Supporting civil service decision-making: the role of finance
When Workday’s Ed Bass worked in finance for the Home Office back in the 90s, he says, “I think it is fair to say we used to keep score”.
But these days things are changing. Information on costs, revenues and spending efficacy is now at the forefront of change programmes and service reforms across government. Mike Driver, head of the UK Government Finance Function, argues that these changes, along with the wider digital transformation agenda, “put finance at the heart of decision making – driving the agenda, not just keeping score”.
Together, fiscal and operational data hold huge potential for helping departments to “function optimally”, says Bass, who now works as an account executive at Cloud finance and HR specialists, Workday. However, he adds, fragmented data and legacy IT systems can slow this transformation down and this is “holding back the public sector very much”.
Bass was speaking during a webinar hosted by Global Government Forum in association with Workday on 10 July, alongside his colleagues Stephen Creech, senior product marketing manager, and senior solutions consultant, Andy Gough.
They each gave presentations on the future of finance in government and how new technologies like machine learning and chatbots can enhance decision making for operational leaders.
“We need to be joined up with the data”, says Bass. Financial data that is “enriched with operational information”, provides better oversight for heads of department and will “drive much better-informed decisions”.
“In other words finance is put right back at the centre of decision-making within government,” he says.
But in practice, combining all of this information can be difficult. As Creech pointed out, while there’s more data and information out there than ever before, “finance [officials] are being asked to do more with less and it’s quite often on these same old systems and spreadsheets”.
There are other considerations too. Gough says Workday has recognised that the data its customers typically find the hardest to model and extract to a ‘data warehouse’ are their finance and HR structures because “that sort of data changes frequently, there are multiple hierarchies, snapshots and so on”.
Now that GDPR is in force, moving HR data from an organisation into a data warehouse also throws up issues around how to secure it, he adds.
“Finance transformation has been talked about for a long time and that’s partly because there hasn’t been a solution which has kept pace with changing technology,” says Creech.
Up until now, that is. Workday believes it has found a solution with its system that combines real-time financial data with operational information using machine learning.
While the technology behind it is complex, the system is easy-to-use and allows employees to “drill through from high level HR or finance metrics to operational drivers” in order to help them understand what’s going on in their department in detail, according to Workday.
Targeted reports and analytics are fed into the system so that the right people have the right data at their fingertips when they need it. This prevents people “making blind decisions,” says Gough, instead making choices based on real-time and contextual information.
The system is not just for heads of departments to collate data and derive operational insights. It aims to enhance people’s working lives at every level of the organisation.
For example, Workday Assistant, which is currently being trialled at the Cabinet Office, allows employees to get personalised financial and HR information in an easy and convenient way. The automated assistant answers questions such as ‘How much holiday do I have left?’, in conversational language, as well as putting in a request for annual leave – all in a matter of moments.
Gough believes this is the way things are going. “In the future, information will be provided in a much more conversational manor,” he says. “We won’t be looking at traditional reports, it will be much more about having dialogues and conversations with the information.”
As Gough demonstrated during the webinar, the Workday system goes further than facilitating everyday admin tasks, providing personalised services such as an ‘opportunity graph’ showing what steps employees can take if they are looking to progress their careers. “It’s very much about providing easy information to do the things [employees] need to do and do them in an informed way,” says Gough.
Machine learning continually updates the Workday system as employees add new information and save changes. The impact of certain decisions “is cascaded through the model automatically,” Gough adds. For instance, if a manager decides to hire a new member of staff, with the click of a mouse, “I’ve immediately updated both my forecast and all of my out-turn and variance calculations as well.”
“Everything’s flowing up in real time at every level of the organisation that I might choose to look at,” he says.
Workday is also working on a system that will provide targeted financial briefings via employees’ smartphones and an anomaly detection system that will not only flag up financial issues but suggest what is likely to be causing them.
As for automation, going forward, Creech says it will “fundamentally redefine the role of finance and the impact that it will have on the organisation” and that time-saving technologies will allow finance to focus on strategy and use insights “to drive department heads to make the right decisions”.
Automation also looks set to perform routine tasks “and only involve people where human intervention is required,” while augmented analytics will flag up potential issues “with cause and effect and present them in new and useful ways,” Gough says.
“This may be seen as a Star Trek futuristic vision,” he adds, “but what Workday is trying to do is ask what problems finance people are facing and how new technology can be applied to it. “Our plan is not to provide chatbot toolkits or frameworks but to provide real solutions and those real insights to business problems.”
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