There’s a lot that account-to-report (A2R) organizations can do right now to optimize the way they deliver services to stakeholders by standardizing, automating, and centralizing processes and sub-processes and redistributing activities among corporate, global business services (GBS), centers of excellence (COEs), and the business units (BU). Too many activities are still handled at the BU level. Too few are fully automated.
However, digital technologies are bringing finance overall, and A2R specifically, to an inflection point. Digital transformation will not only help make A2R processes faster and more efficient; it will ultimately change the level of the organization at which these processes take place. The introduction of technologies like robotic process automation (RPA) will reduce the need for manual labor and shrink the footprint of the GBS, while promoting greater use COEs, which house high-skill knowledge workers.
According to research conducted by The Hackett Group, the market for RPA is real and growing. It has the potential to change the business process outsourcing (BPO) landscape, GBS organizations, and broader business-specific processes. Adoption is expected to be in the 40%-50% range through 2020, transforming our idea of automation and service delivery. RPA can be a game-changer because it allows companies to achieve substantial cost savings without needing to change their overall technology infrastructure. Process and data must be rationalized and cleaned up, of course, for RPA to work. Everyone dealing with legacy systems knows just how valuable that can be. The same goes for the painful change-management implications that come along with process redesign.
RPA is software that sits between other applications and executes rule-based work that would typically be done by people. RPA mimics human interactions with business applications at the user interface level – for example, logging in and out of an application, copying and pasting data, or choosing from a drop-down menu.
Two big factors are driving RPA adoption in finance and elsewhere:
- Speed of impact: RPA has a short development cycle and yields quick benefits like reductions in FTEs, based on low initial investment with a significant ROI in weeks and months, not years.
- Enhanced capabilities: RPA-enabled processes are highly auditable and consistent and have extremely low error rates; they are also very scalable and provide the data required to run sophisticated analytics.
When does RPA make sense?
RPA has a wide range of applications within the finance organization because many of its processes fit its application model, specifically those in A2R, such as general ledger entries and reconciliation. Several providers offer end-to-end robotic-enabled solutions that encompass activities such as payables, receivables, tax and treasury, asset management, general ledger and cost, and management accounting. With an RPA-powered close, up to 80% of the process is handled by robots, from accounting system operations, output preparation, period-end closing, internal controls, frequency and quality of transaction processing, and master data maintenance. Only about 20% is manual, including the interpretation of the outcomes and judgment and policy setting.
As A2R executives update the placement and execution of key services considering new digital developments, they should ask the following questions to decide whether a specific process is ripe for RPA:
- Is the process executed frequently and in large volume? It doesn’t make sense to use a robot to perform a process that happens only infrequently in small batches.
- Does the process require access to multiple systems? A robot can much more quickly and efficiently log in/out of applications and cut and paste data from one application to another.
- Can the process can be broken down into unambiguous rules? Unlike people, software needs clear rules. If there are judgment calls, it cannot perform its task.
- Is the process structured and digital data available? The robots need to follow an established and well-understood set of process steps and have access to all necessary data.
- Is the process prone to human error? Robots don’t make mistakes when switching applications and re-inputting data.
- Does the process require limited exception-handling? Too many exceptions cause problems for robots. RPA’s ROI is built on doing large volume of repeatable acts. If many of the actions are kicked out for human intervention, it defeats the purpose.
- Does the process, once started, require limited human intervention? If the process needs a lot of human intervention, it doesn’t make sense to get robots involved.
- How complex is the stakeholder/process ecosystem? Processes that serve multiple stakeholders and exist in very complex ecosystems may not lend themselves well to fully automated solutions because they require different outcomes.
There’s a lot more room for traditional service models to go further and achieve better results. But A2R executives seriously rethinking their service delivery model should evaluate whether it still makes sense to place activities based on the old model, or fundamentally redesign how work gets done using emerging technologies. Ultimately, RPA will alter the traditional finance delivery model and where different activities take place.
For more on digital transformation in finance, see Machine Learning: What’s In It For Finance?