While finance departments are not insulated from this disruption, they often find themselves lagging compared with the investment undertaken by other corporate functions and, in turn, find they are being asked to deliver more with less.
What’s the current state?
While the journey through digital disruption lies on a broad spectrum, organisations can generally be grouped into three categories: reluctant adopters, early adopters and future-focused.
Reluctant adopters are reluctant to adopt digital solutions, hoping that the need to adopt such measures will be passed onto the next generation. While organisations at this stage are becoming the minority, they see the constant churn of new technology and new ways of working as a barrier to beginning their digital transformation. This group will eventually adopt new ways of working, but prefer to wait for more certainty on the direction to take. They may be waiting a long time.
Early adopters have started their transformation journey and are seeing the benefits, primarily through cost reductions brought on by efficiencies. An example of this is the adoption of Robotic Process Automation (RPA) to speed up business processes such as customer order processing, the accounts payable function, payroll processing and incoming customer email query processing.
Organisations in this group aim to minimise costs and gain more value from their employees by transitioning them into more fitting roles, as opposed to replacing them with technology. It gives the employees of those organisations an opportunity to perform more analytical tasks such as evaluating the data output from those RPAs, challenging the numbers and drawing patterns.
Future-focused organisations are leading the charge on digital transformation and redefining the role of the finance function. While they continue to benefit from efficiencies now embedded in their business-as-usual practices, these efficiency gains are reaching their peak and are hampered by the finance function’s traditional skill set. As a result, future-focused organisations have started to change their hiring and training practices, broadening roles outside of those typically associated with accounting and finance functions — one of the key steps in the evolution from traditional finance function to effective business partner.
This is enabling the finance function to participate in conversations previously out of their grasp, providing new business insights to CEOs and other senior members of management. Organisations in this category may find themselves struggling with incoming data validity, highlighting the need to embed controls typically only seen in the finance function (e.g. three-way matching and other validation checks, standardised input) within other corporate groups.
What do we think the future will look like?
While terms such as “big data“, “artificial intelligence“ and “machine learning” were uncommon up until a decade ago (unless you specialised in those fields), they are now the newest breed of buzzwords organisations have to navigate. As organisations and people undergo their own digital transformations, the world will continue to become more volatile, uncertain, complex and ambiguous — or VUCA, as this set of conditions is now known. Successful organisations won’t be those that can predict the future, but those that can act with agility and respond to this VUCA environment. The ability to provide real-time predictive modelling (i.e. that enables agile approaches to achieving an organisation’s goals, objectives and purpose) will be at a premium.
Below are some shifts we predict will take place over the next 10 years in the corporate finance function:
FP&A is king!
A great finance function is an effective and trusted partner to line business units. This starts with finance, planning and analysis (FP&A) support — helping to make sense of sales trends, business performance and forecasts.
However, a challenge many organisations face is substantially dispersed, un-integrated and poor-quality data, with a blurred starting point that makes it difficult to organise in a homogenous format. Many organisations run different platforms for their various corporate functions, which results in data being stored across different systems with no common structure, making analyses very challenging.
This presents an opportunity for a leading-edge finance function to assist organisations to assess the landscape of their data and, using data cleansing techniques, align the various data points in a way that enables analyses. Once this cross-functional data is in a homogenous format, further data techniques can be employed to validate the data points. This will ensure the data that is driving corporate decisions is valid and the conclusions drawn through analysing it are founded.
The second part of a transformation lies in making analysis real time. Historical data will no longer be limited to month-end close periods that are often only available weeks after the period closes. Forecasting fares even worse, typically set as a plan annually and updated perhaps quarterly at best. By 2030, expect all forecasting to be dynamic, underpinned by: (i) real-time automated continuous close of historical results; (ii) AI-based extrapolation models that can amend plans to take account of input variable changes and remove bias in historical forecast versus actuals; and (iii) forecasting models that are far more sophisticated, being able to draw insights from correlation with multiple external data sets such as weather and population demographics.
Lastly, expect the way information is provided to users to change. Dashboards and visualisation will become ubiquitous. AI will do much of the heavy lifting in analysis to identify trends drawing on correlation with all manner of data sets, as noted above. Organisations may also choose to draw on a multitude of providers to support them via various cloud and SAAS models — where analysts no longer need to be based in one location or even one country to effectively collaborate.
Digital upskilling and transformation
The early adopters group will continue to grow, with finance professionals forced to digitally upskill themselves as RPA and other automation techniques remove repetitive and low-value tasks. Employees will be able to reduce their focus on the actual number crunching and data entry aspect of their roles, and increase their focus on analysing that data to make better decisions for the business.
Critically, if KPIs are not set early and ambitiously, finance functions may not pivot in time, or even at all, to a 2030 digital model. Human nature is to maintain the status quo: it’s easy to avoid change unless teams are supported and encouraged to digitally upskill.
The human edge
Humans are irrational, technology is rational. This difference will work in our favour: if there is one thing that technology cannot do (yet), it’s to mimic human emotions. As a result, people and group management skills will be a greater focus in the workplace — a shift that is already evident and will continue to play a major part in the hiring process for organisations.
The ability to understand human emotions by developing emotional intelligence in the workplace, and raising your emotional quotient (EQ) to deal with different personalities, will become vital. This will cause a change in how KPIs are measured by organisations.
As traditional finance roles are displaced, finance professionals will find their “soft skills” put to the test as they focus on coaching, mentoring and developing a department with a broader set of skills. They will also find themselves having conversations with departments they previously had limited interactions with, placing further pressure on their ability to communicate with impact.
We already see this where incoming new digital finance tools are relatively intuitive, requiring little technical user training BUT substantial investment in making a culture change for teams to embrace the new tools. Lastly, we would say, spend your investment in digital transformation wisely. In any team, it’s likely the majority will want to learn and be open to change — this is where you’ll get the most uptake.
While we can’t tell you which technologies will win out or what data modelling skills you should start brushing up on, we can tell you this: technological disruption in the finance function shows no sign of slowing down. Like anything else, accepting and adopting the changes sooner rather than later will benefit individuals and organisations by helping them deliver more with a digitally transformed finance function.
Alan Garner, Nisha Mehrotra and John Ratna, PwC