When to quit

When to Quit

You have probably heard the maxim, “Winners never quit, and quitters never win.”

But is that really true? Management thought leader Peter Drucker said, “The most dangerous traps for a leader are those near-successes where everybody says that if you just give it another big push it will go over the top.” 

The “Winners never quit” maxim is typically accompanied by inspiring stories of entrepreneurs and artists who received hundreds of rejections and slogged away in anonymity and poverty for years, but they never quit, and eventually became rich and famous.   

The success formulas are similar: Visualize the future you want. Set lofty goals. Copy the strategies used by the winners. Work hard. Put in 10,000 hours. Track your progress. Stay focused. Keep believing. Never quit. Eventually, you will win.

These stories blind us to the cognitive error called “Survivorship Bias”, which is our tendency to glorify the survivors who prevailed, while ignoring the majority who failed. 

Many times “the failures” followed the same success formula as “the winners”, but they were not so lucky.

I learned the term “Resulting” from professional poker player Annie Duke in her book “Thinking in Bets”. When we get a “good result”, we assume that we must have made a good decision or that we are highly skilled. Conversely, when we get a “bad result”, we assume that we must have made a bad decision, or we lack the necessary skills. 

Good result = I made a good decision. I rock.
Bad result = I made a bad decision. I suck.

Not so fast. “Resulting” discounts the role of statistical probabilities and luck.

Professional poker players know the mathematical probabilities of each hand they are dealt and place their bets accordingly. But making “good decisions” does not guarantee a successful result in a card game. A novice poker player can be ignorant of the “right” way to play, get a string of lucky hands, and beat a professional poker player on occasion.

Whether you win or lose, luck always plays a role. 

Nassim Taleb in his book “Fooled by Randomness” argues that we shouldn’t just look at the one “history” that actually happened, but all the other “histories” that could have happened but didn’t.

Ask yourself, “If the same scenario was replayed 100 times, how many times would you win?“

If the odds of winning are not in your favor, quitting can be the wisest choice.

When to quit?

Imagine you choose one of the following scenarios:

– Launch a new product or service
– Open a branch office in a new geography
– Hire a new senior manager
– Pursue a career with a “fat tailed” distribution (where a tiny % of outliers capture almost all the success, e.g. venture backed startups, authors, actors, musicians, content creators) 

If success is eluding you, how will you know when to walk away?

Here are 2 concepts that my clients find helpful:

Fire Bullets, Then Cannonballs.

I learned this concept from business author Jim Collins in his book “Great By Choice”. He states that we should validate our assumptions before we commit serious resources.

First, you fire bullets. You conduct low-cost, low risk experiments to figure out what works and what doesn’t work.

If you fire a bullet that “hits the mark” – where you get data that validates the direction you are exploring, then you fire the big cannonballs. You concentrate your resources and double down in that direction.

But if you fire bullets, and they don’t hit the mark, you make a course correction, or find a new solution.

In other words, if your bullets don’t hit the mark, you quit investing more time, money, and energy in that direction. You try something else.

Kill Criteria (Stop Loss).

Not only have we been conditioned to believe that “winners never quit”. There is the psychological hook of “sunk costs” – the amount of time, money, and energy we have sunk into the pursuit. 

The pain of losing makes it tough to walk away from things we are emotionally invested in.  Let’s face it, how many resumes brag about the projects you pulled the plug on? Product lines you discontinued? Customers you fired? Your “stop doing” decisions are where you demonstrate true strategic leadership.

It goes against human nature to walk away, so to protect yourself, set “Kill Criteria” or “Stop Loss” rules in advance that force you to make a wise decision at the appropriate time. Annie Duke wrote about this in her book, “Quit: The Power of Knowing When to Walk Away”. 

If you don’t set Kill Criteria in advance, you can be tempted to hang on and keep trying, hoping that things will turn around. This can set you up for an even bigger loss or failure. 

Example 1: Mount Everest Climbers

Climbers get up early in the morning from Camp 4 and make a push for the summit. The professional mountain guide sets a “stop loss” rule. If you do not make it to the summit by 1pm you must turn back. This rule removes emotion and sunk cost thinking when you are in “the death zone” and oxygen deprived. If you don’t turn back, you risk losing your life. 

Example 2. Professional Investors

Professional investors set automated stop loss rules. If a share price drops to a certain level, they automatically sell at that price to limit their loss to that amount. They don’t hang on and hope the share price will rebound (as retail investors are prone to do). They remove emotions from the decision by automating their decisions in advance.

Example 3. Hiring Managers

If a new employee does not reach an agreed standard of performance by the end of the 90-day onboarding process, the new hire will be removed from the team. I encourage my clients to set performance milestones at day 30, 60, and 90 when onboarding new hires, and make an objective go or no-go decision at the end of 90 days. If the new hire has not clearly demonstrated A-Player performance, cut your losses and recruit someone else (especially when hiring for management roles).        

The best Kill Criteria combine two things: a “State” and a “Date”. 

State (X) = Objective measure (or milestone) that you either achieved or missed
Date (Y)  = By when

Examples:

Milestone: “If we have not achieved X (result) by Y (date), we will quit.” 

Resource Cap: “If we have not achieved X (milestone) after spending Y (time, money, effort), we will pivot.”

New Venture: “If this new (product, service, geographic location) does not achieve X (revenue, market share) by Y (date), we will pull the plug.”

Career: “If I am not earning X (monthly income) as a podcaster by Y (date), I will get a corporate job.”  

Define your Kill Criteria in advance so you are not tempted to second guess yourself later.

There is an old country song called “The Gambler”, by Kenny Rogers. The chorus goes: “You’ve got to know when to hold ’em…know when to fold ’em…know when to walk away…know when to run”

Winners know when to quit.

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Until next time…
Stephen