Process Audit: How Process Mining Enables a Smoother RPA Roll-out

Advancements in artificial intelligence and machine learning have allowed a growth spurt in the RPA world. Yet, RPA doesn’t work on every business process.

Before bots can be deployed, you need to have a firm handle on the “as-is” state of the processes to be automated, requiring what’s known as a process audit. Why? Because some processes will always require human judgment or input, and you need to distinguish them from those that are automation ready.

Process Mining helps you run this process audit initiative and get processes sorted into the right category.

Why Do You Need a Process Audit before Automation?

First, Transparency

The bottom line is that RPA can’t fix a bad process.

Automating a chaotic, ad hoc process with side processes and inconsistencies doesn’t make a lot of sense, does it? The process will still be a mess — just an automatic mess. None of the efficiency gains will be seen and the ROI will be non-existent.

RPA must be applied selectively, as automating the wrong processes can lead to hiccups, redundancies, and even complete process failure.

The tricky part is that these inconsistencies are often hidden behind layers of employees or spread across departments.

The complete transparency offered by Process Mining allows you to see through the clouds and get straight to the root cause of any non-conformities so a solution can be developed.

Use Process Mining again to test the reworked process and ensure standardization is achieved before the implementation of RPA.

Second, Identification

Process Mining and the interactive process map it provides are ideal for selecting the right processes for automation.

By highlighting inconsistencies, workarounds, and side processes, you can see whether a process is indeed ready for automation, if there is work needed to bring the process into compliance, or if there is simply too much human interaction involved.

Once the selected processes are sorted into these three categories, determining which processes to begin with becomes much easier.

Aspects of an automation-ready business process include the following:

• Consists of finite steps that are easily reproducible
• Is data-driven
• Is rules-based and standardized
• Requires little intuition or creative thinking (the more monotonous, the easier to automate)

Simply put, RPA loves a good standardized process.

How To Select the Right Processes for RPA?

Process audits are how you can get a full picture of the processes at work in your organization. To see the entire picture, you’ll need to see the ad hoc side processes, redundant steps, and gaps that exist in the real-world process.

Process Mining is the right solution to achieve this level of visibility.

To return the highest ROI possible, RPA software relies on 3 process characteristics:

Data-driven: RPA works best on processes that involve large amounts of data.

Repeatable: Automation thrives in situations where the steps of a process are easily repeatable. These are the processes that workers consider mundane and/or a waste of their time, and errors can quite often creep in.

Rules-based: Bots are trainable like humans. However, they do better when the process they’re given is based on clearly defined rules.

Conducting a full process audit before your RPA initiative gets underway will help determine how well all prospective processes fit these three criteria, and weed out those that are just not good candidates.

Then, using the data generated by Process Mining, you can determine which processes are the best candidates in their as-is state, and which need some reworking to optimize them for automation.

And finally, once you have these remaining processes sorted appropriately, you can use Process Mining again to verify that the adjustments did indeed bring the processes in line with one another, and that they meet the right set of criteria to be considered standardized and ready for automation.

Could you pinpoint right away which processes are ready for automation in your organization or would you need to run a process audit? Let us know in the comments or try our Process Mining solution first.

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The article was originally published on the Minit.io blog.

Photo by Jeremy Bishop on Unsplash