Start with insight, not just sentiment. That’s how to unlock better service delivery, says Derrick Pledger.
It might seem obvious, but it is easy to get distracted, explained Pledger, chief digital and information officer at Maximus.
“Before you click a button or choose a tech solution, you need to understand what people actually need and how they feel about the service today. That intelligence should be the foundation for everything that follows,” Pledger told Federal News Network for our Forward-Thinking Government series.
That’s why it’s critical to understand sentiment and how it changes over time, he said. “It should be at the center of any customer experience journey, especially when you’re trying to do something at scale for millions of people.”
Intelligent data strategies are redefining how agencies understand user needs and mission performance. The technology and the data let the organization align with sentiment to meet that mission and be proactive, Pledger said.
“It’s really the investment in people,” he said. “You understand who you’re serving and how they like to be served.”
Pledger shared a strategy for keeping intelligence at the forefront as federal agencies continually evolve their digital environments and deploy emerging technologies in pursuit of mission.
Start with the customer journey, then back into the tech
The frantic pace of technology tends to pull attention away from people.
“We’ve been overly consumed by ‘Let’s build a technology, solutions, or service roadmap.’ But what you need to have first is a customer experience or a customer journey roadmap,” Pledger said. “That’s what should be at the top right. There’s a certain experience, or a certain outcome, that you, like your customers, need to achieve in [a certain] amount of time. Then you layer in technology.”
In a basic construct, that customer journey roadmap must, in an agile and circular manner, keep addressing some basic questions:
- Who are the people we’re serving?
- What do they need and expect?
- How do they interact with our systems?
- How do we deliver those outcomes efficiently?
By leveraging AI and automation, agencies can shift from reactive service delivery to predictive and personalized engagement, Pledger said. “Intelligent data allows us to see issues before they escalate and design services that meet users where they are, when they need help.”
It’s not that agencies in the government or organizations anywhere set out to create broken, slow or ineffective workflows. Technology now is giving organizations the ability to tap into sentiment as the through line, to make workflows effective based on the desired outcome and to be responsive on the fly, Pledger said.
“If we just take a breath and figure out the problems that we’re actually trying to solve and what those journeys are, I think we’d all be better suited,” he said.
By not over-focusing on technology, organizations also become more agile. Technology will continue to change, and sentiment lets the organization know how to make the best use of technology capabilities as they emerge and evolve, Pledger pointed out.
“If a person is having a terrible experience, or it’s a lot of friction to get something done, that is the legacy way of looking at CX. CX now is very much different,” he said. “It’s a spectrum. It’s efficiency first, but then you move into effectiveness. And then, how do you translate from effectiveness to insight and action?”
Manage knowledge, not just data
Tapping into sentiment and the experience of people was not possible in the way or at the scale that it is now. That’s where data and technology come into play, Pledger said.
But he also shared a critical caveat: “The issue that agencies, both public sector and private, have been trying to solve is a knowledge management problem. It’s more knowledge than it is data.”
With that perspective on the CX journey, the people and sentiment then come back into focus.
“How do you use technology to sit on top of your data layer, understanding that there’s going to be so many different places where your data lives, to make sure that you can democratize the data behind that?” Pledger said. “To give an example, at Maximus, we use an AI-powered knowledge management framework that sits on top of a lot of our data sources across the company. If I need to ask a question in a conversational way with AI — ‘I want to know three things about X? ’— it goes across all of our different data sources that we’ve put into an index and then provides me with an answer.”
Remember, AI isn’t the solution, it’s the accelerator
AI will do three things for agencies, Pledger said. “It’s going to change the way we work. It already is doing that. It’s also going to change the way you deliver service at scale, especially citizen services, and it’s going to change the pace at which we’re able to innovate.”
Because AI and automated technologies themselves are evolving quickly and they give organizations the ability to iterate quickly, Pledger reiterated the importance of keeping the focus on outcome and people. Planning is how to do that.
“Planning for the deployment of AI is a lot more important than the actual deployment and care and feeding and operationalization of it,” he said. “Because if you’re not deliberate, if you don’t have forethought around what you’re trying to solve, just getting a software as a service tool or a new tool from Silicon Valley is not going to solve your problem. We have to be judicious about how we’re going to deploy the capability.”
But planned AI implementation will help solve people challenges and keep pace with sentiment. Pledger recommends pairing the latest AI capabilities with knowledge management. In that way, agencies can keep monitoring and learning from sentiment and then iterate services and enterprise technology accordingly.
By way of example, he pointed to agencies like the Veterans Affairs Department and the Social Security Administration. AI will reduce the time it takes to make sure a person can get to a particular outcome, Pledger said.
“There are millions and millions of people that are waiting for a particular outcome, and there’s not enough people to be able to address that, so we have to use AI as an enabler — AI as a superpower.”