning paper.  I actually use baseball stats in one exercise in my nonprofit business model course to help illustrate a thought process. 

One great thing about baseball is that it lends itself to measurement, and you can construct a reasonably (though not perfectly) clear story through a data report.  The people running the business of baseball have figured this out, and they use stats in marketing the game through online databases, fantasy leagues, and broadcasts.  Sportswriter Gene Collier wrote this hilarious column about modern-day TV broadcasts, illustrating the absurdity of over-abundant data: 

Mr. Collier’s point is really that most data is just numbers.  Does it really matter if a batter has a .439 average against left-handed relievers on Tuesday night road games in June?  This is pure trivia.  Don’t get me wrong—trivia can occasionally be interesting or entertaining, but in itself it isn’t very useful, and if we don’t realize this fact it can have a real downside: distraction from what’s important.  Most data is trivia—it doesn’t help tell any particular story, and can fill up our limited bandwidth.  That’s true in organizational data too, whether we're talking about programs, activities or money.

Two-Dimensional Metrics

The first dimension of data is measurement—we have a raw number. 

A second dimension is attaching a level of meaning.  In baseball, this might be a batting average or won-lost percentage.  In nonprofits, this might be a financial bottom line, an average gift per donor, or an operational output such as clients served as a percentage of the goal.  These stats often show up in management reports, sometimes amid a sea of information.

Unfortunately, management and board meetings are often places data reports go to die.  A big reason is that they can be filled with trivia and/or two-dimensional metrics.  Another problem is that data can be misrepresented, sometimes unintentionally. 

For example, I sat in on a recent board meeting in which staff presented data about a “hugely successful” fund raising campaign.  The board apparently ate it up, even though the data  suggested a different story: lower returns than other activities, failure to accomplish the strategic goal of building long-term supporters, and a possible drain on the budget.  Just having data doesn’t mean your organization is “data-driven,” another popular buzzword.

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More Wheat, Less Chaff

Good management reports generally have less information, not more.  The key is to identify metrics that help tell the real story about the organization and where we’re headed.  The third dimension is depth that increases our understanding of critical parts of the enterprise.  To get there we need to proactively identify what really is critical, and then work backward to pinpoint which data will inform us. 

Three-dimensional metrics may be key trend indicators or drivers of financial health, service quality, employee productivity, or overall mission impact.  They’ll vary by organization and the situation. 

Three-dimensional data allows managers and leaders to focus on what is essential, while eliminating the background noise.  Most important of all is the context: We need to let data analysis tell the story, without prejudging the outcome.  If the result is puzzling or contradictory to our assumptions, we may need more data or better assumptions.

More good news is that deeper insight into data requires thought and care, but not expensive new software tools, fancy graphics or a staff of PhD statisticians.  And all of the information may be readily available. 

The first step is to ask questions about the story we want to understand.  

Posted
AuthorScott Schaffer