The Road
What does data readiness look like?
Universities have lots of data. Is it ready for use?
By Dr Paul Thurman, Chair, QS EduData Summit
"Readiness is often in the eye of the beholder and is suspended in a temporal dimension."
“Data quality, trust and connectedness are no longer nice-to-haves.”
What does ready really mean?
Does it mean we can react quickly, or does it mean we need to be proactive ahead of anticipated change? It’s almost like counting down with someone to jump into a swimming pool: 3…2…1… jump! Do we jump as we say the word “jump", or do we say the word “jump” and then jump? Readiness can mean different things to different people, especially inside institutions often focused on vocabulary and definitions: universities and colleges!
Like most qualitative measures, readiness is often in the eye of the beholder and is suspended in a temporal dimension. We either should get ready, we are ready, or we were ready.
But are there better and more quantitative ways to measure readiness? Armies measure readiness by how many soldiers they have and how quickly they can be deployed once given orders. Emergency services providers measure readiness in terms of response times. Most of us just use a clock and a mirror in the morning to assess the condition as binary: either we are ready to go or we are not.
In higher education, however, we have data that we should be using to assess our readiness: how quickly can we secure the best students and faculty, how much research funding can we deploy to innovate, and how equipped — or ready — are our graduates when it comes to matching the demands of the job markets out there. We have all this data, but are they at the ready for us to use strategically to both make sense of our ecosystems and to make decisions that help us deploy our resources as quickly and as efficiently as possible to prosecute our missions?
Honestly, I don’t think so. And I suspect you may have your doubts, too.
As a test, consider your answers to these quick readiness questions:
- How confident are you in the data you use to make important decisions?
- Are you collecting the right data — or do we even know what the right data is — to ensure and prove success tomorrow?
- We know what our students are learning, and we know what our employers want. Have we ever lined up both sets of these data on the same page at the same time, or do we just hope that what we supply will show up when we ask (not as often as we should) what demand is?
- With new technologies always at our doorsteps, are we just managing them, or thinking more strategically about how to govern them (e.g., AI)?
- How do we actually — or how should we — measure learning quality? Checking off competency boxes is easy, but how well are those competencies being engrained in our students., and then noticed easily by employers?
- And given all the questions above, do you have a playbook — literally, a set of policies, procedures, guides and governing principles — that outline exactly how we collect, analyse, report, synthesize, decide, implement and announce results from all the data we are (or should be) using to actually improve our institutional effectiveness in terms of research and employability?
If any of these questions make you a little nervous, good!
This year the 2026 QS EduData Summit seeks to answer these questions and more. Our focus will be on The State of Data and What Readiness Really Looks Like. We want to take data in education to a (much) higher level and understand the imperatives around connected and trusted data that will truly determine “best in class” from just “in class.”
Most higher education institutions have tons of data—but do you have the right data at the right time connected to the right other data that actually informs decision-making? If not, why not? Why don’t you trust or connect your data?
Let’s go deep on these topics in June, and let’s co-create a readiness playbook that will help you collect, analyse, trust, and decide what makes the most sense for your institution in a way that gets others on board, and not suspicious, quickly.
If we don’t, we run the risk of discussing a few other big business buzz-words that are also entering the higher education vocabulary these days: existential, make-or-break, and survival.
Understanding how to better connect, trust, use and deploy data that makes a difference may also determine who survives and who thrives moving forward. Lots of higher education institution are facing existential threats— from funding shortages, employer and student abandonment, researcher attrition, technology advances (AI!) and suspect skill and learning quality.
Data quality, trust and connectedness are no longer nice-to-haves. They are make-or-break elements that are critical to institutional success and better success means we need a better plan. We don’t just need to be good. We need to be ready.
Join us at EDS 2026 to build that plan and learn how to put it in place so you and your institution are ready to not just be but to be better. And to survive. I look forward to seeing you in Singapore in June!