Five Programmatic Lessons in Scaling Impact
Scaling impact has become a favored ambition for international development projects. But what does it mean? More than simply counting the number of project beneficiaries who adopt innovations, scaling requires a different mindset and skills. To succeed at scale, projects must tackle the complex issues that underpin current systems and identify levers for change.
The current paradigm of scaling is dominated by a “product, end-user and number focused” mindset anchored in donor processes that pressure project implementers to deliver specific outputs within time bounded funding. This mindset feeds systematic resistance to embracing systems change as part of the solution.
To serve the public good, we must shift from a mindset of “maximum potential scale” for a few to one of “responsible scaling” for many. This means recognizing that scaling is not necessarily quantitative, and that bigger is not always better. It must also be inclusive and involve a variety of actors.
While improving products based on customer data is important, this alone won’t scale an intervention. Consider how hard it is for competitors to imitate product enhancements that occur quickly, such as those seen in credit bureaus and information aggregators like LexisNexis and Thomson Reuters.
Instead, a competitive advantage can be gained when the data improvement cycle is slower or when it leads to an ecosystem effect. This is why it is important to understand what elements are needed to reach scaling ambitions and be strategic about which aspects of a multifaceted program should be adapted.
Many international development projects are aimed at scaling their innovations beyond a pilot project. Unfortunately, this usually means a focus on “maximum potential scale,” which ignores the fact that societal outcomes like poverty and food insecurity require significant shifts in social, technical, and institutional configurations, not just more people using an innovation.
The most successful efforts at scaling impact work to understand the complexity of systems change and design their programs with that understanding. This requires a different mindset and a different skillset than the traditional stand-alone project mentality that focuses on product, end user, and number. It also demands a new kind of evaluation: dynamic evaluation that looks at how, for whom, and under what conditions changing actions produce impacts. Modern analytics tools make this possible.
Efforts to scale often result in changes that impact more than the original project beneficiaries. Responsible scaling focuses on optimizing the impact for all stakeholders. For example, if an irrigation program increases crop yields for some farmers, it may decrease water availability for other users in the same region or community. This approach is guided by the principles of complexity science.
Despite the many challenges, there are reasons to be hopeful about the prospect of scaling. A growing number of organizations are starting to recognize the value and potential of scaling research, development and innovation in tackling global problems like poverty, food security, climate change and other global challenges.
Systems thinking is an enabling framework to support scaling that involves developing shared pictures or stories of a problem and its context. It is particularly useful for addressing complex or wicked problems, which are too big for any one person to understand from a single perspective.
