Just finished attending a super presentation about research administration metrics – specifically, how to develop them to manage research administration more effectively in the research business environment. The presentation was given by the VP of Research at Duke University, and focused on linking factors in managing research grants to business outcomes and compliance.
The analytical process they used at Duke to measure the effectiveness of departments was very interesting, and multi-layered. The aim was to measure the complexity of the award portfolio managed by the department, and to overlay it with information about the department’s practices with training, hiring, and procurement. Each assessment received a score, and the overall score is averaged.
A low score indicated a department that is managing its portfolio well, has the needed training and skill set, is hiring enough (but not too many or too few people at the right levels) and those staff are using existing enterprise systems (to reduce cost transfers and other red flags).
This is one of a growing number of presentations that I’ve heard where compensation is tied to the complexity of the types of grants that research administrators administer – Duke is using this data in their medical school to tie back to compensation in HR.
While this is a new trend and may not be practicable in this economy, it’s great to see large institutions recognizing that a measure to capture the complexity of research administration is possible – and it is more accurate in describing the nature of our work than determining a standard dollar amount (grant load) that a research administrator should be able to handle.
Metrics enable us to describe, in a common language, the value of our work and its impact on our institutions over time. There are a lot of important metrics to collect, but you need a few key metrics to tell the right story about how your team is making a difference.
What metrics are you measuring? Where are you trying to move the needle?