In the first of this three-part series, Simon Dennis, Director, Future Government and AI Evangelist SAS UK, will examine how the public sector can integrate its way out of a crisis situation and reduce costs in government
As the UK tentatively emerges from the economic stall of the initial COVID-19 disruption, the Government must now concentrate all its efforts on driving a sustainable economic recovery – and, of course, the size and shape of public sector spending will be a critical element. Whilst there are assurances of no-return to the austerity measures used by Chancellor Osborne in the post-Labour deficit years, the Comprehensive Spending Review (CSR20) announced by the current Chancellor will look at necessary re-prioritisation to release funds for economic growth programmes.
We can imagine the senior civil servants across Whitehall preparing their submissions for the CSR with four things on their minds: The hundreds of billions spent by the government during the crisis at; then the last decade of austerity cuts will be brought back into painful focus as they search for opportunities to make savings. The third factor lumbering into view is the very imminent challenge that the UK’s exit from the European Union represents and the consequent work burden.
With such competing pressures and moving at pace, the CSR decision-making process could leave some citizens harder hit than others, or result in service gaps or duplication of effort across overlapping central departments and local delivery teams. To achieve an optimal balance, seamless communication and collaboration between government departments will be needed – starting now in policy and continuing into operational delivery.
It would be little surprise therefore if the fourth factor was the recent announcement of Francis Maude’s return to the Cabinet Office on a consulting basis. It will not have escaped attention across Whitehall that Lord Maude might be keen to see how the reforms he led have progressed. It is clear that a joined-up approach is now vital and given that one of Maude’s ambitions a decade ago was the creation of a culture of data sharing and collaboration – exactly the culture that is required to face the challenging times ahead – it would be nice if his reforms had borne fruit.
However, with the technology and data estates of departments remaining largely disconnected, there’s always a danger that the data silos that plague the public sector will continue. The ramshackle of heritage technologies interweaved with a few adventures in open source development by enthusiastic civil servants, makes a hesitance to modernise understandable. Yet understanding the value of data is the first step towards getting the best from it, and data quality never improves until data is used in anger by the business – and right now is the time to get the data in order as we enter the Age of AI.
It’s not the winning, it’s the taking part…
Collaboration and joined-up working thrive on the people involved, not the technology that facilitates the sharing of plans/ideas/data/algorithms – and whilst a process will almost certainly be developed, it isn’t the catalyst that makes things happen. It is only by people trusting each other across organisational boundaries and taking managed risks or even leaps of faith, that will encourage others to follow suit and, in turn, this will drive strategic alignment towards citizen outcomes.
Of course, as necessary activities along the way there will be practical instances of vital data sharing, know-how transfer, experimentation and prototyping – and eventually deployment of transformed services. The technology should enable not lead the programme and modern, enterprise, cloud-native AI-platforms will ensure that the focus remains on the business outcomes, the security, governance and ethical practices that are vital to retain trust in these times of fake news and citizen manipulation. The alternative would be wasted investment on managing the integration of a variety of govtech open source applets.
Sharing compounds efficiency
With future policy decisions based on all the available data, unfair decisions stand a far better chance of being eliminated and operational value for money assessments can be conducted as a continuous process against policy objectives in a holistic context. A shared approach will also benefit from a larger pool of evidence data and also enable risk mitigation to be managed at a portfolio, or even whole-of-government fashion by the Treasury reducing departmental contingency provisions.
Machinery of Government changes like those advanced by Dominic Raab and the Free Enterprise Group within Parliament purport to offer billions of pounds in in the way of savings, but these often have a significant latency period before savings are realised and may require an upfront investment of hundreds of millions in departmental restructuring costs. By using data and clever orchestration of staff from multiple organisations to deliver services, offers a far easier option than moving people between departments. Using AI to create a hybrid delivery framework that can flex its composition according to the citizen demand, will reduce dependency on local services provision yet offers resilience to cope with local demand.
So, joining up people and plans will in effect create new, virtual departments that offer a new route to efficient service delivery. In turn, analytics conducted in these virtual departments can produce actionable insights which will further break down silos.
Not all analytics are created equal
As we enter the CSR planning phase, departments will use models to plan where services can be streamlined or curtailed. However, while a history of fragmented and diverse operating models has created local efficiencies, it has failed to deliver the full potential that national roll-out promises. This lack of scalability is why many exciting plans for digital transformation in the public sector fall flat.
Just like the private sector, governments should start by acknowledging that COVID-19 has changed attitudes. Many existing models are unlikely to be accurate. Now, with an increased digital dimension, the uncertainty following the huge uptake of the furlough scheme, an increase in job seeking and the redefinition of the national socio-economic landscape has changed things dramatically. Old models will need recalibration to ensure they’re fit for purpose in the new normal, and new approaches such as scenario simulation can spring into action at speed.
The full collaboration of all departments is required. Introducing a shared, analytics platform to integrate work across data science and IT delivery will help produce insights which push strategy in the right direction. The system should support many open source technologies, opening up the chance for innovation while still meeting security, resilience, governance and engineering standards that the public sector must hold to.
AI and machine learning capabilities can help human decision-makers not only to see deeper meaning in the data than ever before, but to receive exponentially valuable insights over time. Overall, advanced analytics has the potential to speed up decision-making without compromising on quality, ideal for navigating a painless path out of the recession and ultimately shortening the recovery.
Mobilise and innovate to transform
With technologies so disconnected across the public sector, uniting them to generate collaborative plans for navigating our way to economic recovery is easier said than done. Digital transformation projects in the public sector have rarely got off the ground thanks to their ambition and expense.
However, the existing pockets of analytical excellence across the public sector hold the key. Having nurtured analytical talent for years now is the time to move these innovative ideas from IT rooms and coding corners into full deployment across departments. Those in the know should share their expertise and demonstrate how each model can make a difference in day-to-day work, strategy and, ultimately, to the lives of citizens across the country.
Armed with the broadest range of trusted analytical functionality they are the key to navigating our best route and maximising the agility with which we recover. And at the same time laying the foundations for the potentially vast efficiencies that Artificial Intelligence and Intelligent Process Automation promise.
So, with clear processes supported by the right technology, it’s possible to facilitate the transition from experimental prototype to stable delivery. Robust intelligence capability will help public sector leaders more easily collaborate and share best practice. At the same time, they’ll discover new ways of automating and streamlining services, ultimately leading to the ability to make better decisions in the interests of the country, the economy and every citizen.
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