Summary of Play Five

Defining the initiative’s goals in a logic model lets you pinpoint the different indicators that you can use to monitor outputs, outcomes and intended impact. This process can help you design a roadmap to tackle the problem, and highlight any assumptions, external factors, and ignored consequences that may be barriers to achieving results.

Once you complete this play, you can review and check:

• if there are any actors or exchanges missing from your data ecosystem map

• that your policy and ethical assessments account for the activities and assumptions underpinning your initiative

• that you have enough of an understanding of the required data assets and skills for your initiative to achieve its desired impact.

Additional resources: ODI (2020), ‘Using logic models to design data access initiatives’ Created by Doteveryone (now hosted by the ODI), ‘Consequence Scanning – an agile practice for responsible innovators’ toolkit W.K. Kellogg Foundation (2004), ‘Logic Model Development Guide’ Keystone Accountability (2009), ‘Developing a theory of change’ UK Department for International Development (DFID): ‘Logframe Guidance For Research Programmes’ NHS Midlands and Lancashire Commissioning Support Unit (2016), ‘Using Logic Models in Evaluation’ Tools4Dev, ‘Theory of Change vs Logical Framework - what's the difference?’ ODI (2020), ‘Can thinking about the world as a complex, interconnected system help us solve difficult problems?’ ODI (2020), ‘Changing behaviour to solve challenges’’ ODI (2021), ‘Infrastructure for common challenges’ Center for Health Equity - Minnesota Department of Health, ‘Logic Model Tip Sheet’