While day-to-day spending on functions including health, education and defence will rise in 2019 by 1.8%, 3.8% and 1% respectively, many other departments will experience sustained budget reductions into next year.1 This still leaves many departments battling with ongoing issues around how to improve service quality, operational efficiency and citizen outcomes with less available money. This is especially difficult in the post-recession era, where all available cuts to budget through traditional means – particularly procurement and resources – have already been made, many times.
However, the challenges facing government are far from budgetary alone. All departments are in the midst of an incredibly complex period of decision-making and planning around Brexit. Forecasting the implications of exit decisions, modelling scenarios and evaluating risk alongside eventual outcomes is an extraordinarily complex and tough process. One that requires the broadest, deepest and most contextually-aware insights possible.
Similarly, delivering an increasingly joined-up, personalised and fast service to service users, whether they are organisations or individual citizens, via the ubiquitous ‘digital transformation’, is both an ongoing challenge and opportunity for government organisations.
So the question is: what do better decisioning, value-based operational efficiencies, accelerated deployment of digital services, and complex policy evaluation all have in common? They can all be addressed with data. Specifically, they can all benefit from the rich, accurate and rapid answers that advanced analytics can deliver.
All this can only be made possible if government collects a broader range of data and relevant insights are shared across departments that collaborate rather than compete. Many have already made a start using analytics to answer their most challenging questions; more must now follow, if advanced analytics is to sit at the heart of everything. One should note, however, that not all analytics capabilities are the same. Some are really only capable of telling civil servants what has happened. The kind of analytics now required are able to provide the hindsight to see what has happened and the foresight to predict and model what might come. As in-depth and valuable as those insights will be, government cannot wait months or even weeks to acquire them. Speed-to-insight is essential, and actionable insights must happen immediately, making the ability to analyse real-time data absolutely mission critical.
What can be achieved?
A great deal. In a paper called ‘Analytics for Government: Better decisions, smarter policies at less cost and risk’ analytics provider SAS discusses a very broad range of use cases from as far afield as DWP, HMRC, the British Army to the NHS and the police. A surprisingly diverse and powerful suite of applications appears. The British Army, for example, has found new ways to realign what it spends money on and to eradicate £770 million of waste. In policing, SAS is powering the analysis of huge volumes of intelligence data rapidly, so that teams can cut through the noise and focus on real and emerging threats. At the Royal Brompton & Harefield NHS Foundation Trust, they have deployed SAS capabilities to create a single data repository so that information on infection rates can be analysed and shared between specialists, supporting the development of prevention and treatment best practices. I recommend reading these use cases and others in full, as food for thought.
What is the one key takeaway from these case studies? Once an organisation has developed a culture of evidence-based decision-making and has begun to derive meaningful benefits, analytics will be firmly embraced and its value will multiply.
However, as with all great ideas, taking them from theory to execution can be problematical. As simple as it might seem to collect more data, share insights and power key decisions with evidence, there are a number of practical steps that government agencies will need to undertake in order to yield the benefits of advanced analytics.
What are the practical steps to becoming a data-driven, analytics powered organisation?
It’s not an overnight change. However, following these critical steps will put your organisation on a proven path.
- Getting buy-in from senior leaders to explore the opportunities for advanced analytics and present these alongside the risks doing nothing
- Demonstrating the value through workshops to understand possible use cases
- Learning from best practices, benchmarking against the outcomes experienced within other industries
- Educating the organisation to embrace a new evidence-based culture of decision-making
- Coordinating and sharing ideas, resources and budget across linked departments will help to optimise the value of advanced analytics
- Auditing information assets so that you have one central information register rather than largely unknown silos of data
- Building trust in data by cleaning it and maintaining it at a minimum level of quality
- Consolidating information assets, skills and tools is a certain way to expose gaps and to drive value
- Partnering with experts will help to reduce initial costs, fill in skills gaps and shorten project lead times
- Create centres of excellence in order to pool expertise and skills and share success stories to multiply value across government organisations
Whether your primary objective is to seek out new cost savings, to develop smarter, evidence-based policies, or even to explore new service scenarios that improve citizen outcomes, there is certainly a very powerful business case to be made for embracing advanced analytics. And in the age of AI, now is most certainly the time to act, given that analytics is the capability that can make AI smart for government.
My opinion is that when it comes to ‘better decisions, smarter policies, more efficient operations’ government organisations most certainly can have it all.
For further information, take a look at the SAS paper Analytics for Government: Better decisions, smarter policies at less cost and risk