“If you can’t measure it, you can’t improve it.”
Robotic Process Automation (RPA), an innovative form of business process automation technology that was introduced in 2000, has witnessed immense adoption in past few years. As per a recent survey conducted, 53% enterprises have already started their RPA journey and this is expected to increase to 72%1.
The benefits of RPA adoption are significant and it is no surprise that RPA has become a buzzword in technology space, drawing a lot of interest from industry and investors. With the payback reported in less than 12 months, enterprises have observed improvement in compliance (92%), higher quality / accuracy (90%), enhanced productivity (86%) and reduction in cost (59%)2. While RPA is brimming with potential, a recent research by EY claims that 30-50% of the RPA implementations have failed3 in generating desired outcomes, leading to questions on RPA capabilities. It has also been observed that many CIOs have stalled their ongoing process automations to revisit their decision.
What drove CIOs to significantly invest onto untested and unexplored technology? The untapped potential of RPA to drive valuable business results in terms of higher accuracy and productivity were of course attractive and considered. The limitations of a RPA solution were probably ignored. To measure the results of a solution, it is essential to know the success metrics and this critical parameter was unfortunately set by very few enterprises before selecting a process for RPA adoption. Investing without the possibility to measure benefits is an absolute risk.
This is where RPA Analytics comes in and becomes an integral part of Automation Implementation journey. Integration of analytics with RPA, i.e. the information resulting from the systematic analysis of data and statistics, has now made such investment decisions more informed and calculated. Analytics in RPA can be applied in 3 stages:
So, when should an organization seek analytics in RPA? The pre-requisite for analytics is the data generated for a process. To enhance the value of RPA, quality data must be analyzed using the RPA adoption tools at the right intervals. Analytics will help firms shortlist the right use cases and decide whether to proceed with RPA.
Analytics will not just bolster the enterprise RPA strategy, but also ensure a successful adoption of the latest technology.