Here’s why your RPA projects keep failing (and what to do about it)

According to recent stats, between 30 to 50 percent of business-wide RPA deployments fail - find out how you can mitigate the risk and reap the benefits of full-scale automation.


Robotic process automation has the potential to revolutionise the way we operate our businesses but without the fundamentals, in place, many of our best-laid plans are destined to fail. 

This is the message from multinational consultancy firm EY, which discovered that 30 to 50 per cent of initial RPA projects fall by the wayside. This is an alarmingly large number when the stakes are so high and the potential gains are so massive – and it all boils down to one overarching issue:

You can’t fix processes that you aren’t completely in control of. 

It’s easy to get caught up in the hype cycle of what RPA can achieve and dive into the proverbial deep end. From a managerial perspective, it’s easy to believe that your processes are simple and two-dimensional, when in fact they are extremely dynamic and unsuited to automation on the ground floor. The truth is, when you don’t understand your processes completely, then digital workers are not likely to solve your problems. 

You need to have a handle on every facet of your business before you can use automation the way it was intended. 

The upside is that a business that adopts RPA correctly will reap significant benefits now and in the future, including cost savings, significant process improvements and a wide-scale redeployment of resources to higher, more value-creating tasks. 

But first, we need to know why RPA projects fail, and how we can stop that from happening:

1. You’ve chosen poorly 

One of the most common pitfalls of RPA is choosing the wrong process to automate. Remember that bots need rules-based structured data to work well and when you choose a process that requires case-by-case inspection or creative thinking, you face an uphill task getting it to work. That’s not to say you can’t automate parts of those processes, but you will still want humans involved to handle exceptions, customer interactions and other complex actions. Remember that the vision for RPA is to automate repetitive tasks and to leave humans to do what they do best, which is thinking logically and laterally to solve dynamic problems.

2. The goalposts change

There is a misconception that RPA and AI are synonymous and that just isn’t true. RPA is for automating tasks that use structured data and don’t deviate too far or too frequently. Digital workers do what you tell them to do and follow your instructions to the letter, making them unsuitable for work that is constantly changing. If you change the flow of a process you need to withdraw your bots and instruct them on the new way of working before redeploying them. If you change the goalposts, don’t blame the bots – make their performance part of your thinking when considering new strategies and workflows. 

3. You haven’t managed expectations

As mentioned before, it can be easy to get caught up in the hype of automation and bite off more than you can chew initially. Because RPA solutions are becoming so widely adopted there is an expectation that they will work straight out of the box but this is rarely the case. Automation, by its very nature, is a very consultative deployment and requires professional expertise to make sure you get it right the first time. 

How to get the most from RPA

If automation is on your radar for the coming year then it’s time to take a step back and get full visibility of your business processes. Once you have identified a structured process – or part of a process – that you can automate, it’s time to look at the metrics that will deliver the most meaningful results over the long term. Think of RPA as a long-term play: it isn’t going anywhere. Build the right relationships and support systems and there is still plenty of time to get ahead of the curve.

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