It’s difficult to measure the emotional business of alumni relationships, but we communications people should not see numbers as the enemy. Photograph: Alamy How we use metrics in higher education is a fiercely debated topic , and as the Teaching Excellence Framework is rolled out, looks set to stay…
How we use metrics in higher education is a fiercely debated topic , and as the Teaching Excellence Framework is rolled out, looks set to stay high on the agenda. Yet academics are not the only ones facing an increased emphasis on measurement. Over the last few years administrative staff have also felt the pain of the numbers game. But there’s been very little debate about how the shift to a data-driven culture is affecting us.
What does the emphasis on metrics mean for people who work in alumni relations? Online tools such as Google Analytics, for example, have been used to check web statistics for quite a while. But workplaces are constantly evolving, putting staff under pressure to generate more and more data.
Much of the issue boils down to how we measure “engagement”. It’s a worthy aim but difficult in practice. How exactly do you put a numerical value on the quality of relationships? And the truth is that donating to your university is as much an emotional activity as it is a financial one. No amount of number-crunching should blind us to that fact.
Another problem with metrics is that people focused on targets can become allergic to risk, yet alumni relations is a fundamentally creative role. It is hard to be creative without taking risks.
Perhaps the biggest issue is that metrics, handled badly, can be profoundly divisive. Much has been said about the gulf that threatened to open up between the arts and the sciences as a result of the impact agenda, introduced as part of the Research Excellence Framework. As a result, academics pushed for an ethical approach to measuring impact and theIndependent Review of the Role of Metrics in Research Assessment and Management was set up.
It’s not impossible to imagine a divideoccurring in alumni teams; with metrics driving a wedge between fundraising staff, whose progress against financial targets is easily measured, and communications staff, whose work on engagement is much messier and harder to quantify.
But we communications people should not see numbers as the enemy. There are lesson to be learned from academia, in particular, the adoption of “altmetrics” or non-standard indicators of quality. Altmetrics embrace the idea that because quality is a multi-dimensional concept, we need a holistic approach to measuring it. The key is to capture our activities from many different angles instead of using misleading metrics in isolation (follower numbers on social networks is widely acknowledged as a bad metric in communications circles, because you can’t be sure those followers are actually reading your feed).
In alumni teams in the US and Canada, the use of altmetrics to track alumni engagement has already been trialled with some success. George Brown College in Toronto and Ivy Tech Community College in Indiana are two institutions that have designed bespoke systems to measure return on investment in alumni relations. They have done this by counting activities such as event attendance, participation in discount programmes, and volunteering hours, then weighting them based on the level of commitment involved.
An important caveat is that the development of an engagement tracking system is a serious piece of work that cannot be developed quickly or easily. George Brown College conducted a survey of alumni, followed by a literature review and consultations with a number of Canadian and US institutions before putting together a tracking system.
In addition, the responsibility for devising altmetrics lies with both fundraisers and communicators; it is only by working together that we can make a proper case for investment.
Given the amount of work involved in tracking and reporting engagement, at some point you will probably be tempted to fudge the numbers. What’s the harm in selecting a few dodgy measures to impress the boss? Why do we need a strategy when we have data?
My advice is to resist this kind of thinking. Data work best when they tell us unpalatable truths that can help us to improve. We have a responsibility to refuse requests for bad metrics that distort our efforts, and we must work harder at communicating why.
We must keep questioning how metrics are used within universities. There will always be those who try to game the system but if the Ref and the Tef have taught us anything, it’s that metrics have enormous power over people’s lives and careers. And where is the job satisfaction in falsifying the evidence?
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