The 2008 financial crisis led to a shift in customers’ expectations and relationships to companies. No longer is it enough to sell quality products, these have to be delivered hand in hand with personalised and excellent customer services, everywhere, all the time. Finance and Supply chain offices, being less exposed to those frontline changes, have since been playing catch up to this seismic shift. It’s now time to show that they are equipped with the skills and technology to bring various sets of data together, with the help of automation, to deliver on their role as internal strategic consultant.
Customer-facing functions have spent a decade dealing with rapid and disruptive change. What journey have the ‘back office’ teams been on?
For finance in particular, there has been a fundamental shift beyond managing raw numbers. Collecting, verifying and reporting numbers – often manually – used to be the core role of the finance team. But the complexity and the volume of data that is coming into finance now is growing exponentially and this is making things really difficult for finance leaders.
Are some companies are in denial about this growth of complexity of data on the one hand, and inflated customer expectations on the other?
Research suggests only 40% of finance leaders feel ‘quite comfortable’ with the amount of data they’re expected to manage. (Note that only 43% feel that the security they have within their organisation is also adequate. This suggests a degree of complacency given what we know about cyber threats…)
Even for a finance team primarily focused on internal, transaction-related data, there are new challenges. The granularity of today’s data breaks a lot of old assumptions about what constitutes ‘good enough’.
For finance leaders expected to provide compelling insights on the past, projections of future performance and contributions to growth – particularly around strategic decisions such as M&A – the gap is potentially wider. CFOs without the right support risk falling further behind as these expectations grow.
Even on compliance and risk management – also ‘traditional’ finance deliverables – in-the-field-data is getting more complex. For example, IDC predicts that by 2022 digital risk will need to be a standard part of financial reporting.
So even the ‘old’ roles are changing to adapt to new sources of data?
Today, all that data, that finance insight, is being used to new ends, too – not just to optimise returns, but also shape the behaviour of people and transform culture. It’s not just cost-to-serve for digital versus offline, or even uncovering new potential revenue streams from digital channels; analysis can help leaders embrace disruption with confidence and accelerate innovation.
CEOs expect this insight around customer behaviours; they want data-driven advice, not opinions; and they need increasingly accurate projections on future performance. We are working in an era where even the biggest brands have to embrace ‘the pivot’. But if finance is running to stand still on the basic data hygiene tasks, it’s going to struggle to bridge the gap between these critical needs and their capabilities.
So if the CEO and the wider leadership team cannot rely on hard data to inform those radical decisions, there’s a problem, right?
Agility backed by knowledge creates competitive advantage. Data is fuelling a new dialogue within companies, between companies and their stakeholders – especially customers – and beyond. Ultimately, finance is a language, and using the right language to describe new interactions is a must.
Scottish Water – a market-leading supplier in the UK – is a great example. It’s a challenging, highly competitive, industry. So the team there looked at their business model, they looked at what insights do they actually get, and started to focus on articulating potential benefits to the consumer. That work has delivered an 85% drop in complaints and a 21% rise in customer satisfaction – just from using data to better understand what people want.
Those customer insights clearly deliver top-line value, then. But even inside the finance team, new approaches powered by AI and cloud are delivering to the bottom line.
One trend we’re seeing among the leading finance teams is automation.
It’s compelling. Getting the basics delivered via robotic process automation (RPA) allows for a step change in efficiency and means finance staff can focus on delivering business and financial insights.
APIs, which are one ingredient for better RPA, are developing into a whole ecosystem, building connections between organisations, standardising data and enhancing the finance function’s ability to deliver against this new promise. And as we create these much broader platforms – systems that are capable of generating and analysing data of every type – we also allow the same kind of analysis to pervade a variety of other functions.
Where else can these technologies help companies speed up the strategy to execution time cycle?
Supply chain management is an obvious candidate. Today’s supply chains are global, extended, must be flexible yet reliable – and without proper visibility can introduce huge risks into an organisation. Data-driven insights from a properly connected supply chain mean cost savings to boost the bottom line, better risk management and opening up a new strategic markets.
So what’s holding up teams that are looking to catch up on exploiting data?
One challenge for their leaders is visualising a strategic roadmap, given their need for agility and the effect of uncertainty. It can be hard to develop a fixed idea of the objective when so much is changing. Then legacy technology infrastructure and processes can block adoption of new approaches. If they feel even the early steps are tough because data is stuck in silos, or there’s an interoperability problem between systems, it’s hard to visualise the kind of automated, efficient, open platforms this future works on.
Needless to say, there are ways to leapfrog some of the digital transformation challenges – not least by looking at well-established, secure cloud platforms that deliver precisely the kind of secure, flexible approach that’s required today.
How will finance and other functions know when they’ve caught up?
The ideal is enterprise-wide systems that are interoperable thanks to APIs and cloud availability; that can adapt to different data; and deliver the kind of holistic analytical insights that a single view of big data can bring.
‘Catching up’ means that different teams all operate at the same speed, with a shared view of the data. Then finance leaders can set teams free: automation of routine tasks allows them to focus on value-enhancing questions. When the CFO works in partnership with the CMO, for example, they can bring together different data sources to foster genuine innovation.
When the CEO is turning to those finance and supply chain leaders as the first test of strategic decisions – and to generate new strategic directions – they’ll know they’re in good shape. They’ll have truly caught up with expectations that they should be a kind of hyper-informed internal consultant.
We apply these same principles inside Oracle, too. Our teams use the same Oracle cloud capabilities as customers – and the kinds of automation that high transaction volumes demand so our finance leaders are able to offer precisely that kind of strategic support. Whether it’s dash-boarding capabilities to visualise real-time data, or applying machine learning to refine the automation of increasingly complex tasks, we know it works.