As federal employees embrace modernization, data products are the next frontier
56% of participants in our 2023 digital modernization report indicate that adopting a cloud-based IT infrastructure is the most critical advancement their agency can take to modernize the IT environment. And 82% agree that it’s impossible to modernize without using low-code/no-code solutions. But, interestingly, operating without third-party support (34%) is down from 2021 (50%), which suggests an openness to relying on expertise from outside consultants.
The cloud is enabling data analytics scenarios that were previously impractical. In the past, for example, analytic tools to support healthcare fraud detection or perform regulatory surveys were focused on individual providers. But for agencies to take a more proactive and forward-looking approach, they need to be able to analyze data across providers and beneficiaries to identify trends and patterns. These kinds of scenarios require access to more data and compute resources. And to be innovative, data scientists need to be able to rapidly explore large datasets and experiment with various machine learning algorithms. The cloud enables this innovative behavior by empowering users (e.g., analysts with some programming skills) to provision these compute resources on demand and then discard them when they’re finished.
But simply putting these cloud-enabled technologies into the hands of mission teams doesn’t guarantee success. As our research points out, 80% of federal IT employees have at least one, and in fact, 40% cite five or more existing programs or solutions that are not being regularly used by their agency. And 37% cite change in leadership or direction as a reason for sporadic use.
A lack of “product thinking” may be contributing to these outcomes. If data leaders strive to change their agency’s culture to begin thinking about data as a mission-critical product (in its own right), rather than only the technology solutions that expose the data, then the link between these data products and the mission will be clearer. This product thinking will ensure that proper attention to data quality and interoperability is applied and maintained by the organization over time and across changes in leadership.
Data leaders can also apply best practices learned through industry experience in delivering operational IT products over the last couple of decades. For example, domain-driven design is a technique that has proven its value in the delivery of software components. In the context of data analytics, it helps identify data products. This domain-driven, data-as-a-product perspective helps inform interoperability standards as well as data warehouse design to enable sharing and analysis across domains. With these data-as-a-product principles and modern data access mechanisms, agencies are more readily able to meet mission objectives such as increasing data quality, which, in turn, makes it possible to take more forward-looking approaches by applying machine learning techniques; or to coordinate responses to rapidly evolving emergencies, like we had with COVID-19.
Communicating the link between mission and modernization
As our research points out, 35% point to a lack of clear vision from leadership, and nearly as many (33%) cite a culture that is resistant to change. Without a clear message describing the value of data and analytics modernization solutions, CDOs are unable to effectively advocate to the C-suite and achieve agency-wide buy-in. Too often, the link between mission and modernization gets lost. But when a data-as-a-product approach is applied to modernization efforts, it ensures that the value proposition to mission users is used to drive the technology choices, and that this value proposition is delivered in a persuasive fashionâfacilitating efforts to achieve buy-in. It is this buy-in from mission users that will prevent technology solutions for data and analytics from falling into disuse even through changes in leadership and direction.
In the study, 87% of federal IT workers say that agency staff views new modernization solution announcements optimistically. And this jumps to 94% among those working in agencies that have reached modernization milestones. So, delivering âquick winsâ on time helps build momentum and support. Also, more than 2 in 5 federal IT employees (41%) say that navigating regulations and compliance is a hurdle in dealing with their agencyâs data. In organizations that don't yet have a data-driven culture, it is hard to get the momentum to move forward with these larger goals of common governance and unified data access. So, we need strategies to build this momentum.
Building modernization momentum
An important first step is to begin involving line-of-business users in the analytics process so that they can clearly see how analytics supports the mission. One way to do this is to provide self-service tools, like interactive BI dashboards, which clearly support tactical objectives in the short-term. This will help create the appetite and momentum for longer-term, strategic initiatives. Another important step is to enable lines of business to begin delivering their own data as a product, using good software engineering practices and DataOps pipelines. With these pipelines in place, CIOs and CTOs will begin to see how data products fit into the software delivery process in a manner that is analogous to the operational components that they may be more familiar with, like microservices. By engaging domain owners and IT leadership in this way, we can motivate support for the investments that are necessary to achieve the longer-term, strategic initiatives.
For example, ICF worked with the Centers for Medicare & Medicaid Services (CMS) to introduce a suite of automated and self-service data and analytics tools for the Quality Payment Program (QPP). As a result, this line of business was able to reduce the time it takes to simulate policy changes by 99% to just 3 hours. This made it possible for the policy analysis team to evaluate more potential policy changes and better guide the program toward achieving its goals.
Just as low-code/no-code solutions have empowered federal agencies to more rapidly automate their operational processes, modern data and analytics ecosystems are democratizing access to analytics through “augmented analytics,” which uses AI to engage mission users—who don’t have deep statistical or programming skills—in the analytics process. However, even these advanced capabilities often fail to bridge the gap between the data skills of the agency’s workforce and the skills needed to transform data assets into meaningful insights. As the research shows, agencies rely on trusted partners who can pair domain knowledge with technology skills to effectively deliver data and analytics products that propel the mission forward.
