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10 steps public sector CEOs can take to make smarter use of data

A couple of weeks ago I attended the City Region Economic Development Institute (City REDI) AnalystFest event in the West Midlands.

The room was packed with a diverse group, from data analysts in public health, fire and local government, to academics, senior council officials and data science companies, providing a useful chance for open dialogue between sectors and organisations.

Martin Reeves (Chief Executive of the West Midlands Combined Authority) introduced the session, and laid out his concern that the public may lose faith in the power of data to make positive change if they don’t see results that improve their lives.

How should we respond to his challenge?

From data analysis to real-world impact

There was clear agreement from those present that any data gathered and analysed by the public sector must actually be used to deliver quicker decisions and interventions to help communities; that the impact of those actions be properly evaluated; and that services or processes be improved (or even abandoned) based on real evidence of what works.

Getting that data-driven approach right could have huge benefits over the more traditional and sluggish model of: Survey -> Committee report -> Service design -> System changes -> Survey. In short, evidence that leads to more evidence, but little action.

Yet it is clear that, currently, huge volumes of the free, real-time data being gathered every day by frontline staff are not being used to their fullest potential. There are many different reasons for this. But a significant part of putting it right surely lies with public sector leaders themselves. So what specifically should they be asked to do?

Here are 10 actions I believe chief executives can prioritise now:

  1. Make sure your organisation is optimising data collection to run efficient services and measure outcomes, but without overburdening front line staff or taking them away from spending time with clients.

  2. Start getting all staff to collect clean data first time, for example a phone number and full first name. It may not seem obvious, but if a service doesn’t have a phone number, in an emergency situation someone has to visit.

  3. Make sure staff can capture data in the easiest possible way. And get actionable data back to them so they can make the best decisions in the field. If they are mobile workers (e.g. housing inspectors, social workers, parking attendants, care workers, etc.) they should all have suitable mobile devices to do this. Far too many are still forced to work with pen and paper.

  4. Ensure all your main internal system datasets are cross-referenced - both for people- and place-based data. Once you have linked up internal data, you can link up with data from external partners much more efficiently and get real-time data insights (see my previous blog on the benefits of a Residents Index).

  5. Check if you have published all data that can be open data, if it’s in the public interest. This data can then be used by partners across the public sector without any legal hurdles to jump.

  6. Take a risk-based approach to information sharing, recognising that there are risks to not sharing data as well. Tools like privacy impact assessments enable this to be done responsibly.

  7. Trust other public sector bodies’ legal teams to give good advice on information sharing or establish a delegated team to do it - it makes no sense for each organisation to pay staff to come up with different interpretations of the same laws.

  8. Bring your data analysts and business intelligence teams together (federated or centralised) to work across silos. Free up their time from performance indicator production and ad hoc ‘nice to have’ reports to work on projects that have a real-world outcome.

  9. Get external help to train up your analysts so they can operate as data scientists. Data scientists and analysts are in huge demand in the skills market - they are a very valuable resource and should be treated as such.

  10. Release frontline staff to spend time working with analysts to look at data and give their insights. Data-driven interventions cannot just be made by policy people.

At Nesta we want to help local authorities share learning about what works. Please do comment below or contact me on Twitter if you have any questions.

Author

Hilary Simpson

Hilary Simpson

Hilary Simpson

Hilary worked in the Government Innovation Team at Nesta, helping to unblock information sharing issues for the Office for Data Analytics pilot projects.

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