Businesses are excited about what Robotic Process Automation (RPA) can do for them.
After all, be it a hotel or a hospital, RPA makes it possible to focus on the customer – and on what matters most. It’s what gives businesses the competitive edge, reduces costs, and accelerates digital maturity.
Increased efficiency of #staff due to #technologies like #RPA is leading to better #CustomerExperience. Here's what one of the largest #hotels had to gain with #ProcessAutomation https://t.co/fsFYKRyMFJ#BPM #Analytics pic.twitter.com/1odZp0nFik
— GS Lab (@_gslab) June 2, 2018
RPA is easy to implement, and in trials and pilot projects, is delivering outstanding results. However, when companies scale up – they tend to build hundreds of bots to automate thousands of tasks.
That’s great, except for the fact that most businesses don’t plan for any kind of infrastructure to support their RPAs.
Given the benefits that RPA brings to organizations, a Deloitte report concluded that RPA will have achieved near-universal adoption within the next five years.
However, the roaring success of the technology raises an important question: How do you make sure you get the most out of your bots?
Getting the most out of RPA bots
“An organization could have hundreds of bots running simultaneously, but over time, one of them might break down, and the business needs to know what has gone wrong,” said Sneh.
Once deployed, companies must track the performance of RPA bots. With one or two bots in play, tracking and monitoring them is easy – but when you scale it across the organization and build a couple hundred bots, you’re bound to struggle.
According to the Deloitte study, RPA is gaining popularity primarily because it helps improve compliance and reduce inaccuracies. In order to consistently deliver on that value proposition, businesses need to be able to track when things go wrong. Failing to do so could result in severe penalties and significant reputational risk.
Further, many businesses get too excited about the idea of automation and all the cost savings it can bring that they forget about the fact that when you’re running a couple hundred bots, you’re going to need computing power.
As a result, bot operations need to be optimized in a way that they not only achieve the goals they’re expected to achieve but also keep ‘additional’ costs on the lower-end as far as possible.
Neglecting this can easily whip your RPA implementation project out of shape, eating up many of the cost-advantages that were initially outlined and promised.
The need for an effective RPA CoE
“Governance, or some form of reporting, maybe even a dashboard can help managers gain visibility into what they need to fix before things get out of hand,” explained Lim.
It’s as simple as Lim says. Getting it done is actually the easy part, once managers and business leaders understand the need for RPA governance.
For organizations with a few bots running routine, non-critical tasks, a dashboard might suffice.
For more serious RPA deployments, businesses could institute a formal center of excellence (CoE) that helps create some sort of structure among the bot workforce and ensures there are strong processes and policies around monitoring and evaluating bots.
On the surface, it might seem like governance has a somewhat tactical role to play in the overall RPA framework. However, that’s far from the truth.
Governance, in fact, is critical to the evolution of bots.
Operational logs the governance function collects can help an AI engine, for example, to help determine how to improve the bots and take them to the next level. Those very logs could also help understand which tasks (and therefore bots) could be merged.
All of these activities could further reduce the computing power, time, and resources required to run the bots, creating more efficiencies and further reducing costs.
There is no question that RPA is disruptive, but it is also a great tool to help achieve immediate cost reduction and process efficiencies. However, to realize the full and long-term value, companies need to build a CoE.