By securely sharing data, public sector organizations can not only enhance operations and reduce costs, but also improve the lives of millions of Americans.

Andrew Kuoh, Principal, Data and AI, Capgemini Government Solutions

April 17, 2023

6 Min Read
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Data powers analytics, enables digital transformation, and ultimately drives mission outcomes. This is especially critical in the public sector where security, health, education, and benefits missions are at stake. But there are significant gaps. Looking at recent reports from the United States Government Accountability Office (GAO), it’s clear that ineffective data ecosystems are at the heart of many operational challenges -- whether that’s in relation to public health response plans, food distribution programs, defense services oversight, or energy projects.

 But what causes ineffective data ecosystems? For many federal, state, and local entities in the US, it’s likely a lack of collaborative data sharing partnerships. Individual programs may have some of the pieces needed to create data ecosystems that drive data management, operational insights, and performance improvement; but without the right partnerships, the pieces remain siloed and ineffective.

The Promise of Data-Sharing Partnerships

The best way to create data ecosystems using trusted sources is to form data-sharing partnerships. These ecosystems are particularly poignant in the public sector as organizations often face interconnected challenges that may be alleviated through data sharing. From natural disaster responses to distributing small business grants, US federal, state, and municipal agencies often need to collaborate to effectively serve the public and support each other. Therefore, if these organizations face interrelated challenges or perform interdependent roles, then it would only make sense to share data with one another as these insights can enhance efficiency, transparency, and customer engagement.   

 Unfortunately, a recent report from Capgemini found that only 35% of the American public sector has deployed or is currently deploying data ecosystems. Despite the fact that public sector leaders across the world believe data ecosystems can enable 9.5% improvement on average in the use of government funds and resources, the U.S. -- like many other nations -- is largely failing to scale these data-sharing agreements.

Identifying the Delays in Data Ecosystem Deployments

As the third-most populous country in the world with thousands of government organizations employing 19.5 million state and local workers and another 4 million federal employees, it’s easy to understand why the American public sector has struggled to launch data ecosystems.

 There are countless obstacles inhibiting public sector organizations from successfully scaling their data-sharing plans, but the following barriers are perhaps the most pressing for today’s government leaders:

  • Trust – Perhaps the most formidable obstacle inhibiting data ecosystems is a widespread lack of trust from external stakeholders, between agencies, and even sometimes within agencies. Citizens are weary of sharing their data. IT leaders across the public sector also are skeptical of the quality of each organizations’ data as well as the data-handling practices ecosystem partners are expected to abide by. Central to the lack of trust is the ever-present threat of a wide-scale cybersecurity breach that could occur if just one agency is a weak link due to inadequate internal data management practices and privacy technologies.

  • Talent – As it stands, many public sector agencies do not have properly trained workforces that can support data-sharing initiatives. They will need to upskill employees, and this cultural shift in prioritizing collaborative workstreams must be fully supported by leaders.

  • Technology – Similarly, many organizations lack the digital capabilities to help enable data ecosystems. And to make matters more challenging, agencies often do not have compatible data infrastructures.

Kickstarting Data-Sharing Partnerships

While public-sector leaders cannot dismiss these concerns, they also cannot allow these challenges to prevent them from sharing data. Given the extreme and diverse size and scope of public sector organizations, there isn’t a simple one-size-fits-all data sharing solution. However, Capgemini found that there are three essential actions organizations need to take to establish the data sharing partnerships that drive data ecosystems:

  1. Set up or reinforce your organization’s data sharing foundation. Before public sector entities even enter external data ecosystems, they must work on their internal data management guidelines and secure leadership buy-in. This can be done by establishing a governing body to serve as a point of contact for accountability and develop a code of conduct to ensure compliance with the US Open Data This group will also have to determine what data can be shared, when it can be shared, how it can be shared, and with whom can it be shared. Among other processes, the governing body will also have to create a Memorandums of Understanding or Agreement (MOA/MOU) to bring in appropriate stakeholders at the appropriate time. Next, the governing body should also conduct an inventory of available technologies to assess which data sharing tools are available. With these internal elements settled, organizations should also plan to publicize their data sharing strategies early on to promote transparency, outline benefits, and explain data usage.

  2. Build collaborative relationships -- with guiderails and baselines in place. After constructing the foundation and self-evaluation, public sector agencies can start working with others. In order to ensure they are collaborating with the right partners, the governing body should help organization’s leaders to assess use cases and prioritize based on urgency, ROI, and common goals. Organizations would also be wise to start small, limiting the number of parties and scope of the ecosystem. Once partnerships have been established, the ecosystem must collectively leverage each partner’s existing technology -- particularly cloud-based solutions that will help to scale their data sharing initiative. However, leaders must never forget to focus on quality over quantity throughout the evolution of their data ecosystems -- and document all successes for future learnings.

  3. Use positive reinforcement to scale up. Simply put, partners cannot rest on their laurels after successfully launching their data-sharing ecosystem. To promote growth and further successes, each organization must build upon their internal data-sharing cultures. This can best be done by training talent through communal activities like sandboxes, labs, or hackathons or by providing courses. Each organization can also help the partnership scale by establishing democratized data with federated data management and identifying the right platforms and cloud-based tools for their data sharing needs. Lastly, every partner must help to celebrate their collective success, giving credit where credit is due and showcasing the ecosystem to incentivize more partners to join and build trust in the broader public sector and beyond.  

Public sector leaders recognize the importance of data in propelling smarter operations and services --and ultimately improving public safety, welfare, administration, and countless other governmental outcomes. However, most organizations do not have enough of the “right” data because most organizations have not fully scaled data-sharing partnerships. There are considerable internal factors that of course must be addressed as well as external factors like compliance regulations, but the future of the public sector’s digital transformation relies on data sharing ecosystems. The United States, and the world, is only become more digital, more connected -- and the longer public sector organizations wait to form and scale their data sharing partnerships, the harder it will be to keep up.

About the Author(s)

Andrew Kuoh

Principal, Data and AI, Capgemini Government Solutions

Andrew Kuoh is a proven leader and collaborator with more than 20 years of experience guiding teams across public sector, Fortune 500, and start-up, organizations to accomplish mission objectives. As a Principal in Capgemini's US Public Sector Data and AI practice, he is a champion of AI/ML, analytics, and data management solutions that combine advanced technologies with robust methodologies to help clients discover critical insights, improve performance, and maximize ROI.

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