Blinded by our love of metrics, we pursue data. Yet, as we recently explored, the cost of that pursuit is often high. Staff time is assigned, support contracts are signed, information technology systems are built and secure storage facilities are negotiated.
We are also blinded by an assumption: that data is critical to anticipating the future and investing public funds responsibly. We’re intrigued, entranced, obsessed. We worry about the gaps and suspected errors so we dismiss any extrapolated insights as flawed. And, then we come right back because—like all codependent relationships—we believe we need it (data) to exist.
In spite of this conundrum, we get sucked into the data game like we’re at a carnival. We go back time after time trying to get enough tickets to buy the big prize—but suspecting somewhere in the back of our minds that the stuffed animal is worth a fraction of what we spent to “win” it. And despite working in a time of notable budget shortfalls, the cost to collect data is rarely being scrutinized or the efforts to collect data cut back once they’re started.
Our data appetite is insatiable. Why? Because we’re desperate for answers. When we’re not exactly sure what the questions are, we believe data is the first step on the right path to getting there. In fact, you’d be hard-pressed to find a federal program manager (or their consultant behind the scenes egging them on) who didn’t think having more data was a good thing. Perspectives like that of Kevin Cincotta in Government Executive make so much sense on the surface that data collection efforts often go unchallenged.
Our data appetite convinces us that we’ll use it if we have it. In reality, nothing seems further from the truth. Forrester reported last year that a meager 12 percent of the data collected is ever analyzed. Yikes! This number might be startling at first glance, but it won’t really surprise many federal employees who live this reality. Within our federal programs, there is a limited awareness of the data available, concerns about data quality, a lack of analytical skill available to analyze it, and a just plain old lack of time. The time factor, to me, is the single biggest downfall with collected data. It’s expensive to collect and sadly, much of it goes unused. Plain and simple, it’s a waste.
So, we’re stuck, right? Maybe not. Responsible and assertive leaders must chart another path—up and around the hurdle created by the need for data. This path consists of three steps:
1. Build awareness
To start, agency leaders need a clear understanding of the data collection efforts underway within their organizations. This understanding doesn’t require an exhaustive inventory, but it does require a broad understanding of the top five or so programs requiring data collection and maintenance. Understanding what directives staffs are working under and what the response looks like—the number of staff assigned, the rough value of support contracts, and related systems. This exercise is necessarily conducted at the leadership level—it’s not a program by program problem.
Next, look at the internal and external reports being produced. Stretch beyond what information is being conveyed on the surface and dig deep to determine what (if any) insights are being gained. Which data elements do staffs depend on regularly to make decisions about the direction of the organization?
Based on the understanding gained by agency leaders in step 1, plot the big data collection efforts on a simple 2×2 matrix. Label one axis “federal mandate” (yes, no, or sort of) and the other “high mission utility” (yes, no, or sort of). Obviously, two combined “yeses” earns a green light, while two combined “noes” means an effort is phased out. The “sort of” rating equates to the work of program managers and leadership to either move certain data collection efforts solidly into one box or the other.
2. Vigorously push back:
For any data collection efforts falling into the “yes it’s a federal mandate, but has no mission utility” quadrant, agency leadership should vigorously push back, request an exception, or work to change the requirement so that it better fits the agency’s purpose. Agencies (and the government as a whole) simply don’t have the discretionary budget it takes to apply blanket rules to a deeply nuanced environment.
3. Reenergize analytics:
The biggest thing leaders can do to get more value out of the time invested in data collection is to ask for the reports. Ask program managers to share with you what they think is important. Be careful not to ask too loudly about what else would be nice to know—remember that anything you ask for has a trickle-down effect that costs more money.
Responsible leaders know the costs of data collection and continuously weigh the benefits. They also ask the right questions in the pursuit of data: Are we getting the insights we need? Are we getting the return on insights for the investment in collection? Would the public agree?
This article originally appeared in Bloomberg Government.