Digital Transformation » The three biggest areas of finance automation failure

The promise of automating routine processes to speed them up and reduce the amount of errors means that robotic process automation (RPA) deployment in finance departments is accelerating rapidly. Gartner expects nearly three quarters of controllerships will be using the technology by 2020.

However, early adopters treating RPA like a traditional IT implementation have run into problems in many cases. Unlike many new technologies, RPA can deliver significant business benefits from the outset but making this happen requires finance leaders to embrace a new more agile mindset when implementing it.

Agile?

Agile is a well-worn term in the technology space, so it’s sensible to define clearly what it means in this context. Broadly speaking, it’s a methodology, a way of organizing teams and working that has proved particularly effective in software development.

It means working iteratively, aiming to deliver a regular stream of small wins. When each small step is complete, refocus and plan the next step, working closely and collaboratively with the end-user of the software to ensure the development is guided by their needs and feedback.

This kind of open-ended and continuous approach often doesn’t sit very well with the mentality of a finance team which tends to prefer defined costs and benefits before making any significant investment.

Yet the irony is that having a more agile approach tends to reduce costs and demands on resources and delivers returns faster in RPA implementation for finance functions. It’s worth looking at the specifics at each stage of a typical RPA deployment process.

The planning and building stage

Many finance departments plan their foray into RPA by looking at automating an entire end-to-end process. The more distinct activities that are marked for automation, the more planning is involved.

This focus on mapping the entire process before automating a single activity will delay implementation significantly and, in fact, create extra work. This is because, once one activity has been successfully automated, the code and lessons can be quickly applied to other similar activities within the same or different processes.

The lessons from implementation can also significantly alter aspects of the entire plan, so initial planning time was arguably not well spent. Instead, it’s better that finance departments start relatively small with RPA by focusing on using one bot against several individual activities. It’s still conservatively possible to see an output gain of up to 10 times, compared with a full-time employee working during the same amount of time

In this way, organizations can reap immediate efficiency gains from RPA, without investing a lot of time planning, standardizing and implementing. Then, when the pilot is working well, they can move to other similar activities and processes in an agile, iterative way.

This means planning and building run almost concurrently, and the plan develops in scope and complexity as bots are successfully built and deployed. As more human time is freed, there will be more resources available to work on more complex automation projects or other judgment-based work.

The testing stage

Relying too much on IT teams and vendors to identify the issues and needs for deploying robots can be a barrier to success with RPA. The people most familiar with the activities tasked for automation need to be the ultimate arbiters of how successful an RPA deployment is, and how it can be refined in further iterations.

Gartner recommends clearly defining responsibilities for RPA activities so that the RPA and IT teams deal efficiently with issues such as setting up and monitoring robot performance, with IT providing support for the underlying technology infrastructure.

Due to the highly iterative nature of RPA technology, and the unique needs of the business it addresses, the most important aspects of managing robotics requires internal steering.

Relying on traditional, fixed finance roles for this purpose is likely to be problematic, and the RPA team should be made up of people with the right skills. Finance department leaders should identify the new competencies needed for successful RPA management, centered around digital process design. These are largely hard-to-train and may need new hiring processes to ensure the right skills for the job.

The benefits of successful RPA deployments within finance include a reduction in errors from manual work and a redeployment of full-time employees to higher value activities, but robots are only as good as the people who design and manage them.

CFOs and finance leaders should start any RPA deployment by ensuring they understand the new agile mindset needed to implement the technology and have the right talent in the finance organization to manage it.