The Trouble With Averages

One of the biggest mistakes in process improvement is believing that the average tells the whole story.

For years, process improvement has relied heavily on averages.

• Average cycle time.
• Average defect rate.
• Average wait time.
• Average downtime.
• Average throughput.
• Average customer satisfaction score.

Averages are useful. They help us summarize large amounts of information into something manageable. They help leaders quickly understand performance at a high level.

But averages also hide things. Sometimes, they hide the very problems we are trying to solve.

Imagine a major airline proudly announces that its historical cancellation rate is only 1.22% across all mainline and regional flights. On paper, that sounds excellent. Most executives would probably feel comfortable with that number. Most dashboards would glow green.

Then imagine your last four flights with that airline were canceled. From the airline’s perspective, the cancellation rate is still only 1.22%. From your perspective, the cancellation rate is 100%.

That disconnect matters.

The average describes the system overall. The customer experiences the instance.

That is where many organizations get into trouble.

Averages Create Comfort

One of the dangers of averages is that they create false confidence. Leaders see an acceptable overall number and assume the process is healthy. Meanwhile, pockets of instability, inconsistency, and failure may exist underneath the surface.

• A hospital may report an average emergency room wait time of 28 minutes. However, some patients may wait two hours while others are seen immediately.
• A manufacturer may report an average lead time of five days. However, certain customers may consistently experience delays of two weeks.
• A call center may report an average hold time of three minutes. However, certain times of day may regularly spike to fifteen minutes.

The average smooths out the pain. Unfortunately, customers do not experience the average. They experience individual moments – they experience the pain!

Process improvement professionals must learn to see beyond the aggregate.

Variation Is Often More Important Than the Average

This is why variation matters so much in operational excellence. Two processes can have the exact same average performance while behaving completely differently. One process may be highly stable and predictable. Another may swing wildly between excellent and terrible outcomes. The averages may match. The customer experience does not!

This is one reason why relying solely on averages can lead to poor decisions. When organizations focus only on overall averages, they often miss important patterns hiding within the data. The process may not actually be capable or stable at all.

Instead, you may simply be averaging good days and bad days together.

Getting to the Instance

Strong process improvement requires getting closer to the actual event, not just the summary.

Instead of only asking:

“What is the average defect rate?”

Ask:

• “When do the defects occur?”
• “Who experiences them?”
• “What conditions existed at the time?”
• “What was different about those specific instances?”
• “What patterns emerge when we study the failures individually?”

This is where real understanding begins.

The goal is not to abandon averages entirely. The goal is to avoid stopping there. The average is often the starting point, not the answer.

For example, imagine a manufacturing process with an average scrap rate of 2%. That may appear acceptable. However, deeper investigation reveals nearly all defects occur:

• During third shift
• On one specific machine
• With one material supplier
• During humid weather conditions
• After tool changes

Now the organization has something actionable!

Without examining the instances surrounding the defects, those patterns may never have been discovered.

Context Matters

This is one reason why process improvement professionals should spend time on the process itself.

Data matters … charts matter … metrics matter.

But context matters too.

The conditions surrounding an instance often explain more than the average ever could.

A delayed shipment may involve:

• A staffing shortage
• A system outage
• An inexperienced employee
• A supplier issue
• A poorly defined process
• A conflicting priority

The average delay time will never reveal those interactions by itself. Organizations that become obsessed with summary metrics often drift away from operational reality. They begin managing dashboards instead of processes.

The best improvement professionals learn to investigate the story behind the numbers.

The Customer Lives in the Exceptions

Customers rarely remember the average experience.

They remember the exception.

They remember:

• The canceled flight
• The incorrect invoice
• The delayed surgery
• The defective product
• The support ticket that sat unresolved for days

This is why studying failures at the instance level is so important.

One major defect can outweigh hundreds of successful transactions in the customer’s mind. Operational excellence is not simply about producing acceptable averages. It is about reducing the likelihood of painful exceptions. This requires understanding variation, conditions, triggers, and patterns at a much deeper level.

The Real Goal

In process improvement, averages are useful indicators, but dangerous conclusions. They help identify where to investigate, but they rarely explain why problems occur. Real improvement comes from studying the actual events, understanding the surrounding conditions, identifying patterns within the variation, and reducing instability within the system. While executives may manage averages, customers experience instances.

And improvement happens one instance at a time.

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