What does my school data cost?

Xporter
3 minute read
cost of data

If you are one of the 20,000 UK schools using Groupcall Xporter to collate the data from your schools, you will be aware that the cost of acquiring the data is apparently zero. Once the product has been set up, it will be updated automatically, and give you streams of whatever data you’ve asked for without your having to do anything further.

But note the word ‘apparently’ hiding in that sentence. As any good interior decorator will tell you, much of the time and effort – and in our case, cost –  has to go into the preparation. Get that right, and you’re far less likely to have to retrace your steps later on, usually at a far greater cost in terms of time and inconvenience.

What data?

So what preparation needs to be done? The first thing is to decide what data you wish to collect. The answer may seem obvious: pupils’ name, attendance, punctuality and so on. Yet there are further decisions to be made. For example, will you include only morning and afternoon registration, or attendance in every lesson?

Also, you may not be aware that you can ask for different sets of data from each school. If one of your schools is in a wealthier area, you may wish to collect data on how many pupils in that school enjoy the benefits of extra tuition.

Why?

Another ‘obvious’ point, but one worth making, is that you need to think about how the data will be used, or in other words why you want to collect it in the first place. Because of the conditions imposed by data protection laws, you cannot simply adopt a strategy of measuring everything you can think of. Yes, it may well be the case that hair colour has a direct bearing on attainment, but you would have a hard job convincing parents and the Information Commissioner that you need to collect such data.

How can you begin your own journey to data driven decision making? Find out how Tom Rees and Northampton Primary Academy Trust did it. 

How?
Once the data has been produced, different users will want it in different formats for it to be most useful for them. So one of the costs to take into account will be to find out what different users prefer. To save time on this, and to avoid the kind of paralysis that can come from too much choice, it might be an idea to produce two or three sample report formats and ask each stakeholder which one they prefer.

The product can handle data in any format, but it’s worthwhile working with Groupcall to produce a few different sets of outputs just to check that all is working smoothly. The last thing you want is to be faced with an unexplained anomaly when time is critical.

Analysis

So the data sets have been decide upon, and the formats of different reports have been agreed. The next cost comes in the form of the time spent analysing the data. Are there any ‘outliers’, either in terms of a trend (a sudden upsurge in lateness at school A) or between different schools?

It may be useful here to recall the statistician’s motto: a difference is only a difference if it makes a difference. A one-off blip may not be worth fretting over, but it turns out to be just the start of a new trend then time will need to be spent analysing it and discussing it. At that point it becomes a matter for the senior leadership rather than the data collection team.

Compliance

Finally, as has already been hinted at, there is the cost of compliance, and the (rather hefty) costs of non-compliance. New data protection laws in the form of the General Data Protection Regulations are here, as we mentioned in Data Protection, and schools, local authorities and multi-academy trusts need to already be on top of the implications of GDPR now. Fortunately, there is plenty of advice on the Groupcall Resources Page to get you started.

Conclusion

What this article has shown is that the while the costs of data collection may be relatively small, the costs of handling the data can be quite high once all aspects have been considered. However, it’s much less costly in the long run to plan assiduously than to simply collect as much data as possible ‘just in case’!

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