https://governmenttechnology.blog.gov.uk/2016/11/09/how-can-we-make-big-data-work-for-government/

How can we make big data work for government?

Share knowledge

James Stewart recently blogged about the changes that we’re making to the Technology Leaders Network. The blog outlined how keen we are to involve technologists across government in some of the sessions that we run.

I work in James’ team and help run the Network. We recently held our first session which was open to a wider guest list than just the Tech Leaders. We decided to blog after each of these sessions so that those who aren’t able to attend can read about what we discussed.

Bringing the Leadership Networks together

We want to improve the relationships between the Technology, Data and Digital Leaders Networks so we decided to run some sessions which we could invite members of all three Networks along to.

Last month we held the first in a series of Data Seminars and opened the invite up to anyone in the Digital, Data or Technology professions across government.

We’re picking topics which cut across these three areas of work and aim to broaden people’s awareness and thinking about how we can work with data. If you are interested in hearing about future sessions get in touch.

Mastodon C

We welcomed Francine Bennett of Mastodon C to talk about her experiences of how businesses can best utilise data.

Thanks to modern technology, such as mobile phones, data is now more readily available than ever before. But what is more important than the data itself is the way you use it. Applying analytics allows you to spot and squash problems or take up opportunities earlier and better assign your resources to the most important areas.

Fran drew on an example of a project Mastodon C ran with Defra. Vets from all over the country send cattle post mortem reports to Defra. Individual vets would only be able to see a problem if there was a very clear and obvious pattern, which could mean there are delays in identifying new diseases.

The project looked at how a database could be used to track any new diseases or increases of existing diseases in livestock. The text in the reports from across the country could be analysed to see if there were any patterns of wording, allowing new diseases or trends to be spotted early. Of course there were some false alarms, due to the jargon being used, but expert analysts could define what patterns were worth following up on.

Lessons learned

Fran then gave the group an overview of the main lessons she has learned from dealing with data. The key message is that there is no shame in failure. When it comes to data analysis there should be a culture of testing and learning. She emphasised the importance of giving projects a strict, fixed time period with checkpoints along the way to ensure things stay on track.

A common mistake people make is thinking that the data needs to be clean and perfect before they begin analysing it. It will be a never ending process and raw data which can be reshaped can be far more helpful.

Fran also warned of the pitfalls of work becoming paralysed by trying to find the perfect technology option. Invest in smart resourceful people, not hero technologies. There are plenty of good, open source technology options available but ensuring you have the right people to steer the tech is far more important.

Fran also recommended following a ‘low politics path’. Having a well understood, shared business goal is important. Avoiding getting caught up in politics avoids projects stumbling early on.

And make sure that everyone working on a project, regardless of their specialism, is communicating. Multidisciplinary teams are key to success.

What next

This month we’ll be running the second session in the series. We’ll be visiting Facebook who’ll be telling us about the work they are doing on trust and privacy. Keep an eye out for more blog posts coming soon.

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