Have you ever been told to get the best possible results with the least amount of effort?
Enter: the Max-Min Principle.
The Myth of Max-Min
You’ve surely heard of it. Everyone has.
Almost no one questions it. Maybe you’re even using it.
Well, it’s crap and it doesn’t work. Because it can’t.
Why?
It misses anchoring.
When two factors like effort and result are interdependent, optimizing both simultaneously is impossible.
If more effort gives you better results, the least amount of effort can’t give you the best results.
Bullshit Management Advice
In management, to reach results, we plan with different inputs:
- Time
- Money
- Work Capacity
And many managers often default to: “Let’s try to get the best result with the least amount of time / money / capacity.”
That’s bullshit.
Realistic Expectations
Consider results and time.
You can either get the best possible result within a specific timeline:
“Let’s build the best product we can within the next six months.”
Or aim for a specific result in the shortest time possible:“Let’s build this well-specified thing as quickly as possible.”
But you can’t say (well, you can, but it’s stupid):“Let’s build the best product we can as quickly as possible.”
A startup launching a new app can either aim for a feature-rich product that takes as long as needed to build, or the best possible version they can launch within three months.
The Ultimate Management Formula
If you like logic (like me), you can translate the Max-Min Principle into a simple formula where output (results) is a function of inputs.
Results = f(Time, Money, Capacity)
You can either maximize your Results (output), requiring a certain amount of Time, Money and Capacity as input.
Or you can minimize your Time, Money, Capacity (inputs), resulting in a certain Result as output.
You can’t do both simultaneously.
Now, what many actually mean when they apply the Max-Min Principle is something like this:
”Give me the best input/output ratio.”
The best bang for your buck.
Mathematically, that’s an optimization function. But without knowing exactly what a change in Results and Time, Money, or Capacity is worth, optimizing this function is guesswork.
How valuable is a 20% better result? What’s the value of saving six weeks vs. saving $100k vs. freeing up two employees?
Who knows. And that’s a manager’s job to determine. Not the team’s. But many managers avoid it because it’s incredibly challenging.
The Practical Solution Most Miss
So what can we do?
Anchoring.
You set a for either output or input and try to achieve this target optimally. You your approach to one side of the equation.
When you must achieve a particular level of result:
→ Anchoring to Output
“We need to achieve this [very well specified] result. Get there as quickly / cheaply / efficiently as possible.”
Implication: You might need to add more time, money, or people.
When you are heavily restricted with your time, money, or capacity:
→ Anchoring to Input
“We have this amount of time, money, and people available. Let’s built the best thing we can with that.”
Implication: You might have to accept a suboptimal result.
Conclusion
The management magic lies in knowing which approach to take given your constraints and business goals.
Next time you’re facing a Max-Min situation, ask (yourself): "What's our anchor?"
