Several years ago, I was sitting at a conference table with a group of federal employees to discuss their data analytics and reporting requirements. The reports we were building were part of a data warehouse with more than 100 valid measurements. “What measures matter the most to you?”, I asked the group, “What do you want to include in your reports?”. Without hesitation, the lead spoke up: “Everything.” The others in the room nodded and then a co-workers interjected, “Yes, just as long as we don’t ‘boil the ocean.’”
That comment resonated with me. Today I still wonder if the team realized the contradictory nature of the two messages—to have everything in your data system available while at the same time avoiding too much complexity. For me, this highlights the main problem with establishing an effective data analytics strategy; the users want to have, yet not have; to see the data from all angles, yet not be overwhelmed by too much insignificant information. I suspect that what these employees really meant is that they wanted to have the most meaningful data available to them without having to suffer through the “noise” that is the byproduct of deep-dive granularity. They wanted to know what really matters for their organization, but did not know how or where to begin given all the possibilities.
Not having a starting point is a common issue, especially among agencies where the mission driving reports can be broad, non-specific, and subject to various levels of interpretation. Most officials agree, however, that timely data collection and reports are required to assess program effectiveness. Congress itself recognized the need for better performance measures with the passage of the Government Performance Results Performance Act of 1993 and the subsequently revised 2010 Government Performance Results Modernization Act (known as GPRA or simply “The Modernization Act”. The GRPA guides the establishment of Performance Management systems, enabling agencies to monitor and report on various program goals and to address the effectiveness of their program activities, products and services. But the guidance only specifies the process and does not necessarily address the direction an individualized data analytics program should take. We are still asking what are the collective goals of the agency and how are the data requirements designed to meet them?
There is no one-size-fits-all solution and we must expect that each agency will have a unique reporting agenda once the requirements are outlined. There are general rules of thumb that can put this process in motion. Perhaps the most important one is to remember that the collection, synthesis and analysis of data serves a single purpose: to provide those in charge with the ability to make better decisions. Put another way, data analysis is NOT about how many reports, drill-downs or database variables can be gathered over time, but rather, the results of good analysis lead to educated decisions that in turn create positive, important outcomes. Depending on the agency, such outcomes could include the following:
- Enhanced Customer Service and Satisfaction
- Better access and care of citizens, employees, or other populations
- Improved organizational processes
- Reduction of measurable fraud, waste, and abuse
- Forecasting to improve service demand and delivery systems
By recognizing and highlighting the results first, and then working backwards to ask: “Which measures would help the agency make better decision to get to these outcomes?”, an agency can start establishing a plan for effective data analytics. If the gathered measurements boost improved decision-making, then this should be part of the plan. If not, then they can be set aside until deemed otherwise. Through this method, stakeholders can avoid the contradiction of wanting to have it all yet retaining simplicity. Answering the single question “What measures matter the most to you?” involves the thoughtful consideration of outcomes, recognizing which decisions will have the most impact, and being aware that data reporting in moderation—as opposed to providing “everything”— will offer the right type of value and still keep the oceans from boiling over.