Bringing hidden issues into the light is at the heart of good benchmarking, and more broadly – data-led decision-making. In assessing the cost and effectiveness of a university’s day-to-day operations this means giving senior leaders a reliable picture of whether certain services are truly high cost (or indeed under-resourced) in the context of how big and research intensive the institution is as a whole.
The results always offer surprises. Perhaps your HR services are much leaner than you keep hearing, with too much reliance on temp staff – which allows you to decide whether to make them a target for investment. Or maybe your teaching support capacity is too heavily focused on papering over an excessively bureaucratic, siloed set of processes rather than on actually serving students. Vital things to know if you’re interested in maximising the resources available for what matters most.
The problem is that because it’s so illuminating, benchmarking can also feel exposing. Whilst based around the collection and analysis of ‘hard’ data, any benchmarking is an intervention with a very human dimension. There are likely to be fears about the feasibility of a data collection exercise if it coincides with busy periods for certain teams. Managers may be concerned about the results undermining their business case for hiring more staff, and deans and other faculty leaders can worry that benchmarking is the precursor to centralisation. And what about the attitude of the jaded, initiative-weary sceptic: that nothing will really happen even once the results are in?
Key to addressing these risks and concerns is, paradoxically, getting going more quickly – by starting small, building momentum and – crucially – sharing data across the university as soon as possible, in a way that allows everyone to get to grips with it and use it to inform practical change.
People Factor 1 – start where it’s easiest
Achieving lasting, sustainable change means building an institution-wide coalition of the willing. In challenging, high stakes environments as the one that most universities find themselves in at the moment, making the case for any significant decision or wide-reaching undertaking can be very hard indeed.
The good news is that there will always be areas of the university that, at a point in time, are better suited to being in the vanguard. Perhaps it’s the service area that has long been acknowledged as being in need of reform, and where staff are chomping at the bit to get going on improvements. Or it might be the teams keen to use the upgrade of a key system as the vehicle to achieve process change.
One university in the UniForum group took exactly this approach: focusing on central HR services to begin with and collecting a limited amount of data about capacity and effectiveness to understand key priorities for improvement. When this was allied with Cubane sector insights about best practice around topics like the most effective approach to business partnering, the management team was able to see ‘for real’ the benefits for other areas of the university too.
People Factor 2 – use early results to build momentum (and tackle misconceptions)
Everyone knows that change takes time, especially across institutions like universities that are often devolved and loosely aligned. But that doesn’t mean that there’s time to wait for data when you’re in the business of demonstrating impact.
One of the universities in the global UniForum group has tackled this tricky balancing act by adopting a phased ‘release-driven’ approach whereby clear tranches of change are identified and delivered over a period of time. Their focus has been on process change and role redesign solutions that free up resources from routine, repeating tasks to do more of what matters. To support this change, they have needed up-to-date service resourcing data.
Using Cubane’s ‘progressive’ data capture approach, their change teams have been able to review their program of activities, reframe their plans if needed, and follow a genuine continuous improvement approach to their change process.
‘Progressively’ captured data, through data capture tools that are integrated with the university’s business as usual resourcing processes, enables the university to get regular updates on how changes are progressing. Using such data, one university was able to quickly dispel myths around the impact of moving to a new finance operating model. There had been concerns expressed that the impact had disproportionately fallen on faculties, however the data showed very transparently, that the impact had been much more evenly distributed. Momentum was then maintained by being able to use early results to refine processes and address unintended issues before they become major distractions that undermine the larger program.
People Factor 3 – maintain transparency all the way through to results
The most common blocker to using service resourcing benchmarking data as an input to build buy-in to change, is confidence in its reliability. Cubane research has found that benchmarking approaches using activity breakdowns of roles based on position titles are grossly unreliable. They miss significant opportunities by under-representing the breadth of many roles, and not recognising material contributions to many activities. Using such data to engage local teams on the case for change rapidly unravels as it become apparent that these high-level role breakdowns have no credibility with local teams.
It is now well established through the UniForum program that building buy-in and trust in the data requires a transparent process to source data from local units on the make-up of roles in each team. This trust comes from engaging local unit managers and supervisors of small teams to consider the roles within their team and the activities allocated relevant for each role.
This bottom-up role level data creates a trusted basis for analysing priorities for change (for example, by understanding where generalist vs specialist roles exist in the university). These insights provide the basis for engagement with local teams on the nature of the changes envisaged and on the change management planning needed to maintain momentum.
Through ongoing progressive data updates the university can also track the results of change – further demonstrating transparency all the way from early decisions through to measuring outcomes.
If you’d like to hear more about how Cubane’s approach to benchmarking helps build momentum and confidence for change through a flexible, staged approach to getting started, and rapid early access to results, then please get in touch by contacting us here.