Changing the Game: A New Playbook for Government Financial Management

By Oftelie, Antonio | Government Finance Review, December 2014 | Go to article overview

Changing the Game: A New Playbook for Government Financial Management


Oftelie, Antonio, Government Finance Review


The game is changing for government chief financial officers. The convergence of advanced analytics, evidence-based budgeting, and behavioral economics has the opportunity to transform not only how programs are evaluated and decisions are made, but also how program design can be improved to create greater public value. Together, these methods will help solve the problems that are often present in traditional ways of managing program investment--a zero-sum game where someone wins and someone loses, the "budget office" becomes either a hero or villain, and value for citizens isn't fully achieved.

MANAGEMENT TECHNIQUES

Advanced Analytics. Advanced analytics is the use of technological platforms, social networks, environmental sensors, data storage, and data analysis methods (both people and software, and what's referred to as "big data") that allow better measurement across the entire enterprise of inputs, outputs, outcomes, and impact. When these measures are put together, leaders can assess the performance of a system from a wider perspective --across departments, agencies and jurisdictions--and from deeper within programs and operating units. This analysis can then drive innovation in programs and the creation of new services.

As a case in point, the New York City Mayor's Office of Data Analytics is now employing analytical techniques at an enterprise level to capitalize on opportunities to improve and transform services. The office began in 2011 with just three junior analysts, some old computers, spreadsheets, a lot of performance reports, and data that were siloed in different agencies. Now, the unit is working on city-wide challenges, and its insights help city employees perform their jobs more effectively, with a measureable impact that benefits New Yorkers through more responsive and accurate services.

For example, the "Databridge" platform allows authorized users to analyze and share current and historical data, enabling predictive modeling to uncover useful insights buried in the data. (1) For one project, the analytics team developed a mobile inspection app to combine data from different departments and agencies for buildings and neighborhoods. Previously, anyone who led a property inspection had to gather information from multiple agencies.

Databridge is useful in real-time as well. In the past, first responders to emergencies had little advance information. Before sending out a fire truck, they might have had to query the Department of Environmental Protection system about hazardous materials storage and check with the Department of Buildings systems to find out about recent construction that could affect sprinkler systems. Now, the app allows the fire department to query all building records and assess the circumstances immediately, predicting the most dangerous situations and ultimately saving lives.

Evidence-Based Budgeting. Evidence-based budgeting uses rigorous analysis of program investment, outputs, and impact relative to outcomes to quantify return on investment and other financial metrics. The "engine" of evidence-based budgeting is the randomized control trial, which compares metrics of one program (via data on program outcomes and impact) to those of a control group or program. Historically used for scientific experiments, this technique is rapidly gaining acceptance for use on social programs and initiatives that produce a lot of data. This form of analysis is unequaled in its ability to measure or provide "evidence" of a program's results.

Evidence-based budgeting is becoming a central strategy within the White House and the executive branch. A recent U.S. Office of Management and Budget (OMB) memorandum notes, "An important component [of the president's management agenda] is strengthening agencies' ability to continually improve program performance by applying existing evidence of what works, generating new knowledge, and using experimentation and innovation to test new approaches to program delivery. …

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