Conduct Relevant Analysis
So far this guide has focused on performance management or results-focused management which is only one half of the equation, because there needs to be an analytical engine under the hood of every organization. Analytics is not new. People have been trying to understand our world since we first woke up in it. This diagram was published by statistician Florence Nightingale who pioneered use of the polar area diagram to explain causes of death in the British army during the Crimean War. The diagram showed that epidemic disease, which was responsible for more British deaths than battlefield wounds, could be controlled by a variety of factors including nutrition, ventilation, and shelter.
At GovEx, we encourage governments to build a performance and analytics practice to turn information into insight. Performance analytics is what’s under the hood and encompasses a broader suite of competencies necessary in 21st century governments. Along the way, analytics helps answer some core questions faced by government leaders:
- What happened? Descriptive analytics helps us understand what happened. We can’t just use dashboards, metrics, and KPIs to answer these questions. We have to have more real-time analytics.
- Why did it happen? We usually wait for Stat meetings to ask and answer these questions but governments need more opportunities for self-service analytics so every employee can answer questions like this at his or her desk.
- What will happen? Governments sometimes think benchmarking against other jurisdictions will answer this question, but it helps to maximize what your know about yourself first. Knowing what will happen often starts with analyzing your own performance trends.
- How do we make it happen? Very few government organizations are taking advantage of more robust data and the latest technology to optimize their performance with predictive analytics.
Understanding analytics through a traffic jam
| Question | Type of Analysis | Traffic Jam Example |
|---|---|---|
| What happened? | Descriptive | A driver knows there is a traffic jam because he is stuck in it. |
| Why did it happen? | Diagnostic | A traffic reporter in a helicopter tells listeners the traffic is due to an overturned truck. |
| What will happen? | Predictive | Google Traffic uses color to show users there is bad traffic ahead. |
| How do we make it happen? | Prescriptive | Waze optimizes your route to minimize traffic and drive time. |
Analytics in Practice
New York City, NY established the Mayor’s Office of Data Analytics (MODA) to leverage data science practices across city operations:
- Used open data to identify, with 95% accuracy, restaurants that were illegally dumping cooking oil into sewers doubled the city’s hit rate in finding stores selling bootleg cigarettes
- Sped the removal of trees destroyed by Hurricane Sandy
- Helped steer housing inspectors to lawbreaking buildings where catastrophic fires were most likely to occur
Washington, DC began a significant investment in data-driven decision making in 2007:
- Used better data on HIV transmissions to implement behavior interventions that have reduced transmissions year over year
- Improved data collection on students with disabilities to reduce segregation in DC public schools
- Launched Track DC and Grade DC to engage residents in performance and accountability discussions
- Infused high-quality analytics into CapStat, SchoolStat, and EdStat
Chicago, IL established a Chief Data Officer in the Department of Innovation & Technology to manage data science projects for the city
- Used open data to identify restaurants likely to experience critical violations to more effectively deploy inspectors violations were found, on average, 7 and a half days earlier. That is, an additional 37 establishments would have been cited for violations in the first month, as opposed to being discovered later, potentially after patrons became ill.