In a world of remote work and on-demand delivery, it’s hard for any organization to win consumer trust with bad digital services. The same is true for the federal government which lags the private sector on customer satisfaction, scoring lower than any other industry or sector studied according to research firm Forrester. But President Joe Biden recently signed a sweeping executive order aimed at modernizing government and improving customer experience and service delivery at federal agencies. The move comes after decades of delays and missed deployment dates that have contributed to the glacial pace of digital transformation in government.
But while it remains to be seen whether Biden’s executive order will turn things around, one notable technologist thinks federal agencies are already making headway in living up to the promise of digital transformation.
Enter Kirke Everson, principal, low-code practice leader, US government, and public sector at KPMG, a technology consulting powerhouse with over $32 billion in revenue and more than 236,000 employees in 145 countries. In the following interview, Everson shares his optimism and drops some serious knowledge on the future of intelligent automation, and the rise of low-code development, AI, and automation use cases in the public sector.
The promise of digital government never dies. These days, it caroms around the internet in the form of remarkable use cases and stories that signify success. So, stay tuned and grab some munchies. It’s time to roll the tape on Everson as he gives us an inside look at the rise of human-machine collaboration in government, decodes how low-code is helping agencies optimize customer experience, and spills the tea on why federal CIOs are betting on low-code to streamline acquisition and operations and innovate faster than ever before.
Note: The questions have been edited for clarity and brevity.
There are a lot of commentaries out there about the need for digital transformation in the federal government. I wonder what you make of research that shows most federal workers think their agencies are not keeping up with technology trends.
That’s a hot question, but it’s a good one. I think many agencies have been doing a lot of proof-of-concept (POC) and prototyping, especially when it comes to robotic process automation (RPA). I would say five or six years ago, there was a good volume of POCs. But I think now we’re seeing more and more agencies embracing low-code.
As you think about low-code and how it’s catching on in the public sector, what are the biggest barriers to accelerating adoption?
Agencies are constrained by legacy IT. And they’re trying to get what they can out of existing systems before investing in new technology. Low-code’s a great way to do that but to move the needle on adoption means educating customers about what low code is. I think there’s some confusion about what low-code is. But we (KPMG) found that when we educate clients on the benefits of low-code and the speed to value it offers, we generate excitement about it.
Let’s talk about the impact of COVID on federal IT modernization. In the private sector, the pandemic has had a massive impact on business process automation. What impact has the pandemic had on digital transformation at federal agencies?
Obviously, COVID has forced agencies to rethink their service delivery models for federal employees and citizens alike. And so, we’ve seen a paradigm shift in the public sector. We know that digital transformation enables the virtual delivery of government services. But COVID really forced agencies to think differently about delivery models to improve customer experience. The fact that the President signed an executive order to improve the federal customer service experience is critical.
The (President’s) order identifies more than 30 agencies that need to rethink how they deliver services to citizens from a customer experience standpoint. That spells digital transformation all day. And I think low-code will play a huge role in implementing the President’s order.
You mentioned digital transformation. You recently did an interview where you talked about enhanced automation and the three levels of intelligent automation maturity. How does that fit into the digital transformation narrative for large federal agencies?
When I talk about digital transformation as it relates to federal agencies, I’m talking about the maturity of an agency’s adoption of digital solutions, I’m talking about the complexity of the technologies in an agency’s digital toolbox. So, if you think about the most basic low-code capability—for example, situations where you’re leveraging RPA and bots to implement automation at the desktop level—many agencies are already implementing that kind of human-initiated RPA.
We’re seeing a lot of adoption with that kind of basic automation. But when you add things like natural language processing and low-code app development, you’re talking about enhanced intelligent automation where you’re leveraging platforms to build workflow-based solutions.
You’re trying to leverage APIs (application programming interfaces) to external sources and use a low-code platform to bring it all together in a hyper-automation kind of construct. And that brings us to the most advanced part of that technology stack, where you’re integrating artificial intelligence (AI) and machine learning (ML) into the workflows that you’re automating.
Practically speaking, how would you break that down. How would you describe enhanced automation in the context of a federal agency use case?
So, for example, maybe you have a fraud use case where you’ve got a case management solution and a low code platform with some RPA pulling data into the platform. And maybe you’re also leveraging a predictive analytics algorithm or some other AI solution to identify patterns in the data. So, now you’re providing cognitive automation to what you’re doing. Another way to look at it is to think about basic RPA as the arms and legs of automation and cognitive functionality as the brainpower. Obviously, there’s much more to it than that, but that’s a simple way to look at enhanced automation.
You’ve also talked about the critical success factors for deploying AI. How would you break that down for a federal CIO?
First and foremost, you really need to have an agency-wide digital strategy, and low-code needs to be a part of that. Identify the right use cases. Make sure you’re harnessing data in the right parts of the organization.
Make sure you’re looking for the highest potential return on investment. Take an approach that applies to different use cases for the different offices you’re going to be working with, as well as the different data sets that you’ll need to access.
This is why it’s essential to have a digital strategy and technology roadmap that allows you to determine the right tools for the workflows you should automate.
The second factor is very closely aligned to digital strategy. It’s creating and communicating a workforce plan to deal with the shift to remote work, leveraging more automation, and using more low-code solutions to enhance agency systems. So, working with the chief human capital officer to create a communication strategy, a workforce plan, and career architectures for citizen developers are all essential to helping the organization leverage people and technology deliver on the digital strategy.
The third factor is governance and policy. Using new solutions may require access to other systems. Sometimes this access goes against policy. This means you may have to update policy to access certain systems for unattended automation, as an example. Also, as agencies bring on new technologies to solve use cases, it creates a demand management challenge that should be addressed to reduce technical debt, identify use cases, and deliver solutions.
The challenge of getting from POC (proof of concept) to scale is tough enough. But, if you do it without governance, you could end up with disconnected solutions.
There’s growing pressure for organizations everywhere to scale automation. And many are considering low-code solutions to do that. But talk about the importance of analyzing and optimizing processes before scaling them.
Process analysis is the fourth success factor. In fact, evaluating processes and data is paramount to any successful implementation of a low-code platform. It keeps you from perpetuating problems in flawed workflows. It allows you to re-engineer processes and improve data sets. This is why agency CIOs are starting to look at their offices and teams as innovation hubs and not just as guardians of technology and infrastructure. These are the four success factors for digital transformation for any organization.
Let’s switch gears for a minute and talk about the amazing evolution of artificial intelligence which now touches so many aspects of our work and personal lives. How is AI being deployed in the federal space, and can you give some examples of how it’s improving the delivery of citizen services?
As a result of COVID, we’re seeing a range of AI-powered apps being spun up on low-code platforms for return-to-work vaccine tracking and those sorts of use cases. We’re also seeing chatbots being deployed for employee self-help and use cases that help customers resolve problems without dialing into a call center. You can couple chatbots with a low-code platform to implement any kind of (self-service) ticketing system.
We’re also seeing agencies leverage low-code platforms, as well as RPA, to review resumes as part of their talent recruiting efforts. Contract writing is another use case that’s catching on.
Another trend we’re seeing is low-code and natural language processing being used by agencies for acquisition management and procurement contract writing. So, these are some of the things we’re seeing especially with agencies focused on service delivery and call center automation which is becoming really critical for state and local governments. In the early days of the pandemic, there was a big influx of unemployment insurance claims.
But the legacy systems of many state and local agencies weren’t built for the exponential growth in claims. Because they didn’t have the call center strength to handle it, we implemented a lot of call center automation via low-code, RPA, and IVR (interactive voice response system) integration. We also leveraged chatbots by integrating them through RPA and low-code to backend systems to provide updates on claims status and the like. The use cases for low-code are plentiful. It’s definitely a great way to reengineer an agency’s processes and adapt them to a new mandate or a changing regulatory requirement.
You’ve argued that digital transformation—artificial intelligence, back-office automation, and the rest—has become a driving force in federal IT modernization. But you’ve also reminded us of the importance of re-engineering bad processes and not automating processes that are broken. So, I wonder what you make of the convergence we’re seeing now in process automation and low-code development in government and elsewhere?
I think they’re almost synonymous—low-code and process automation. I would say that when you’re looking at automation, you don’t want to just prove the technology works. Many agencies are getting past proof of concept and going right to a limited implementation. In the past, you documented the processes you wanted to automate, did a gap analysis, and then filled the gaps. But it was all very much a manual process with humans involved in the workflows.
Today, process automation is about human-machine collaboration.
And so, now when I’m looking at automating a process, I may look at automating the front end via RPA or ingesting different data sets from what used to be a manual process with someone logging into five or six different systems. Then I can use low-code to re-engineer the processes based on threshold-based approvals. That approach reduces the infrastructure and human labor cost of automating processes. It just makes sense to automate and re-engineer your processes at the same time.
Let’s switch gears and talk about the explosion of artificial intelligence (AI). What impact will it have on the federal workforce and how government agencies operate in the future. What are your thoughts on that?
The government is organizing around AI. For example, the DOD (Department of Defense) just reorganized and combined their AI with their data analytics efforts. So, they basically created a chief data and AI officer position that oversees AI, digital, and data across the entire organization. I think agencies are making investments and organizational changes to keep up with the growth of AI and automation.
So, I think as you create those constructs at the very highest levels of government, it sends a message to the workforce that this is an important part of achieving our mission and strategy. The way that that impacts the workforce, especially with a low-code platform, is that you’re seeing the democratization of AI and data analytics.
With low-code, you don’t have to be uber technical to use AI and other technologies to develop solutions that five or 10 years ago would’ve required a team of developers to implement.
Another hot trend that’s getting some buzz is citizen developers. What do you make of non-developers getting involved in application development—with governance and guardrails. And is citizen development a thing in the federal government?
We’re seeing the standup of citizen development programs at federal agencies. In fact, we were on a call today providing some suggestions on how to do that by looking at the current cohort of employees in your government agency and finding ways to get them involved in leveraging automation via low-code solutions. And that kind of engagement creates excitement. It boosts workforce morale, and it allows workers to rethink how they’re getting work done.
Each agency is reevaluating its digital strategies annually because the pace of change and enhancements to solutions is happening almost on a quarterly basis. And so, having a digital strategy that’s looking out five years won’t cut it. It’s almost like you have to revisit your digital transformation strategy every year. And that includes the human element—the workforce.
So, going back to the citizen developer trend, the democratization of AI, all of these things are permeating the day-to-day operations of government agencies and employees. So, I think it’s an exciting time to be in the federal workforce.
This leads to another question I wanted to touch on which is the argument that the biggest barrier to digital transformation is cultural resistance to change. As you think about that argument and about what you just said about low-code and the democratization of application development, how does low-code fit into the change management conversation?
I would say the idea of change management and resistance to change impacts every organization. We see it in the private sector as well. Anytime you bring transformation into the picture, there’s going to be an aspect of change management. So, I would say that’s going to be a factor with any large organization looking to do low-code development and digital transformation.
But what we’ve also seen is that as we start to educate the workforce and get them involved in the process—like the programs I mentioned earlier around citizen development—people get excited about how these solutions can make their lives easier with workflow solutions. I think one of the biggest actual resistances to change is just the long procurement cycles you see in government.
But the good news is agencies are getting creative. For example, you’ve got the Navy’s Information Warfare Research Projects where low-code is being used to prototype workflow solutions.
The Department of Commerce has the National Technical Information Service’s joint venture program that leverages digital innovation procurement in a rapid way. These are just some of the ways that government agencies are trying to streamline acquisition and operations and get innovative a lot quicker. Finally, another barrier to innovation in government is more procedural, like getting a platform approved, getting the authorities to operate on agency networks, getting security accreditation, and the like. But once you get a low-code platform approved, building applications on them is so much easier than before.
Looking over the horizon, are you hopeful about the future of IT modernization in the public sector in 2022 and beyond?
Yes, I’m hopeful. The way forward is rapid prototyping and implementation of solutions like low-code to quickly optimize the delivery of citizen services. The days of taking five or 10 years to stand up a large enterprise-wide system are over. Today, agencies can’t wait that long. So, having the ability to stand up a mission-critical application in a week to satisfy a new requirement, or to meet new demand, you can’t wait years for that, you can’t even wait months in some cases.
I think the executive order the president signed recently underscores the urgency of accelerating digital transformation in government. I think public sector CIOs recognize their agencies really need to prioritize the customer experience. It’s long overdue. The roadblock is legacy IT.
So, how do you overcome that challenge and get speed to value? It’s going to be through technologies like low-code. It’s going to be through automation. And it’s going to be through leveraging AI. These solutions are like arrows in the quiver that agencies can use to improve customer experience. I think low-code is here to stay, and I’m excited about the solutions low-code will bring to agencies in the future.