2019 Intelligent Automation Survey: Automation and the Government Finance Office of the Future

Due to recent growth in the use of automation in public sector financial management, Guidehouse collaborated with the Association of Government Accountants (AGA) to survey members on their knowledge of automation and plans to utilize it in their work in the coming years. Results are separated by the levels of government, whether federal, state or local, in which respondents work to exhibit variations in automation usage among the sectors. 

The perceived benefits of automation represent a primary finding of the survey. Among respondents, a significant share express belief in automation to positively impact government audits by improving the accuracy (83%) and availability (80%) of data. Half (50%) report feeling automation will reduce the complexity and cost of audits. Even more (60%) say they believe automation will improve the security of information systems by reducing opportunities for human error. Interestingly, only 26% report cost reduction as one of the top three benefits of automation. Although cost reduction is a downstream effect of many advantages frequently cited, this finding may highlight a belief that, despite upfront costs to successfully implement automation, its real value lies in steering the current government workforce toward higher value work instead of chasing and correcting errors. 

Another key survey finding is that survey participants think government entities generally understand where automation can best be applied but lack the dedicated funding and skills to take advantage of it. When an organization begins an automation effort, a significant first step is identifying processes that could feasibly and substantially benefit. Surprisingly, a vast majority of respondents (87%) report feeling confident in their ability to identify processes that could benefit from automation but face substantial hurdles in obtaining the necessary funding and skills to support the undertaking. 

Few (8%) indicate they receive a dedicated budget each year for automation, and most (80%) cite hiring, training or retraining staff to support the change as one of the most critical challenges to implementation. Echoing the need for the development of required skills to implement automation, roughly 40% of respondents state they have neither the knowledge nor the skill sets to assess the feasibility of such projects or to identify the tools available to support them. Without financial support and trained staff, it becomes clear why only 23% have developed a standard framework for automation projects and why even fewer use more mature automation tools, such as Robotics Process Automation (RPA) or machine learning-assisted processes.

Federal agencies, in particular, indicate more maturity in their automation efforts. While a small number of respondents (roughly 3%) from state and local agencies report using RPA, nearly five times as many (17%) from federal agencies say they are leveraging the technology. Further, compared to state and local agencies, federal agencies more frequently indicate having a standard framework in place for automation projects. This finding — that federal agencies seem more mature in their automation efforts — is particularly interesting when coupled with the discovery that federal agencies less frequently identify funding and appropriate software among their greatest challenges.

Inevitable struggles emerge in implementing automation and advancing the maturity of automation efforts. The survey results revealed the most acute problems faced are obtaining financial and staff support. Without these critical foundations, agencies face difficulties not only in implementing automation but also in advancing the maturity of their efforts. A holistic approach to automation and its successful execution does not happen overnight, but the resulting benefits of data accuracy, availability and cost reduction are worth the journey.

Special thanks to contributors Bob Dunmeyer, Elaine Slaven, Alexander Yow, Kerry Keys and Amy M. Oksol.