Process Discovery – Commonly Faced Challenges

[PratyushGarikap]

Whether you are just about starting with your RPA journey or you are well along the way, Process Discovery has a key role to play in ensuring visibility and sustainability of your project pipeline. Incidentally, Process Discovery is also the most common stumbling block most enterprises face in their endeavor to drive digitization within their organizations.

If you are in early stages of RPA adoption, you would most likely have selected simpler processes – and rightly so – for automation because your goal is to prove that RPA works for your organization. Once this proof-of-concept phase is over and you have established a RPA COE, you now have to deliver financial and/or non-financial value back to your organization. And this is where the first challenge arises – where to find processes for automation pipeline?

If you have managed to get over this hurdle and have a pipeline of opportunities available with you – then congratulations! You have overcome a challenge that over 50% of enterprises struggle with. But this is no time to stop and smell the roses. Once you have the pipeline, you need to quickly identify what are the success metrics that will define the value from each of these opportunities. Herein lies the second challenge – what are the ROI metrics to measure success of automation projects? 

A fast follower to the above challenge is how to prioritize/sequence the automation projects? Rationally, one would sequence their projects based on the impact it can create and the urgency it poses. However, depending on your COE’s structure and how it engages with rest of the organization, sequencing projects can tend to be a tedious affair. There will always be the possibility of conflicting priorities vis-à-vis limited resources, and therefore prioritization needs to be managed and governed carefully.

The prioritization itself could be for two different reasons – (1) prioritize the opportunity for Process Analysis, or (2) prioritize the process for build. The latter will move into a delivery lifecycle approach which should be highly predictable and have a project management rigor to ensure high build quality. If it’s the former, then the question simply is how to do process analysis?

Author's Note: There are two prevalent approaches in the industry to conduct process analysis – either conduct Process Assessment sessions to analyze the process manually; or use Process Mining techniques. The goal of both techniques is to assess automation feasibility, implementation effort and potential benefit. It’s safe to say that jury is out on which approach is better, but we believe that both approaches have their merits and limitations.

While we certainly have a point of view on the above challenges, we would love to hear from you. Have you faced any of the above challenges? If yes, how did you overcome them? Are there any other challenges you may have faced that you can share with us? If you prefer writing to us directly, please email to pratyush.garikapati@blueprism.com.