NextGov: “Analytics is often touted as a new weapon in the technology arsenal of bleeding-edge organizations willing to spend lots of money to combat problems.
In reality, that’s not the case at all. Certainly, there are complex big data analytics tools that will analyze massive data sets to look for the proverbial needle in a haystack, but analytics 101 also includes smarter ways to look at existing data sets.
In this arena, government is making serious strides, according to Kathryn Stack, advisor for evidence-based innovation at the Office of Management and Budget. Speaking in Washington on Thursday at an analytics conference hosted by IBM, Stack provided an outline for agencies to spur innovation and improve mission by making smarter use of the data they already produce.
Interestingly, the first step has nothing to do with technology and everything to do with people. Get “the right people in the room,” Stack said, and make sure they value learning.
“One thing I have learned in my career is that if you really want transformative change, it’s important to bring the right players together across organizations – from your own department and different parts of government,” Stack said. “Too often, we lose a lot of money when siloed organizations lose sight of what the problem really is and spend a bunch of money, and at the end of the day we have invested in the wrong thing that doesn’t address the problem.”
The Department of Labor provides a great example for how to change a static organizational culture into one that integrates performance management, evaluation- and innovation-based processes. The department, she said, created a chief evaluation office and set up evaluation offices for each of its bureaus. These offices were tasked with focusing on important questions to improve performance, going inside programs to learn what is and isn’t working and identifying barriers that impeded experimentation and learning. At the same time, they helped develop partnerships across the agency – a major importance for any organization looking to make drastic changes.
Don’t overlook experimentation either, Stack said. Citing innovation leaders in the private sector such as Google, which runs 12,000 randomized experiments per year, Stack said agencies should not be afraid to get out and run with ideas. Not all of them will be good – only about 10 percent of Google’s experiments usher in new business changes – but even failures can bring meaningful value to the mission.
Stack used an experiment conducted by the United Kingdom’s Behavioral Insights Team as evidence.
The team continually tweaked language to tax compliance letters sent to individuals delinquent on their taxes. Significant experimentation ushered in lots of data, and the team analyzed it to find that one phrase, “Nine out of ten Britains pay their taxes on time,” improved collected revenue by five percent. That case shows how failures can bring about important successes.
“If you want to succeed, you’ve got to be willing to fail and test things out,” Stack said.
Any successful analytics effort in government is going to employ the right people, the best data – Stack said it’s not a secret that the government collects both useful and not-so-useful, “crappy” data – as well as the right technology and processes, too. For instance, there are numerous ways to measure return on investment, including dollars per customer served or costs per successful outcome.
“What is the total investment you have to make in a certain strategy in order to get a successful outcome?” Stack said. “Think about cost per outcome and how you do those calculations.”…”
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