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.
The disruption brought on by the pandemic in 2020 highlighted two key finance weaknesses in some organizations:
- The gaps in their finance capabilities to support organizational agility, and
- The underinvestment in finance digital transformation that created these gaps
These two points usher the urgency to accelerate finance digital transformation. Finance teams that are 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 need for modern robotic process automation
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 a necessity to reach the “low hanging fruit” rather than any particular vision. In addition to cost savings, modern day RPA also focuses on how automation can help to generate greater insights, as well as 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 focus when it comes to digital transformation. Customer-facing segments of finance tend to transform more quickly – for example the popular integration of 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 digitization of all documents; it is now streamlining processes that enable businesses to operate more efficiently through insightful analytics.
Four ways in which RPA help to find the “A” in FP&A
- Fact finding
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 for 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. First, it generates a clear sense of direction for the project. Second, it clears out the clutter and encourages process harmonization. Third, it allows stakeholders to voice “the good, the bad and the ugly” of the current processes to help identify where improvements are necessary and feasible. It is worth noting at this point that finance digital transformation should not be seen as an IT project, but as a finance project.
One way RPA brings about efficiency is through process harmonization. Finance teams can take the lead and gather information to arrive at a consolidation view of the current planning process. Through fact finding, finance teams can find out why there are differences in processes used by different business groups, and work with the stakeholders to harmonize the process while delivering the required insights. Harmonization encourages collaboration and best practices in BPF throughout the organization.
- Instant review
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 allows FP&A teams to focus on review and analysis. With increased visibility, standardization, and faster processing speed, the business receives an instant view of the financial impact of their potential change course. This in turn helps with scenario planning, which is key to improving responses to crisis situations.
- Agile planning
During events like a pandemic, uncertainty is one of the biggest challenges that FP&A faces in forecasting. Time is of the essence. RPA harmonizes processes and collects data in a standardized fashion, requiring FP&A teams just focus on working with the business to identify drivers. RPA 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 being reactive to proactive, in search of opportunities.
Benefits of RPA for FP&A
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 standardizing data formats. With RPA and specialized 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 the forecasting process and finance teams become more engaged in the decision-making process. These changes help to transform finance from the traditional bean counter, in the Dickensian days, to a modern-day influencer.
How RPA can help to evolve FP&A into xP&A
AI and machine learning (ML) have yet to evolve to make autonomous decisions. AI and ML weigh out the risks and opportunities within the confines set by the organization. Therefore, they can only deliver benefits of speed and efficiency 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), FP&A teams may become more native, in other words, becoming part of the operational team. This may cause a more matrix-like FP&A organization. The benefit of this is enhanced collaboration and enriched analytics.
Above all, analysis is only as good as the data on which it was based. No amount of RPA can replace good quality data. RPA can help to improve the quality of the data and the speed at which it can be accessed. However, it is up to FP&A teams to take the reins and deliver the best out of the digital transformation process for BPF.
Author: Simone Collins, ACCA and FPAC, and author at FP&A Trends
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