RPA and the Finance Function - predictions for 2019
2018 was an exciting year for those of us who work within RPA as the interest and uptake continued to snowball. Within Finance in particular, our Proservartner Automation Index (a study of over 600 UK businesses, released in November), found that just under a quarter (24%) of businesses had automated components of their Finance function within the past six months.
Unsurprisingly for such a new technology with so much potential, there have been some dramatic shifts within the marketplace within a very short timeframe. So looking forward, what will this year hold and what will these changes mean for Finance leaders?
Given that it is the start of the year, I want to share my five predictions for RPA in the Finance function for 2019:
1. RPA will precipitate a move to insourcing
The type of tasks – manual, repetitive and transactional, that have traditionally been outsourced are also the prime candidates for RPA, especially if those tasks have been standardised within an organisation. Therefore, we predict an increasing number of Finance outsourcing contracts will be brought back in-house as businesses look to retain control and reduce cost through automation. Those contracts up for renewal in 2019 will be prime candidates for this approach.
An example of where we have seen this trend deliver significant benefits for our clients is accounts receivable. A typical customer utilising RPA to match payments to invoices, now completes the process in less than half an hour; replacing two day's work previously delivered by their outsourcing partner in a low cost location.
2. Finance functions will increasingly combine unattended and attended automation
Attended bots work alongside a human employee - a bit like having a robot PA. They undertake (and speed up) repetitive parts of a process when triggered by the individual to do so. For example, a bot could be programmed to undertake the credit checking tasks involved when an individual is processing a sales order. Attended bots can give a good return on investment even when applied to a non-standard process.
Unattended bots work independently, undertaking tasks at any time 24/7. There is huge opportunity to allocate tasks such as journal uploads or posting accruals to reclaim precious time at month-end.
While today we see significant use of unattended automation in Finance, we predict in 2019 organisations will combine attended and unattended bots to optimise the number of processes that can be automated.
3. The lines between AI and RPA will become increasingly blurred
As RPA technology improves its functionality, the tasks that can be automated will become increasingly broad and include more complexity than today. RPA vendors differ in their approaches but are introducing elements that would strictly be termed artificial intelligence or machine learning to enable their RPA solutions to deliver more.
This means that bots will be able to carry out more complex processes within the Finance function. In P2P, for example, they will be able to read and work with unstructured/non-standardised invoices
4. Ongoing investment in ERP systems will decline RPA will increasingly be leveraged as an alternative to additional investment in ERP systems, especially in terms of customisation and building APIs. RPA can execute tasks across multiple software applications at the interface level. There is therefore a huge opportunity for CFOs to realise improvements to employee satisfaction, while also saving money. More agile user interface solutions, enabled by RPA, will replace customisations to large, relatively inflexible systems.
5. The RPA vendor hierarchy will change
I am frequently asked about the key players within RPA. Currently, UiPath, Automation Anywhere and Blue Prism are considered the ‘Big 3’ but I predict that this picture will have changed by the end of the year. The organisations that are most focused on providing a broad and effective functionality (including attended and unattended automation), and who are easy to contract and work with will be most successful.