While preparing the RPA implementation plan, the first thing to consider is the major challenges that would find its way in technical implementation.  While the use of workflow and decision-making technologies has grown over the years, new challenges are arising.

Challenge 1 – Seamless Integrations and Dependent Processes

One emerging concern is what happens when there are dependencies among automated activities, such as activities performed by bot 1 that triggers those performed by bot 2? In some instances, implementations required more resources and time than expected, especially in large organizations. The solution lies in the tactful RPA design and integration sequence.

Challenge 2 - Ownership

Who will own RPA implementation is another important consideration. Depending on the services institution involved, an automation initiative may live in the information technology (IT) department or the group that owns the process being automated. Regardless of who technically owns the effort, the success of RPA implementation will depend on seamless integration between IT and the business function, and the consistent involvement of those two groups. Finally, once RPA is implemented, ongoing bot management will require clear definition of how issues will be handled to achieve timely, effective resolution. Also, a defined set of performance metrics, such as key performance indicators (KPIs), is critical for measuring the ongoing effectiveness and efficiency of RPA.

Challenge 3 – Identifying right processes and qualifying them for automation

It is not always possible to automate all the processes completely and the ROI of automation also differs from process to process. It is important as well as challenging to identify right set of processes for automation. Also it is important to consider where the cognitive automation can be used. The dealing with unstructured data has been a challenge for the industry and remains to be seen how it can be dealt with using cognitive automation as well as smart tools. Business analysis of processes from RPA perspective and process mining can help in overcoming this challenge.