Public-private data collaboration holds great promise for solving some of society’s toughest challenges, but a holistic data-governance framework is needed to help build trust and address risks.

As the technologies of the Fourth Industrial Revolution continue to evolve, the role of data has become indisputable. In an effort to extract even more value from data, organizations are increasingly linking and connecting diverse data sets, a practice that stands as one of the primary factors shaping today’s global economy. From 2017 to 2019, the %age of companies forming data-related partnerships rose from 21 % to 40 %. A growing share of business competitors are also deciding to connect their data—rising from 7 % to 17 %. Overall, McKinsey estimates that connecting data across institutional and geographic boundaries could create roughly $3 trillion annually in economic value by 2020.

The application of commercial data-sharing practices to confront humanitarian and development challenges (in areas such as poverty, public health, environment, and sustainable agriculture) is also gaining momentum. Data collaborative that include leveraging private companies, research institutions, and government agencies to help solve public problems offer great promise. Yet, while there have been some impressive results from public-private partnerships to date, there are still few global success stories where large-scale, commercially controlled personal data is used for the common good. An entangled set of legal, technical, social, ethical, and commercial risks have created an environment where the incentives for innovation have stalled. And lack of trust among individuals and institutions creates even more uncertainty.

Given the risks and challenges, it can be easy for leaders to forgo pursuing public-private partnerships. However, the cost of inaction can be immense as well. According to the director of UN Global Pulse, the lack of data innovation is resulting in a failure to protect the public from preventable harm.

So how can leader’s best balance the imperative to innovate for the common good with the need to protect against emerging risks?

Based on the output of a series of global workshops and summits with business, government, academic and civil society leaders and experts and practitioners, the World Economic Forum, in collaboration with McKinsey & Company, has outlined a holistic governance framework designed to help leaders strengthen trust, balance competing interests, and deliver impact.

This article, extracted from the full report – Data collaboration for the common good: Enabling trust and innovation through public-private partnerships – summarizes key findings. From a stakeholder perspective, this report focuses primarily on the commercial entities that function as the data holders from the supply side (particularly from the mobile-network-operator, financial-services, healthcare, and social-media sectors) and, from the demand side, the needs of large-scale international organizations and the United Nations System.

Strengthening trust to achieve impact

While growing evidence shows the value of public-private data collaboration, the challenges and risks remain daunting. Interconnected issues related to security, privacy, commercial risk, cross-border data flows, reputational concerns, due process, and regulatory uncertainty all serve to create an environment that operates at a slow and deliberate pace. Underlying these concerns is a profound and growing lack of trust among individuals, institutions, and governments.

Strengthening trust will require a number of coordinated actions related to the economics, operations, and governance of public-private data collaborations. Without this cooperation, these partnerships will face difficulty balancing tensions between the need to protect data and the opportunities to innovate in its use.

Aligning on shared taxonomies can serve as an initial step for diverse stakeholder communities to pursue common goals in concrete ways. Accordingly, the World Economic Forum has arrived at six dimensions of trust:

  • Security
  • Accountability
  • Transparency
  • Auditability
  • Equity
  • Ethics

Establishing an evidence-based framework

Through a series of global workshops, expert interviews, and use-case analyses, the World Economic Forum has established an evidence-based framework designed to identify specific areas for strengthening trust. The approach’s emphasis on iterative alignment, consistent communication, and comprehensive governance is intended to help stakeholders understand and respond in pragmatic and practical ways. This holistic approach identifies five areas – stakeholder alignment, responsible data governance, insight generation and validation, insight adoption, and economic sustainability and scalability – for strengthening trust and catalyzing action.

  1. Achieving stakeholder alignment at the outset of a partnership. The first step toward effective data collaboration is for all relevant stakeholders – including government, industry, civil society, nongovernmental organizations, and individual data producers to align on a shared value statement and to gain assurances that there is a long-term commitment by all parties.
  2. Establishing responsible data governance. This phase aims to establish an approach that is legal, fair, and just in the use of data. The scope of governance concerns extends beyond privacy and data protection to include a wider set of issues related to the agency of individuals and safeguarding against group harms in the use of demographically identifiable information
  3. Delivering insights that are accurate, unbiased, and explainable. As it relates to trust, the concerns at this phase are multilayered: the data inputs should be legitimately collected, complete, and accurate; the data processing should be reliable, replicable, and interpretable; and the derived and packaged outputs should be valid, fair, and interoperable within a defined context.
  4. Providing decision makers with the tools, processes, and support to act on new insights. Barriers to insight adoption most often arise due to challenges implementing data products and/or a lack of alignment around the monitoring and evaluation of the success of new decision-making processes.
  5. Ensuring long-term economic sustainability. Given that many existing collaboratives were initially underwritten by donors (or started as “data-philanthropy” donations from the private sector), the question of sustainable economics has historically been less of a priority for data collaboratives. However, as early-stage data collaboratives mature the question of how to establish sustainable economics has promoted the need for a more holistic framing of the challenge.

Addressing society’s most complex global challenges, making the best decisions during times of crisis, and monitoring progress on UN Sustainability Development Goals all require access to the most granular, timely, and complete sets of data available. That won’t be possible without robust public-private data collaboration.