Are You Driven by Analytics or Instinct?
Intuition is great, but analytics is better: Executive branch department creates data-driven culture
With a $686 billion budget, $2.3 trillion in assets, 3.4 million employees, and multiple offices and divisions, this federal department is one of the largest entities in the world. This huge federal department was stuck in the past though. Many of its processes were old-fashioned and relied on legacy-based analytics with no actionable insights — often forcing leaders to rely on gut instinct to make decisions.
This department knew it needed to change, so it developed a culture that embraced and leveraged data. It had data scientists create reports that combined data from multiple sources. These reports drove transparency, results, and accountability across the department and helped leaders use analytics, rather than instinct, to justify budgets and investments in new projects.
Organization: Executive branch department of federal government
Goal: Move away from old-fashioned, legacy-based processes to modern analytics-based processes
Solution: Build a collaborative, results-based culture guided by logic, management, and data
Results: New processes inspired transparency, actionable insights, and accountability across the department. Leaders now use analytics, rather than instinct, to justify budgets and investments in new projects.
A bright point of light amid two hurricanes: Advanced analytics paves the road to recovery for over 100,000 people using geospatial and predictive insights
We can’t control hurricanes, but we can control our response to them, and that’s exactly what Atkins, a contractor to the Federal Emergency Management Agency (FEMA) did. In response to Hurricanes Irma and Maria, they built an advanced analytics model that combined geospatial information systems (GIS), strategic field assessments, and predictive analysis to determine how much damage a building was likely to have after the storms.
Normally, a task like this would require hundreds of people going to each structure and filling out reports by hand — work that could take years. With their new model FEMA didn’t have to inspect structures in person and could move much more quickly. Using predictive analytics, they evaluated approximately 200,000 structures and were able to dispatch aid to the most affected areas. They saved years of recovery time for communities and years of assessment for themselves, not to mention tens of millions of dollars in response effort.
Organization: Federal Emergency Management Agency (FEMA)
Goal: Rapidly assess the damage to structures caused by Hurricanes Irma and Maria
Solution: Build an advanced analytics model to determine how much damage a building was likely to have after the storms
Results: FEMA rapidly evaluated approximately 200,000 structures, speeding the recovery for people and communities by reducing the years of assessment for themselves and saving tens of millions of dollars in response effort.
Plugging the leak: Saving tons of water (and $$$)
The only thing worse than a water leak is a water leak that goes unplugged for two months. This is what the city of Tallahassee, FL, wanted to avoid. For years, two or three analysts would receive a 600-page PDF report every day, detailing water usage for around 200,000 water meters. The analysts would eyeball the document for potential leaks. If a property looked like it had a problem, a notice was sent to billing, and then a technician would visit the property to leave a door hanger notifying the customer. On average, the whole process from detection to door hanger took between 50 and 55 days. Tallahassee decided to automate these processes.
They built a model that automatically identified customers with unusually high water usage numbers. Their new system alerts between 15 and 40 people per day that they may have a problem and cuts the detection to door hanger time from 55 days to just five, saving customers a lot of money and water. Customers can now address the problem before they receive a shocking water bill.
Organization: City of Tallahassee, FL
Goal: Notify customers of a potential leak before they get a $1,000+ bill
Solution: Leverage analytics to turn the manual processes of detecting water leaks and notifying customers into an automatic process
Results: Improved the process of detecting a leak and notifying a customer from 55 to just five days, saving customers a lot of money and water.
From geospatial information systems that help with disaster response to models that predict leaky pipes, see how government and public sector entities can leverage data and analytics to modernize processes and save both time and money.