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Three principles to improve public services with big data

 

Increasingly organisations are using big data ‘dashboards’ to help staff make management decisions based on large flows of information.

New analysis from leading cross-party think tank, Demos, reveals the potential – and limitations – of using big data to transform public services and private sector operations.

Using visualisation tools or dashboards to make huge quantities of data intelligible to the non-technically trained, provides a remarkable opportunity to build more efficient and data-driven services and operations in the public and private sector. In recent years the government Digital Services team has been rolling these out across departments, with over 800 built so far.

These have massive potential to help local and national government operate more efficiently and responsively, but can frequently be poorly implemented.

Off the shelf programmes mean the dashboards sometimes are not responding to the keenest challenges that organisations face; they are prone to bias users towards short-term operational issues, rather than longer-term issues; and frequently staff do not have the skills needed to operate them effectively, or fail to buy in to the change in operations.

In this new Demos paper, the risks of poor data dashboard implementation are identified, along with solutions to overcome these challenges.

The three principles identified that should shape any government use of data dashboards are:

1. Identify purpose and use

Dashboards are a generic response to collect, analyse and act on large data sets. In and of themselves, they are not necessarily the best way to understand all problems, and must be carefully designed to match real organisational needs. Once the purpose has been identified, it must be communicated clearly to its designers as well as its intended users.

2. Understand limitations

Dashboards have the potential to mislead as well as inform. By their nature, dashboards leave out more than they include: usually with the user not knowing how the data presented was created. Users can be blinded by large numbers or have insufficient understanding of the strengths and weaknesses of the big data they are using.

Dashboards will often prioritise operational issues, rather than longer-term strategic issues, and may marginalise more reflexive approaches to a problem. Like all metrics they can be gamed, and so users must be encouraged to have a critical eye for the dashboard’s limits.

3. Select the right staff and skills

Just because they are designed to be user-friendly, it is dangerous to assume users will intuitively understand how to use them. To maximise the take-up rate among staff, they will need to be provided with training to understand the dashboard’s purpose, where the data is drawn from and the way that it is framed.

The skills to create and manage dashboards are extremely valuable and sought after in the private and public sectors. A whole new generation of analysts will need to be trained, with a new combination of skill sets, ranging from data analytics, design, social science and public policy.

Organisations will also need to appreciate the danger of off the shelf models. Government or private bodies will have to choose between using a commercial provider or designing something bespoke. While bespoke dashboards allow for more flexibility and more tailored design – as well as often being cheaper – pre-existing dashboards will often be easier to learn to use, supported with external training courses, and so are often better suited for organisations with high staff turnover.

With the public increasingly concerned about the privacy of their personal data, having a clear purpose for any data dashboard should also guard against mission creep and make sure these large, secure data sets are only used for their original, intended use.

This article was originally publshed on smallbusiness.co.uk and can be viewed in full

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