Understand impact – impact management project gas engine efficiency

The five dimensions of impact guide the data that we collect, analyse and assess, so that we can understand our impact and improve (or re-set our goals). The impact experienced by people and the planet cannot be understood or benchmarked if we only have data about one or two dimensions out of context of the others. We therefore try to collect data as a ‘set’ across the five dimensions of impact, alongside data about financial performance.

For example, imagine two investment opportunities, both aiming to improve educational outcomes for kids by increasing the student transition rate from one level of school to the next. Both provide counselling to 11-16 year olds and they even work in the same city. But Investment A is a proven intervention to re-motivate teenagers who are skipping school, while Investment B is testing a new approach to helping teenagers with learning disabilities. A’s transition rate shoots up from 50% to 85% and the investment generates attractive financial returns, while B’s moves from 50% to 65% and the financial return doesn’t justify the risk taken. If you benchmark what A achieves versus B (the student transition rate and the financial risk-adjusted return), what have you really learned? That A is more efficient than B – and resources should therefore be diverted away from B? Or just that B’s goal was to take a higher level of risk to impact a harder-to-reach demographic? By comparing these two opportunities without data across the other dimensions – for example data on who is being affected – we would diminish our impact. It could lead us not to make that investment B at all, pulling resources away from our toughest problems.

Over time we might be able to build up enough evidence to illustrate how a difference in one or two dimensions of impact affects the result across other dimensions but, for now, information is useful for managing impact if kept in the context of all dimensions.

For example, information about the demographics we reach (who), an understanding of the significance of effects we have on someone’s life (how much) and a benchmark of our performance against what the market is likely to do anyway (contribution) all help us to tailor, improve and differentiate our products or services, or the quality of our employment.

This means that much of the collection of information about our effects on people and the planet can form part of a general management approach and the cost is a legitimate use of capital from investors or funders. However, when the field as a whole will benefit from a deeper understanding of an enterprise’s impact (for example, if looking to replicate what looks like a successful model), philanthropic or government sources can play an important role in helping fund studies. We might choose to do a deeper study of impact to understand what impact achieved can be directly attributable to the enterprise, or whether customer feedback is sufficiently unbiased, or how the enterprise interacts with a wider system.

Enterprises collect information that enables them to make decisions about whether and how to improve performance or re-allocate resources. When this information across all dimensions is communicated as a “set”, other organisations relying on that information (such as investors, funders or policymakers) can use it to make decisions and improve their own allocation of resources, helping them compare ‘apples to apples’ when looking at the performance of different enterprises.

Enterprises who share information about their impact performance publicly help everyone to improve. As we understand what different people want and need – and which enterprises do and do not work – we contribute to existing bodies of information (including our own). By contributing to existing bodies of information, we either reinforce the validity of existing information (does the information we have support what others have found?), or challenge it. This helps us all to set and re-set our goals and design or identify approaches with the greatest likelihood of success.

Sometimes there are too many sets of information for an organisation to analyse and use for decision-making. For example, a passive asset owner may have a range of investment managers through whom they invest. Taken together, these managers are investing in hundreds of underlying and diverse enterprises. The asset owner will typically not want or have the time to process data sets from every underlying enterprise. We therefore need to be creative about how we summarise impact performance, without losing its value for decision-making.

• An investor may choose to assess an enterprise’s impact performance on each dimension and convert the assessment into a quantitative score or rating. Scores of individual enterprises can then be summed to provide a view of portfolio-level performance. Sometimes investors use conversion to socio-economic value (expressed in monetary terms) to express performance, which can also be summed to show the performance of the portfolio as a whole.

• An investor may choose to assess an enterprise’s impact performance on each dimension and convert the assessment into a quantitative score or rating. Scores of individual enterprises can then be summed to provide a view of portfolio-level performance.

• An investor may choose to conduct due diligence on the strength of impact management processes. For example, they might ask questions about how an investment manager has built impact management into their governance, incentives, processes and systems. Being transparent about what our impact management process involves is therefore very helpful for everyone and we anticipate accredited assessments of this kind in future.

• An investor may choose to sum data that is comparable across enterprises and relates to one or two dimensions of impact only – for example, the “total number of low-income people accessing services that relate to good health and well-being”. This sort of information can give a ‘flavour’ of the effect achieved but it does not give the whole picture. An individual metric like this typically includes a mix of performance across the other dimensions (for example, the depth of improvement in people’s health), so it cannot help us to learn whether one enterprise, or portfolio of enterprises, is performing better than another, and therefore improve. When investors or funders want this kind of data for communication (rather than improvement) purposes, they can ideally extract it from the data sets that enterprises collect anyway, so that enterprises can always focus their limited resources on collecting data sets that enable learning and improvement.

There is a growing number of resources that enable investors and funders to collect and analyse either data ‘sets’ (to support their investees and improve their allocation of resources), or to score and sum performance, or to assess the strength of an organisation’s impact management processes. See the relevant resources highlighted below.