Data-Driven Impact: A new era of impact measurement
Executive Summary
The investment industry needs a data-driven approach to impact measurement, that addresses the nearly $23 trillion of professionally managed assets in values-based investing, as individual and institutional investors seek to invest with both profit and purpose.1 We analyzed various methods of defining and measuring impact to see what is working and where there is opportunity for improving the state of the art, through conversations with over 20 industry experts. Our investigation revealed that the existing frameworks for impact assessment suffer greatly from the poor quality of the data that goes into them. The question of which framework to apply is frequently debated, yet the question of data quality is rarely discussed, and the field of impact investing suffers from a loss of credibility as a result.
Measurement frameworks and data vendors alike have been important to analyzing impact outcomes, making the case for greater disclosure and transparency. Yet, frameworks are ultimately only as strong as the data on which they rely. The influx of new methods to capture and analyze data holds the promise of revolutionizing the way investors are able to understand and manage impact.
Quantitative methods that generate accurate and reliable data, and integrate machine learning and advancements in the social sciences are emerging to better predict human behavior and drive investment decisions. Advanced statistics and higher quality, objective data help to move impact measurement from a cottage industry of boutique consultancies, poorly translated estimation methods, and self-reported information, into a disciplined realm of scalable, repeatable science. The data revolution can help better define new standards for corporate behavior, and scientifically demonstrate correlations between responsible growth, social inclusivity and environmental behavior that minimize volatility and mitigate risk. It also enables investors to track intentions and outcomes in a way that is credible, legitimate, and transparent.
Data-driven impact measurement eliminates many shortcomings found in existing techniques, such as the subjectivity of survey methods, and “aggregate confusion” caused by comparing dissimilar impact goals in the same single measure. It creates more precise, objective measurements that allow for more granular insights, most specifically within the social sector, such as socio-economic, cultural or geographic issues that do not lend themselves well to quantifiable measurement.
We conclude that rich data streams create very fine-grained observations on human behavior, improving the decision making process for investors and provide the following benefits:
Sufficiency: A combination of techniques that is sufficient to measure the desired dimensions of impact.
Precision: Methodology is precise enough to be useful.
Repeatability: Methodology produces persistent and consistent results.
Accuracy: Results accurately measure dimensions of impact sought.
Materiality: Outputs measure only significant factors.
Comparability: Measures can be compared from one project to another.
Distilled Analytics and Boundless Impact Investing have partnered to show that behavioral analytics and data science can rapidly transform the ways in which impact and sustainable investors make decisions, advancing better outcomes and the ongoing professionalization of impact investing and measurement.