Real-time information makes for good university decisions

Business Intelligence is the latest buzzword, but how can we integrate it into the complex world of HE? Steve Williams explains

On 17 August, A-level results are published in England. Almost every university will be involved to some degree in clearing. To make good decisions, universities simply must have the best possible information on how full courses are, on the constraints to accepting students, and on the prospective students themselves. Many will have developed real-time information reporting, with information available live to academic staff.

Thinking about this now is timely. It seems a long time until August but, in fact, you need to start now if you want your information to be as good as it can be, come results day. If you don’t do this, your competitors will. Think it’s not a competition? For all but a tiny handful of universities, it is.

Results day is the most vivid example, but the principles of timely and accurate information apply across many disciplines. There’s a lot of talk at present about how organisations use information to make good decisions. Business Intelligence (BI) is the latest buzzword. Universities work in complex environments, so this is not a simple issue.

This short paper sets out three principles for effective BI. Use these principles and you will be on the right track to effective information and therefore more reliable decisions.

·      Focus on the outcome you want.

·      Rubbish in, rubbish out.

·      Organise to deliver.                        

Leading organisations invest either in organising the data in their core systems or on cleaning it up in a ‘staging’ database before reporting on it.                               

Focus on the outcome you want

Far too often, decisions in universities are taken on a whim. ‘Professor Bloggs saw XYZ software used for reporting at his friend’s university, so that’s what we need.’ That way madness lies. Don’t start with ‘we need a report to do x and y’ or, worse, ‘we need to put XYZ software in.‘ Instead, start with simple, plain-English, one or two sentence statements of the benefits you are trying to achieve.

Examples might be:

We are losing 24% of our students, damaging our reputation and costing us £30 million. We aim to improve retention by a fifth, improving reputation and saving £6 million.


We handle 3000 potential students on clearing day. We want to offer places to more of them, more quickly.


Our research income is targeted to increase from £20m to £40m. We want to manage that increased volume more efficiently, without increasing admin headcount.


We know that we will be affected by changes in data protection law with the General Data Protection Regulations (GDPR.) We need a suite of reports to prove that our data is managed in line with the new laws. 

This benefits-led approach will then translate much more easily into the changes in business process and (possibly) in people’s jobs that will be needed. In turn, this allows a sensible case for investment in systems to be made. Remember, never invest in technology unless you can describe clearly the outcome you are trying to achieve.

Rubbish in, rubbish out

Back in the 1970s, hi-fi geniuses Linn Products caused a revolution by encouraging customers to spend a great deal on a wonderful turntable, and less on the amplifier and speakers. Their logic was that a good source would lead to the purest sound. Bad source data, with a good amp and speakers, would just lead to loud, clear rubbish. It’s the same with BI.

Far too often, universities waste masses of time arguing that ‘my system says we have 300 students and yours says we have 280.’ The way to improve this is to have clear data definitions and for the planning department (or whoever ‘owns’ the BI) to work closely with the developers and BI experts in the IT department or external company. Nirvana is ‘this report says we have 300 students, that one says 280. And that’s because this one is reporting on those who commenced, and that one on those who graduated. Here’s the data on the 20 who left the university.’ 

Do this by focusing on the base data. This is unfashionable. But leading organisations invest either in organising the data in their core systems or on cleaning it up in a ‘staging’ database before reporting on it. As a side benefit, your finance department and your auditors will love this; clean data makes a massive difference to the accounts of the university as well as its management reporting.

Now, some may think I am off message here. Surely the most exciting work is in developing dashboards of imaginative graphs and elegant presentation of information. Attractive reporting is obviously important. But a slick graph of inaccurate information is, I suggest, worse than useless.

By the way, if anyone from Linn Products is reading this, I’d still love a Sondek turntable… 

The right tools for you will depend on your core systems.

Organise to deliver

Understanding the ramifications of a BI project is complex. Such projects manage information from multiple sources. This places a load on the team who deliver the BI. So what is the best way to do this?

It’s tempting to set up a team in-house. That way, people develop a valuable understanding of the business context as well as the data. But it can lead to too much information being held in one or two heads – which means that these people can name their price and makes it risky if they leave. BI skills are in heavy demand across all sectors. It’s also possible that people might become ‘stale’ and embedded only in one way of doing things.

So what about an outsourced solution? Specialist companies are able to share work across multiple staff, and to keep on top of best practice. But an organisation’s data is its family silver. It’s not ideal to give it away or even lend it out! And there’s an additional concern – a BI solution needs to be secure and carefully tested. That guardianship is best provided in-house.

The best way to approach this may well be a combination. Have a team in house which ‘owns’ the reporting, but seek external support on some of the development. That way, the family silver stays inside the organisation but it’s polished by experts. If this strikes a chord, I’d be pleased to discuss it further….

In conclusion, you may be surprised that there is nothing in here about specific technologies, given that the author is an experienced IT Director and works for a tech consultancy. But actually, it is not about the technology. There are a number of good BI products which can produce clear reporting. Some need technical configuration and may slow live systems down, but are very powerful. Others are great for spinning up reports easily, but have problems with data integrity. The right tools for you will depend on your core systems. My former university had wall-to-wall SAP software, so used SAP for business reporting and had very good data integrity. Universities with a range of different software might want to standardise on the Microsoft stack for BI, as it has good tools to link and import data from different systems. There is no single best answer. Think about what you are trying to do, take the right advice and good luck!

Steve Williams leads the Higher Education practice at consultancy firm Waterstons Ltd, based in Durham and London. Previously he was IT Director at Newcastle University for eight years. He’s a Principal Fellow of the Higher Education Academy.

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