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Is Process Mining useless? -2

  • Oct 7, 2026 5:12 PM UTC
  • 2 replies
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Rahulstronaut
Level 4
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I hate just how limited Process Mining feels beyond the Process Explorer map.

 

How can PM consultants be expected to identify opportunities to improve a process when the people operating it may have years of experience and a much deeper understanding of its practical realities? What unique information does Process Mining provide that materially changes the decisions those people make?

 

I have been assigned to the Process Mining Team and have been struggling ever since to find its usefulness beyond the process map. Many of the other analyses and dashboards I build seem reproducible using regular reporting and analytics tools, which makes me question what the incremental value of Process Mining actually is.

 

I have also struggled to find case studies that clearly explain the complete chain from a Process Mining analysis to a specific business intervention and then to a quantified business outcome. Many case studies describe the problem and the eventual improvement, but I rarely see exactly how the Process Mining analysis itself led to the decision that produced the improvement.

 

Conformance checking also doesn't make much sense to me in many situations. Why should it matter that the observed process doesn't match the designed approach if the deviation does not result in worse outcomes? A deviation from the designed process isn't necessarily a problem unless there is some evidence that it affects efficiency, quality, cost, risk, or another meaningful business outcome.

 

If I keep asking "So what?" questions for each insight that comes from these tools, many of them don't seem to inform any specific action. Implementation ultimately rests with the business, and the people operating the process are the ones who understand how practical a particular change actually is.

 

So, beyond describing what is happening in a process, I am struggling to see where Process Mining consistently provides enough additional value to justify itself over conventional reporting and analytics.

Rahul

2 replies

abhishek.chatu14
Level 12
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I think the main issue is that you may be judging Process Mining by what it can describe, rather than what decisions it can improve.

Process experts will almost always understand the process better than a consultant. The consultant's value isn't to tell them something obvious; it's to use data to show what is happening at scale, how often it happens, where it is concentrated, and whether it actually affects a business outcome.

1. Observation → Business impact → Root cause → Intervention → Value

For example:

Observation: 30% of invoices deviate from the standard process.
Impact: Those deviations take 5 days longer.
Root cause: 70% come from three suppliers and one approval path.
Intervention: Redesign that approval rule.
Value: Reduce processing time and manual effort.

The Process Mining value isn't discovering that deviations exist. It's connecting the deviation to the outcome and identifying where action will have the most impact.

2. Process experts already know the problems

A business user might say:

“We have suppliers that frequently cause invoice delays.”

Process Mining can quantify it:

“Actually, 8 suppliers account for 64% of all invoice delays, despite representing only 15% of invoice volume.”

Now the business knows where to focus rather than trying to fix the entire supplier base.

3. Reporting can show KPIs; Process Mining can explain the path behind them

A dashboard might tell you:

“Average PO cycle time is 12 days.”

Process Mining can show:

“The 12 days is mainly driven by a specific sequence of approval → rejection → rework → approval, which occurs in only 9% of POs but creates 45% of the delay.”

Now you've identified what to intervene on, not just what the KPI is.

4. Conformance doesn't mean “deviation = bad”

You're right that a deviation isn't automatically a problem.

For example:

Standard: PO → Approval → Goods Receipt

Actual: PO → Goods Receipt → Approval

If those cases are actually processed faster without increasing risk or errors, the deviation might be an opportunity to remove unnecessary bureaucracy, rather than something to fix.

So conformance should ask:

“Does this deviation produce a worse business outcome?”

5. The “So what?” question is actually useful

For every insight, keep asking:

“So what decision does this change?”

For example:

“Invoices are frequently reworked.”

So what?

“Reworked invoices take 7 days longer.”

So what?

“80% of rework comes from one data field.”

So what?

“We can fix that field upstream and eliminate a large portion of the rework.”

Now you have a business intervention, not just an interesting Process Mining finding.

The simplest way I'd look at it

Process Mining shouldn't compete with process expertise or BI.

  • Process experts: Why does this happen and what is practically possible?
  • BI: What happened and how much?
  • Process Mining: How did it actually happen, where is the problem concentrated, what is it connected to, and which intervention is likely to matter?

And if you cannot get from insight → decision → intervention → measurable outcome, then your instinct to ask “So what?” is correct.

That isn't a weakness in your thinking. That should be the standard by which Process Mining insights are judged.

    Rahulstronaut
    Level 4
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    Okay, this was really helpful.

    Rahul
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