Process Discovery Best Practices: A Business Analyst’s Perspective
By, Michael Gispert – Accelirate Automation Business Analyst
Selecting the first set of processes in an RPA journey can be daunting. The high-overhead costs add pressure to select processes that give an incredible amount of ROI that justify the investment. This leads to rushed projects that are high-risk and at the end of the development do not meet business expectations. As a trained automation business analyst, I am able to guide clients through a structured methodology that helps them avoid pitfalls when selecting processes for RPA. For organizations who may not have BAs available and do not have a stable process discovery practice in place, below are some common scenarios we run into and some advice for how to resolve them.
Look Out For Processes That Are Large In Scope
Large processes with multiple branching scenarios that are long and arduous are not good candidates for beginning RPA initiatives. Often what happens is the development timeline is underestimated, and the resources required will eventually push the project overbudget.
Companies can avoid this by selecting scenarios based on volume. Developing the top two or three scenarios of a big process can allow a business to see FTE savings and lay the groundwork for improving the automation to handle more in the program’s second phase of automation.
Avoid Processes That Require Human Communication To Perform
Occasionally organizations are presented with a process that is repetitive but requires a lot of human communication to complete it. What companies forget to consider is that defining business rules to replicate human communication is tedious and requires a lengthy analysis timeline.
The general rule of thumb is that most RPA initiatives should take about 1-2 weeks of analysis time in order to submit an initial draft of the Process Design Document (PDD). A business analyst can gauge analysis time by determining the number of unknowns they have after the first meeting with a Subject Matter Expert (SME). If an analyst finds themselves with more questions than answers, it is a clear sign that this is not an ideal process to automate in the early stages of an RPA program.
Focus On Processes That Can Be Automated Only With RPA Tools
Machine Learning, Optical Character Recognition (OCR), and similar technologies can be fruitful and provide innovative solutions within process automations. These solutions can be extremely enticing to pursue as they offer a high amount of ROI, however, adding in a secondary technology early on is an ambitious decision.
When beginning an RPA initiative, quick wins are the best way to prove to stakeholders that automation is worth the investment. Adding in technologies that supplement RPA such as OCR and Document Understanding is not impossible in the early stages, but they require longer development times, and are far more complex. The risk here is that if they don’t work out or take too long, its likely a young program will lose support from the executive board based on a lack of returns. Any process that requires a Machine Learning, or similar, component is labeled as “high complexity” within the context of process automation. Not only does it require more resources to tackle it, it extends analysis to two-three full weeks and increases development to at least 12 weeks before the automation is ready for testing. As a young program, save these processes for a later date. Machine Learning and other smart technologies enhance ROI substantially, and it is a mistake to not consider implementing them, however, do so once your program is in a more mature state. Selecting processes that will present similar ROI but do not require external technology will put your enterprise in a less fickle position and put bots into production far sooner.
Process Discovery is an important part of the automation journey. Knowing what to avoid is the best way for a young program to advance into a mature and strong automation initiative. For more information on Process Discovery or automation business analysis training, contact us at email@example.com.