The Certainty Tax - When Going Wrong Becomes Predictable

THE LOW EFFORT ADVANTAGE

CERTAINTY WEEK • ESSAY 03

When going wrong becomes predictable

Why uncertainty creates anxiety for customers, avoidable work for operations—and a hidden penalty on loyalty and profit.

By Stuart Corrigan

9-minute read

Every Monday to Friday, I have the same routine. I’m up at 4:45am. Cardio at 6am. Then breakfast at the gym café. That’s it. And yes, I’m habitual, pernickety and tired in the mornings. It’s called being human. 😂

I order roughly the same breakfast every day. An omelette. No greens. A bottle of water. And, most importantly, coffee.

One morning, there was a new guy working behind the café bar. My omelette arrived covered in cress. I’d specifically asked for no greens. Who wants cress on an omelette? Seriously. He forgot my water. Then my coffee arrived 30 minutes later—after I had chased him twice.

Yes, yes. Champagne problems, Stuart. But then it happened again. And again. Every time this particular guy was working, something went wrong. Eventually, I started looking for him before ordering. If he was behind the counter, I went somewhere else.

It wasn’t really about the cress - though who wants cress with their eggs!

The café had trained me to expect failure.

Bad news is stressful. Not knowing can be worse.

Researchers at University College London conducted a fascinating experiment involving electric shocks. Sometimes participants knew they would receive a shock. Sometimes they knew they wouldn’t. At other times, there was only a probability that the shock was coming.

You might reasonably assume that people would be most stressed when the shock was guaranteed. They weren’t. Stress peaked when there was approximately a 50% chance of receiving it. When people didn’t know what was going to happen, the uncertainty itself became stressful. The researchers observed it in what participants reported. They also saw it in physiological responses including pupil dilation and skin conductance.

Bad news is stressful. Not knowing can be worse.

That matters enormously for service organisations. When customers cannot predict what will happen, they pay a psychological price. They think about the problem more. They check. They chase. They call. They escalate. They prepare themselves for failure. And eventually, they may go somewhere else.

That is the certainty tax.

But the customer isn’t the only person who pays it.

The mythical average customer

Let me show you what the certainty tax looked like inside one health-claims operation. Customers were being told that claims took an average of 72 days. That statement was mathematically correct. It was also operationally useless.

72 days THE AVERAGE

12 days THE LOWER LIMIT OF VARIATION

331 days THE UPPER LIMIT OF VARIATION

That is a range of 319 days. The longest experience was more than 27 times the shortest. Imagine telling a sick and worried customer:

“We usually resolve claims in 72 days.”

What does that actually tell them? Very little. No customer experiences an average claim. They experience their claim. Unless, of course, they happen to be the mythical average customer whose claim takes precisely 72 days. For everyone else, the honest promise would have been:

“We’ll settle your claim in somewhere between 12 and 331 days.”

Perfectly accurate. Not especially reassuring.

An average can be mathematically correct and operationally useless.

Customers pay in anxiety. Organisations pay in money.

When a customer cannot predict what will happen, they contact the organisation. They call because nothing appears to be happening. They email because nobody has called them. They chase because a promised date has passed. They complain because nobody seems to own their claim. Each contact creates more work without necessarily progressing the original claim.

In this health-claims operation, between 60% and 70% of incoming demand was failure demand. It was demand caused by the organisation failing to do something—or failing to do it correctly—for the customer. People reopened claims they had already examined. Customers repeated information they had already supplied. Managers handled avoidable escalations. Specialists became involved because cases had drifted.

The customer’s uncertainty had become the organisation’s workload.

And that creates a brutal cycle:

→ Uncertainty creates contact.

→ Contact consumes capacity.

→ Reduced capacity creates delay.

↺ Delay creates even more uncertainty.

The organisation then hires more people to handle the additional demand. Costs rise. Everyone becomes busier. But the original work doesn’t necessarily move any faster.

The organisation is paying people to manage the consequences of work it has not completed.

Then the customer leaves

This isn’t merely an efficiency problem. It’s a loyalty problem. Accenture surveyed 6,754 insurance customers across 25 countries. It found that 31% were not fully satisfied with their recent home or motor claim. Of those dissatisfied customers, 30% had already switched insurer. Another 47% were considering switching. Settlement speed was cited by 60% of dissatisfied claimants. Accenture estimated that poor claims experiences could place as much as $170 billion in global premiums at risk over five years.

That is the certainty tax expressed commercially.

The customer pays it through anxiety and effort. The organisation pays it through additional contact, consumed capacity and disappearing premiums. And losing customers has a disproportionate effect on profit. Research reported by Harvard Business Review found that acquiring a customer can cost between five and 25 times more than retaining one. It also reported Bain’s finding that increasing retention by just 5% can increase profits by between 25% and 95%, depending on the business and industry. That doesn’t mean every insurer improving retention by 5% will automatically increase profit by 95%. But it does show something important:

Small changes in retention can create disproportionately large changes in profit.

The certainty tax is therefore paid four times:

1 - More failure demand as customers chase.

2 - Less capacity because employees repeatedly handle the same case.

3 - Lower loyalty because customers learn not to trust the organisation.

4 - Lower profit as premiums disappear and replacement costs rise.

And still, the usual response is:

“We need a status bar.”

A status bar is not a solution

I can see how this happens. Leaders see customers chasing and reasonably conclude that they need better information. So the company sends more updates. It builds a portal. It adds a beautifully designed tracker.

Claim received. Claim being reviewed. Claim still being reviewed. Claim sitting in precisely the same place it was last Tuesday.

Communication matters.

But a beautiful tracker showing that nothing is happening is merely a more attractive description of failure.

You cannot communicate your way out of variation. The communications team did not create the uncertainty. The operating model did. If one health claim takes 12 days and another takes 331, the primary question is not:

“How can we explain this more clearly?”

It is:

“Why is our process so unpredictable?”

Start with capability

Look beyond the average. Study the complete distribution. Find out why one claim takes 12 days and another takes 331. Follow claims from receipt to resolution.

· Where do they wait?

· Where is information missing?

· Where is work passed between departments?

· Where does responsibility become ambiguous?

· Where does ownership disappear?

Certainty requires somebody who can do more than describe the delay.

It requires genuine end-to-end ownership, supported by the authority to act. And please don’t respond by launching 25 improvement initiatives. Find the largest source of delay and variation. Focus on it. Improve the hell out of it. Measure what changed. Then focus again.

You do not reduce variation with more priorities. You reduce it with fewer priorities pursued relentlessly.

What really changed

When we redesigned that health-claims operation, productivity increased by 2.7 times. End-to-end times fell from hundreds of days to approximately 15–48 days. Lawyer involvement reduced. Complaints reduced. Renewals improved.

Those are important results. But they weren’t the most important result. These customers were sick. Many were frightened. Some were facing the most uncertain period of their lives. They didn’t need another update telling them their claim was being reviewed. They needed the money they were entitled to. And they needed it when it could make a difference.

The most important result was that sick and worried people were paid more quickly—at a moment of acute uncertainty when they needed to know that money was one thing they did not have to worry about.

That is what operational certainty actually means. Not a status bar. Not a reassuring email. Not an SLA hidden inside a management report.

A system capable of doing what matters, when it matters.

It was never about the cress

The café didn’t lose my breakfast order because of one bad omelette. It trained me to predict the next experience. Once going wrong became predictable, I changed my behaviour. Customers do the same thing. They may not leave immediately. They might wait until their claim is finished. They might wait until renewal. But when the opportunity arrives, they remember how your organisation made them feel when they needed it most.

It was never really about the cress or the missing coffee. It was the certainty that next time would be exactly the same...lunch, dinner etc, it was going wrong.

You don’t create certainty by describing an unpredictable system more clearly. You create certainty by making the system predictable.

Remove the variation, and you begin to remove the certainty tax. That means less anxiety for customers. Less unnecessary work for employees. Lower operating costs. Greater loyalty. And better profits.

BRINGING IT HOME

The leadership question

Where is uncertainty being created because the operation cannot reliably complete, explain or own the customer’s journey?

Do not begin with another communication layer. Begin with capability: follow the work end-to-end, expose variation, identify the largest source of delay, and focus leadership attention there until the system becomes more predictable.

Until next week,

Stuart

Sources

• de Berker, A. O. et al. (2016). Computations of uncertainty mediate acute stress responses in humans. Nature Communications, 7, 10996.

• Accenture (2022). Poor Claims Experiences Could Put Up to $170B of Global Insurance Premiums at Risk by 2027.

• Harvard Business Review (2014). The Value of Keeping the Right Customers, reporting research by Frederick Reichheld and Bain & Company