Small things can make a big difference

In most universities I’ve seen there’s a problem with using space efficiently, and one of the issues is the small meeting room which each department has “because it’s never possible to book a centrally controlled one when you need it.”

I saw technology in use today which, in its small way, knocked my socks off.  The blurry photo below (sorry for picture quality) is one of the room controllers outside every meeting room at the Life Sciences Hub Wales.

It’s got a touch sensitive screen like a tablet device.  It shows the bookings for the room; allows a user to book the room there and then for a quick meeting; and updates automatically (its connected to the central scheduling system). So you can see if a room is free; make a booking there and then (or online, automatically).  And when a room is in use the border glows red not green, so you can see from a distance whether the room is busy or free; even better, you can use the screen to find an empty room instead. And book it there and then.

Fantastic. It would take investment for the network infrastructure and the timetabling/scheduling system. But it removes the uncertainty about a room’s usage, and also the need for the printed weekly/termly timetables which are pinned to the door of many university classrooms.

Technology in itself doesn’t solve problems, but it can create possibilities for people. And I bet that once users are confident that they will be able to find a room, the pressing need to ‘keep control’ of the departmental meeting room will fade.  Technology here really could help with efficiency.

So should every university go out and install these? Not necessarily – the business case would depend on the specific rooms, usage, space costs, and a host of other things. But they might help change the language, from “centrally controlled room” to “easily bookable room”.  And once that’s believed, change can really happen.

And they do feel very Star Trek. I’ve seen the future. In Cardiff Bay. And it looks like it might work.

[For the record - I've got no connection with the company that makes these. Other similar ones might well be available.]

Operational effectiveness

Any manager will at some point have worried about achieving reliability and efficiency in delivering a service. There’s a powerful combination of two established management tools which can help you.

The first tool is to use Standard Operating Procedures – SOPs. This isn't (just) an instruction manual for how to do something. It’s also a set of habits which keeps that recipe card current. Here’s how.

Document the procedure – and have it done by those who actually operate it. SOPs are common in laboratories and in manufacturing processes – here's guidance from the US EPA which includes examples – but they also apply to administrative processes, and particularly those which use complex databases or other IT systems. SOPs should articulate the critical steps; and identify any choices that the operator has to make, and the parameters for those choices. They should also not be so long that they become unusable.

Have the procedure reviewed and signed off by a senior member of staff, not involved in its drafting – the head of section or, if it's a small team, their manager. This is so that the process has formal authority as well as the expert authority that comes from the knowledge of its authors. It also means that any organisational or resourcing issues have to be addressed. And finally, it shows that the SOP is serious: make the sign-off process a real hurdle, and people will see that it matters.

Include in the document the reasons for the steps. Tell people why something matters and they are more likely to do it. Robert Cialdini reports a fantastic example of this in his book ‘Influence’, reporting on work done by Ellen Langer of Harvard University. Ellen Langer conducted experiments in which she asked people queuing to use a photocopier if she could push in.

• When the question was Excuse me, I have five pages. May I use the Xerox machine because I'm in a rush? 94% let her go ahead of them
• When the question was Excuse me, I have five pages. May I use the Xerox machine? only 60% let her go ahead of them
• And when the question was Excuse me, I have five pages. May I use the Xerox machine because I have to make some copies? 93% let her go ahead of them

So when you give a reason – because – you get much more agreement. And note that the reason doesn't even have to be a good one – ‘because I'm in a rush’ and ‘because I have to make some copies’ get pretty much the same response, but the second reason adds no extra information. Why stand in a photocopier queue if you don’t want to make copies? So use a because and people will more likely notice.

Train people in using the procedure. It doesn't have to be a full day's training session, but at least talk them through the procedure; let them ask questions; observe and coach if they're unsure.

Set a review date; stick to that date; and involve those who operate the procedure in the review. Keep the procedure current; make sure you take account of any other organisational or priority changes which might impact; and learn from the experience of operating the procedure.  What tips and wrinkles have the operators identified? What would they change to make it better?

So that’s the first tool – standard operating procedures.

The second tool comes from Lean thinking, and is both simple and devastatingly powerful. It’s about identifying the nature of the tasks to be done, and makes the following distinction.

• Runners are tasks that occur on a daily basis, and are of sufficient volume to justify having a specific process to deal with them
• Repeaters are tasks that occur on a regular basis, but not frequently, and are not part of the day-to-day business of the organisation
• Strangers are tasks that occur infrequently

Now apply this distinction to a standard operating procedure. Does a single procedure try to cope with too many different types of event? Are you dealing with repeaters and strangers when you could be focusing only on runners? This can lead to delays where questions get passed around the organisation, and bottlenecks are created in workflow. I've seen this happen in processes around the student journey, where one non-standard case delays processing a whole batch of students, resulting in disproportionate problems.

The trick is to design the bottlenecks out. Make the procedure work for one specific task. If there’s another task which occurs, have another procedure. You can’t make apple pie with a recipe for blancmange. And make sure that you have triage at an early stage: work out if a case has the right features to be dealt with by a given procedure. If it has, then process it. If it doesn't, then refer it elsewhere. Just like a hospital, making sure that the broken bones go to the fracture clinic, and the blocked ears go to ENT.

And there you have it. Think about runners, repeaters and strangers, to make sure that your procedures have the right scope and focus. And then write and use a standard operating procedure to improve quality and reliability.

Good luck!

Happy Birthday, Janet

(Or, five things you need to think about to make a shared service idea work)

Janet – the Joint Academic Network – is thirty this month. There’s a website giving some of the history of Janet, and fascinating it is. (I particularly like the second upgrade to a whopping 256kb/s. At the time this would have been spectacularly fast – but my! how things have changed.)

It’s a good example of a shared service. Undoubtedly Janet provided staff with connectivity on a uniform and high quality basis which they wouldn’t otherwise have had, and thereby enabled collaboration between universities. This makes it very important: the UK’s universities are very impressive internationally, and it’s only by making the most of our strengths that they can continue to be so.

Janet’s just one of the shared services in higher education which makes a positive difference. Other examples of sector-wide shared services include UCAS and the Leadership Foundation for Higher Education. And smaller groups of universities collaborate: internal audit services such as UNIAC or the Kingston City Group; and there’s a fascinating development in Wales: the Wales Higher Education Library Forum (WHELF), which includes all HEI’s in Wales, the National Library of Wales, and NHS libraries in Wales, is jointly procuring a library management system. These are all good things which grow the capacity of individual universities, and which enable more value to be had for less money – what’s not to like?

And for this reason shared services have been very popular with governments and funding councils. But it’s felt to me that the promise has never been fully realised. The 2012 Finance Act included provision for cost-sharing groups to have VAT exemption, which removed one barrier. But there are others, more practical, about managing the transition to a shared service. Here are five things which you should think about, if considering whether a shared service approach might work for you.

How core is the service to your operation? If you share the service you inevitably lose some control, whether it’s over the details of things are managed and prioritisation when things get tough, or whether it’s in the specification and working out what matters in designing the shared service in the first place. If the service that you’re thinking of sharing is critical to your offer – because it’s a fundamental building block, or because the specific quality, price or location matter to those who you serve, think hard about whether sharing is right for you. It’s an expensive mistake to rectify later.

How stable is the environment for the service? Sharing is a long-term activity, and if there’s foreseeable disruption round the corner, you need to factor this into your considerations. Many shared services have at their heart a common database or IT system for managing processes. How would the model look if the technology underpinning it changed completely? In the same way that cloud computing changed fundamentally the business model of many organisations in the field, so other technological (or legislative) changes will make a difference too. This need not be a show stopper, but time spent thinking about the core of the shared business model and how stable this is will be time well spent.

What is the business model? There are many activities in universities which get cheaper and better by being larger – think about the many processes which involve bulk handling of data, and once you’ve got the workflow it doesn’t cost much for a computer to repeat a calculation or a process. But if this is true for universities it is true for other sectors as well. Take payroll, for example: if several universities shared their payroll operation then the unit cost of managing a salary payment would certainly be cheaper. But banks and other commercial providers are managing payroll systems which pay millions of people every month: that’ll be cheaper still. Unless a shared service provides a benefit which is unique to the sector, then it’s quite likely that the financial savings will be outweighed by those available by looking at a different sort of provision. And that’s a big impact upon the business case.

Are you doing it for efficiency or for service quality? Shared services can deliver either, but if you’re thinking of sharing an existing service then you need to be very clear about this. You’ll have staff, buildings, customers and systems involved in what you currently do, and thinking about the change that a shared service will mean for them, thinking about how you’ll manage this, and whether the efficiency savings will really materialise is an important exercise. You’ll get more buy-in from staff and customers if you’re talking about making things better; you’ll have a stronger business case if you’re talking about efficiencies and cost saving. And it’s really hard to do both at the same time.

Do the sharers have the commitment to learn to trust each other? The human dimension is really important, and easy for management teams to overlook. Put simply, the people who will make this work come from all of the different sharing organisations, and unless they trust each other enough to work openly, honestly, and without a hidden agenda, then even mighty efforts can be frustrated. Time spent at the outset of a shared service project in bringing teams together, letting them get to know each other, and learning to work well, is critical to the project’s success. Remember the forming, storming, norming and performing model for team-building? You need to go through all four stages, and do so consciously. Make sure that it’s someone’s job to see that this happens, and listen to their concerns.

Don’t let these issues put you off – the benefits of good shared services are real and long lasting. But if it was easy, there’d be more of them.

Big data, small budgets - 7 ways to make a difference

You don't need a big budget to get more from the data you have.

I saw this morning an advert from a company specialising in big data for universities – how to join together the data that universities already hold, turn it into useful information and get value from it in making a university more effective. There were some very impressive applications on display, enough to make any university management green with envy. All very good – but the client list is the big beasts of the higher education jungle: University of Michigan (income $3.4bn, 60k students), Oxford University (income £1bn, 22k students), Cornell University (income $3.1bn, 22k students), Brown University (income $700m, 8k students), Texas A&M (income $4.1bn, 53k students), Berkeley (income $2.1bn, 35k students). It can take big bucks to get big data.

In many UK universities budgets are tighter, and investment in the databases and analytics software that frees up big data isn’t this year’s (or next’s) priority. But it isn’t a lost cause: here are seven ideas which can make a real difference.


1. Know what data you have. Universities will have systems to record information and transactions about admissions, enrolments, exams, staff, space, finance, timetabling, learning resources, alumni, donors, research and more. Some of these systems may only be a spreadsheet, or paper-based files stored in one place, but knowing what is there can make a real difference. University management teams will see the possibilities of combining information; planning professionals will want to know what is there, make sure that its meaning is understood, and what the limits are on sharing the data.

2. A focus on data quality can be a real help. Look at where errors are creeping in to your data. Are you double-entering data because systems are not set up to be compatible? Have you got good documentation – with clear, unambiguous and relevant definitions of data fields, and good guidance for users – for all of the IT systems which you use to manage your background processes? A data quality policy will get you a tick from the governing body when it comes to the annual return to the funding council, and it can help you identify where you need to address problems.

3. Use the expertise you have. Universities have plenty of people who understand data and statistics – within the professional services, but also amongst the academic staff. Often these people will be only too pleased to be involved in making the data work better for their university. For staff in a professional services team, being part of a wider group looking at data can be a way to get a glimpse beyond the silo of their current role; and for academic staff, the chance to contribute on an institution-wide basis can be good for career development and professional recognition.  

4. Get in training. Train people in what data you have – sharing this knowledge opens up possibilities.  Train people in using the functionality of spreadsheet software – there’s power in these tools, for analysis and for presentation, which might surprise you. And train people in numerical reasoning – we all know an otherwise-high-performing-professional who has a real block with numbers, and overcoming this can be very empowering for them and for you. 

5. Use the data you have. It’s always possible to want better quality data, in different formats, and bringing together data sets which don’t match. And there are some questions where you do need real accuracy. But the data you have is good enough to help answer an awful lot of questions: focus on what you can say, rather than what you can’t, and don’t let the quest for perfect data get in the way of effective use of data. Read ‘How to measure anything’ by Douglas Hubbard to get a sense of what is possible. And think about letting a postdoc scientist loose on the data – it’s their capacity to see and understand the numbers that matters, not their knowledge of the underlying business. You’ll be surprised at what a data scientist can do!

6. Look for bottlenecks in your systems.  Do you have a colleague whose job it is to manage data requests, or is it a little bit of many people’s jobs?  Is the data team in IT and disconnected with users, making prioritisation difficult?  Sometimes sorting out one or two little problems can have a dramatic effect on how data can be made available and shared.

7. Spring clean your reports. Many data systems have reporting functions which require knowledge of SQL, for instance, to generate a report. Is the library of reports which have been coded a manageable size, and they reports which you still need? Find out what reports have already been written, remove duplicates, specify what you need now, and share the menu with others. Manage requests for new reports – if there’s real value in a new report, then it’s worth coding, but sometimes a colleague can happily use what already exists.


These seven tips won’t give you big data – you’ll still be casting longing glances at the analytics some universities use – but they will help you make an impact. And once the management team gets an appetite for data, who knows where that will go?

Bigger is better?

Every now and then there’s a splash about the sheer number of administrators in higher education – see, for example, Registrarism’s post in February 2014 picking up on a scare story in the Chronicle of Higher Education.  If you set aside the nostalgia for imagined lost days of senior common rooms, pliant students and No Administrators, there is a an interesting question about how much universities actually spend.

In the UK at least this is public data, from HESA.  I looked at the proportion of staff spend by UK universities which was not on academic staff.  I excluded staff spend on premises (ie estates and facilities management) and residences because these are sometimes contracted out, which would skew the data.  And I plotted this data, for 2011-12, against total income of institutions in that same year.  The resulting chart can be found via the Resources page on hughjonesconsulting.co.uk, here.

And what do we see?  Well, there does seem to be a correlation between scale and less spend on professional service staff.  (Remember – correlation does not imply causality, although as Edward Tufte observes, it sure is a hint.)  But what a variation there is too – spend is pretty much all over the place.

It’s important not to jump to conclusions about this.  Importantly, there’s no data here about the quality of the service provided, and maybe you get more and better if you spend more.  And UK universities aren’t all the same, and don’t operate in a vacuum.  So, I’d want to look at subject mix; location; research-intensiveness; and history (because patterns of spend tend to lock themselves in over the years; and because many universities saw their unit of resources squeezed by late 1980’s and early 1990’s public funding mechanisms).

But there’s also food for thought.  Are you above the line or below it?