The Critical Role of Data in Impact Investing (part 3)
When impact investment fund managers make decisions about the activities they choose to invest in, they look for both financial and impact returns. But with eager investors looking for impact data to support their investment decisions, how can fund managers avoid being too hasty in selecting projects?
Surely, long-term or lasting impacts are better than short-term, or short-lived, impacts. Some positive outputs of a project may be short-term, such as increased local employment and income, enhanced crop yields, reduced emissions in a local area. But are those impacts necessarily long-term?
A public-private infrastructure partnership, for example, may create a large number of jobs for the local community. But what happens when the project is completed? Is there less traffic congestion, are commute times lower, are living standards improved? Has the project delivered on creating a long-lasting impact?
Long-term impacts can be difficult to measure. Even more difficult over longer time horizons is evincing the link between the original project and long-lasting improvements. There may be other factors that contribute to or detract from the impact of the initial investment.
There may also be a range of externalities. Negative impacts can arise as a result of a change implemented by well-meaning companies or organisations. Unexpected positive impacts, similarly, can arise. And if these things are not being measured for, they may not ever be fully understood.
Engaging local communities in a feedback loop over a long time horizon can be enormously helpful in evaluating granular changes that take place over a period of time. Longitudinal studies that involve intended beneficiaries of a project help organisations capture real-time, on-the-ground insights from those whose lives were intended to be impacted.
Beneficiaries who are stakeholders of a program will likely have an enhanced understanding of the program’s impact at the practical, day-to-day level. Even if they are unaware of the causation between inputs and outputs, their insights are invaluable for determining whether the project’s theory of change was correct.
Technology such as Havuta’s can help recipients of impact funding to remain connected over long time periods to the beneficiaries of the programs they implemented, providing a rich source of data not only for proving impact, but for learning and ensuring efforts and decisions are data-driven.
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