Voices from Accenture Public Service


I discussed in a recent blog our research into Decoding Organizational DNA. There is an abundance of valuable data available on work and the workforce. The workforce within public service organizations can act on this data through applied intelligence, yet many don’t know how. By applying intelligence in meaningful ways, they can solve the greatest workforce challenges facing government organizations.

In my experience I’ve seen that some have scratched the surface, using analytics to track workforce skills and shortages. However, few are unleashing the full power of this workforce data.

Applying intelligence

At Accenture, we think of applied intelligence in three layers. I believe each layer is quite valuable and, depending on an organization’s maturity, there is great potential to apply all three approaches to enable the workforce to do their jobs better and allow agencies to build a workforce that has the necessary skills.

1. Analytics

Analytics is essential to understanding the skills, roles and opportunities for growth within the existing public service workforce. By analyzing workforce data and making correlations, agencies can strive to upskill and reskill existing employees, or identify which skills they need to acquire for the future.

The challenge we see is that the data many agencies have is not structured to do so. Agencies also need access to a variety of data because the stronger the input, the more relevant the analytics can be to produce effective insights. Ideally, data from all agencies will be connected to create a more comprehensive picture of workforce opportunities. For instance, imagine if talent were shared across agencies. Analytics could help with matching people with the right skills to high-priority tasks—such as finding certified accountants to help during tax season. Analytics could also help with fluidly shifting people to other roles to manage turnover or gaps created by retirements.

2. Automation

As many of you experience, day-to-day work done in public sector agencies is largely transactional. Processing paperwork takes employees away from opportunities to truly add value to the citizen experience. Applied intelligence will automate a series of tasks to enable greater efficiency. By automating low-value-add tasks, the workforce can focus on high-value, complex tasks that require judgment, problem solving and one-to-one interactions with customers. For example, what if a worker could help a young single mother to find the right suite of services and benefits she qualifies for, rather than spending time processing her applications?

3. Artificial intelligence

Artificial intelligence (AI) involves having a machine learning system that learns as it works. We have seen AI take on a more important role, moving from being a back-end tool to being a tool that amplifies human capabilities.

Through our research, we found that 80 percent of public service executives said that the automation of certain simple tasks through machine learning will “free up employees to focus on more critical—and rewarding—activities that are more closely aligned with citizens’ needs,” and that this “will improve the job satisfaction of current employees.”[1] For example, the Italian Ministry of Economy and Finance (MEF) implemented an AI-driven helpdesk to handle citizen calls. The system can manage greater call volume than human operators, so citizens get faster assistance, which has led to customer satisfaction rising by 85 percent. Workers are then free to focus on helping citizens with complex situations or tend to important tasks that require the critical thinking and judgment of a human.

The foundation to support applied intelligence

I believe that before agencies use applied intelligence to transform the workforce’s activities, they must be prepared to transform. Successful transformation will require an investment in the right model, the right people to lead change and the right technology to bring the agency into the new.

Process – The introduction of applied intelligence enables an agency to streamline internal processes and eliminate certain tasks, which allows the workforce to focus on the most complex cases.

People – Leaders must champion data sharing and applied intelligence. They will need to forge a new “give to get” relationship with employees and share more control with them over their own data. Right now, only 16 percent of public service executives surveyed said, “We appoint C-level executive(s) to be accountable for responsible use of workplace technologies and data.”[2]

Technology – Traditional legacy systems cannot fully support the move to applied intelligence. Agencies must consider how to pivot to the new while ensuring workers can continue to successfully perform their jobs. Technologies such as cloud are essential to allowing agencies to access vast data. Agencies must modernize their core systems, transforming back office technology while continuing to deliver high-quality services.

France maximized process, people and technology to improve service delivery in social security. The agency supports more than 30 million families, providing benefits each month. The agency successfully migrated its old legacy system to the cloud, supporting applied intelligence while the workforce continued to serve citizens.

Clearly, applied intelligence has vast potential to improve the way government shapes and manages its workforce. But to take advantage, some groundwork must be done first to access the full benefits.

Let’s continue the conversation. Connect with me on Twitter and LinkedIn and stay tuned for upcoming blogs on the future workforce and the transition to an agile organization. When the world moves, move ahead.


[1] Accenture, “Emerging technologies make their mark on public service,” 2017, https://www.accenture.com/us-en/insight-ps-emerging-technologies

[2] Accenture, “Emerging technologies make their mark on public service,” 2017, https://www.accenture.com/us-en/insight-ps-emerging-technologies

Submit a Comment

Your email address will not be published. Required fields are marked *