The drive for improved public services is ongoing, especially in the UK, where many departments are being asked to cut costs by as much as 40%. The public sector is also having to cater for a rapidly growing population, meaning they must spread what was already a small amount of jam over even more toast.
Increasingly, governments are looking to Big Data analytics to enable this. The amount of data available to the public service is huge. However, recent studies have shown that they are less familiar with Big Data than private firms, with the rather obvious exception of the security services. There may also be some reluctance surrounding the cost of implementing such programs, although the amount of open source software available, and the size of government contracts, mean that is extremely cost effective.
Big Data can be useful to organizations in a number of ways, primarily in streamlining their operational processes. By looking at worker productivity and where time is being wasted for little apparent ROI, analytics makes it easier to cut funds without significantly damaging the framework of a department. This does not necessarily mean redundancies. The data that HR holds can help to establish an individual’s best working practice, and how they can best be managed. This can even be cross-referenced with others’ data to optimize how different teams work. This not only ensures higher productivity, but can lead to better retention of the best staff. The public sector cannot offer the same wages that private firms can, so they must be creative with how they provide the best working environment.
One public service organization making use of data to the benefit of operational processes is US Rail, which has conducted a Big Data initiative to realize fully customized predictive maintenance. The scheme has enabled a drop in mechanical problems of 75%, and maintenance costs of 20%.
Healthcare is a good example of where data and analytics might be put to good use. It can help with medical research, by analyzing bloodworks for certain illnesses en masse and finding trends. It can help people avoid readmission after surgery, based on an analysis of risk factors related to an individual’s circumstances. It can even help predict which areas of the country will provide certain drugs and equipment, to streamline the supply chain and avoid unnecessary stockpiling.
Collaboration across the public sector is also far easier thanks to data visualization and new technology that enables fragments of related information to be matched and linked together rapidly and non-persistently. Sharing data in this way not only greatly speeds up communication between different organizations, it also helps them collaborate to drive innovation.
The public sector faces a number of different challenges to the private sector when using data. There is more regulation and a clearer train of public accountability when it comes to collecting and using personal information. For analytics professionals too, it is often more of a challenge to hire the required talent, and for governments to appreciate that the short term costs in training will benefit in cost-savings longer term, because of the political ramifications of a hit to the budget deficit.