Identifying the underlying assumptions of A World that Counts

The present report benefits from a series of consultations with SDSN TReNDS members as well as comments from other experts in the SDG data space. It builds on their experiences, expertise, and commitment to the SDG data agenda. SDSN TReNDS members are leaders within the global scientific, development, and public- and private-sector data communities. From October 2021 to April 2023, they formed a working group to review the assumptions underlying A World that Counts, with the aim of identifying lessons learned that could advance the “data for development” agenda and pinpointing areas where shifts are needed in our thinking. In doing so, they brought to light a number of key assumptions that were largely implicit in A World that Counts. 

Assumptions are too often unrecognized, unstated, unquestioned. Yet they are often predicated on future potentials. Our analysis seeks to reveal and examine the assumptions that were embedded within A World that Counts, and to validate the extent to which these beliefs and the change processes they anticipated have held true. 

=========   Assumptions Criteria =========

Guided by the four enabling pillars of actions recommended in A World that Counts, we developed the following criteria to identify the key assumptions underpinning its implicit theory of change:

  • The key assumptions should reflect how the use of data would differentiate the SDGs and the 2030 Agenda from past global policy initiatives (how government and non-government sectors would harness big data to further an inclusive, globally-adopted development agenda).

  • The key assumptions must align to the four pillars/enablers under which the actions recommended in A World that Counts are organized.

  • The number of assumptions must be limited to represent only those most critical to success and which must be valid for the expected results to happen.

Using these criteria, we identified six key assumptions within A World that Counts’ four pillars of recommendations:

  • Technical Progress Would Enable Greater Data Availability (Assumption 1)

    The SDGs Would be the Driving Force for Data Innovations for the Public Good (Assumption 2)

  • Information Gaps Would be the Major Reason for Policy Failure (Assumption 3)

    The SDGs Would Enable Resource Mobilization for the Data Revolution, Accelerating Progress Towards Outcomes (Assumption 4)

  • The Public Sector Would Guide and Drive Data Innovations to Target Sustainable Development (Assumption 5)

  • Data Would be a Standardizing Force and a Mechanism for Greater Participation and Accountability (Assumption 6)