How to Use Process Mining to Uncover Automation Opportunities

How we think we complete our work is often different from reality, and the same goes for the when and the how frequently.

Think about it – if I asked you how much time you allocate to a specific task each week, it would probably be difficult to give a straightforward answer. Many tasks vary from one day to the next, and outliers may come to mind. Now, if I asked a team of 20 to guess how long a task takes or how often they complete a function, you can probably imagine just how many more variations in estimation I would receive.

This is a problem that organizations run into regularly when planning for digital transformation. Human bias can severely impair an organization’s ability to optimize its processes.

Eliminate Bias in Your Processes & Findings

That’s why process mining is so appealing to organizations undergoing transformation, and why companies like SAP and UiPath are acquiring and developing functionality to match industry leaders like ABBYY Software.

Using data, process mining lets us uncover the undeniable truth regarding the who, what, where, when, and how often of process-driven questions.

Let’s dive into 3 examples of organizations that have used process mining to eliminate bias in their processes to further optimize them.

3 Examples of Process Intelligence Customer Success

1. Process Mining in Claims Processing 

Using only a traditional discovery process, one organization thought they had automated every step they could in their complex claims process. After a closer review of their results, they found they recognized only 20% automation, despite anticipating a value closer to 70%.

The customer then used process mining to analyze the data related to their claims process. In doing so, they realized that there were 2,000 different variations of a claim running through their system and process. Before using process mining, their team had identified only ten variations.

Not every one of those variations had high enough volume to be managed with automation. However, the link between what they had identified and what the data brought forward as automation candidates were substantial.

2. Task Mining in Financial Services 

One Financial Services organization used Task Mining to uncover process bias impacting their automation efforts. Employees indicated that a given task was completed within two days of month-end, and that it only took them two days to complete it.

What the data showed was different. The reality was they started the process within two days of month’s end, but the process took five times as long as the employees indicated. Were the employees lying? Not intentionally, but technology tells us the reality when our human recognition is inaccurate.

3. Conversation Mining for Enhanced Efficiency in Email Communications 

Another organization used conversation mining to analyze 150,000 emails. This technology was able to identify insights like:

• Approximately 60 percent of people who were CCed on emails never took any action.
• Only 25 percent of all emails received were forwarded to the appropriate endpoint.

When we can recognize these types of redundancies and change our behavior, we can remove manual work like email deletion and forwarding while simplifying processes.

A quick disclaimer, data cannot do it all.

Process Mining cannot answer questions like:

• Why does a process happen?
• What happens outside of a system?
• Why has the team developed a workaround?
• What are the desired outcomes?

In these cases, we can combine process mining with consultations with your digital transformation partner. With this winning combo, you’ll be able to see all facets of your process and come up with a holistic solution to the problems at hand.

Want to learn more about process mining, consultation, or both? Drop a question or comment in the chat below to start the conversation. We’d love to hear from you.

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