Qinthara Fasya | 29 September 2021
Managing Director International, ICAEW
Finance functions across sectors have developed and adapted in response to an increasingly digitalized environment. The ongoing Covid-19 epidemic, as well as the increase of remote working, have hastened this change, emphasizing the necessity of new skill sets for accounting and financial professionals looking to further their careers.
Boards and senior management are increasingly expecting finance divisions to use digital technology to improve operational efficiency and reduce time spent on low-value activities. Automation is a critical tool in achieving this aim, and it has been prioritized. Finance teams utilize the technology extensively in areas such as journal processing, reconciliations, and typical help-desk enquiries, and it may enhance efficiency in month-end or quarter-end closings and all associated procedures. DigitalCFO Asia spoke with Mark Billington, Managing Director International, ICAEW, who shared more on what is required to make this change including steps to change culture, behavior, and leadership mindset.
The Evolvement of Finance Functions
The first wave of change follow transition to a remote-first environment as countries entered lockdown. Making sure that employees had access to an electronic workflow process in an audit-proof document management system was key for many businesses to help them review and approve invoices and other business transactions in a secure manner. Agile reporting and forecasting of finances became a critical tool for organisations to manage their cost flow and tighten their bottom lines amid increasing uncertainty and rapidly changing environments.
The second wave followed when consumers settled down into a new digital norm and businesses had to evaluate not only how to sustain their business but also, how to innovate to keep pace with customers who look forward to seamless digital experiences. Across industries, businesses had to rethink how to digitalise their core internal operations such as production and R&D to interactions in supply chains to make sure they were creating long-term, instead of simply tactical changes. To support this transformation, finance functions were also pushed to adopt new processes, interpret and apply data to solve priority business challenges.
Finance automation goes hand-in-hand with wider efforts to digitalise finance operations. As paper-based processes are replaced with technology, the need for tedious, manual work diminishes. This simplifies the back-end processes for businesses and help them design in a new and more efficient way.
Automation can also lead to improved controls and compliance. In scenarios where large companies are conducting millions or even billions of transactions a month, automation can provide faster data – a growing demand from regulators- while reducing the margin for errors.
For example, Johnson & Johnson implemented Robotic Process Automation (RPA) with a goal of automating aspects of intercompany requests, invoice creation and postings. What started out as a pilot became a long-term process when the company saw improvements in its workflow and processes such as being able to handle a volume of transactions in an accurate manner and impact on staff resource who could focus on high level operations.
Leveraging Automation & Emerging Technologies (AI, Blockchain & Data Analytics)
The introduction of technologies like artificial intelligence and data analytics has brought about many opportunities to improve efficiency, provide greater insight and deliver more value to the business, for example through being able to work with:
- Large data volumes –AI can process huge amounts of data (structured and unstructured) – much more than humans ever could; for example, the results of every piece of medical research carried out on a topic, or every piece of financial regulation. This provides a powerful basis for learning.
- Complex and changing patterns – It can also be critical in helping businesses pick up anomalies where it may be difficult for the human eye to detect. Where feedback loops can be built into the models, they can also be highly adaptive and learn from errors or new cases.
- Consistency – AI can help manage work that may be more mundane, enabling finance professionals to innovate and deliver meaningful work like how to better connect digitally with their customers.
Successful finance transformation projects require a sensitive process with workload and management implications. For that reason, businesses should make sure that this is led by experienced and qualified staff. Indeed, many businesses are grappling with the challenge of finding, nurturing, deploying, and retaining the right blend of talent to allow finance to thrive in the digital future.
This makes it more critical for CFOs to act now to identify the skills needed in the short, medium, and longer terms, and plug any existing or predicted knowledge gaps by up-skilling existing team members or through wider recruitment policies within and outside the organisation.
In building up their dream team, business leaders might also want to consider appointing sub-project leads for individual streams within the local teams to enrich their understanding of the project and give the project stability.
At the core, changing the culture through communication regarding the importance of transformation and embedding technologies like AI and automation is key. Finance leadership can help align the objectives of the transformation to the culture by taking concrete steps such as agreeing to service level agreement and taking time to actively listen to feedback across cross-functional teams.
As finance talent models evolve rapidly, a premium is placed on data scientists, business analysts and “storytellers”, who can communicate in an engaging way about what data means for real people in the real world.
Core skills for the digital future will include data intuition skills to identify and understand what is important and significant from the numerous outputs and data communication and visualisation for finance professionals to describe their conclusions to technical and non-technical colleagues.
To translate their technical know-how to business value, finance professionals should also act as the intermediary and build trusted relationships with the wider business and data scientists, communicate with clarity, instigate breakthrough conversations, and bring together cross-functional teams to support data-driven decision making.