The FP&A Trends Webinar: Digitised FP&A Business Partnering: The Formula for Success
Click here to view details and register
The FP&A Trends Webinar: Digitised FP&A Business Partnering: The Formula for Success
Click here to view details and register
By Simone da Silva Collins, Senior Financial Controller at Sony
The disruption brought on by the COVID pandemic in 2020 highlighted two key financial weaknesses in some organisations:
These two points usher the urgency to accelerate finance’s digital transformation. Finance teams behind in their digital transformation journey have found themselves on the back foot within uncertain environments when attempting to support the delivery of a company’s competitive advantage. This is because they lack the capability to provide insightful decision support analytics in an agile way.
The use of Artificial Intelligence (AI), such as Robotic Process Automation (RPA), is one area that can help finance teams transform their analytical capacity and capability. Traditionally RPA was about weeding out manual processes and achieving cost savings through reducing headcount. It originated from the necessity of reaching the “low-hanging fruit” rather than any particular vision. In addition to cost savings, modern-day RPA also focuses on how automation can help generate greater insight and enable finance teams to carry out value-adding tasks.
Advantages of automating the budgeting, planning and forecasting (BPF) processes include time savings, cost efficiencies, increased visibility and, in some cases, improved planning accuracy. Despite these obvious advantages, FP&A and BPF do not always receive the same level of attention and focus when it comes to digital transformation. Customer-facing segments of finance tend to progress more quickly, e.g., purchase to pay (P2P) and order to cash (OTC). This is because finance teams fail to demonstrate to management the connection between process change and the advantages of automation and how process changes can impact profitability.
Automation is no longer the replacement of humans with robots or the digitisation of all documents. It is now streamlining processes that enable businesses to operate more efficiently through insightful analytics.
As with any business transformation project, the first step is to find out the current process. This allows us to examine each step of the process, any dependencies and interdependencies. With clear data and a process plan, efficiencies and redundancies can be identified. This may seem like a time-consuming exercise, but the value from this first step paves the way for successful finance automation:
At this point, finance digital transformation should not be seen as an IT project but a finance project.
One way RPA brings about efficiency is through process harmonisation. The finance team can take the lead and gather information to arrive at a consolidated view of the current planning process. Through fact-finding, the finance team can find out why there are differences in processes used by different business groups. The finance team can then work with the stakeholders to harmonise the process while delivering the required insights. Harmonisation encourages collaboration and best practices in BPF to be followed throughout the organisation.
RPA removes the manual tasks involved in preparing and generating a base case plan, such as data collection, template distribution and pre-population of inputs. This means FP&A teams can focus on review and analysis. With increased visibility, standardisation and faster processing speed, the business receives an instant view of the financial impact of their potential change course. It, in turn, helps with Scenario Planning which is key to improving responses to crises.
During COVID, uncertainty has been one of the biggest challenges that FP&A has faced in forecasting. Time is of the essence. RPA harmonises processes and collects data in a standardised fashion, and FP&A teams have already worked with the business to identify drivers. These tools allow FP&A teams to be in a stronger position to advise the business of the potential financial impact of their strategy. They also allow FP&A teams to transform from reactive to proactive in search of opportunities.
One of the most complained about areas in BPF is data collection and cleaning, as it is time-consuming. RPA takes care of this by automating data collection and standardising data formats. With RPA and specialised BPF tools, FP&A teams can move away from overreliance on spreadsheets.
Finance automation also changes the way finance analytics are conducted. FP&A teams are no longer tied to fixed reporting cycles and historical comparisons. BPF is now part of continuous improvement for the business rather than an arbitrary fixed horizon exercise. A Rolling Forecast becomes second nature in forecasting, and finance teams become more engaged in decision-making. These changes help to transform finance from the traditional bean counter, in the Dickensian days, to a modern-day influencer.
AI and Machine Learning (ML) are yet to evolve to make autonomous decisions. AI and ML weigh out the risks and opportunities within the confines set by the organisation. Therefore, they can only deliver speed and efficiency benefits in the BPF processes. If FP&A teams rely solely on AI and ML to improve BPF, they risk turning BPF into a purely mathematical exercise. To enrich BPF processes and provide insightful decision support, FP&A teams need to engage non-financial stakeholders to help understand the data and its analysis. With this additional qualitative information, FP&A teams can work with the business to deliver an integrated BPF approach that covers all three key financial statements rather than simply focusing on the profit and loss.
As FP&A teams evolve towards Extended Planning and Analysis (xP&A), they may become more native, in other words, become part of the operational team. This may cause a more matrix-like FP&A organisation. The benefit of this is enhanced collaboration and enriched analytics.
Finally, analysis is only as good as the data on which it was based. No amount of RPA can replace good-quality data. However, RPA can help improve the data quality and the speed at which it can be accessed. Therefore, it is up to FP&A teams to take the reins and deliver the best out of the digital transformation process for BPF.
Any views or opinions expressed in this article are solely those of the author and do not necessarily represent those of any companies that the author has or is working for.
This article was first published on the SAP Blog.
Watch this video to learn a Case Study from Sandoz about the Analytical Transformation of FP&A...
Is your most fancied FP&A RPA initiative not delivering the anticipated benefits? You are not alone. So...
According to research conducted by the Hackett Group, the market for robotic process automation (RPA) is...
Future coordination is a brainer - not a no-brainer. Combining the Now and the Future requires...
According to research conducted by the Hackett Group, the market for robotic process automation (RPA) is...
So why are we as finance professionals so slow to adopt digital transformation when there are...
We will regularly update you on the latest trends and developments in FP&A. Take the opportunity to have articles written by finance thought leaders delivered directly to your inbox; watch compelling webinars; connect with like-minded professionals; and become a part of our global community.