If a machine or production line is overburdened on the shop floor, you catch it within an hour. But you, as a leader, may be running on overload for months. And somehow accept it as reality you have to live with. Until it turns into a crisis you can no longer ignore.
Ever wondered why so many managers never even consider this as a problem?
Even the most intelligent and disciplined leaders fall into this trap because of how we perceive the situation.
In this post, we will explore the biases that shape our perception and prevent us from seeing things as they are regarding our own capacity to lead. Armed with this knowledge, I hope you have sufficient tools to avoid this trap in your own practice.
The contradiction that should trouble you
A production line misses the planned out for an hour, the team lead will be running to see what is going on, if it misses another couple of beats the issue is escalate to production manager. For most manufacturing operations there is a way to know when things are abnormal and a way to deal with that abnormality.
Now imagine yourself on Tuesday morning. You had to postpone the planning of a strategic project because you are dealing with a supplier issue for past two hours. Next, you know, the coaching meeting your direct report needs to be cancelled for this week again, as you need to stay late to finish a report that you could not get to because you were firefighting for most of the day.
You can go on for days or weeks, missing your planned output. But no one is raising the flag.
Why is it that you accept this as normal, but the same on the production floor would cause an alarm? Why does this go unnoticed for your own leadership work?
There is a lack of tools to measure the leadership capacity, but this a much deeper problem than just measurement. The signals are visible, yet we ignore them. We take longer to make decisions, coaching starts disappearing, and the strategic work is permanently deferred. Yet we don’t recognize them as overburden; we rationalize them.
To understand this rationalization, we need to look at it through a different lens. The way our brain works to process information about itself versus about external systems. We need to be aware of the biases that cloud our judgment.
Bias 1: Normalcy Bias
Normalcy bias is a cognitive bias that leads us to disbelieve or minimize threat warnings. Applied to our own personal capacity: It is our tendency to interpret a slowly deteriorating condition as the new normal rather than as a deviation from the standard.
On the production floor, we have standards. When the cycle time creeps by 8%, the effects can be observed in the output of that line. The deviation is clearly observed, without doubt.
But for our own capacity, we have no defined standard. We have never defined what sustainable leadership looks like. So when load increases gradually, one extra commitment here, one deferred task there, individually, it feels reasonable. What should be an overloaded state becomes a new normal.
We can catch that change on the floor because we have standards and measurements. Without that reference point, the deviation is invisible in the leadership process.
Bias 2: Optimism Bias
Optimism Bias, or Unrealistic optimism, is a cognitive bias in which individuals overestimate the likelihood of positive events and underestimate the likelihood of negative events happening to them compared to others.
Applied to leadership capacity, it is our brain’s tendency to overestimate future capacity and underestimate the future demand. It is the little voice that tells us, “Next week will be better”. But that never happens.
Our brain tends to believe that future conditions will be better than our past can justify.
In the production process, this bias shows up in capacity planning. We commit to the production schedule based on the best-case cycle times, with no supplier issues or machine downtimes, and perfect attendance. Problems arise the moment the plan goes into action, as they always do, the schedule fails to keep up, and it becomes a constant firefight.
If you have led operations for some time, you know this reality. You are aware of the variations that will affect your schedule. So you build a buffer into your plan because you know the optimistic scenario is not the operational reality.
The same bias applied to our own capacity is never diagnosed. We make all kinds of excuses to convince ourselves that nothing is wrong. It is just a busy week. Once the product launch is over, we will be back to normal. I will get back to coaching when things stabilize.
But those things never happen. New projects pile up before the previous ones are over. There is new fire to fight before the last one is out. But the Optimism bias keeps us from making the very changes the system needs to stabilize.
Why?
Because the problems feel temporary.
When creating a production plan, we would never accept ‘The next month will be better’ as a capacity plan. But most of us accept it as a personal strategy indefinitely.
Bias 3: The Sunk Cost Fallacy
The sunk cost fallacy is a cognitive bias that leads you to continue an endeavour solely because you have already invested time, money, or effort into it, even when the current costs outweigh the benefits.
Applied to overburden: we continue to absorb everything that comes our way, because stopping it feels like admitting the previous absorption was wrong. We are committed to this path because we are invested in it, even though producing the right outcome is not guaranteed going forward.
On the shop floor, this shows up in equipment decisions. An old machine is repaired repeatedly, thinking it saves us from making a huge capital investment in a new one. Over time, we have invested too much time and money in the repairs to keep it running, so we keep delaying the replacement, which in reality would be an economically correct decision.
An experienced manager will see this and make the right call. Because the decision will be made based on the data that clearly makes the case for replacement.
But when it comes to applying this to our personal capacity, we fail to understand that we even have the problem. For someone who has been absorbing all the work for the past 2-3 years, it is hard to acknowledge that the approach is wrong. The story they’re telling themselves is that they are dedicated to their work, which seems like a much better story to believe in, even though it means a complete failure of capacity.
In investment decisions, data override sunk-cost reasoning. But for personal capacity, there is no equivalent data or model to make a case. The bias runs unchecked.
Why the Shop Floor Catches it, and The Leader Doesn’t
There are three main reasons the production floor detects overburden that the leadership system cannot. These the reasons why the biases are visible on the floor, but not in the leadership process.
- Defined Standard: There is a defined standard, such as takt time or target cycle time. This standard makes the deviation visible, providing a point of reference. Without a standard, it would have been hard to define what is abnormal.
- Measurement Mechanism: There are systems in place to collect the data and process it to make intelligent decisions. This happens regardless of how the operator running a particular line feels on that day. It objectively tells the performance of the process based on actual data, not on what the operator believes is happening.
- External Observer: There is an objective external observer. It could be a leader doing the gemba walk. The quality audit. The daily accountability meeting. There is someone outside the process who can see what someone inside it cannot.
A leadership system inherently has none of these mechanisms in place. There is no defined standard for the sustainable utilization of leadership capacity. No objective measurement mechanism and no structured external observation of the leadership process itself.
The cognitive biases fill that vacuum. The normalcy bias constantly redefines the standard downward. Optimism bias replaces objective measurement with hope. An the sunk cost reasoning prevents the external recalibration that would otherwise correct both.
How do we break this cycle?
How to Overcome Each Bias
Awareness was the first step. Now that you know the cognitive blind spots that prevent you from seeing how your capacity is being eroded, the next step is to identify interventions for each bias and actively prevent the issue from occurring in the first place.
These interventions will follow the same logic as the shop floor. For each bias, we will build a systemic countermeasure that makes it visible before it causes damage.
How to overcome Normalcy Bias:
We need to define a standard for sustainable utilization of our capacity before we need it. We need standard work for the leader that defines what needs to be done. This is the work that determines whether the business moves in the right direction. Once you have a standard, you can then see whether there is personal capacity to do that work sustainably and identify any disruptions that take you away from your path.
How to overcome the Optimism Bias:
We need to plan for a realistic scenario, not an optimistic one. If you have standard work and are measuring your disruption, you will know how much of your work is due to disruption. If the last four quarters each had three to five hours of unplanned work per week, the next quarter too will have this. It will be prudent to have a designed capacity built in as a buffer to deal with these unplanned tasks. This buffer capacity planning will protect you from being overly optimistic.
How to overcome Sunk Cost Fallacy:
We need to separate our identity from our behaviour. We have been asking the wrong question: was absorbing all commitments in the past wrong? This needs to change to: Does continuing to do it produce the right output going forward? That is the same question you would ask if the decision involved a critical machine. The data becomes the basis for the answer. You need to start gathering that data.
Armed with this knowledge, you can start your journey to recover the capacity and direct it to work that matters.
The most important takeaway from this is that you need a measurement mechanism independent of your own perception
