Wednesday, 27 April 2011

Doing less with more ...

No, the title of this post isn't a typo, it's quite deliberate. I could have called it 'Whither University Information Services part 96' but didn't. Catchy is better.

However it is about the future format of Computing Services in universities.

Just about everything can be outsourced. Google Apps, Office 365, Wikis, blog services, notebook services etc. Classroom environments can be replaced with virtual environments and you can people to to build and maintain them for you. Likewise if you still want to provide pc's you can get companies to look after them for you and maintain the disk images.

And, while a lot of people are a little uncomfortable with this, a lot of the MIS functions, paying people, counting leave applications etc can be outsourced

And on the whole these companies are better at the individual activities than you are because each activity is what they focus on.

Which kind of leaves your average university computing service looking distinctly surplus. While you do need some in house expertise, in the end a lot of what they end up with is service portfolio management. And the thing that changed this is having decent high speed internet links meaning that for a large number of operations, they don't need to be on site anymore.

Ignoring the recent Amazon outage, basically if you need a service, storage or compute power, you can rent it. I havn't done a cost analysis so I don't know how costs compare, but I have this gut feel that some outsourced services provide a better and more cost effective service than can be provided in house.

So, all we are left with is a few local experts, some people to manage the service portfolios and look after those few services that can't be outsourced. In other word the computing service does less and less and becomes more and more narrow in its expertiese and capability, and more and more is outsourced.

This could be taken as a dystopian view, but in fact it's an opportunity.

Years ago, before PC's were either common or powerful, most universities had some reasonably beefy machines to provide business services, general purpose computing and some specialist facilities such as text processing. And because of the roots of computing in the numerical and engineering sciences it tended to mean that almost all the general purpose stuff was very numerical.

At the same time the programmers and developers who looked after the computers knew the academic researchers and often helped them with coding, complex statistical analyses and the like - they essentially worked part of the time as research facilitators, helping researchers do what they wanted to do more efficiently.

One example I remember from then was a guy who had recorded the orientations of every neolithic long barrow tomb in northern Scotland and who had a simple question:

Did the long axes of these tombs point to where the sun would be on either solstice in 4000BC?

Basically a very simple bit of statistical analysis - work out where the sun would be, work out the standard deviation of the orientations (plus or minus a bit of fiddling to deal with date variation) and see if there was a statistically significant effect.

The archaeologist concerned was ecstatic - a problem could be answered in a day rather than having to carry out weeks of tedious manual analysis, and all because he'd had the wit to come and talk to the computing people

Today it could be done with Excel, and probably more quickly than it was then.

And then when I listen to some PhD students describing their research analysis methodology for handling and analysing large datasets, I suddenly realise not much as changed. While everyone can use simple spreadsheets, text processing, email and the like, most people lack computing skills. They need someone to suggest a solution, help them with a little bit of code to upload their results, suggest more efficient ways of manipulating data etc.

In other words they need technical facilitators - just as the tomb man did - people who know what's possible, who're used to working out how to translate research problems into computing problems, and who are interested and engaged. The only problem is that these people were, on the whole exactly those who were either let go or moved on to other things ...

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