The concept of Big Data has become very popular over the last decade, with many large technology companies successfully building their business models around its exploitation. The UK’s public sector has tried to follow suit, with local governments in particular trying to introduce new models of service delivery based on the routine extraction of information from their own big data. These attempts have been hailed as the beginning of a new era for the public sector, with some commentators suggesting that it could help local governments transition toward a model of service delivery where the quantity and quality of commissioned services is underpinned by data intelligence on users and their current and future needs.
In their Policy & Internet article “Data Intelligence for Local Government? Assessing the Benefits and Barriers to Use of Big Data in the Public Sector“, Fola Malomo and Vania Sena examine the extent to which local governments in the UK are indeed using intelligence from big data, in light of the structural barriers they face when trying to exploit it. Their analysis suggests that the ambitions around the development of big data capabilities in local government are not reflected in actual use. Indeed, these methods have mostly been employed to develop new digital channels for service delivery, and even if the financial benefits of these initiatives are documented, very little is known about the benefits generated by them for the local communities.
While this is slowly changing as councils start to develop their big data capability, the overall impression gained from even a cursory overview is that the full potential of big data is yet to be exploited.
We caught up with the authors to discuss their findings:
Ed.: So what actually is “the full potential” that local government is supposed to be aiming for? What exactly is the promise of “big data” in this context?
Fola / Vania: Local governments seek to improve service delivery amongst other things. Big Data helps to increase the number of ways that local service providers can reach out to, and better the lives of, local inhabitants. In addition, the exploitation of Big Data allows to better target the beneficiaries of their services and emphasise early prevention which may result into a reduction of the delivery costs. Commissioners in a Council needed to understand the drivers of the demand for services across different departments and their connections: how the services are connected to each other and how changes in the provision of “upstream” services can affect the “downstream” provision. Many local governments have reams of data (both hard data and soft data) on local inhabitants and local businesses. Big Data can be used to improve services, increase quality of life and make doing business easier.
Ed.: I wonder: can the data available to a local authority even be considered to be “big data”—you mention that local government data tends to be complex, rather than “big and fast”, as in the industry understanding of “big data”. What sorts of data are we talking about?
Fola / Vania: Local governments hold data on individuals, companies, projects and other activities concerning the local community. Health data, including information on children and other at-risk individuals, forms a huge part of the data within local governments. We use the concept of the data-ecosystem to talk about Big Data within local governments. The data ecosystem consists of different types of data on different topics and units which may be used for different purposes.
Complexity within data is driven by the volume of data and the large number of data sources. One must consider the fact that public agencies address needs from communities that cross administrative boundaries of a single administrative body. Also, the choice of data collection methodology and observation unit is driven by reporting requirements which is influenced by central government. Lastly, data storage infrastructure may be designed to comply with reporting requirements rather than linking data across agencies; data is not necessarily produced to be merged. The data is not always “big and fast” but requires the use of advanced storage and analytic tools to get useful information that local areas benefit from.
Ed.: Do you think local governments will ever have the capacity (budget, skill) to truly exploit “big data”? What were the three structural barriers you particularly identified?
Fola / Vania: Without funding there is no chance that local governments can fully exploit big data. With funding, local government can benefit from Big Data in a number of ways. The improved usage of Big Data usually requires collaboration between agents. The three main structural barriers to the fruitful exploitation of big data by local governments are: data access; ethical issues; and organisational changes. In addition, skill gaps; and investment in information technology have proved problematic.
Data access can be a problem if data exists in separate locations with little communication between the housing organisations and no easy way to move the data from one place to another. The main advantage of big data technologies is their ability to merge different types of data; mine them for insights; and combine them for actionable insights. Nevertheless, while the use of big data approaches to data exploitation assumes that organisations can access all the data they need; this is not the case in the public sector. A uniform practice on what data can be shared locally has not yet emerged. Furthermore there is no solution to the fact that data can span across organisations that are not part of the public sector and that may therefore be unwilling to share data with public bodies.
De-identifying personal data is another key requirement to fulfil before personal data can be shared under the terms of the Data Protection Agreement. It is argued that this requirement is relevant when trying to merge small data sets as individuals can be easily re-identified once the data linkage is completed. As a result, the only option left to facilitate the linkage of data sets with personal information is to create a secure environment where data can be safely de-identified and then matched. Safe havens and trusted third parties have been developed exactly for this purpose. Data warehouses, where data from local governments and from other parts of the public sector can be matched and linked, have been developed as an intermediate solution to the lack of infrastructure for matching sensitive data.
Due to the personal nature of the data, ethical issues arise concerning how to use information about individuals and whether persons should be identifiable. There is a huge debate on ethical challenges posed by the routine extraction of information from Big Data. The extraction and manipulation of personal information cannot be easily reconciled with what is perceived to be ethically acceptable in this area. Additional ethical issues related to the re-use of output from specific predictive models for other purposes within the public sector. This issue is particularly relevant given the fact that most predictive analytics algorithms only provide an estimate of the risk of an event.
Data usage is related to culture; and organisational changes can be a medium to longer term process. As long as key stakeholders in the organisation accept that insights from data will inform service delivery; big data technologies can be used as levers to introduce changes in the way services are provided. Unfortunately, it is commonly believed that the deployment of big data technologies simply implies a change in the way data are interrogated and interpreted and therefore should not have any bearing on the way internal processes are organised.
In addition, data usage can involve investment in information technology and training. It is well known that investment in IT has been very uneven between the private and public sector, and within the private sector as well. Despite the growth in information and communications technology (ICT) budgets across the private sector, the banking sector and the financial services industry spend 8 percent of their total operating expenditure on ICT, among local authorities, ICT spending makes up only 3-6% of the total budget. Furthermore, successful deployment of Big Data technologies needs to be accompanied by the development of internal skills that allow for the analysis and modelling of complex phenomena that is essential to the development of a data-driven approach to decision making within local governments. However, local governments tend to lack these skills and this skills gap may be exacerbated by the high turnover in the sector. All this, in addition to the sector’s fragmentation in terms of IT provision, reinforces the structural silos that prevent local authorities from sharing and exploiting their data.
Ed.: And do you think these big data techniques will just sort-of seep in to local government, or that there will need to be a proper step-change in terms of skills and attitudes?
Fola / Vania: The benefits of data-driven analysis are being increasingly accepted. Whilst the techniques used might seem to be steadily accepted by local governments, in order to make a real and lasting improvement public bodies should ideally have a big data strategy in place to determine how they will use the data they have available to them. Attitudes can take time to change and the provision of information can help people become more willing to use Big Data in their work.
Ed.: I suppose one solution might be for local councils to buy in the services of third-party specialist “big data for local government” providers, rather than trying to develop in-house capacity: do these providers exist? I imagine local government might have data that would be attractive to commercial companies, maybe as a profit-sharing data partnership?
Fola / Vania: The truth is that providers do exist and they always charge local governments. What is underestimated is the role that data centres can play in this arena. The authors are members of the economic and social research council funded business and local government data research centre for smart analytics. This centre helps local councils use their big data better by collating data and performing analysis that is of use to local councils. The centre also provides training to public officials, giving them tools to understand and use data better. The centre is a collaboration between the Universities of Essex, Kent, East Anglia and the London School of Economics. Academics work closely with public officials to come up with solutions to problems facing local areas. In addition, commercial companies are interested in working with local government data. Working with third-party organisations is a good method to ease into the process of using Big Data solutions without having to make a huge changes to one’s organisation.
Ed.: Finally—is there anything that central Government can do (assuming it isn’t already 100% occupied with Brexit) to help local governments develop their data analytic capacity?
Fola / Vania: Central governments influence the environment in which local government operate. Despite local councils making decisions over things such as how data is stored, central government can assist by removing some of the previously-mentioned barriers to data usage. For example, government cuts are excessive and are making the sector very volatile so financial help will be useful in this area. Moreover, data access and transfer is made easier with uniformity of data storage protocols. In addition, the public will have more confidence in providing data if there is transparency in the collection, usage and provision of data. Guidelines for the use of sensitive data should be agreed upon and made known in order to improve the quality of the work. Central governments can also help change the general culture of local governments and attitudes towards Big Data. In order for Big Data to work well for all, individuals, companies, local governments and central governments should be well informed about the issues and able to effect change concerning Big Data issues.
Read the full article: Malomo, F. and Sena, V. (2107) Data Intelligence for Local Government? Assessing the Benefits and Barriers to Use of Big Data in the Public Sector. Policy & Internet 9 (1) DOI: 10.1002/poi3.141.
Fola Malomo and Vania Sena were talking to blog editor David Sutcliffe.