The Case for Government Investment in Analytics


Jane Wiseman

Date Published:
September 20, 2019

Government stands to gain $1 trillion globally from using data analytics.1 Few government data teams have the resources to document their value, but those that do can show as much as eight-to-one return on their cost. There is significant non-financial benefit as well, as public faith in government may improve when saving time and money is paired with increased transparency and accountability.

This blog highlights an analytical framework for government use of data and analytics to improve public outcomes proposed by Jane Wiseman. In her paper, Ms. Wiseman cites successful case studies to support her proposed framework and makes a strong case for governments at all levels to invest in analytics and data-driven approaches.

Executive Summary

Many leading governments are already innovating with data and improving results, but these exemplars remain in the minority. While there are over 30,0002 units of local government, only two dozen local governments have a data leader who participates in the Civic Analytics Network, a peer network of data leaders hosted by Harvard Kennedy School. Similarly small numbers of state and federal data leaders are in place. And fewer still have been able to document the concrete value of their results.

How can other state and local governments tap into this potential for public value? And how can they measure their impact and demonstrate value? This paper documents successful data analytics efforts in government and describes approaches to calculating returns. The purpose of this paper is to enable jurisdictions to make the case for investment in data analytics with a goal of advancing the state of data-driven government.

While there are many possible ways to describe the value to government of using data, this paper addresses three types of value created:

  • Financial return attributable to analytics efforts;
  • Operational process improvements achieved due to data and analytic approaches; and
  • Increased faith in government attributable to data and transparency efforts.

With increasing availability of low-cost tools and large volumes of data for analytics, now is an excellent time for further investment in government analytics capabilities. Low cost and user-friendly analytics tools such as visualization and dashboarding allow for pattern analysis. Advanced analytic models can identify and predict negative outcomes that would have been overlooked by human judgment alone. Internet of Things (IoT) sensors, drones, and modern mapping tools have rapidly increased the availability and speed of location-based data analysis. In this environment, government leaders should carefully examine the successful examples here of providing financial benefit, operational efficiency, and improved faith in government.


While the application of big data analytics in government is not new, it is yet to be uniformly adopted. And yet, there is significant value to be achieved for those jurisdictions that adopt data analytics and related digital and technology approaches.

The consulting firm McKinsey estimates that globally, government stands to capture $1 trillion by using big data analytics to identify both revenue not collected and to recoup payments made in error.3 Looking at the return on investment, the firm’s research shows that efforts to apply data analytics to eliminating waste, fraud, and abuse in government can have returns as high as 10 to 15 times their cost.4 There is significant non-financial benefit as well, because as governments improve efficiency and decrease waste, fraud, and abuse, their esteem among the public grows and faith in government improves.

A great deal of excellent work is being done by data leaders in federal, state, and local government, as the examples in this paper demonstrate. Often, data leaders such as chief data officers are under-resourced and juggling competing demands on their time. Precious little time is left for calculating and documenting the return on investment for their projects. And yet, setting aside time to evaluate and record the benefits of their work might result in government leaders realizing how powerful an asset they have and investing more resources.

Leaders in jurisdictions and agencies without a current data leader may see that creating such a position would bring value and help advance an agenda of not only better service to the public, but also improved public faith in government.

Many experts believe that the gap between analytics leaders and laggards is growing, not closing. As technology author Tom Davenport points out, advanced analytics tools are likely to help those already at an advantage as “big companies get bigger.”5 This is true in the public sector, as networking helps the leaders accelerate their achievements, while momentum to appoint new data officers is dissipating.

With this in mind, it is critical that state and local governments that have not already become leaders in analytics begin now to address this challenge, and an important first step is making the case for investment. Ms. Wiseman’s paper aims to help in that regard by providing evidence as well as an analytical framework for measurement of three types of value created: financial, operational and public trust in government.

Analytical Framework

The paper describes the three categories of public value: financial, operational, and public trust in government, and then provides examples and methods of measuring each type of result.

  1. Financial Return on Investment – Very few government performance or analytics teams have the available resources to measure the financial return on investment for their work. Financial returns from analytics projects can take a variety of forms. Examples in her paper address cost recovery and revenue gained through fraud detection, process efficiency improvement, improved data and service targeting accuracy, and revenue capture.
  2. Operational Process Improvements – Data analytics and digital transformation can significantly improve the efficiency of government operations. Consulting firm Deloitte has estimated that applying automation technologies such as machine learning, natural language processing, and robotics could save 1.2 billion hours of effort by federal government workers and save $41.1 billion.6 Applying data analytics can turbo-charge a government efficiency effort. The consulting firm McKinsey surveyed state, local, and national government officials in 18 countries and found that most government transformation efforts fail, with less than one in five “very or completely” successful in achieving their goals.7 However, the government transformation efforts that used analytics were twice as likely to succeed as those that did not. 
  3. Improved Trust in Government – Not all value that data leaders deliver is easily quantified. In fact, some types of public value are very difficult to measure or are measured very rarely, such as the contribution of government services to the well-being of individuals or society as a whole, or to environmental sustainability or economic mobility. Some promising efforts are bringing the voice of the customer into government operations, via 311 system customer satisfaction surveys, social media sentiment mining, and online feedback forms, but most of these efforts are narrowly focused on one task or department. A small number of state and local governments regularly measure public satisfaction with their results, but they are the exception rather than the rule.

Read the full paper here to explore details of the analytical framework and supporting case studies that make a strong case for increased government investment in analytics. 

[1] Cunningham, Susan; Davis, Jonathan; and Dohrmann, Thomas, “The trillion-dollar prize: Plugging government revenue leaks with advanced analytics,” January 2018, McKinsey & Company.

[2] United States Census Bureau, Census of Governments, 2017.

[3] Cunningham, Susan; Davis, Jonathan; and Dohrmann, Thomas, “The trillion-dollar prize: Plugging government revenue leaks with advanced analytics”, January 2018, McKinsey & Company.

[4] Cunningham, Susan; McMillan, Mark; O’Rourke, Sara; and Schweikert, Eric, “Cracking down on government fraud with data analytics”, October 2018, McKinsey & Company.

[5] Davenport, Thomas H. The AI Advantage: How to Put the Artificial Intelligence Revolution to Work, MIT Press, 2018, page 32.

[6] William Eggers; Schatsky, David; and Viechnicki, Peter; “AI-Augmented Government: Using Cognitive Technologies to Redesign Public Sector Work,” Deloitte University Press, April 2017.

[7] Allas, Tera; Dillon, Roland; and Gupta, Vasudha; “A Smarter Approach to Cost Reduction in the Public Sector.” June 2018, McKinsey & Company.