Why Do We Need To Talk About Automation?

Originally, many saw it as a potential career limiting advancement due to our role’s susceptibility to automation, but now it’s seen as an opportunity for software to help humans enrich their roles, by performing repeatable computer and business processes – things that we just don’t want to do anymore.

Manual double entry, high-volume transactional work, transferring of data from one place to another, the processing of data to create business intelligence and reporting. These are all tasks that can be made more effective and efficient with the use of automation tools.

So, why isn’t everybody automating?

The early hype around automation and RPA services was huge. 

RPA, or robotic process automation, is the technology that allows software to mimic human interactions with a computer in order to perform repeatable tasks and processes. Back in 2017, I compiled a list of RPA service and software companies, numbering close to 50 different organisations across the globe. One of the more established general automation companies grew its revenues that year by 629% and has continued to grow its global share to this day. 

The initial marketing of these RPA services was based around replacing humans with robots; transforming entire business processes with robot armies supervised by a greatly reduced human workforce. The business case was highly attractive from a cost reduction perspective.

But it wasn’t that easy.

Although some processes are ideal for automation, sometimes the business case just didn’t stack up. The ambition of end-to-end transformation quickly met with the reality of the declining value of requirements and benefits, and good old Pareto’s law, meaning the full transformation was not required or probable.

The cost-benefit analysis showed that some tasks just aren’t worth automating, and even heavy data collection and data processing tasks would be capped at around 60% automatable.

The human in the middle

This led to humans and robots sharing the process, not the robot replacing the human.  This was good news for transactional teams. They saw that their roles could be improved with automation, and they would being included in the ongoing process. They were not going to be turkeys voting for Christmas.

This gave us an opportunity to rethink the hype of end-to-end transformation. Big, wholesale changes and huge cost saving programmes are great for selling consultancy and software licences. In reality, the practitioners started working on tiny automations, understand that getting better 1% everyday leads to an exponential improvement over time, rather than waiting for external heros.

Tiny automations focused on narrow use cases, which were easier for existing staff to support, as they could devote small amounts of time to these projects and could see improvements to their roles without any risk to their job.

The tiny approach also gave people time to understand what automation actually is, how to go about automation and what other people were creating in the accounting and finance industry so they could do the same. It felt easier to bring in tiny automations over a period of time that focused on the specifics of accounting and finance, than focusing on a Big Bang end-to-end transformation.

And with a skills gap in the market, learning on the job was super important to the eventual success of these automations. The majority of people will be learning automation for the first time, even the huge RPA service providers. These providers are using newly trained RPA engineers and working with fast-evolving technology, so even the ‘experts’ were not working in an established industry with an experienced workforce.

Narrow use-case automation

The ambition and reality of end to end automation remains, but in many business functions where there is a lack of RPA knowledge, tiny automation and narrow use cases are the chosen approach to improving process efficiency and effectiveness. 

Exponential maths note to self; tiny over time equals big!

Although these narrow use cases were less sexy and less significant in the growing market of RPA services and software, these narrow use cases were creating real benefits for the teams who employed them.  Month-end reconciliations and month-end reporting was an obvious place. A high-volume process and a highly standardized process allowed RPA tools to be applied, speeding up the cycle.

Right place, right time!

This speeding up of the process created time for the team when it was most needed – during month end.  A pinch point for accounting and finance teams when they should be applying expertise and managing stakeholders and generally meeting the businesses demands for more information and more decision support.

Automation speeds up the cycle during month-end and allows us time to work in the business rather than in transactional processing. It allows us to apply our full skills and expertise, and maybe most importantly, it allows us to focus on the tasks that are most human, the tasks that are more motivating, and the tasks that are most difficult to automate.