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Three characteristics of a better future
Data and insight for decision making, equity, and learning in the social sector
Being clear on where the social sector wants to go with monitoring, learning, and evaluation, and on the difference between the expected and better future, is important to creating the willingness to change course and embrace innovation and experimentation. In this section of the Re-imagining Measurement toolkit we discuss three characteristics that participants within and outside of the social sector believe should be defining pillars of a better future for monitoring, evaluation, and learning.
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- Putting decision-making at the center
- Better empowering constituents and promoting DEI
- More productively learning at scale
Understanding the three characteristics of a better future
Throughout our research and conversations, we consistently heard three essential principles that stakeholders both inside and outside the field believe are necessary to create a better future for monitoring, evaluation, and learning: (1) more effectively putting decision-making at the center; (2) better empowering constituents and promoting diversity, equity, and inclusion (DEI); and (3) more productively learning at scale.
- More effectively putting decision-making at the center: The capacities, incentives, and practices to create useful and meaningful evidence, integrate it effectively in decision-making, and subsequently change behavior continue to be elusive for most organizations.
- Better empowering constituents and promoting diversity, equity, and inclusion (DEI): Despite widespread aspirations, many social sector organizations continue to struggle to develop incentives and integrate feedback processes to consistently engage constituents in ongoing, systematic, and measurable ways.
- More productively learning at scale: New opportunities abound to develop collective knowledge and integrated data efforts that promote learning at the scale of the problems we face. However, incentives for transparency seem insufficient, infrastructure development requires resources, and collective action problems remain difficult to untangle.
Putting decision-making at the center
Putting decision-making at the center is about the “why” of monitoring, evaluation, and learning. It involves both the generation of data-driven insight and its application as an important organizational moment to change behavior. If we focus on the questions we want to answer, their importance for essential decisions about how to allocate resources, make strategy adjustments are clear:
- What do we want to accomplish?
- Are we doing what we said we would do? (Should we be doing something else instead?)
- How are we doing and what can we do better?
- What impact are we having?
On the one hand, this is obvious, and data for decision-making is an idea that’s widely embraced. However, it is difficult to achieve in practice. Too often the starting point for measurement is understanding reporting requirements and on what metrics and methods to use, rather than on deeper questions about what decision-makers need to know to make smarter choices about creating impact. As one expert told us, “Instead of evidence-based decision-making, we need decision-based evidence-making.” Strategy and decision-making require more agile and continuous feedback loops that link decisions with the right data, the development of persuasive analysis, and the integration of these insights into decision-making processes.
Better empowering constituents and promoting DEI
If Putting decision-making at the center is about the “why ” then Better empowering constituents and promoting DEI is about the “who.” It is about reframing who gets to define what is needed, what constitutes success, and what impact we are having. It is also about data as an asset, and who gets to benefit from and control that asset. If we view constituents as active participants rather than passive recipients in any intervention, their ability to provide input and obtain access to data is inherently vital and valuable.
This characteristic brings together two important strands that are interconnected but not identical: a focus on constituent voice and an emphasis on diversity, equity, and inclusion. We bring these two strands together in the context of monitoring, evaluation, and learning because they support and reinforce each other. Enabling constituents to define what matters and what works is an important path to inclusion and equity. Using an equity lens in the creation of data and knowledge opens up possibilities for engaging and empowering all constituents.
More productively learning at scale
More productively learning at scale encompasses the interrelated, but distinct ideas of collective learning and collaborative action. Collective learning depends on individual programs and organizations sharing what they are learning: the good and the bad. It also requires the development of a collective knowledge base that is broadly usable and promotes actionable learning. Organizations need to build on what has come before them, rather than recreating knowledge for individual use or replicating solutions and implementation strategies that have previously been found insufficient.
Collective learning allows the social sector to marshal its resources effectively by avoiding duplicating efforts in the articulation of social problems, development of potential solutions, and determination of what works and in what contexts. Collaborative action is required for the social sector to develop field-level insight and support interventions at the scale of the problem. Complex, system-level problems require coordination and the development of shared data infrastructure to promote broad hypothesis testing and analysis.
Throughout our work, we have found that these key elements—which we refer to in this document as “the three characteristics of a better future”—serve as an important touchstone for understanding and organizing the types of changes that practitioners and experts in the nonprofit and philanthropic arena believe will lead to a more impactful future. To learn more, explore our complete toolkit.