Six tips for fostering trust in data sharing partnerships
Despite exponential increases in the availability of data in recent years, countries still face gaps in terms of access and capacity to assess progress toward development goals. Before the pandemic, research showed data was available for just “19 percent of what is needed to comprehensively track progress [toward the Sustainable Development Goals] across countries and over time.” Sharing existing data is an important way to fill this gap, but organizations are often hesitant to do so. Why?
That’s the question my organization set out to answer. Athena Infonomics recently completed an extensive landscape analysis examining data sharing partnerships for public good. Our most surprising result was this: We found trust to be the single most important factor in determining the success of data sharing partnerships. Whether by enabling or inhibiting progress, trust between partners emerged as a minimum and necessary precondition for all data-sharing partnerships and one that must be continuously fostered throughout the lifecycle of a partnership.
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Now, this might seem obvious. After all, trust is a core foundation of any functioning relationship. What’s remarkable is how little attention, time, and resources are typically dedicated to intentional trust-building among data sharing partners and other stakeholders. There’s a general lack of information about what makes trustworthy partnerships and about how to build them. As a result, trust is often an overlooked factor in forming new partnerships. In this post, I’ll break down some good practices for building trust and offer ideas to address this gap that emerged from our research.
Why is sharing data so hard?
Data-sharing partnerships can be win-win situations for governments and private companies. In the public sector, improved data-sharing can “improve public services, facilitate research and innovation, and inform policy making.” Data sharing can serve societal good and help businesses identify new models to promote economic and social benefits.
A 2013 study in the UK estimated the direct and indirect impact of public-sector data sharing to be around GBP 5 billion (USD 6.5 billion) per year. This estimate included direct revenues and indirect impact on data users such as time saved from access to real-time travel data. The Organisation for Economic Co-operation and Development (OECD) estimates that improved data access and sharing could generate benefits equivalent to up to 2.5 percent of national GDP.
Yet, we know from our analysis that many data partnerships fail to launch or fail to thrive for reasons not related to technical capacity or interoperability. Organizations are cautious about sharing their data and are wary of exposure to legal, reputational and operational risks. This is why trust, defined as the “willingness of a party to be vulnerable to the actions of another party based on the expectation that the other will perform a particular action,” is so important.
Without it, organizations are unlikely to even come to the table to talk about sharing data, much less to engage in sustained data sharing with un-trusted partners. And, as each of us knows from personal experience, building trust is not a one-time exercise. It’s a dynamic process that must be nurtured through the lifecycle of any relationship, including data-sharing partnerships.
Unlocking trust in data-sharing partnerships
Existing data-sharing partnerships highlight ways to foster trust. The list that follows includes insights from our landscape analysis of multi-stakeholder data-sharing partnerships in the public sector, drawing on interviews, case studies, and secondary research. Here’s what we learned about building trust from the experiences of the partnerships we studied:
Invest with intention in sustained communication. Communication is often an afterthought in planning partnerships to share data. New initiatives need to invest in extensive communication with relevant stakeholders to reach consensus on objectives and monitor progress.
Stakeholder consultations and trust-building workshops can help build consensus around goals and objectives. Initiatives such as Microsoft’s Open Data Campaign and the Data for Children Collaborative began with stakeholder workshops for each data-sharing project to define the goals, roles, and responsibilities within the partnership.
Some initiatives have developed publicly-available tools for partners to clarify their objectives, evaluate their data availability, and define the role of each stakeholder. An example of this is the GovLab Public Problem-Solving Canvas which is designed to help data-sharing partnerships define their objectives and develop actionable strategies toward achieving them.
Build on existing trustworthy institutions and initiatives. Initiatives founded by or housed within a trusted institution such as the United Nations did not face the issue of trust deficit in their inception. Since they were building from decades of technical and institutional credibility, data partners found them to be trustworthy, and they were more likely to attract the right partners for the initiative. Establishing the legitimacy of the initiative itself was less burdensome in such cases.
Don’t reinvent the (partnership) wheel. Working with partners who have a prior history of collaboration with each other builds new partnerships on existing foundations of trust. Prior history means there are generally existing communication channels and relationships, which can help ease the process of working together. Prior collaboration between partners improves the baseline level of trust and comfort—even when prior efforts may not have been successful. In some instances, even previous failed partnerships contributed to the success of a new data-sharing partnership. With new partners, pilot programs can build similar foundations for trust among partners.
Recruit champions to bring partners to the table. Securing buy-in from organizations to share their data can be hard given the sensitivity with which organizations guard their data and additional costs they may incur to make their data shareable in terms of staff time and funding. Data-sharing initiatives also require coordination across teams, such as policy, legal, and technical departments. As such, sharing data often requires a cultural shift in the mindset of the top leadership.
Internal champions are well-equipped to navigate these challenges. In addition to their familiarity with the organization, they can help establish credibility for the cause. (See examples here and here). For example, a water district manager in California, through personal endorsement and advocacy, helped bring partners together to engage in the California Data Collaborative, a state-wide system among multiple districts to monitor water supply and demand.
Strike while the iron is hot. Aligning new initiatives with external factors can contribute to their success. New laws or policies can create the right preconditions for data-sharing and incentivize partners to work together. For example, in Hong Kong, a government policy change towards intermodality in transportation encouraged partners who were previously reluctant to share data for commercial reasons to come together to create a Data Trust to share transport data.
Use frameworks to encourage transparency and trust. Some partnerships adopt legal or other frameworks to govern the sharing, processing, storage and handling of data. This can help build trust as it defines the expected behavior of each partner, and substantially reduces the risk of misunderstanding.
For example, a contract details every aspect of the data-sharing process, with clearly outlined responsibilities for each of the involved parties. It delineates the permissible uses and access restriction of the data and clarifies ownership of the data goods produced from sharing. This structure aims to bring transparency to the functioning of the initiative and lets partners know how their data will be handled. More detailed data-sharing agreements are needed when commercially valuable or sensitive data is involved.
Most data partnerships walk a fine line between control and flexibility within the operations of the initiative, often influenced by the nature of data shared, the purpose of data-sharing, and prior engagement between partners. Trust, though, is a precondition for any data sharing partnership—regardless of the initiative’s objectives, context, or stakeholders. Working intentionally to foster trust can be the difference between a successful partnership and one that fails. I hope this research inspires conversations within data sharing partnerships about ways to establish trust that open the door for more data sharing for public good.
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