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Responses to Metrics 3.0: A New Vision for Shared Metrics

In a recent issue of the Stanford Social Innovation Review, Mike McCreless et al. proposed a new approach to measuring social impact – Metrics 3.0: A New Vision for Shared Metrics. This new approach seeks to build on the progress made in using metrics for accountability and standardization. McCreless et al. argue that the next step is to integrate impact, financial and operational metrics, and to shift towards evaluations that are targeted, actionable, broadly useful and that serve collective learning. In this Skoll World Forum series, co-edited by Mike McCreless, a range of different experts present their responses to the Metrics 3.0 vision.


Decision Data: Metrics Must Lead to Action

Decision Data: Metrics Must Lead to Action

Tom Adams

Managing Director, Lean Data, Acumen

August 27, 2014 | 2232 views

Conversations on impact measurement and metric collection often lead to questions about proving impact. Funders want information on social performance, and rightly so: we can’t be accountable to stakeholders – from investors to customers – without information on whether we achieved our goals (Metrics 1.0). Ideally we’d also like to compare that performance to highlight and incentivize exceptional achievement too (Metrics 2.0).

We have made significant progress toward this goal. The infrastructure of Metrics 1.0 and 2.0 has been studiously built; for example the IRIS standards offer an array of exceptionally well-constructed social metrics. There also exist a plethora of effective data methods.

Yet despite this progress, there remain strikingly few examples of successful social metric collection, beyond a handful of broad-based output indicators – lives touched, jobs created, etc. The scaffolding is up, but the building has yet to get above the ground.

Specifically, the extensive, rich datasets required to support the first two iterations of the impact agenda remain underdeveloped. Not only is this frustrating for those calling for greater accountability, but there are further dangers. We see increasing numbers of conversations on metrics and impact leaving more and more people dissatisfied. Impact fatigue is setting in; the din of talk about metrics is not being backed up by a corresponding flood of useful data.

Failure to adapt to realities of funds and firms 

The reason for the lack of data is, at heart, fairly simple. Despite metrics and methods and good intentions, we haven’t been able to adapt these approaches to the realties and constraints of investment funds and of the small and growing firms who need to collect and use the data.

This is not so much a technical issue as a practical one. It involves addressing four C’s that are holding back the sector: capability (a measurement skills gap across the sector), the cost of evaluations (which need to come down), confusion (uncertainty about whether formal evaluation is always needed to report impact) and courage (the perceived wisdom that impact measurement is hard and distracting, and will only uncover deeper complexities that are equally hard to resolve).

Correcting this requires reconsidering why we collect data, and the motivations of all stakeholders across an ecosystem to demonstrate the value of impact analysis. Here Metrics 3.0 is a breath of fresh air. It places emphasis squarely on the incentives behind data collection, explaining clearly the value for various actors of gathering and sharing different kinds of information. Especially important is 3.0’s emphasis on integrating measurement approaches at the organizational level. This is where all the good stuff begins.

We must accept that Metrics 3.0 will take time to properly execute. But it can also benefit from a demonstration effect, as high quality metrics plans are implemented and implemented well. To achieve this at Acumen we are driving “decision data”, the simple premise that data must be relevant to firm-level interests. If that data will not lead to action, or has no bearing on choices, it is largely meaningless. This approach has led us to pilot a range of new innovations such as our Lean Data Initiative, which is using every trick we can think of to improve the efficiency of metric collection matched to firm interests.

Once there are enough examples to refer to, we will be closer to fulfilling the potential of Metrics 1.0 and 2.0. Here then, 3.0 also saves its predecessors.


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