Robotic process automation (RPA) is an easily accessible and low-cost-for-entry solution to automate task-level processes. Used smartly, RPA technology can bring about significant cost reductions by eliminating the need for expensive manual labor on highly repetitive, high-volume tasks. Implementing a successful RPA solution lies in selecting the right processes. This places heavy emphasis on evaluating, rating, and prioritizing process candidates against criteria that will enable success.

Because RPA technology isn’t suited for all processes, candidates must be evaluated against attributes that showcase RPA’s key strengths. A quick and simple means to creating a valid process pipeline is to utilize a scoring mechanism that objectively rates how well each process candidate fits the attribute. Shown below are a list of various criteria that define a good RPA process candidate.

Attribute Description Scoring
Rule Based Tasks that have clear instructions for how they are processed and that use clearly identified and predictive business rules are great candidates for automation. Those that do not conform to this attribute likely require more human judgment and greater use of exception scenarios, making them not ideal for RPA technology.

For processes that are mixed or heavily judgment based, consider applying other improvement methods first (LEAN, Six Sigma) before applying RPA.

Judgment Based = 1

Both Rules and Judgment = 3

Rules Based = 5

Structured, Readable Input Processes that pull standardized and structured electronic data sets are easier to automate than those that don’t. Bots have a much easier time reading from Excel spreadsheets, Word documents, emails, presentations, and PDF files than from scanned documents or even manual input. Not only are electronic inputs preferred but they should also be standard in nature. Processes that are triggered by inputs that vary are not ideal candidates. Unstructured Input = 1

Mixed Input = 3

Structured Input = 5

Standardized/ Low Exception Rates Standardized processes with clear business rules (and little to no human judgment) have low or no exception rates compared with those that are less standard and defined.

Processes that experience high exception rates should be analyzed to determine why frequent exceptions are occurring and how they may be more streamlined to reduce them before applying RPA technology.

Not standard/high exceptions = 1

Partly Standard = 3

Standardized/low exceptions = 5

High Volume Processes that have a high frequency of occurrence, as well as high transaction volumes, are ideal candidates for RPA as the technology will greatly reduce (or eliminate in most cases) human error involved with manually processing the sheer volume. Reducing error also reduces risk.

Medium- to low-volume processes may also be good candidates for RPA but may not return as high return as those with higher volumes.

Low Volume = 1

Medium Volume = 3

High Volume = 5

A less subjective scoring mechanism for volume is ROI.  Larger volume processes will likely have higher ROIs than those with lower frequencies/volumes.  Those with higher ROIs should have higher priority.

High Error Rates High-volume, manual processes are prone to high error rates usually resulting in rework that could be reduced or eliminated with RPA technology. Low Error Rates = 1

Medium Error Rates = 3

High Error Rates = 5

Manual Rekey Frequency Processes that require the rekeying of data across multiple systems are ideal candidates for RPA technology. No Rekey = 1

Some Rekey = 3

Frequent Rekey = 5

Unchanging Processing Methods Processes whose methods will change in the short term (or frequently) are not good candidates for RPA technology. Instead, look for processes that remain stable and consistent in their methodology, architecture, and inputs. Changing Process = 1

Stable Process = 5

Low Process Adherence While processes may be standard on paper, resources may not always adhere to them as closely as intended. Processes that are not adhered to, especially those involving internal or external controls, make great RPA candidates. Total Adherence = 1

Mixed Adherence = 3

Low Adherence = 5

System Changes If automating a process would result in significant system changes, it may not be as a good a candidate as one that requires fewer system changes or integrations, due to the cost involved. Significant System Changes = 1

Low/No System Changes = 5

A cost/benefit assessment may be a less subjective measurement for this metric.

Customer Satisfaction Processes that more greatly affect customer satisfaction are better candidates than those that have little or no impact. No CSAT impact = 1

Some CSAT impact = 3

Significant CSAT impact = 5

Once process candidates have been assessed, they can be ranked by total score with those scoring the highest put at the top of the list for automation. While the above is an extensive list of attributes to consider, each organization may add their own based on the nature of the business and strategic imperatives. Once a process is selected, you should consider building a business case that more accurately reflects the potential benefits of automation.

RPA isn’t a one-stop answer to automate all tasks within your organization, however. For example, processes that require human judgment and intervention would best be automated using a robust BPM platform, while other complex, non-repetitive processes may not be automatable at all.

In summary, using the criteria listed as evaluation tools to determine RPA suitability will enable any organization to feel secure in knowing the processes chosen are very suitable for automation using RPA technology. Utilizing a business case approach will then allow your organization to rank suitable processes in order of their return on investment. When creating a business case, be sure to consider all of the applicable costs the current state process incurs against all of the costs and benefits of an automated process. Once obtained, a simple ROI calculation can easily determine a prioritized ranking of process candidates.