RPA is one of the major players in business digital transformation, and RPA adopters have measured its success in numbers. However, in order to maintain and manage a successful RPA solution in your business, you need to measure important post implementation KPIs which can be difficult to identify.
In this article, we identify the 5 most important steps to measures after solution implementation.
1. Measure the ROI after the initial RPA implementation
Measuring RPA’s impact helps elevate the role of the implementation team, builds an appetite for further productivity improvements and encourages the team to identify areas where they can improve. Though it is complicated to do a thorough A/B test with process automation, looking at output and size of related teams before and after the RPA implementation will give a good idea about the impact achieved with RPA.
Vendors claim significant KPI improvements:
- IBM commissioned a third party, Forrester, to examine the ROI of IBM’s RPA implementation in a Brazilian credit union. The study was a projection of a three-year period, with these findings:
- Thanks to RPA, the company was able to free up 10% of their staff in the first year, 50% the following year, and 80% in the third year, from manual work.
- The growing percentage of the staff dedicating their time to more value-driven and strategic tasks brought about $740K to the organization.
- The RPA technology was able to proactively signal 2% (worth $225K) of the fraudulent activity within the company.
- Over the three-year sample period, the net present value (NPV) of RPA adoption was estimated to be $594K, or a 124% ROI.
- The added productivity value of the RPA technology, coupled with the avoidance of fraud-induced losses, and the general benefits of the software itself, meant the solution paid for itself in 16 months.
2. Keep track of already automated processes
Long term IT investments can sometimes be planned in isolation of capabilities developed by non-tech teams. And RPA gives non-tech teams a strong tool to automate their tasks. Therefore it is important for tech and non-tech teams to collaborate and ensure that automations completed with RPA are not re-programmed in applications. Scarce technical resources would be better deployed in building changes to applications that can not be completed by RPA tools.
3. Launch an RPA center of excellence
Once you have proved the benefit and viability of RPA projects, you need to consider how you can launch new RPA projects effectively. Most large companies choose to have RPA centers of excellence that help teams launch, audit, and improve RPA projects. The crucial thing here is ownership. The business units themselves must be responsible for RPA installations or else center of excellence teams will find themselves responsible for processes they do not completely understand. Center of excellence teams should focus on aggregating best practices and helping teams ramp up quickly.
4. Manage RPA impact on jobs and existing teams
RPA will inevitably lead to predictable redundancies as bots take over more work from humans.
For all/most employees, once most of their responsibilities are automated, new responsibilities can be assigned. The good thing is that you will know in advance which personnel will be redundant which gives managers time to identify new roles for the personnel and train them for the transition. However, this can not be a departmental effort. HR should coordinate the new assignments and managers across the organization should be motivated to take on employees that have become redundant.
As with any industrial revolution, post-AI world also makes some formerly valuable skills redundant. Workers who are specialized in automatable tasks will inevitably be let go if they fail to improve themselves. Though hopefully such cases will remain rare, it is critical for management to handle those cases as professionally as possible. People need support from their old managers to continue their professional lives in the best way possible.
5. RPA Training
Since RPA bots need to be programmed, there’s a whole industry of RPA courses and tutors. If you are aspiring to get a job programming RPA software solutions, think twice before you pay for any training. RPA companies are doing their best to make sure that their solution is the most popular among developers so there is quite high-quality free training and community support online. I would first take some free courses and then explore paid alternatives after getting familiar with the products.
5 Ways to Measure RPA Post Implementation Success article is originally published on AIMultiple.