Across the federal government mission landscape, I see a central challenge: how do agencies take full advantage of their data to enhance decision velocity and quality to advance their missions?

The world faces many complex threats today. To steer the nation through this perilous time, federal agencies need to be able to leverage the entirety of the data at their disposal to deliver on their missions now and into the future.

Agencies and other stakeholders are rising to the challenge by aligning on technology-supported, science-backed solutions. The data we need to understand the world’s most critical challenges is out there but is often fragmented and locked in siloes or structured in formats and taxonomies that make it challenging to integrate. It must be liberated, collected, integrated, shared, understood, and put to use to deliver better mission outcomes for people and communities. Increasingly, that’s what’s happening, despite the many technical, operational, and cultural challenges that must be resolved along the way.

The path toward fully data-enabled missions is clarifying, and progress is accelerating in the right direction. Now it’s time to put everything we’ve learned into practice and take the steps that we know are necessary to fully leverage the world’s data toward achieving the missions that matter most. 

Agencies are in different places in their journeys toward realizing their data’s full power. The particulars differ between missions, but in all the data-enablement work I’ve overseen during my years at Booz Allen, it’s been my observation that the following milestones must be hit along the way. 

What data sources are important to your mission? Where are they? What state are they in? What are the obstacles to bringing them together and safely democratizing access to them? Is there data that’s not being collected that should be? What measures must be taken to start collecting it? Begin your data journey with an audit. Once you can clearly see the distance between your data needs and your data reality, you can enact a plan to bridge the gap. This is an iterative process as gaps in data and improved methods of collection will constantly be identified. New missions will emerge as a consequence of solving problems. 

Making the most of your data requires IT infrastructure that keeps everything secure while simultaneously making more data more available to more stakeholders for more uses in more locations. Among other things this means moving from on-premises to cloud at enterprise scale. It’s a hefty lift, but the sooner completed the better—the potential mission impacts are too great to sleep on.   

Cloud-based operations make it far easier to scale data capacity and processing power up and down as needed and to securely move and share data across and between organizations. The most advanced cloud platforms can host any combination of today’s most advanced software applications. This empowers organizations to assemble a flexible kit of the digital tools necessary to advance evolving missions through unpredictable circumstances. 

The most advanced tools you can add to that kit are those that harness the increasing power of artificial intelligence (AI) and machine learning (ML). As advanced cloud platforms make it possible to bring together more data than even the world’s smartest people are capable of sorting through in a lifetime, AI and ML make it possible to analyze all of it, making connections and drawing insights that were previously beyond human reach. 

By gathering the right data and drawing real-time insights from it using AI and ML tools, agencies can supercharge mission outcomes and move toward solving some of the most dire challenges humanity has ever faced. But first, they must modernize their IT infrastructure such that it’s capable of ingesting high volumes of data and supporting the cutting-edge tools that can make sense of it all. 

For decades, Booz Allen has helped federal agencies transform to take on new challenges. We understand the past and present of agency missions and environments. Combining that experience with fluency in data science and its underlying technologies, we not only help agencies understand how to achieve the ability to fully leverage their data toward enabling mission achievement—our data scientists, software engineers, and AI practitioners roll up their sleeves and work side-by-side with our clients to get the right technologies, skills, and processes in place.

As more organizations adopt similar advanced technologies and practices, we’ve seen a network effect begin to unfold. Efforts are building on one another, interoperability is inching closer to the norm, and sharing and collaboration across agencies and sectors is growing easier and more fruitful. At a time when news coverage of the world’s gravest challenges seems to spotlight more roadblocks than progress, it’s been a heartening experience to observe how data-enabling work in one area tends to reverberate across others for far-reaching positive impacts felt by a diversity of stakeholders.

Consider weather data. Terabytes of weather data continuously pour into municipal, state, federal, and defense organizations from sensors on Earth and in orbit. Most of it ends up trapped in information siloes within the organizations responsible for its collection. When it’s deliberately made more accessible, other federal, state, and local agencies can then use it for life safety decision support, but the benefits don’t stop there.

Democratized access means that state and federal transportation and infrastructure agencies can use it for emergency response to severe weather. Public health organizations can use it to anticipate the expanding impacts of heatwaves, vector-borne pathogens, and wildfires. Democratized data also enhances economic development by enabling commercial sector innovation across energy, transportation, infrastructure, and agriculture.

Look at health-related data and you’ll see something similar. When healthcare organizations succeed at securely and anonymously opening up more of their data, patients benefit from health records that travel with them between doctors, life sciences researchers gain more data to help them develop and evaluate new treatments, and public health organizations and the populations they serve benefit from stronger threat signals and more longitudinal research data. 

Such impacts extend to agencies that provide services directly to the American public as well. As the Department of Treasury and Federal Trade Commission gain a more encompassing view of their data, evidence of fraud, tax evasion, and other financial crimes can be detected more consistently and passed along to law enforcement organizations. As the Department of Veterans Affairs and the Department of Health and Human Services collect, process, and integrate more data on the warning signs of impending homelessness, more can be done to intervene and keep people in precarious circumstances from losing access to housing.

And as more programs and agencies embrace the tools and technologies of data-powered missions, the network effect we’ve observed will only strengthen. Each organization’s progress toward data optimization will benefit from the experiences of agencies that have preceded them on the journey. Solutions and best practices, from software development to cybersecurity, can be templated for cross-sectoral use and adapted and hardened for differing environments, needs, policies, and regulations. Established architectures, DevSecOps pipelines, and other tools and processes can be adapted and updated, saving time, building efficiencies, foregrounding opportunities for automation, and freeing technology professionals to focus more of their time on innovating for mission impact. 

While the threats we’re facing as a nation—and as part of the worldwide community of humanity—are certainly great, varied, and numerous, we have everything we need to rise to the challenge. With data flowing in and an experience-born roadmap in hand, the path toward fully data-enabled missions is clear. It’s time to align on solutions and see them through.