Do you have an algorithm for making decisions?
It’s a question I like to pose, as it always gives pause.
Rarely does anyone offer a concrete answer. More often than not, the reply is a motley tray of excuses that collapses at the first sign of trouble.
It’s clear to me those I encounter aren’t alone. On reading the results from a recent survey of business professionals, it emerged that more than half do not have a defined decision-making habit.
No routine.
No process.
No algorithm.
What might surprise some (though not me) is the general belief that most still think they make sound decisions.
I suspect this can be traced to Nassim Taleb’s perspective: we’re prone to confusing correlation with causation.
Or as Annie Duke writes in her book, Thinking in Bets:
“What makes a great decision is not that it has a great outcome. A great decision is the result of a good process.”
Outcomes should never define the quality of a decision.
But for many, including the 91% from the survey who believe they make good decisions, the judgement springs from this mistaken correlation.
That’s a little alarming.
Without habit or routine, decision fatigue multiplies tenfold.
No business leader can truly be effective without a defined approach to decision-making.
For many, the jump from generalities to specifics makes it hard to define a simple algorithm. This results in leaders working without any habits.
There’s comfort in systematising operations. Yet, the insanity trap of ‘doing it this way because we’ve always done it this way’ stagnates improvements. Here’s where Musk offers a way out:
Elon Musk’s algorithm is five commandments.
Five rules that cut through both specificity and vagueness, forcing a hardcore focus on what matters.
Elon’s algorithm consists of these commandments:
Used recursively, it’s a lever for efficiency and speed.
It slams the trapdoor on business insanity—with impact.
There’s no room for ‘business as usual’.
From my perspective, Musk’s algorithm begins where few others do.
By questioning every requirement, you’re testing specifics from a first principles perspective.
In one business I worked in, a requirement for a repair job was a manual authorisation if a cost threshold was crossed. The fallout was significant—75% of jobs required the engineer to call the office for approval.
Ironically, there were two thresholds.
The first was meant as a checkpoint for the engineer and management, stopping excess parts use. The second, far higher, preserved economic limits.
For the first threshold, the call centre simply gave out a code.
A detailed review of calls showed no operator ever checked the job or questioned the parts used.
Why would they? They weren’t engineers.
When I questioned the requirement, the flaw was obvious.
So, we scrapped the lower limit. Instead, we set up random audits by an in-house engineer to catch excessive parts use.
Incoming call volumes dropped by 50%, just from that one change. Jobs sped up, as engineers no longer had to phone for closure.
Assumptions are painfully vague. Requirements, refreshingly specific.
Business insanity traps are everywhere.
They creep up, like a spider sheltering as the autumn deepens, because they’re the natural result of systemisation.
Systems win.
So, what’s needed is a decision-making process that lets you pursue systemised efficiency.
That’s where Musk’s algorithm steps in.
It’s a tool, not only for strategic management (though it fits here), but for challenging the effectiveness of any system.
That’s invaluable for your business.
So, do you have an algorithm for making decisions?
