Delivering on the promise of public-private data collaboration for the common good requires attention in five priority areas according to a new report, Data Collaboration for the Common Good, published by the World Economic Forum today.
The report, done in collaboration with McKinsey and Company, represents a year-long effort with business, government, civil society leaders, experts and practitioners to advance public-private data collaboration to address some of the world’s most pressing humanitarian and sustainable development challenges.
The linking, connecting and sharing of data has emerged as one of the primary factors shaping today’s digital economy. From 2017 to 2019, the number of companies forming data-related partnerships has risen from 21% to 40%. Against this backdrop, the report provides an evidence base of use cases of data collaboration for the common good as well as pragmatic tools for strengthening stakeholder trust.
“Having experienced the positive impact of public-private data collaboration in improving the epidemic readiness in South Korea myself, I sincerely believe in the promising future that public-private data collaboration will lead us into,” said Dr. Chang-Gyu Hwang, Chairman and CEO of KT. “I would like to encourage more world leaders and thinkers to join World Economic Forum’s effort to make lasting and fundamental changes for humanity with trustworthy data and data collaboration.”
The report provides a holistic governance framework designed to strengthen trust, balance competing interests and deliver impact. It offers insights to balance both the need to innovate in the use of data and the mandate to protect vulnerable populations against known and emerging harms.
“Data holds great promise as a transformative resource for social good,” notes JoAnn Stonier, Chief Data Officer, Mastercard.
The report identifies five key areas for action, across the data collaborative lifecycle:
Stakeholder alignment – Ensure stakeholders commit to intended outcomes by conducting rigorous due diligence to ensure commitment and resource availability
Responsible data governance – Build a secure, resilient and fit-for-purpose governance and technical infrastructure and invest in comprehensive data-impact assessments to identify and manage the risks to vulnerable populations and communities.
Insight generation and validation – Verify the provenance, completeness and accuracy of data inputs and establish effective governance processes on how packaged data products/services will be used to make decisions in the field.
Insight adoption – Invest in last-mile implementation capacities and the leadership to create a data culture within organizations with
Economic sustainability and scalability – Look beyond early stage data philanthropy and donor underwriting to create sustainable economic models.
Given the likelihood and severity of disease outbreaks and natural disasters resulting from climate change, the report calls for a greater focus on how private sector data can be used for epidemic readiness and natural disaster preparedness.
“Public-private data collaboration is foundational for building a shared digital future that is more inclusive, trustworthy and sustainable,” notes Derek O’Halloran, Head of the Future of Digital Economy and Society, World Economic Forum. “This new report provides pragmatic approaches for using private sector data to deliver faster decision-making during natural disasters, a better understanding for how to be ready for epidemics and new ways to measure progress on achieving the SDGs.”
Project advisors and participants include representatives from Bayer, Cloudera Foundation, Dharma AI, Digital Impact Alliance, Edelman, Facebook, Flowminder, Global Partnership for Sustainable Development Data, GovLab, Harvard University, Kaiser Permanente, KT Corporation, MIT, Mastercard, MERL Tech, NetHope Inc., New York Presbyterian, Nielsen, SAP, Sustainable Development Solutions Network, University of Washington, UN Global Pulse, UNOCHA Centre for Humanitarian Data, Verizon Communications, World Bank.
Key Priorities Across the Public-Private Data Collaboration Lifecycle