AlastairThomson.com

I occasionally have people stop by my social channels who tell me they disagree with my views on AI.

(Quick summary: I hate it. The people who stop by my socials to tell me I shouldn’t all appear to be on heavy medication of some sort.)

One of my objections to the technology (I have many others) is its widespread copying of other people’s intellectual property. Progress, my social stalkers say, has always been built on the achievements of people who came before us.

Which is absolutely true, of course. Except nobody stole Pythagoras’s idea and only told you that the square of the hypotenuse is equal to the sum of the squares on the other two sides if you paid their tech platform $200 per month.

Also, there’s a big difference between copying someone else’s idea wholescale to monetise it and using an idea as inspiration for something else – which is pretty much how people have “stood on the shoulders of giants” in past generations.

Every physicist inventing something today builds on Newton’s Laws of Motion. None of them are going on Twitter claiming they have just discovered that objects remain at rest unless an external force is applied to them, which is essentially what AI does when it “discovers” things flesh-and-blood human beings have known for millennia.

This came to the fore for me recently when AI music started to become a thing.

I’m a big music fan, and my deep scepticism about AI meant this was hard to view as a positive development.

But…the red pill addicts on Twitter say…throughout musical history composers have “borrowed” from what went before them.

Again, at a very superficial level, that’s true.

There are 8 notes in a musical scale. Millions of people have played an A-sharp before I ever did. None of them “owned” A-sharp, though, and I’m not claiming to have invented something new when I play that note.

I just press the key one semitone up from A natural, and there it is. A-sharp.

The notes in a musical scale are not a secret. They’ve been public knowledge for centuries. So using them to make a piece of music is nothing like the sort of plagiarism AI gets up to.

The key to being a successful composer is not in knowing that A-sharp exists. It’s in knowing how to use that in a particular context where that makes an emotional impact on the listener in some way.

There is maths involved

Of course, again at a very superficial level, there’s maths involved in music.

There are 8 notes in an octave.

There are 4 beats to the bar. At least most of the time.

There are 88 keys on a grand piano.

There are even mathematical ways to describe chord progressions like I – V – vi – IV. (Now that might look like letters not numbers, but that’s because musicians use Roman numerals to describe chord progressions. They’re still numbers.)

And sometimes there are some very neat mathematical things going on in a musical context. The introduction to Stevie Wonder’s “Superstition”, for example, is based on filling in every note in a bar of music piece by piece, with different instruments until every note has some instrument playing something on it. (Linked below if you want to check that out for yourself.)

None of that means music is all about maths.

Maths is involved in the same way as me keeping my eye on the numbers on my car’s speedometer means maths is all I need to know to drive from London to Glasgow.

AI folk would have us believe that everything is about maths, because everything in their lives is about maths. But I’ve yet to come across anyone who enjoys music because of the maths involved.

Sure, sometimes there are neat things going on which can be described in mathematical terms, but that doesn’t make a song special. I can assure you Stevie Wonder didn’t get out a setsquare and a slide rule to write the intro for “Superstition” even if the results of that process can be expressed mathematically.

But there’s a disconnect here for tech folk. They think because you can describe something in mathematical terms the maths is all that matters.

Worse than that, they think replicating, for example, a I – V – vi – IV chord progression on their laptop makes them a composer. Little kids who’ve been learning the piano for a relatively short amount of time know how to do that. It’s nothing special. But little kids are generally less delusional than people who write AI software.

The question is, once you know about a I – V – vi – IV chord progression, what do you do with it, so that that it moves the listener emotionally, because that’s what good music does.

Despite what tech folk think, only an infinitesimally small proportion of the population listens to music to enjoy the mathematics in it. Outside the tech industry, and a few secure institutions, very few people get that excited about maths. All the benefits of listening to music…every tiny little bit of it…comes from the emotions they create in the listener, not in the mathematics deployed by the composer.

Yet tech folk think that just because they can use technology to replicate infinite variations of I – V – vi – IV chord progressions, on the receiving end that will move people emotionally in the same way as a human composer might. After all, a piece of music is just I – V – vi – IV, right?

Unless you work in tech, you’ll likely see that argument as complete bunk.

But songwriters have taken that chord progression and turned it into a variety of very different emotional experiences for listeners.

The same maths are deployed in, for example, “All Of Me” by John Legend, “Another Girl, Another Planet” by The Only Ones, and “Despacito” by Luis Fonsi, featuring Daddy Yankee and Justin Bieber. That’s a pretty wide selection of different emotional responses from the same maths.

So maths alone isn’t what music is about. Although some maths is peripherally involved, music isn’t maths. Music is something else entirely.

And that’s true of most situations where you are trying to move a human to action in some way. Maybe you’re a songwriter trying to make someone happy…or sad. Maybe you’re a marketer trying to get people to see your product as aspirational. Maybe you’ve just noticed someone across a crowded bar that you’d like to get to know better.

Maths is not the most important element of any of those situations, although some part of all of them could be expressed in mathematical terms, even if that’s just the 20 steps between you and the person you’d like to get to know better.

“Not maths” is more efficient than maths

This might seem like an odd thing for an accountant to say, but even in accounting the numbers are of limited importance.

They’re necessary, to a level, of course. But numbers are the by-product of decisions made elsewhere. If you want your numbers to be different, you have to change the decisions made elsewhere. Working on the numbers themselves won’t change them – they are just the surface-level encapsulation of the results from all those upstream decisions made by other people.

And most of the time, you need to translate numbers back into emotions before people pay much attention to them.

“You’ve made 9 sales this month” is factual information and interesting up to a point.

“Make just one more sale and you’ll double your commission rate” is received entirely differently by the person you’re talking to, even if we’re still talking about the same 9 sales.

That’s why maths alone is poor at moving emotions. It might be factually accurate, but it’s usually seen as grey, beige, and/or dull on the receiving end.

So it’s something of a mystery to me why tech cos are trying to take something like music – which, by its very definition, is trying to move people emotionally – and then engineer all the emotion out of it.

They do that mostly because they’re emotionally-bereft sociopaths, of course, but also because they need to convert emotion into maths before they can get a robot to “write” music for them.

While it’s a close run thing, a computer has even less emotional capability than the average person working for a big tech company. But computers are very good at maths. So the only way a computer can “write” music is if the inputs are expressed in entirely mathematical terms.

This means computers are always less efficient than humans because a decision a human can make in a fraction of a nano-second (“Oh, I love this song!”) is replaced with thousands of API calls while some AI bot tries to cross-reference your Spotify playlist, YouTube views and Google searches with listening stats for both you and everyone else in the world to identify that, of all the songs in the world, you’re a statistical outlier in terms of the number of times you’ve listened to this particular one and the enthusiasm you clearly feel for listening to it.

Just think about that last paragraph for a moment.

Odds are high that there’s a piece of music that makes you go “Oh, I love this song!” whenever it comes on the radio or TV.

Odds are also high the second part of that paragraph left you a bit cold with, at most, a tiny element of “that sounds pretty clever” lurking around.

But set the instant “Oh, I love that song!” reaction against the $1000 in compute which takes a couple of minutes to come through and you’ll see that the emotions are vastly faster and vastly less expensive than getting to the same result via maths alone.

Replication

Once you’ve expressed music in maths, it becomes fairly easy to replicate, though. So there’s a particular breed of tech-obsessed person who thinks that’s a great idea because they can now replicate that song a bazillion times and monetise the outputs.

Except that’s not really the case. Because now you have musical notes without emotion and frankly nobody much cares about that.

John Legend’s “All Of Me” didn’t sell an estimated 12 million copies around the world because people loved the maths which underly the chord progression he used. It sold 12 million copies because it moved people emotionally.

“Despacito” didn’t sell 13 million copies because of maths. It’s because the song moved people emotionally too…but in an entirely different way to the way John Legend did it, even though Luis Fonsi (and co-writers Erika Ender, Daddy Yankee, and Justin Bieber, in varying combinations) were using the same maths.

And just to prove the point, “Another Girl, Another Planet” by The Only Ones, despite being critically acclaimed as one of the finest rock songs every recorded (an acclamation I’d fully agree with – I love that song), never even made the UK Top 40.

If maths alone could explain music, that would be impossible. Yet it’s the truth.

So, if maths alone can’t predict people’s emotional reactions – and certainly can’t predict whether they buy either 13 million copies of a record, or, essentially, zero copies – why do we think maths alone can be successful in any other field where human emotions matter?

Know, like and trust

Sticking purely to business here, as my experience of chatting up random strangers at bars is neither extensive enough nor successful enough to yield many helpful examples, if you’ve ever tried to sell anything to anyone, you’ll be familiar with the expression “know, like and trust”.

In essence, if you want someone to buy from you, they need to know who you are, like dealing with you, and trust you to do what you say you’ll do, without ripping them off.

No matter how you dress it up, in every sales relationship that’s what goes on. And pretty much all of the elements of “know, like, and trust” are emotionally-based.

The “know” element isn’t entirely emotionally-based because, for example, you might need to run a series of ads to make sure enough people know you in the first place.

But even how you do that has a big impact. Most people ignore most of the ads they see in a given day, and can’t even recall seeing them, if asked.

So the “know” bit is slightly more maths-based than the other elements. Unless you’ve put enough ads in enough places for long enough for people to notice them and register who you are, random strangers won’t know you exist, so you fall at the first hurdle.

But even here, it’s a lot more expensive to get people to know you through the use of beige, insipid AI copy and AI-generated visuals. That always blends into the background. Make an emotional impact and people will get to “know you” much faster because they’ll be more likely to pay attention.

So probably half the “know” and all the “like and trust” is entirely about emotions. There’s no maths in sight.

Even if you’re tracking metrics along the way, your prospect isn’t. Very few people outside the tech industry calibrate whether they trust someone or not with the aid of a spreadsheet – you either trust someone or you don’t, and much of the reasoning behind whether you do or not is entirely subconscious.

If you ask them, people often can’t explain why they trust someone or not. The wise ones don’t ignore any little twinges of concern in a business situation – if you think someone’s a bit dodgy, usually they are, even if you can’t quite put your finger on why you think that way.

So, although tech folk wish it were different, most humans are not governed entirely by the laws of mathematics. Maths has very little impact on a decision to, for example, know, like, and trust someone.

Insufficient and inefficient

Given that maths is insufficient for moving humans emotionally, let’s also consider how inefficient maths is in this context.

Tech folk trying to use AI software to connect emotionally with someone, to the extent that it’s possible at all (spoiler: it isn’t) don’t pause to consider how inefficient maths is at doing this.

With pretty much zero effort on my part, I can decide in a fraction of a second if I’m prepared to trust someone.

To use maths to come to the same conclusion – if indeed it did, which is unlikely enough in itself – we’re using up API calls, AI tokens, cloud computing resources, internet bandwith, a gazillion gigawatts of electricity, and goodness knows what else.

All to try (and usually fail) to replicate a decision I’d have taken entirely inside my head, with no external resources, in a nanosecond.

Technology is, by definition, highly inefficient at making decisions based on emotions – or in reacting to humans who are seeing the world through an emotional lens – because the tech folk who programmed them, and the computers who are making the API calls and doing all the calculations, are incapable of connecting with humans on that level.

You might not think that’s too much of a problem.

Apart from the fact that, for example, most buying decisions are made emotionally first and then post-justified with logic. That’s true of every important decision you’ve ever made in your life too. The emotions come first, then the logic.

AI software, and tech more generally, can only deal with logic. So that means AI software turns up only after the battle has been won or lost.

Except it has no way of knowing that yet, because it can’t calibrate emotions. So it deploys all those AI calls and all those computing resource to fight a battle that’s entirely pointless and unnecessary.

Will that AI tool claim all the credit for that sale? Probably, even though it didn’t make the sale – its customer’s emotions did. People will hail that as a success for their AI sales tool and conveniently ignore all the times that resources were wasted in the vain pursuit of an adverse decision that had already been made before the AI tool showed up.

AI tools might well have a helpful role to play in entirely logical activities, devoid of human emotion. But, outside writing code, that describes pretty much none of the decisions the average human makes every day.

Sure, if you ask them, they’ll probably give you seemingly logical reasons for their decisions. But it would be a real mistake to think that was what was really going on.

Maths alone is insufficient to describe, much less predict, human decisions.

And even where maths can be of some help, a human can do in a nanosecond something that takes $1000s of IT resources.

So it’s not only insufficient. It’s inefficient too.

It’s perfectly true that, in the ultra short-term, sometimes you just have to power through a problem to reach a solution and devote whatever resources are necessary – no matter the cost and the trade-off against other important activities that need doing – to achieve a worthy goal.

However, that doesn’t always mean it’s the right decision, or even the best possible decision with an even slightly longer timeline in mind.

If you’re walking up to a bus stop and see your bus about to close its doors and pull away, maybe you should start running, powering through the short-term discomfort, if you like, to make sure you get where you want to get to as quickly as possible.

Equally, if buses on this route come every five minutes and it’s a particularly hot day you might decide not to bother.

Similarly, if you’re recovering from a hip operation.

Or you’re just going into town for a bit of aimless wandering around the shops rather than, say, going to work where you need to be at a particular place on time.

So you can power through things in the short-term. That doesn’t mean you always should. Or that, if you do, that’s always the best answer. Remarkably often it isn’t.

That’s because every time you power through a problem in search of a solution you are almost certainly generating extra costs and inefficiencies in the process.

At a simple level, maybe you’re paying everyone in the factory overtime to get a rush job out, so unless you’re charging your customer extra for a fast turnaround, you’re out of pocket.

And there is always an opportunity cost to powering through anything. Devoting all your resources to a single project, by definition means you starve another project, or projects, of those same resources. Maybe the activity those people could be doing instead would have (net-net) been more valuable to your business in the long-run than whatever they were helping you power through.

But my more fundamental objection to always powering through problems is that there’s an implicit assumption with that strategy that there is no other…and potentially better…way to achieve the same goal.

The minute you make that implicit mental leap, you lock yourself into a rigid, fixed business model which everyone devotes all their time and energy to delivering, to the exclusion of any other considerations. It can become a bit cult-like to the point where often the people who suggest there might be a better way of achieving the same goal are shouted down and seen as naysayers who don’t value the business as much as the people who are sweating blood and tears to reach a solution through power alone.

In reality, though, the naysayers are usually right. Even more so in anything other than the ultra short-term where the compounding effects of continuing to operate inefficiently come back to bite you big time.

Sure, if it’s one of those “once in a blue moon” events, by all means power through it as best you can.

But if you’re doing that several times a week, you institutionalise short-term thinking and bake in a state of constant chaos in your organisation. And that never ends well.

There’s a lot of it about...

There’s a lot of short-term thinking about.

Daily calls lists, monthly sales targets, quarterly profits, the earnings-per-share number your C-Suite’s bonuses are probably based on, and more besides all loom large inside most organisations.

If you work in the public sector, you’ll recognise the same dynamics, but there they manifest themselves through some bureaucrat or some politician trying to make a name for themselves, or some artificial objective put forward to make it look like the world is being improved for the better, when it’s really just a smokescreen for all the other important things they aren’t doing – and should be doing – instead.

How that feels on the ground is exactly the same, though. There is some overriding objective that sweeps through the organisation and everything else becomes entirely secondary to whatever that overriding objective might be.

That overriding objective, in turn, results in a boat-load of short-term thinking while people just power through whatever that objective might be. And, worse, that way of running your organisation becomes institutionalised so that very little happens any more unless it’s directly required to deliver that overriding objective.

At that point, your organisation is almost certainly in mortal danger because you’re deep in “not being able to see the wood from the trees” territory. People will ignore blindingly obvious better ways to achieve their organisational goals because everyone is locked into a fixed operating model which sucks up all the available resources to solve just one of the many problems your organisation likely has to solve.

Objectives aren’t a bad thing

It’s not that objectives, in themselves, are a bad thing.

Far from it – without them, people and organisations just drift aimlessly along, never accomplishing anything of note.

So objectives are important. Just not blind adherence to them, hard-wired into a rigidly predetermined operating model.

Let me give you an example.

If you know me well, you’d know that “doing the very best for our customers” is one of my deeply-held values. I normally bend over backwards to ensure customers are delighted with the service they get from any organisation I’ve been involved with over the years.

But rather than a rigid, unthinking “the customer is always right” approach, it’s a principle that needs to be balanced against a range of other factors.

In my very first Finance Director job, I had the unenviable task of having to explain to my boss, the CEO, that the reason the business didn’t make any money was because every time a job came in for one of the clients he looked after personally, every other job in the factory came to a halt while every resource we had was thrown at keeping the CEO’s clients happy.

Which wouldn’t have been so bad were it not for the fact that his number one client – and our company’s biggest – was also the least profitable client we had. They barely covered their costs…and frequently didn’t even do that…because they had used the immense volume they delivered to drive our prices down.

To be fair to the CEO, who I had a lot of time for, their previous Finance Director had never worked this out, much less pointed it out to the CEO. He focused mostly on producing monthly financial accounts, and didn’t get too excited about the nitty-gritty bit of making sure the factory ran as efficiently as possible.

But once our CEO understood that the problem he had with the bottom line was that all the work on profitable clients stopped the minute one of his break-even jobs came along, we started the process of untangling what had been our biggest client, in revenue terms, up to that point.

So, despite being someone who would bend over backwards to make sure a client was happy with our service, in this scenario, powering through the CEO’s client’s work by throwing all our resources at it made no sense, economically, practically, or logistically.

And it wasn’t like this was a temporary situation that we would eventually get through to the other side of. Our client wanted Rolls Royce service at Lidl prices and had no intention of allowing us to do anything about either end of that equation, so long-term losses from continuing to serve them were pretty much assured.

In that scenario, continuing to put the demands of a “bully” of a customer above everything else we might have done with a given hour of productive time in the factory with the resources at our disposal made no sense.

So we stopped “powering through” their demands. There was a better way for us to achieve our objective of making a fair bottom line return on the capital invested in our business.

Which, in this instance, involved telling our biggest customer to take their business elsewhere. Miraculously, having taken the biggest drag on our profits out of the equation, our business became a lot more profitable.

Weird, huh…?

A modern-day example

That business was a real-world business where people used machinery to make physical products which we sold to customers and shipped to them in trucks.

But the same principle applies today in the digital economy, for example with AI companies’ continued search for “more compute”.

Essentially, they are doing their best to “power through” the task of finding a way for computers to become human.

Leaving aside for a moment any richly-deserved questioning of the sanity of those involved, what all the AI companies have done is what the business in my first Finance Director post had done.

They have locked in a rigid operating model which they hope will deliver the objectives they seek…if only they throw enough resources at it.

It’s actually worse than that. It’s not like each incremental step towards their objective becomes incrementally less expensive, such that a dispassionate observer could discern a path to ultimate profitability.

No, quite the opposite. Each new step forward is more expensive than the step before it and, worse, they are making only tiny, tiny amounts of progress towards their ultimate goal. Incremental costs are huge and incremental benefits are tiny.

As business models go, I haven’t heard anything quite as insane as that at any time in my professional career.

Sure, in the early days, that’s sometimes true.

At a very mundane level, if you buy a new computer to start writing a programme for a new idea you had, that first purchase is an incrementally huge jump in cost relative to what you had before (ie nothing). And, at least in the beginning, you have derived no additional benefits because, by definition, you haven’t written anything you can sell yet.

So, understanding the wider context is important.

But, by the time you’ve spent a bazillion dollars on computing equipment, and you’re only seeing tiny incremental improvements in return for each incremental billion dollars you now spend, you’ve got a fundamentally broken business model.

Powering through that won’t get you where you want to go. It’s time for a rethink.

Despite that, at the time of writing, all the AI companies are in an arms race to pile on more and more capital expenditure in the hope that, if they throw enough computing power at the problem, they’ll solve their stated problem of turning computers into humans.

Again, leaving aside questions about the sanity of people who want to pursue that as an objective in the first place, all the available evidence is that “more power” isn’t the problem here. The AI companies are trying to solve a problem with power which power alone is incapable of solving.

I never cease to be surprised that a group of supposedly smart people seem to have so much trouble seeing that. It’s face-smackingly obvious from where I stand.

Elegance beats power

Going back in time, there was a tremendous example of how an elegant solution solved a problem that would otherwise have cost billions of dollars and taken years to come to fruition.

Back in World War Two, opposing armies had a big problem. The only way there was to communicate over long distances then was by radio. And the problem with radio was that anyone could tune into the same frequency and hear what was being said.

A common way to deal with that was to use a code book to translate a plain-text message into a meaningless string of letters sent via morse code which were decoded at the other end.

When done well, that’s quite an effective way of communicating “in public” in a relatively secure way. But if the enemy captures one of your code books, for example, everything you do is immediately insecure from that point onwards.

There was also the work of codebreakers at Bletchley Park, immortalised in the 2014 film “The Imitation Game”, who used the best technology of the day to throw maths at the problem of breaking the coded messages they had intercepted from the enemy.

The work of the Bletchley Park codebreakers was genuinely insightful and if you ever get a chance to visit Bletchley Park, you should, it’s one of the most fascinating places I’ve ever been to.

Nowadays, we’d use “more compute” to solve codebreaking combinations. And it works at some level. If you let a pattern-matching software programme run billions of combinations of potential words that might be hidden within a coded message, I’m prepared to bet that, sooner or later, you might stumble across the right solution.

The problem is, doing that at scale requires the investment of billions of dollars and there’s a time delay to build the buildings and computers which allow you to even attempt to solve that problem on anything other than a lab-scale basis.

But there was a more elegant solution.

A First World War veteran, who had been brought up on Native American reservations by his missionary parents, proposed that one way of developing an “unbreakable code” for the US forces in World War Two was to recruit Native Americans as radio operators. They could speak their own language to one another over the radio, be safe in the knowledge that the number of speakers of Native American languages in the Japanese and German armies was as close to zero as to make no difference.

This required no ruinously expensive capital investment, and there were no significant delays to getting the idea up and running (once the idea was green-lit) because the people concerned already knew how to speak their native languages and the Army already had the radios.

While this was a function most famously performed by members of the Navajo nation, many other Native American groups were involved too. The only criteria was that the people on both ends of each radio transmission had to come from the same background, for obvious reasons.

To this day, I think the use of “code talkers” (as they were called) is one of the most creative ways a significant problem has ever been solved, in peacetime or in wartime.

While the Japanese and Germans had plenty of people who could speak English, they had nobody who spoke Navajo, or any of the other Native American languages.

No amount of compute would have helped them translate Navajo into English, much less German or Japanese, because it came from entirely different linguistic roots with words, phrases, and grammar for which no direct equivalent even existed in the English language.

As elegant solutions go, this is one of the most inspired ideas there has ever been.

And I think of it often when people’s only solution to a recurring problem is to throw more power at it…whether that’s money, resources, or investment dollars.

When “more power” is your only solution to a problem, I can almost guarantee that you’re on the wrong path. Or, at the very least, a sub-optimal one.

There’s always a better way, but you need a level of insight and creativity to unlock it that you’ll never find through brute force alone.

And that’s true whether you’re a modern-day Silicon Valley tech executive or a Japanese general in the Pacific during WW2.

Elegance beats brute force pretty much every time, so don’t rely on power alone.

Over-index on elegance instead, and 99 times out of 100 you’ll make better, more sustainable, less expensive, more value-adding decisions in the process.

Too often, “it ran according to procedure” is a get out of jail free card for people who do incredibly stupid things.

“Oh, well, if they’ve followed process, we can hardly blame them” is the narrative the people responsible for some catastrophe or other would like you, or their boss, or the police, to think. That way, no matter how harmful the result, they get away with whatever they’ve done.

Now, that’s not to say that there is no value in processes and procedures.

If you’re about to pilot me across the Atlantic in a jet airliner, I’d much prefer that you went through the pre-flight checklist thoroughly than just flung your bag behind the pilot’s seat and went “naah, it’ll be OK – I won’t bother with the pre-flight checks today”.

But in most business situations, this idea of being a slave to the process is ultimately harmful to your bottom line.

The concept itself creates some significant issues. (The biggest issue is also the biggest blind spot of people pushing AI solutions – which is why you shouldn’t use those either, but that’s not the point of today’s article.)

For a rigid process to work unfailingly, 100% of the time, you need:

• a series of activities you can specify so precisely that a robot could do them
• perfect information about every aspect of the situation
• the situation itself needs to be stable and never fluctuate from the pre-determined norm
• there can be no interaction with people outside your business, whether customers or suppliers, or government bodies who may behave in unpredictable ways, and
• you need to have complete control over every aspect of what you’re seeking to achieve in a closed environment

When you think about this for even two seconds, you’ll realise that virtually no activity in the world can possibly tick all these boxes, so valuing and rewarding slavish, unthinking adherence to a process that you know in advance will be wrong 10%, 20%, 50% or more of the time is insanity.

Insanity. Yet remarkably common, as we’ll see in a moment.

While you need some processes in place to manage your business, fundamentally what you really need is people who think to themselves “this is taking us in completely the wrong direction for our people, our customers, and our company” and do something different.

That puts them in a difficult position, because if it all goes horribly wrong and they weren’t following process, they might get fired. And even if they save the company from going down in flames by diverging from the standard, pre-determined response in that situation, some jobsworth will probably feel the need to tell them they shouldn’t do that again or they’ll be reported to HR.

You need the right result, not the right process

As a business, what you’re really looking for is the right result – the right result for the business, the people in it, and its customers.

How you get there is a matter of choice.

Sometimes a rigid process will get you there – if you run payment transfer systems for a bank, for example, a rigid process with sign-offs and transfer limits is a really good idea.

More often, a process will be imperfect, at least some proportion of the time, because whoever designed the process isn’t God (although one or two of them think they are just because they can make a prototype work in a computer lab).

People who design processes tend to be people sitting in a conference room somewhere with some colleagues and some flipchart paper. Or, worse, someone on their own tapping away on a computer keyboard with their headphones on blasting out heavy metal music to shut out the rest of the world while they type.

One way or another, most processes are designed by people who sit far behind the frontline where their processes get used every day.

Funnily enough, this is a concept the armed forces accept. They know it’s impossible for the generals in headquarters to know what it’s like, minute-by-minute in a 10-yard stretch of a trench on the front lines of a battlefield.

So the modern armed forces use a concept called Commander’s Intent to get instructions from the headquarters to the front line.

In essence, the generals set out the objective they would like to accomplish, such as “capture the hill to the south-west of your current position and prevent the enemy resupplying their own troops through the valley that runs under that hill”.

Just by reading those few words you understand the “what” and the “why” – what it is you need to do and why it matters.

But the generals go beyond that. They also provide guidance about what not to do – that might be the need to avoid civilians nearby, preserve some critical piece of infrastructure like a bridge, or not to advance beyond point X until after the airstrike to soften up the defenders has taken place.

They also think about the resources they have at their disposal. Even if the objective remained the same, any sane person would accomplish it entirely differently depending on whether they were trying to achieve it with 20 grizzled Royal Marine veterans or 100 conscripts fresh out of initial training.

Finally, the generals do the most important thing of all. They get out the way and let the commander on the ground make the best decisions they can, in full cognisance of the objective that’s been set, with the resources at their disposal. This approach also allows commanders on the ground the flexibility to make changes to the plan when they discover, for example, that enemy reinforcements have just arrived, or that the enemy has set up a minefield where one didn’t exist before.

Knowing what they know about the what, the why, and the no-go areas, they can make decisions on the fly and still achieve the initial objective, even if that wasn’t done in the way they had originally thought they might.

Weird, isn’t it? For most civilians, the armed forces feels like a very hierarchical place where people blindly follow orders at all times, but it’s not like that at all. Quite the opposite.

In fact, mid-level managers in a large business are likely to have significantly less room for manoeuvre in decision-making than a junior officer on the battlefield would.

The problem isn’t so much one for the manager making the decision, who I accept has to play the cards they’re dealt, as it is a problem with the leadership inside that organisation.

Rigid processes cost more

One of the key points that leadership teams overly fond of rigid processes tend to overlook is that rigid processes are always more expensive to operate than processes more akin to the “commander’s intent” approach described above.

Let’s take a simple example, based on an actual real-life experience of mine.

Most organisations receive calls, letters, and emails from their customers about some issue or other. So the company I worked for had specified a large, complex and, to be fair, very good, CRM system to manage those activities.

To do that, however, they needed to set up processes and decision trees so that a call centre agent could use the CRM to navigate their way towards a solution.

Not entirely unreasonably, that required a degree of diagnosis of the problem, some noting down of information, some time for the agent to think about which option out of the ones available on the screen in front of them was the best fit in this particular situation, and so on.

What that meant, though, was that they had pretty much “hard wired” the call handling time according to how many of each type of enquiry came in that day. And in a call centre, your resource requirements, and thereby costs, are largely determined by your call handling time.

That, of course, was the ideal situation.

What actually happened was that customers weren’t aware of the process and, not unreasonably, didn’t much care what it was. So if the first words out the customer’s mouth were the answer to the question on the 10th screen of the diagnosis process, the agent would, in all probability have to ask the question again 10 screens later as they wouldn’t always remember every detail out of the hundreds of calls they might handle in a day.

Specifying a rigid process, therefore, necessarily built inefficiencies (and cost) into the process of resolving a customer query. This is true every time you build a rigid process, by the way. You inevitably bake in a certain cost base, along with a degree of avoidable inefficiency.

What we did was take the concept and re-do the CRM so that questions could be recorded in any order, not just in the order of the diagnosis process. The agent still had to answer all the questions, but just by taking out the rigid sequencing, we enjoyed significant time savings and drove much greater efficiencies.

So for all the people who claim that rigid processes are unfailingly more cost-efficient, I have bad news. The exact opposite is almost always true. By design, rigid processes are much more expensive to operate than less rigid ones.

Not only is the process more costly to operate, rigid processes tend to spawn layers of management and control, each of which adds further costs into the equation – again the very opposite of being cost-effective.

In a rigidly-controlled process environment, you’ll need a department manager, and a couple of assistant managers to sign things off when the manager isn’t around. The managers in the department will spend a lot of time in meetings with one another, which will mostly not add value to the business. And they’ll also spend a lot of time in meetings with other managers across the business, even fewer of which will be value-adding.

Rigid processes mean you bake in a level of operating cost to run the process, along with higher-than-necessary management and supervision costs.

Rigid processes aren’t more cost-efficient, they are less cost-efficient.

The problem is the objective

But the real problem with most process design is in the way the objective is specified in the first place.

If the objective is “follow the process”, then you’ll probably get grudging compliance most of the time. But you’ll also create a range of – often costly – bad outcomes which were not envisaged as possibilities by whoever set up the process in the first place.

Imagine if the objective was set as “make sure the customer is happy” rather than “take them through 10 different screens full of questions in sequence and give them the answer at the bottom”.

Now we’re in “commander’s intent” territory and, to most people’s surprise, the area of maximum cost efficiency.

Very few customers enjoy being taken through 10 screens of questions in sequence. If you can ask “what do you want to do today?” and go straight to doing that, customers will love you, even if you parcel up the call in 30 seconds instead of 3 minutes.

By doing exactly what the customer wanted – no more, no less – you’ve probably got a much happier customer than any amount of process would have left you with. And you’ve done it in 30 seconds, not 3 minutes, for an 80%-odd saving in resource requirements and therefore cost.

But once you specify an objective in process terms, you lock in higher cost, and usually lower performance, than if you’d taken more of a “commander’s intent” approach.

And AI won’t help. Even leaving aside sky-high (and getting higher) token costs, and the fact that 20% of the time or more AI solutions are wrong (leading to significant clean-up costs), AI is incapable of doing anything other than follow the process because that’s how computers work. So the likelihood of your AI system generating sub-optimal answers and then implementing them, to the detriment of your business, is high.

If that happens often enough, you would have been better off keeping the humans employed and ignoring the shiny-suited tech salesperson who flogged you their AI solution.

But all this boils down to leadership, really.

To run with looser systems, you have to be much clearer on your objectives, and much clearer on your no-go areas, so that your team has the guardrails they need to make decisions without every step having to be specified in advance.

So you might want your customers to be happy, for example. But not if they will only be happy if they get a 90% discount on your normal prices.

To boost your bottom line, clarity about what your objectives really are, and the trade-offs you are prepared to accept, are essential because that allows you to take out most of the inefficiencies created by rigid processes and layers of management.

And ironically the best way to do that is to think like an army general.

Not a general as they are often portrayed in popular culture, rigid, unyielding, a stickler for detail.

But a general as they are in practice today, where they spend a lot of time and effort identifying objectives, explaining why those objectives are important, and setting guardrails for the commanders on the ground. And then they step away and don’t interfere.

Most businesses would become more efficient and boost their bottom line if they operated with “commander’s intent” at the core of their decision-making.

Remember the line attributed to Charles Darwin: “it’s not the strongest of the species that survives, or the most intelligent, but the most adaptable to change”?

The more rigid your processes, the less likely it is your business will survive, no matter how smart the people who designed them were.

Adaptability is key for survival and that means rigid processes, by definition…and by science!…are not as good as more adaptable ones.

In case you’re not from Glasgow, this is a nice thing for someone to say – it means you’ve done something really good, usually far more than might reasonably be expected.

The surprise cake you’ve spent all day baking and decorating to celebrate a loved one’s achievements – when they walk through the door that night, they might say “Ya wee belter!” to you.

If your football team scores a scorcher of a goal from well outside the penalty box, you or someone else in the stands will call out “”Ya wee belter!” to the player who scored it.

Your pal who secured two impossible-to-get concert tickets for your favourite band on the day of their show in the town where you live would deserve nothing less than “Ya wee belter!” as they handed your ticket across.

You get the idea, I’m sure.

Away from Glaswegian patois, though, there’s another use of the world “belter”. And that’s among singers. Especially singers with powerful voices which could fill an entire theatre without a microphone.

Possibly the OG of belters, when it comes to singing, was Ethel Merman. She was a big Broadway star in the 1930s and 1940s and, while you might not instantly recognise her name, you’ll definitely recognise her signature song, Irving Berlin’s “There’s No Business Like Show Business”.

Ethel Merman worked with the greats of musical composition during the 1930s and 1940s – George and Ira Gershwin, Cole Porter, and Irving Berlin. And her reputation as a “belter” was such that Cole Porter once said “When you write lyrics for Ethel Merman they’d better be good because everyone is going to hear them.”

And Irving Berlin advised her not to have singing lessons to make sure she preserved her powerful voice and unique singing style. In his view, singing lessons would have made her sound more like everyone else, losing her distinctiveness in the process.

He was probably right. Love it or hate it, there was never any doubt you were listening to Ethel Merman when one of her songs came on the radio. It couldn’t possibly have been anyone else.

A “belter” is not always what you need

Ethel Merman was primarily a soloist. Having a distinctive voice as a soloist is no bad thing.

But introduce more people in the mix and having a range of distinctive voices, all vying for attention, is a recipe for chaos. It’s never going to sound good.

This, incidentally, is why the common thinking in organisations is mistaken.

You don’t build a great band by having an assortment of soloists with entirely different singing styles fighting to sing louder than one another.

Nor do you build a great organisation by letting a disparate bunch of individuals with different styles, beliefs, and behaviours loose to make their own decisions. Success comes when you can get a disparate group of people working together so that the results of the whole are greater than the sum of their parts.

A good way to think about your organisation is the way one of my favourite vocal groups, The Mama and Papas, operated. (Don’t worry if you’re not familiar with them, there’s a link below.)

There were four members of The Mamas and Papas. Each had their own distinct skills, and each brought a different dimension to the band. But it was in how they worked together to create some of the smoothest harmonies in pop music history that’s the important element here.

John Phillips was the chief songwriter and had one of the finest ears for creating harmonies you’ll ever come across. Nobody was better than him at crafting flower power pop anthems. But he wasn’t the strongest singer and confined himself mainly to singing harmonies around other band-members’ lead vocals.

Michelle Phillips, John’s wife, and occasional co-writer, wasn’t the strongest singer either, but she had a lovely voice, with a high, bright, sweet tone that conveyed the optimistic spirit of the late 1960s perfectly.

Denny Doherty was the main male lead vocalist, which includes singing lead on the song I’ve linked to below. He had a strong voice that sounded just lived-in enough, without straying into the territory of someone who had smoked too many cigarettes and drunk too much whiskey over the years.

And, of course, Cass Elliott, one of my all-time favourite female singers who brought power, warmth, and strength to the band’s vocals.

Cass was a “belter” – she had always wanted to star on the Broadway stage, although she became part of two of the most iconic pop groups of the 1960s instead (The Mugwumps, as well as The Mamas and Papas). She later became a solo star, before her untimely passing in 1974.

What matters here, though, that Cass Elliott understood about making the whole greater than the sum of the parts.

I recently saw an interview with Michelle Phillips, recorded back in the 1980s, in which she said that one of the great things about Cass Elliott was that Cass held back the massive power in her voice so that she didn’t overpower Michelle’s much quieter voice.

I mean, Cass Elliott’s voice was such a significant part of the Mamas and Papas’ sound that, once you spot it, you can’t possibly miss it. But everyone else’s voice is there too, even though Cass on her own could easily have overpowered everyone else put together.

That’s the difference between being a soloist and being part of a group.

As a soloist, to some extent, you can please yourself. If the public likes your distinctive approach, you’ll have a nice career.

As a group, you’re in 2+2 = 5 territory.

You can’t just be a bunch of soloists, each pleasing themselves. You have to work together to make the most of your collective talents instead of maximising your individual performance.

The Mamas and Papas would never have ascended to Rock and Roll Hall of Fame status if Cass Elliott had just overpowered everyone else with her exceptionally powerful singing voice. That’s how she made 2+2 = 5.

You are not a chess grandmaster

The thinking which underpins a lot of businesses is that everything always needs maximising all of the time.

There are performance reviews, KPIs to meet (and ideally exceed), monthly board reports…not to mention rafts of policies, procedures, and working practices designed, at least in theory, to ensure maximum performance at all times.

Yet one of pop music’s most iconic groups had someone who was deliberately not maximising her vocal talents, while being part of a group which created the sound which defined became emblematic of late 1960s San Francisco, when that was the cultural (or, should I say, counter-cultural?) capital of the world.

How does that work?

A lot of businesspeople, especially in tech, think like chess grandmasters. They might be very smart, but they are like solo singers, making all the decisions and deciding where to put their pieces on the chessboard to, they hope, obtain maximum advantage. It’s all about them as individuals and their personal achievements.

However, this ignores that fact that, in most businesses, it’s the interplay of personal relationships between the people you employ, and their interaction in turn with your customers, which determines success or failure.

As it was for Mama Cass Elliott, individual power alone was not enough. Knowing how to use her vocal power to complement everyone else’s voice, and working together with them to make 2+2 = 5…that was the secret of the Mamas and Papas’ success.

And your business success too.

I know it’s superficially tempting to imagine that, if everyone is going “hardcore” all the time, success is assured. On some level it makes sense, as long as you don’t think about it too much.

But if your role depends on bringing people along with you, whether they are internal or external to the business, the likelihood is that’s not the way forward. For example, it’s one reason why overly pushy salespeople don’t make sales as often as they could.

And it’s why, without breaching any company rules, people find a way to undermine managers they don’t like or trust.

And it’s why decisions made purely with technology tend to be poor decisions.

If you get a report that says someone in your organisation is only producing at 80% of their capability, the entirely logical response of an AI agent is to fire that person.

That’s tech-based logic at work. It’s also, at least some of the time, an incredibly stupid thing to do.

If you’re a chess grandmaster performing at 80% of your capabilities, you’d deserve to be fired by an AI agent, because performance in that context is all about you.

In pretty much every organisation, there is far too much interplay between individuals, departments, distribution partners, customers, and suppliers for decision-making to be simplistic enough for tech to be much help.

Cass Elliot probably sung at about 80% of the power she was capable of singing with. If she’d been fired by an AI agent, one of the 1960s’ most iconic groups wouldn’t have achieved the level of commercial and critical success they enjoyed.

It’s not tech’s fault. Tech just applies surface-level logic to every situation. If you’re a chess grandmaster moving the pieces around the board, surface level logic is all you need.

It is, however, your fault, if you try to create a world-beating business that way.

You need to think more like a record producer. Instead of thinking about excellence as a single dimension in a field where all the decisions are prescribed by specific rules, like chess, you need to blend together a range of skills, talents, expertise, strengths, aptitudes, working styles and behaviours to end up with two plus two equalling five.

The reason you don’t see that very often is that making that happen in the real world is incredibly hard. Much harder than playing chess, because there are a million moving parts which don’t exist on a chessboard, but do exist in real life.

But sometimes, the secret to success is nurturing someone who could be a “belter” like Mama Cass Elliott and helping them see that the sum of the whole would be vastly greater if they held back a little and only delivered 80% of what they were capable of.

If you want to reach the business equivalent of the Rock and Roll Hall of Fame, that’s almost impossible if you think you’re playing a logical game of chess, where everyone plays by the same rules, and individual performance is the only thing that matters.

But it’s vastly more likely if you can create the balance in your business to the same level a vocal performance by The Mamas and Papas.

Ironically, part of achieving a world-beating, epoch-defining outcome is sometimes to recognise how important it is for some members of your team to “underperform”.

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As promised, in case you’re not familiar with them, here are the singers I’ve written about in today’s article.

Ethel Merman

The Mamas and Papas

It sounds like it should be the other way round – that complicated things should be harder than simple ones – but that’s not true. Often complicated things are much easier to manage.

Think about this in terms of food.

Go to a supermarket and pick up a pre-prepared meal of almost any kind. What do you find when you look at the ingredients panel?

Probably about 47 different ingredients, most of which you’ve never heard of and, if anything, just make you wish you’d paid more attention in your O Level Chemistry class.

Modified starch? No idea what that is….and modified how, more to the point. Anyway, what’s the problem with using unmodified starch…?

Sodium ascorbate? Dunno. Isn’t sodium something to do with salt? After that, I’m struggling…

Hydrogenated vegetable oil? That sounds like one of those made-up ingredients they talk about in TV commercials for face cream. Why are they putting that in food…I’m going to eat that…!

I could do on, but you get the idea.

Undoubtedly making a supermarket ready meal is complicated, with 47 different ingredients you’ve mostly never heard of to juggle in the right proportions. But – and I can state this with some authority having been a supplier to food manufacturers in a previous role – it’s not really that difficult.

Large scale food manufacturing is done in huge factories, using a lot of automated machinery which has been designed so that people with relatively little training – and ideally who don’t cost too much to employ – can operate them and produce an acceptable result within the tolerances set out by the Quality Control Department.

Your supermarket ready meal is sounding less and less appealing the longer I go on about this, isn’t it…? But let me observe that just having 47 ingredients does not mean a high-quality dinner is being produced here.

Probably the opposite.

(Over)compensating

In case you don’t know, the main reason there are 47 ingredients in your supermarket ready meal is that they are mostly there to make desperately unappetising things vaguely palatable, and to prolong shelf life which helps keep supermarket profits high.

And that’s on top of the usually epic amounts of salt and sugar that get crammed into the typical ready meal.

There aren’t many things human tastebuds respond to more than epic amounts of salt and sugar (especially sugar, in my case). And while there is a biological reason for that, going back to when we lived in caves and hunted woolly mammoths with spears for food, the major food producers, left to their own devices, want to put in enough salt and sugar to keep us hooked on the “high” their products are designed to give us.

Over time, it’s been discovered that many of the ingredients which food producers used in the past to make their food palatable or prolong its shelf life were positively harmful to humans. They were a short-cut which benefited food producers, but at the expense of their customers’ health.

It’s not the only reason there’s an obesity crisis in many Western economies, but food companies using 47 ingredients which are designed to (or have the unfortunate side effect of) making us want to guzzle up more and more of whatever the supermarkets are selling is at least part of the reason.

But that’s a different point, and not one I’m making today, particularly.

However, please note that one of the things all those ingredients do is make something that sounds complicated – making the shelf life of a supermarket ready meal as long as possible – comparatively easy. Just add a few drops of magic ingredient X, and you get another couple of days’ shelf life, no problem at all…!

What real chefs do

Real chefs take an almost diametrically-opposite approach.

Sure, there are some people who use tweezers to pick a single leaf from a special herb kept in climatically-controlled conditions in their basement and pop it on top of a piece of grilled salmon.

But even then, they’re not trying to fool us into thinking that the world’s cheapest piece of chicken is somehow nutritious, like supermarket ready meals try to do. They just believe that the flavour profile of some obscure herb is exactly what that piece of salmon needs to make it perfect. Who knows, they might even be right.

Mostly, though, the chefs other chefs really respect are ones who can make a delicious meal out of just a couple of ingredients.

That takes real skill. Those chefs can’t overcompensate for using poor ingredients or inadequate technique by adding hydrogenated vegetable oils. Their cooking has to stand on its own, the function of ingredients and technique only.

And that’s hard. Much harder than cooking with 47 ingredients. Because there’s nowhere to hide – your ingredients, your technique, your sense of taste has to be absolutely on-point every time.

All the while dealing with the inherent variability of your ingredients – every egg is not exactly the same size as every other egg, for example. For most of us, our level of skill in the kitchen means that will probably be the least of our problems, for a top chef working with just a few ingredients, that can make all the difference.

Take the pasta dish cacio e pepe, for example.

A literal translation (sorry to any Italians reading this) is “cheese and pepper”. Cacio e pepe is a dish from the Lazio region of Italy (although not every Italian sees it quite like that…long story…) and it is literally made from pasta – often spaghetti – cheese, and pepper.

How hard can that be, you might think – there are only three ingredients.

Alternatively, you might be wondering how cheese, pepper, and spaghetti together even produces a creamy sauce and tastes nice. This dish is a million miles away from the tomato-based pasta sauces most people in the UK and further afield would probably think of as “Italian cooking”.

Well, it turns out cacio e pepe is delicious.

But making it well – which I can’t, by the way – is really, really hard because you can’t just lob in another tin of tomatoes if it all goes horribly wrong and still end up with something semi-edible.

What I can tell you, though, is that there are a few key parts of this process:

1. First probably a fairly well-known one – al dente pasta. Very few of us can reliably produce that (I manage it about 1 in 10 tries, personally), but getting that right is key.
2. Then the pepper isn’t just any old pepper you’ve got in the back of a cupboard – it’s fresh peppercorns, warmed gently in a dry pan, and then crushed with a pestle and mortar until the consistency is just right.
3. Next, it’s the cheese. It’s got to be pecorino romano. Got to be. Never use parmesan which, despite being broadly similar in concept, is an entirely different product – using parmesan in cacio e pepe for an Italian seems to be like putting Coca-Cola into 25 year-old malt whiskey is for a Scottish person. So don’t do it unless you’re deliberately trying to cause offence.

But that’s not the hard bit. Although none of this so far is easy.

The really hard bit is ending up with a smooth, creamy sauce which evenly coats the spaghetti instead of a plateful of dry pasta sprinkled with unappetising lumps of dry, un-melted cheese.

Doing that requires an enormous amount of skill on the part of the chef to manage the temperature, make sure the sauce has the right consistency, and the flavours come through as they should.

If you’re not a professional chef, making cacio e pepe is one of the hardest things there is to cook. Yet it only needs three ingredients.

Making a supermarket ready meal, by contrast, is easy. Just load all the ingredients up in a massive hopper and the machinery will take care of it all, relying on the salt, sugar, flavour enhancers, and goodness knows what else to produce something that’s relatively palatable despite being fundamentally beige and unexciting.

KPIs should be like cacio e pepe

Most KPI reports are like a supermarket ready meal’s ingredient panel. Throw enough things in there to make consumers believe they are eating a relatively palatable product and you’re probably OK for another month.

It’s much harder when you’ve only got a handful of KPIs, because there is nowhere to hide.

With 47 different KPIs, you can almost certainly find something that’s going in the right direction to use as a counter when you’re taken to task for something that’s going in the wrong direction.

With just three KPIs, you’re getting the unvarnished truth.

Every time a see a KPI report with 47 different things on it, I know I’m dealing with a business which is at least unfocused, because it’s simultaneously pursuing 47 different things of broadly equal importance. That means each one of them is getting worked on for only about an hour a week – hardly a recipe for significant, and rapid improvement in any metric.

In addition, the organisation is probably, on some level, delusional. Because their organisational culture is almost certainly allowing underperformers on 40 of their metrics to boast about the 7 they’re doing OK on, and for that to be perfectly fine within their management practices.

It’s one reason AI leaves me cold. Sure, it might be very clever, and it might be able to produce 47 different reports in the blink of an eye. But, like the ready meal producer using weird and wonderful ingredients to cover up for the fact that their product is fundamentally of pretty low quality, the real reason people want 47 different reports is to divert attention away from the things that really matter when they go badly wrong.

I’ve got a lot more respect for a business that can be run on just three KPIs than I have for one which has an elaborate KPI reporting system spewing out reams of data nobody will ever read in its entirety every week or every month. (Or even worse, one that builds a real-time data dashboard that nobody ever looks at.)

With cooking, adding another 44 ingredients to cacio e pepe won’t make it better – usually quite the opposite.

So it is with KPI reports. More ingredients usually means what’s inside is much worse than the person doing the reporting would like you to think it is.

It’s a smokescreen. Those extra ingredients are probably about as bad for your business health as the extra ingredients in your ready meal are for your physical health.

You don’t need more KPIs. You need the equivalent of a skilled chef to make your business run with just three ingredients, cacio e pepe style.

Don’t mistake “more” for “better”. It rarely is.

The great thing about business is that business is really about people, much as tech folk would like to convince you otherwise.

There’s never been a truer adage than “people buy from people”, for example.

Or the well-worn advice that people are more likely to do business with those they know, like, and trust.

These are entirely human judgements and, like it or not, almost entirely subjective.

It’s fair to say our tech overlords occasionally do a half-decent job of faking all of those things – certainly good enough to fool some of the people all of the time – but, like all fakery, eventually the chickens come home to roost.

There really is no substitute for humanity in business.

You can pretend otherwise, and believe everything is just about 1s and 0s. But you’re only fooling yourself.

And even to the extent it works, it’s vastly more expensive and resource-intensive to fake things than to be human. Which means the fall from grace, when it comes, it much harder and deeper than it would have been otherwise.

If you doubt me, consider the amount of effort Enron put into trying to maintain the illusion of being successful – up to and including committing outright fraud, for which several people went to jail – when they could have done very nicely out of just being honest about their business.

And if you’re not old enough to remember Enron, stay tuned. I’m expecting a similar dynamic to present itself in the course of this autumn’s slate of IPOs for AI companies.

But Enron’s failure was fundamentally a human failure, not a business one. The human failure came first, the business failure followed.

By the same token, extraordinary humans can make great business decisions. Sure, it requires some creativity, some ambition, some hard work. And humans are flawed, of course, but they’re several orders of magnitude less flawed than tech solutions.

Not every decision a human makes is a good one. But when humans make good decisions, a whole new world opens up.

So today, I’d like to highlight three great decisions made by humans as an example of this phenomenon.

As it happens, they are all women. And, as it happens, they are all examples from the music industry. But every one of these are phenomenal decisions – brave, creative, insightful.

Decisions you’d never make based on a spreadsheet.

These decisions came from the heart, and they are decisions only a human could make.

All three are the opposite of logical. There were millions of really good reasons to do the exact opposite, yet these three women zigged when the world was telling them to zag.

I admire them all immensely.

Taylor’s version

The most recent example is from Taylor Swift – someone so famous that I don’t need to explain who she is, even to people who aren’t fans of her music.

There is a little twist to this tale, even if you think you already know it, so stay tuned.

As a teenager, Taylor Swift signed a recording contract in which the rights to her master recordings belonged to her record company. In fairness, that’s not an entirely unprecedented arrangement in the music industry.

In the blink of an eye, though, Taylor Swift went from being a teenager writing songs on the bedroom floor in her family home to being one of the biggest recording artists on the planet.

After a few years she was so successful, Taylor Swift wanted to buy the master recordings so she owned her entire body of work. However, as a result of some murky, and much-disputed, events (which are not essential to the point of this story) that didn’t happen.

Her record company was bought out by a famous music industry manager, and soon after re-sold to a private equity outfit who proceeded, as private equity companies do, to sweat the assets of the business they’d bought.

Determined not to be bested by her record company, Taylor Swift then re-recorded all her early albums in what became known as “Taylor’s Versions”, so that she now owned the masters of her “Taylor’s Version” recordings of her back catalogue.

With a legion of adoring fans, sales of her original recordings plummeted and sales of the Taylor’s Version recordings soared, even among people who had previously bought the originals.

I don’t know what happened in detail as that isn’t publicly available information, but I think it’s safe to say that value of the income-producing assets the private equity firm bought tanked and their investment was no longer the gold-plated opportunity it had initially appeared to be.

There are two little twists to this story.

The better-known one is that, in 2025, some five or six years after the original buyout of her record company went through, Taylor Swift did come to an agreement to buy her original master recordings back.

By taking a stand, thinking creatively, and being determined not to be beaten, Taylor Swift got what she wanted in the end. All credit to her for demonstrating some top-notch human decision-making there.

The other twist, which I only discovered recently, is that American Idol winner Kelly Clarkson had a hand in this too. Back in 2019 she tweeted to Taylor Swift that she ought to re-record all her songs so she would own the masters, and offered her support.

That’s not to say that Taylor Swift didn’t have the same idea independently – I have no idea one way or the other. And to give Kelly Clarkson full credit as a human being, she has since acknowledged in interviews that Taylor Swift would probably have come up with the same idea herself anyway, so she isn’t looking for any credit.

Wherever the idea came from, though, Taylor Swift executed it to perfection and saw through a course of action that very few people would have taken.

As business moves go, what Taylor Swift did is one of the best ever.

All because she thought like a human, not a machine. And because she said “no” when it would have been so much easier just to say “yes”, and take whatever crumbs were on offer from her record company.

Dolly Parton

Dolly Parton is legendary in the world of country music – somewhat less so outside it. She is, however, one of the best-selling musical artists of all time. Along the way she has picked up 11 Grammy awards and written some tremendous songs – I can’t listen to “Coat of Many Colours” without finding a tear in my eye, just for starters.

Dolly Parton started performing as a child, had some success writing songs for other people along the way, and some modest success in her own right as a singer.

In her early 20s, Dolly was invited to join Porter Wagoner’s immensely popular weekly country music TV show, which gained her considerable public recognition. But she was very much playing second fiddle to an established star and her solo career took a back seat for a while even though a series of duets with Wagoner did well in the country music charts.

She did keep writing songs, though. Standards like “Jolene” were written about this time.

Eventually Dolly Parton decided life as the second act in a duet wasn’t really what she wanted, and spilt with Porter Wagoner, even though I’m sure she could have had a very decent long-term career had she stayed.

That was human decision number one. The logic might well have said “stay”. The heart said “go”.

Human decision number two came along shortly after.

In 1975, Dolly Parton wrote and recorded a song called “I Will Always Love You” about her split with Porter Wagoner, which went to Number One in the country music charts.

Particularly if you’re a Brit, you almost certainly don’t know that version of the song.

But, wherever you are in the world, I can guarantee you know Whitney Houston’s cover for her 1992 film “The Bodyguard”. That version spent 14 weeks at the top of the Billboard Hot 100 in and sold over 25 million copies worldwide.

What is not so well known is that back in the mid-1970s, soon after Dolly Parton wrote “I Will Always Love You”, she was approached by Elvis Presley’s manager to see if she would let Elvis record her song.

Now, at the time, there were probably few better outcomes for a songwriter than having Elvis record one of your songs. And, to be fair, I think he’d have made a tremendous version of Dolly’s song.

The only problem was, the standard deal when Elvis recorded a song was that he’d get half of the publishing royalties.

Dolly Parton reached the very human decision that she wasn’t prepared to sign away half the rights to the song she’d written and said no.

The easy, logical answer would have been to agree to Elvis’s terms. Dolly Parton took a human decision.

I know this is speculation, and involves 20/20 hindsight, but if Elvis had recorded the song he’d probably have had a decent hit with it. It is, however you look at it, a great song.

But I doubt the producers of “The Bodyguard” would have chosen such a well-known song as the centrepiece of their Whitney Houston film – they needed a great song, but not one that everybody knew already.

So Dolly Parton traded a relatively certain million-seller from Elvis for an iconic performance by Whitney Houston and sales of over 25 million copies. Even though at the time she turned Elvis down she had no way of knowing that, 20 years later, someone would want her song for one of the biggest motion pictures of the 1990s.

Taking a human decision generated so much more for Dolly Parton over the year – critically, musically, and financially – than the logical decision she could have taken in the mid-1970s.

As business moves go, Dolly Parton’s human decision was one of the best.

Andrea True

At some level, you are probably familiar with Taylor Swift and Dolly Parton – however superficially.

With Andrea True, that’s much less likely. Unless you’re of a certain age, in which case you’ll certainly remember her biggest hit record. But more on that in a moment.

Andrea True had a very musical mother, and had studied music herself, but wanted to become an actor, and moved to New York from her home in Nashville. Along the way she kept her singing career going in pubs and clubs as a way of helping make ends meet.

She didn’t get the results she hoped for in her acting career, but in the mid-1970s she was hired by a real estate business in Jamaica to feature in a series of TV commercials.

After shooting the commercials the Jamaican government had one of their periodic fallings-out with the US government and prevented people taking money out the country. Andrea True would have had to either forfeit her fee or spend the money in Jamaica before going back to New York.

Instead she took a smart, but very human, business decision.

Andrea True contacted a friend in the music industry who had an instrumental track he’d been working on and used the fee from her commercial work it up into a something more like a finished product with the help of some Jamaican musicians. That music could then, perfectly legally, leave the country.

Back in New York, she and her friend, Gregg Diamond, worked on the song and Andrea added her lyrics to the instrumental track. Along the way the song was turned into a disco anthem and the result was the 1976 UK and US Top Five hit “More, More, More”.

This piece of shimmering disco pop was a staple of the dance floors for a large part of the mid-to-late 1970s and quite rightly features in Billboard Magazine’s 2025 list of “100 Best Dance Songs of All Time” at Number 36.

If you’re not familiar with the song, don’t worry, I’ve got you covered – you’ll find a link to it below.

But before we get there, let’s just reflect on Andrea True’s very human decision that there was no way she was going to let the Jamaican government take the money she’d worked for. It took some “outside the box” thinking and a degree of grit and determination that all good ideas take to come to fruition.

Logically, it would have been easier for Andrea True to book herself into one of Jamaica’s nicest hotels and spend a couple of weeks in luxury, thanks to the fee she’d earned from her commercials, after she found out she couldn’t take her money out the country.

Instead, she used her human powers of decision making to turn the potential loss of all her money into a Gold record in the US and an international smash hit.

Well done to Andrea True – that was a great business move, and vastly better than just spending her money on a nice hotel break, thanks to her human, rather than logical, decision.

What does this mean?

There’s no real moral to these stories apart from the observation that a logical decision is often the easy path. Doing what people would expect, being able to express your decision in seemingly-objective terms, conforming to the norms are all the result of logical decisions.

Most of the time, being logical won’t make you broke.

But being logical also means you’ve likely given up a huge percentage of any potential upside.

It would have been logical for Taylor Swift to shrug her shoulders when her record company went against her, and just keep going with her career.

It would have been logical for Dolly Parton to let Elvis record her song and give up half her royalties.

It would have been logical for Andrea True to have a nice holiday in Jamaica instead of recording a global smash hit.

All of those decisions would have been entirely logical. Completely defensible.

And, at the same time, they would all have given up an upside beyond their wildest dreams.

While logic has a role, the sort of human decisions that only humans can make – often seemingly “illogical” at the time those decisions are made – are where all the upside in life is, inside or outside the music industry.

However these three women from the music industry have, between them, made some of the best business decisions of all time.

We could all learn a lot from them.

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Music mentioned

In case you got this far and aren’t familiar with any of the songs referenced above, here they are:

Taylor Swift “Shake It Off (Taylor’s Version)”

Dolly Parton “Coat of Many Colours”

Dolly Parton “Jolene”

Dolly Parton “I Will Always Love You”

Andrea True Connection “More, More, More”

If you run an organisation of any sort – business, public sector, not-profit, or anything else – you want your organisation to be efficient, right?

You might think this is an odd thing for a CFO to say, but no. You don’t.

What you want is the best return from your organisation’s efforts, whether you think of that in terms of revenue growth, profit margins, or return on assets employed in a business setting, or people helped or missions delivered in the public sector and non-profits.

It’s tempting to think that “more efficiency” will necessarily result in improved outcomes, but that’s not true.

Someone can be very efficient at trying to sell snow to Eskimos, but Eskimos already have plenty of the stuff and don’t need any more of it. Becoming even more efficient in their sales processes isn’t going to help.

Someone else might spend a lot of time, effort, and money trying to sell new cars to people who can’t afford the payments. No matter how efficient they become, they won’t sell many cars.

Yet another person might devote their business to selling premium wagyu beef steaks to a list of members of the Vegetarian Society. No amount of efficiency is going to shift their warehouse full of steaks.

So, if efficiency on its own isn’t enough, what should we aim for?

Outputs beat inputs

I’m glad you asked – you should always aim for effectiveness, not efficiency.

While efficiency, in and of itself, is not a bad thing, it’s a second order question once you’ve developed an effective way of reaching a goal or solving a problem. It’s not where you start.

Both are important for well-run organisations, but they serve entirely different purposes. Getting the two confused, as many people do, is the cause of a large proportion of today’s business and societal ills.

One of the key differences is that effectiveness is an output measure, while efficiency is an input measure.

To take one of the examples above, what I mean by that is the effectiveness of a car sales organisation can only be determined by how many cars they sell to paying customers.

If you work out a way to do that, then by all means see how you can make your sales operation more efficient. Maybe there’s a role for a new CRM system once sales reach a certain level.

But, at the outset, the bottom-line benefits of a CRM will be marginal. The problem here is that the business model is broken. No amount of efficiency will help someone trying to sell products to people who can’t afford to buy them.

Don’t be tricked

Recently I’ve seen people describing, for example, the number of sales calls a salesperson makes in a day, as “an output measure”…which, on the face of it, sounds like a measure of effectiveness by the definition above.

It might be a measure of a salesperson’s personal productivity, but that’s an efficiency measure, not an effectiveness measure.

The key point here for business leaders is that a large number of your people can, with some justification perhaps, claim to be highly efficient. Your job as a business leader is to look beyond that and ask yourself whether, irrespective of the number of calls a salesperson makes in a day, trying to sell new cars to people who can’t afford them is a good idea.

While you’re thinking about that, keep in mind one of my favourite business quotes from Peter Drucker “There is nothing quite so useless as doing with great efficiency something that should not be done at all.”

When you put the focus on your outcomes (effectiveness measure) before you think about inputs (efficiency/productivity measure) you’ll make much better business decisions.

But, to be fair to most people in your organisation, you can only take a view on outcomes at, or close to, board level because that’s the only level where you can see the full end-to-end process which leads to a successful outcome – eg selling a car.

If you employ a room full of telephone salespeople whose job it is to make calls all day long, don’t be surprised if they make a lot of calls, and spend a lot of time trying to convince you that they’re all doing a great job, even if they aren’t making any sales.

“I’ve been working so hard, boss, but people just don’t want to buy a new car at the moment. But hey, I made 400 phone calls this week, so I’m working like crazy to bring those sales in!”

Don’t blame the telesales team for that. The responsibility lies much higher up the organisation. When people there are mixing up the concepts of effectiveness and efficiency, the organisation is sunk, no matter how many calls a day each salesperson makes.

Start with the customer

To run an effective organisation, you have to start with your customer. Their needs, wants, and desires.

Try to do anything which is not addressing at least one of those agendas, and you’re pushing water uphill. That always means your organisation is working much harder, and spending much more money, to get to the same objective than a competitor organisation who thinks about the problem more creatively.

Effectively, organisations who try to power through regardless are using money to compensate for short-changing themselves in the thinking process. That’s always a losing proposition for your bottom line.

It’s like judo – in that sport, you use your opponent’s momentum against them. That’s why a quiet, skinny person with little in the way of visible musculature can defeat someone built like a heavyweight boxer.

In business, creativity performs a similar function.

You can spend a little bit more to generate a brilliant idea or you can spend 10x more in advertising media costs to get some level of recognition across your target audience for an insipid, me-too idea.

All things being equal, I know which one I’d be doing.

But away from the obviously creative areas of your business, the same applies to much more mundane business processes.

You can either solve your customer’s problems with creativity or you can spend vastly more money to get them to do things the way someone in a conference room somewhere decided ought to be done, having never spoken to a customer or used the product themselves.

The classic example

A good example of this in the real world is how difficult many organisations make it for customers to give them money.

There are rare exceptions where there is a legal or regulatory requirement to conduct some checks on your customers before dealing with them, such as the legal and financial services industries’ KYC (Know Your Customer) rules. But most businesses aren’t operating in that arena.

Not so long ago I was dealing with a business (or trying to deal with them, more accurately) which never responded to enquiries via the contact form on their website or to telephone calls made to the number on their website.

Take a quick guess how many sales they made to me?

Admittedly that’s an extreme example, but there are plenty of other examples closer to that end of the spectrum than the “making it easy for your customers” end of it.

A while back, in order to buy a relatively humdrum item for my house, I had to complete a form requiring all manner of demographic information before I could set up an account and…only then…be allowed to buy from this business.

On this occasion I persisted – partly out of morbid curiosity, partly because I was under very strict instructions to buy exactly that item from exactly that store.

Of course, I knew exactly what they were doing. I was essentially pre-seeding their automated marketing campaigns for them, so they could spam me forever more with personalised emails.

I don’t know what their drop-out rate was, but any process requiring a customer to input all manner of personal information is going to have a higher drop-out rate than a process which doesn’t. So straight away they are giving up sales they might otherwise have had, which, off-hand, doesn’t seem like the smartest strategy to boost a business’s bottom line.

The process brought to mind a question old-school direct marketer Dan Kennedy used to ask – are you finding a customer to make a sale or are you making a sale to find a customer?

To horribly paraphrase Dan’s very worthwhile teaching, his recommendation was generally to make it easy for someone to buy at least some sort of entry-level product which you could use to establish a base to grow from, rather than to spend a huge amount of time, energy, and money to find a perfect customer and then try to sell them something.

In other words, make it easy for customers to give you their money.

Once you had a customer, you could build the relationship out further, but at least you had established a relationship, built up a degree of trust, and demonstrated some added value along the way before you tried to sell them more products. All the subsequent sales were easier because of the positive experience you had established in the process of making the first sale.

While that approach might not be appropriate in every sales scenario – if you sell nuclear power plants, you probably can’t sell an entry-level product first and then try to persuade your customers to buy a nuclear power plant on the back of that – it works well in a remarkable number of settings.

It’s not just about sales

This article isn’t just about making sales, though. It’s about enhancing your bottom line. The same principle applies in every other area of your operations too.

You can, for example, buy cheaper raw materials or sub-assemblies for your products than whatever you buy now. However it’s likely that strategy will lead to more quality complaints, more returned products, and higher costs in your customer service department while they apologise for the substandard products which were delivered to your customers.

Generally, the best return for your bottom line comes from buying good quality raw materials and sub-assemblies which don’t result in quality complaints, refunds, and inbound customer service calls.

And don’t be fooled into putting all your customer service online and think you’re saving money. That does nothing to persuade customers your products aren’t shoddy. All you’re doing is making it less and less likely they will ever buy from you again – if there’s one thing worse than buying a shoddy product, it’s buying a shoddy product from a company where nobody cares enough to put their customers’ problems right.

Equally, you can track 1,000 data points and still run a business that its customers have very little time for, or you can track the only three things your customers get obsessive about and make sure you deliver those 100% of the time.

Whatever the cost of all that data management and tracking might be, you can save most or all of it if you just focus on what your customers care about.

Don’t mistake your notion of what makes you more efficient trump the things that make you effective in your customers’ eyes. While efficiency delivered in the context of doing things which make you effective is no bad thing, just wildly pursuing efficiency on its own terms more often takes away from your bottom line than adds to it.

I know that sounds like it shouldn’t be true, but it is – no matter how much third-rate accountants might try to convince you otherwise.

Being effective is about building value in your customers’ eves.

Being efficient is about impressing whoever sits above you in the organisational hierarchy, irrespective of – and often in spite of – the impact it has on your customers.

Whenever you have a choice about delivering on an internal agenda – efficiency, for example, or any one of a raft of internal policies and procedures – or becoming more effective in your customers’ eyes, always go with the latter.

Not a single customer gives a fig for your internal policies and procedures. All they care about is how well you serve them.

And, in the end, the valuation of your business and the state of your bottom line depends entirely on how positively your customers feel about the service they receive.

If in doubt, prioritise that. It’s almost always the best way to boost your bottom line.

You may not have heard of the bus stop problem before. Possibly because I’ve just invented the concept.

However, bear with me as you might spot some things you or your company could do differently, boosting your bottom line in the process.

To explain what the bus stop problem is, though, I need to take you back to 1966, when a song called, surprisingly enough, “Bus Stop” was a big hit for The Hollies.

Nowadays, “Bus Stop” isn’t the Hollies’ song most people would instantly think of. That’s much more likely to be either “He Ain’t Heavy, He’s My Brother” or “The Air That I Breathe” from the early 1970s.

But, in its day, “Bus Stop” was a decent hit, reaching Number 5 on both the UK and US charts.

“Bus Stop” was written by a 20-year old Graham Gouldman, later of 10cc, and is quite a sweet story of a chance meeting turning into true love. It starts like this:

“Bus stop, wet day, she’s there, I say

Please share my umbrella

Bus stop, bus goes, she stays, love grows

Under my umbrella”

As well as being a very neatly written set of lyrics, the harmonies on “Bus Stop” are every bit as tremendous as you’d expect from The Hollies.

But the other key passage is probably this:

“Came the sun the ice was melting

No more sheltering now

Nice to think that that umbrella

Led me to a vow”

You can probably imagine how the rest of the story goes, although there’s a link to it below if you’re not familiar with this classic piece of 1960s pop.

But, in summary: a chance meeting at a bus stop turned into romance and, ultimately, marriage.

The bus stop problem

Unless you have a heart of stone, I think we can agree “Bus Stop” tells a sweet story.

But if you have an MBA from an Ivy League college, or if you work in tech, this whole episode will instantly strike you as inefficient and capable of significant process improvement.

First of all, the fact that The Hollies’ lead singer, Allan Clarke tells the story of just wandering around aimlessly and bumping into a girl entirely by chance suggests a serious lack of strategic thinking on his part.

Surely, our friends with Ivy League MBAs or who work in the tech industry would argue, this is a ridiculous way to find a girlfriend. What you need to do is set a clear strategic objective and then develop a series of SOPs to achieve your goal, which you can track by collecting and reporting data against KPIs on a daily, weekly, and monthly basis.

So let’s look at how they might go about that.

Since The Hollies were from Manchester, let’s use that location to flesh out their strategy.

A bit of research tells me there are about 12,000 bus stops in Manchester, which is a big number. If someone working in tech was going to try to find a girlfriend at each one of those, and only visited one of them each day, it would take them about 32 years to visit them all.

Clearly, going at that pace is for losers when you’re used to “moving fast and breaking things”? Obviously, they need to increase activity levels.

In the UK bus stops are about 300-400 metres apart on average, further research tells me. So if our lovelorn tech pal was prepared to walk, say, 5 miles a day, they could visit about 20 bus stops a day, on average. That would reduce the elapsed time down to just a couple of years, which sounds more do-able.

But wait!

Putting aside for the moment how creepy an idea this is (very on-brand for the tech industry, mind you…) a strategy of approaching random women at bus stops in Manchester with an umbrella only works on days when it’s raining. Inviting people to shelter under your umbrella on days when it’s not raining is either going to get you sectioned or arrested.

Historic weather data says it rains on 140-150 days a year in Manchester, which means that for about 200 days a year, the umbrella idea won’t work.

So we’re back up to 4 years of searching, or thereabouts, if our tech pal walks 5 miles a day with their umbrella, visiting an average of 20 bus stops a day only on days when it’s raining.

To complicate matters further, I suspect that some of those rainy days will be at weekends, when people might be less inclined to use the bus because they don’t need to get to work. They might choose to stay at home on a rainy Saturday instead of hanging around bus stops hoping that someone with an umbrella to share might come along and stand next to them.

All things being equal, I wouldn’t be surprised if our tech pal’s hit rate is a lot lower on wet weekend days, reducing their chances of success.

So maybe a better strategy is for them to keep their search to weekdays only, in the hope of catching legions of commuters either on their way into work or their way back home again. That’s when the maximum number of people are likely to be found somewhere near a bus stop, improving the efficiency of this process dramatically.

Taking weekdays only, and assuming Manchester’s 140-150 days of rainfall occur evenly across the days of the week, that means there are 52 weeks in the year, and 5 days a week while people are at work to play with. Approximately 40% of those working days, or two days a week, will be rainy, and therefore viable candidates for our tech pal’s umbrella strategy.

That, in turn, gives us 104 days a year (2 working days a week for 52 weeks of the year) which, at 20 bus stops a day, means it will take about 6 years for our tech pal to get around them all.

Which sounds like a long time.

Hyperscaling

Thankfully, the tech industry has a way of dealing with this. You take a fundamentally stupid idea and throw money and resources at it, in the hope that you get lucky and something vaguely like the result you were hoping for pops out the other end quickly enough for you to declare victory before the VC money runs out.

This is called hyperscaling.

Since walking is inefficient, maybe our tech pal should get a taxi from one bus stop to another, minimising their walking time. That means they can double the number of bus stops they visit on days when it’s raining.

According to Manchester City Council, a 10 mile taxi ride (i.e. double our original 5 mile target) costs about £30. So if our tech pal runs this strategy on each of the 104 weekdays a year when it’s likely to be raining, that would cost about £3,000 a year.

But wait. That fare for a 10-mile journey isn’t quite right. It significantly understates the true cost.

Believe me, this won’t be the first time a business plan based on data that’s complete baloney has floated across a VC’s desk, but maybe our tech pal should try to make sure their plan reflects at least some approximation of reality.

So let’s think about this again.

On the assumption that buses in Manchester come along every 20 minutes on average (no idea if that’s the right number or not – it’s just a guess), then our lovelorn tech pal needs to hang around each bus stop for at least 10 minutes or so before each bus is due as that’s when they are most likely to find other people waiting for a bus.

With that strategy, they would need to keep the taxi waiting for 10 minutes at each bus stop at a cost of about £4 per bus stop, again according to the Manchester taxi rate card. Multiply that by 40 bus stops a day, now that we’ve upped the coverage to 10 miles a day, and that’s an extra £160 per day, or almost £17,000 a year, just in waiting time.

Add that to the taxi fare, and assuming our tech friend doesn’t take a taxi to the first bus stop of the day or one back home again at the end of their adventures each day, and they need to reckon on spending about £20,000 a year in their quest to find a girlfriend.

However there’s another problem with this model.

It assumes the bus timetables work in such a way that our tech friend can get around them all in 10-minute intervals, which is unlikely to be true. We probably ought to double the waiting time allowance to allow for some inefficiencies where our preferred taxi route and the Manchester bus timetabling system do not allow maximum efficiency in terms of our taxi expenses.

So let’s call that a £40,000 a year cost over, potentially, a three year period at our increased 10 miles/40 bus stops rate on rainy days.

Which is a potential £120,000 over a three-year period if our tech pal needs to get round every bus stop in Manchester before someone agrees to shelter under their umbrella.

It could be less than that, of course. Maybe at the very first bus stop our tech pal bumps into the love of their life and they’ve done the whole thing for under a tenner.

But the odds are against that.

The odds

Leaving aside the fact that this whole thing is a bit odd, the odds of approaching a random human at a bus stop on a wet day and them agreeing to shelter under your umbrella are infinitesimally small just for starters.

The odds of that person then turning out to be the love of your life are so small that, even across a pretty big number like 12,000 bus stops, you’d need a microscope to see the chances of success.

Now, in sweet songs from the 1960s, and Jennifer Aniston romcoms, that doesn’t matter much. There, the concept is being used purely as a creative device. We’re not trying to bring it to fruition ourselves.

But in the real world – something that doesn’t often feature in tech industry business plans – the “approach random humans at bus stops” strategy isn’t very likely to pay off.

If you work in the tech sector, this won’t trouble you much, because people working there are mostly delusional. Or on drugs, which amounts to much the same thing, in practice,

In tech, the prevailing belief is that provided you throw enough resources at any problem, success is pretty much assured – all you need is the data to demonstrate there’s the potential of a positive outcome and diligent activity tracking.

To be able to do that, our tech pal probably needs to build some custom mapping software and have a way to track which of Manchester’s 12,000 bus stops they have already visited.

Some route planning software is probably also required, to make sure they’re being as efficient as possible as they navigate your way from one bus stop to another and minimise their taxi costs. It’s the least their investors expect.

They’ll also need some report writing software in order to keep the investors happy and to enable them to prepare pretty charts and graphs to demonstrate how hard they’re working towards the end goal.

And, of course, a computer to run this on, together with a budget for tokens because if they’re insane enough to try this strategy, they’re probably also insane enough to use AI to help them.

I don’t know what all this would cost, but let’s add in £10,000 a year on top of our existing costs to give us some idea.

We’re now up to an investment of £150,000 for our tech pal to stand a chance of finding a girlfriend.

The key point here – in fact pretty much the point of this entire article – is that spending £150,000 in return for an infinitesimally small chance of success isn’t smart. Just because you can identify some data, work it into a plan, and throw financial and other resources at it, that doesn’t mean this is a good idea.

And, like most of the tech industry’s ideas lately, the whole concept is creepy as hell. Just writing out the plan above makes my skin crawl.

Furthermore, even with all that data – and more that you’ll pick up from your route-mapping software and monthly reporting decks – this has done absolutely nothing to increase the odds that someone you approach will agree to shelter under your umbrella.

You’re dealing with odds no better than The Hollies’ chance of walking up to a random bus stop and offering a gesture of kindness to someone standing there in the rain.

While The Hollies’ chances of ending up with “…a sweet romance / Beginning in a queue…” are low, they didn’t spend £150,000 trying to find a sweet romance. They just went to catch a bus one day when it was raining and happened to have an umbrella with them.

In fact, The Hollies’ chances are probably better than our tech friend’s because you’re very likely to end up on a register, or in jail, if you spend 3 years propositioning women at every bus stop in Manchester every day it rains.

Drucker’s view

A lot of tech is like this fictional example.

I prefer the late, great Peter Drucker’s view – “There is nothing quite so useless as doing with great efficiency something that should not be done at all.”

The mere fact that you can compile a superficially plausible proposition, backed with data, and with some impressive-looking graphs and charts, does not mean that you’re doing anything worthwhile. If you work in tech, you probably think those two are synonymous. But they’re not.

You may be pursuing your own personal fantasies, but frankly in this example our tech pal is just being an obsessive creep who intrudes into other people’s lives in pursuit of their own personal gratification. (In fairness, you could say that about pretty much every tech CEO, so this is a critique of the industry as a whole, not a particular individual.)

Much like AI, this “bus stop project” doesn’t deserve to succeed because of the societal harm it causes and the monumental waste of money required to stand a one-in-several-billion chance of the plan actually working.

Along the way, you’ve creeped out most of the women in Manchester and you’ve probably seen the inside of a police station holding cell on more than one occasion.

This will come as a surprise to Ivy League MBAs and people working in tech, but no matter how excited you are about the outcome, how many stats you have showing what a good idea it is, and how beautiful your project plan and progress reports are, there are some things which are better not done at all.

The tech person in our scenario has burned through £150,000 in cash, made people feel unsafe in pursuit of their own personal gratification, and almost certainly still not achieved their objective, even though a lot of data analytics and graphs have been compiled along the way.

So next time someone comes to you with an investment proposal, consider the financial and the non-financial implications of their idea.

Surprisingly often, the best course of action for your bottom line is to do nothing. It genuinely can be cheaper to pay someone to do nothing than to let them make a jumbo sized dent in your cash flow for no bottom line return.

While doing nothing might not seem quite as satisfying as taking action, a lot of activity for zero outcome, no matter how pretty your charts and graphs are, is a monumental waste of time and money.

Too few organisations realise that activity alone as a metric is profoundly harmful to their bottom line. It’s entirely possible to be really busy whilst having a negative impact on the bottom line, as we’ve seen above.

One of the fastest ways to create a positive bottom line impact is to take Peter Drucker’s advice and just to stop people doing pointless tasks. That includes closing down crazy ideas with a low chance of success before they take up too much time and money.

Sadly, in too many organisations, that’s a lot rarer than it probably ought to be.

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Finally, as promised, here in all their glory, are The Hollies, singing “Bus Stop”…

If you know me even slightly, you’ll know I’m a big music fan. So much so that a colleague introduced me to someone recently as “a huge music nerd” – which I took as great compliment, given the equally-huge musical nerdiness of the person making the introduction.

But beyond my occasionally nerdy tendencies when it comes to music, I firmly believe that music (and the Arts more generally) can teach us a lot about business.

Today’s article is about unsung heroes – the people without whom some of the best songs ever written would not exist. Yet their names aren’t (huge music nerds aside) on everybody’s lips – specifically the people who wrote the words to the songs we all know and love.

Think about it – we can hum along with a melody, of course. But we can only sing along if there are some lyrics alongside the music.

And even if we don’t get the words quite right (quick Boomer reference: “My ears are alight”…IYKYK) we still sing along regardless. Catchy tunes are always welcome, but it’s generally the words that make great songs great.

However, the names of people who wrote the words we sing along with are often all-but invisible, with the person who composed the music or the person who gave the iconic performance of the song are generally much better-known than the humble wordsmith who wrote the words we sing with.

As a simple test, with some very simple lyrics, try imagining “YMCA” without the words. It’s an iconic, hook-laden, joyous, danceable track that gets everyone up on the floor to do the dance moves. It’s still a great tune. But nobody is singing along…and they’re probably not even getting up from their chairs to dance.

And that’s just four letters of the alphabet. Imagine what a whole song can do when a great lyricist is involved, with the whole alphabet at their disposal.

Quick business aside – I’ll keep this brief. Almost anything worth doing in business is a multi-dimensional activity. It’s one reason most tech solutions fail – their programming is based entirely on surface-level logic, which assumes humans handle one activity at a time sequentially when, in fact, we handle dozens, if not hundreds, of simultaneous inputs in parallel, each of which we apply in a range of intensities which vary according to how we feel, minute-by-minute.

That’s something the world’s most powerful computers are unable to do. Or, in my view, will ever be able to do.

So it is with music. It’s not just the music, important though that is. It’s the words. It’s the musicians. It’s the backing singers. It’s the indefinable groove that great players bring to their playing – something that goes so far beyond reproducing the notes on a page, ordinary mortals can’t quite figure out how they’ve done it.

And so it is with your organisation. Whether you realise it or not, your organisation runs largely – perhaps almost entirely – on a range of unsung heroes without whom everything would fall apart. People whose names don’t make it into the board minutes, and who may be almost invisible on your organisation chart. Yet they are the glue which holds your organisation together.

If this article inspires you at all, I’d urge you to make it your business to find the unsung heroes in your organisation and make sure they know you couldn’t do it without them.

Lorenz Hart

This article was inspired by a Sammy Davis Jr performance I heard recently. He was singing “My Funny Valentine” – composed by Richard Rogers, with lyrics by my all-time favourite lyricist, Lorenz Hart.

Sammy Davis Jr, an immense talent in his own right, introduced his performance as “a song by Richard Rogers, one of our finest composers”. The second part of that is absolutely true – Richard Rogers is one of the finest composers who ever lived.

But the first part is not. Beautiful music though it is, Lorenz Hart wrote the words we sing along with, not Richard Rogers:

My funny Valentine

Sweet comic Valentine

You make me smile with my heart

The best-known song Lorenz Hart wrote the lyrics for is probably “The Lady Is A Tramp” – most famously performed by Frank Sinatra, but also recorded by just about everyone who is anyone. (I have a particular soft spot for the Tony Bennett/Lady Gaga version though).

Without an unsung hero in the shape of lyricist Lorenz Hart, we wouldn’t start singing along as soon as we hear “She gets too hungry for dinner at eight…” before we go through a series of Lorenz Hart’s bitingly-humorous lyrics which take the mickey out of New York’s “polite society” in the 1920s and 1930s.

(Fun fact: both “The Lady Is a Tramp” and “My Funny Valentine” – two songs almost as different from one another as it’s humanly possible to write – both come from the same musical: “Babes In Arms”. Rogers and Hart were a songwriting team par excellence, before Lorenz Hart’s untimely early death in 1943.)

Hal David

Not long after listening to Sammy Davis Jr’s introduction to “My Funny Valentine” I was watching a TV show based on, and I quote, “the songs of Burt Bacharach”.

While it’s absolutely true that Burt Bacharach wrote the music for some of the greatest songs of the 20th century, he didn’t write the words. Almost without exception, every Burt Bacharach song you can sing along to had its lyrics written by Hal David.

The Burt Bacharach/Hal David catalogue is so extensive I could probably write 50 articles just about that, but includes Dionne Warwick’s “Walk On By”, Dusty Springfield’s “The Look Of Love”, and The Carpenters’ “Close To You”.

My favourite Hal David lyric is from another Dionne Warwick song, though, “Do You Know The Way To San Jose”:

In a week, maybe two, they’ll make you a star

But weeks turn into years, how quick they pass

And all the stars who never were

Are parking cars and pumping gas

Hal David’s wonderful storytelling chimes very much with the unsung heroes theme. He is writing about someone who went to Hollywood in the hope of becoming a movie star, but ended up moving back home to a dead-end job in a (then) quiet town in order to survive after the studio system spat them out.

How many people with immense talent might be hiding in your organisation, who most people only ever see as doing the equivalent of parking cars and pumping gas.

Bernie Taupin

Pretty much every Elton John song you know had its lyrics written by Bernie Taupin. Yet you could walk past Bernie Taupin in the street and not know who he is.

The chances of you walking past Elton John in the street and not knowing who he is are pretty much zero.

Bernie Taupin is the unsung hero behind Elton John’s breakthrough hit “Your Song” – written when Bernie was still a teenager. Those tender lyrics have stood the test of time more than just about any other song from that era.

He is also responsible for the lyrics of “Candle In The Wind”, originally about the tragedy of Marilyn Monroe’s life and, many years later, sensitively rewritten for the funeral of Princess Diana. That metaphor of a candle in the wind is a particularly haunting one for both those women. Almost 30 years later, the 1997 version of “Candle In The Wind” is still the UK’s best-selling single of all time.

There are very few more poignant lines in popular music than:

Goodbye, Norma Jean

Though I never knew you at all

You had the grace to hold yourself

While those around you crawled

Bernie Taupin wrote those lines while he was in his early 20s – words with a maturity and artistic sensitivity that most people 30 years older who have been writing songs for 30 years would struggle to match.

In Elton John’s case, we know how pivotal Bernie Taupin’s lyrics are. To give Elton John credit, he has often explained that their songwriting process is for Bernie Taupin to hand him a completed set of lyrics, to which Elton sets the music.

So, in a very real sense, without Bernie Taupin, we would never have had the songs most people describe as “Elton John songs”.

Purpose

The purpose of this article is two-fold (beyond giving me a thinly-disguised excuse to write about a nerdy fascination of mine):

1. It’s to highlight that every successful endeavour has its unsung heroes. Their names might not be the ones in lights, but the results wouldn’t have been anything like so successful without them.
2. And secondly, it’s to encourage you to seek out the unsung heroes in your organisation and nurture them. No organisation becomes great without great people, and often the greatest people you employ are hiding in plain sight, parking cars and pumping gas.

I get a lot of sales pitches at the moment from people telling me they can transform my business with AI.

Hardly a day goes by that I don’t see some tech CEO high on ketamine enthuse about robots taking over the world.

And there is no shortage of bots lining up to tell social media users that if they don’t fully give themselves over to AI, they have no future and might as well go and live in a cave now.

I have major problems with all these arguments – mostly because they are all baloney – but there’s one particular problem the world’s tech enthusiasts complete miss. And that’s the fact that any business not being run by amateurs or idiots is going to need a business case, with a bottom-line RoI for whatever you want them to do that’s different to what they’re doing now.

Now it’s possible to lie about the bottom-line benefits. And based on what I’ve seen, that’s mostly the strategy of tech cos nowadays. But even then, the suppliers will be found out eventually, giving them two problems: firstly, they’ll be forever tarnished as liars; and secondly nobody who isn’t an idiot is going to buy from them a second time, even if they claim to have fixed whatever caused the problem the first time.

When I say “lie about the benefits”, that’s sometimes…often, perhaps…a deliberate outright lie.

But quite a lot of the time, it’s because people who think they’re smart imagine they understand things they don’t, and so think what they’re doing makes sense when it doesn’t.

Problem 1: Poor risk/reward ratio

By way of example, let’s look at a field I know well – accounting. Although exactly the same principles apply in every other field too, based on discussions I’ve had with a wide range of experts over the last couple of years.

Firstly, let me say, the AI pitchmen often tell me that their AI system can make it much more efficient to analyse data and convert all the things I do manually into some magic reporting machine which delivers instant results any time I want.

As tech pitches go, that isn’t the most insane one I’ve ever had. And on some superficial level, if you don’t understand what a real CFO does, it sounds like it’s delivering a benefit on some level.

Not a bottom-line benefit, exactly, because no cost has been reduced in this process and no revenue gained. But I acknowledge there’s the hint of a benefit in there.

What that means in practice is that this tech solution provider wants me to give them money and, in the process of doing so, my costs won’t reduce and my revenues won’t increase.

That locks in a negative RoI, to at least the extent of whatever this solution provider wants to charge me. I’m struggling to see the business case here.

The much bigger problem for tech providers is what do they think I do now?

I mean, if I thought about it really hard, I could maybe think of a report I might need for something that I don’t get at present, but by definition (if I haven’t already worked out a way to do it) the impact of knowing that information on the business is marginal at best. We already know that because, if it wasn’t, there would already be a report with that information on it, however inefficient it was to compile.

I mean, if I’ve already got a modern accounting system (even relatively basic packages like Sage and Xero, never mind NetSuite or Microsoft Dynamics) I can produce pretty much any report I want with the in-built reporting tools.

I can set up a live, real-time link to Excel to do any analysis I want. And if I want to do something really fancy, I can always hook up Power BI and produce as many pretty tables and charts as it’s possible to imagine.

So, if I can already get all the reports I need or want, more or less instantly, with the systems I already have, by definition no AI tech solution can provide better reporting than I already have.

As a side note, AI systems are incredibly vulnerable to bad actors, so there is a very real business risk to putting anything on an AI system given how many people can successfully hack their way into AI systems, whether they’ve been coded in Silicon Valley or someone’s back bedroom.

So, not only do I not get anything I can’t already get now. I introduce a whole new set of risks and vulnerabilities into my organisation at the same time. You can understand why I don’t see this as an attractive risk/reward ratio in the context of what we have already established is a negative bottom-line benefit.

Problem 2: Low incremental RoI

The second problem all these AI services have is that they are having to generate an RoI over and above the cost of using them in a field where a huge amount of optimisation has already taken place.

To listen to a tech co’s sales pitch, you’d imagine accountants still used quill pens and handwritten ledger books. Relative to those, of course some new tech would deliver dramatic efficiencies.

The only problem is that’s what everyone already did in the 1980s.

When I was a very, very junior accountant straight out of university, we still had a small number of clients who kept handwritten ledger books (albeit the quill pens were no longer in use). But most of our clients were on a computer system of some sort and those that weren’t soon were.

By the early 1990s everyone was on a computerised accounting system, pretty much, and the days of accounting departments with a couple of dozen ledger clerks, cashiers, and accounts assistants to post all the accounting entries had long gone.

And over time, computerised accounting and reporting systems have got better and better, driving more change and greater efficiencies inside most businesses.

An accounting department which might have been 20-people strong in the 1980s is probably being run by 4 people today – perhaps sales ledger, purchase ledger, payroll, plus someone in charge. That’s about all you need unless you run a massive international business (which most companies are not). And a small business can probably get by with just a couple of people.

So whatever whizz-bang tech solution that comes along isn’t making a business case by comparing itself against an operating model which hasn’t existed since the 1980s. All that does is demonstrate how little most tech cos understand the real world of accounting today and just makes the person delivering the sales pitch look out-of-touch and ridiculous.

While it takes some work, of course, showing a positive RoI based on making cost-savings against a staff base of 20 isn’t the world’s hardest thing to do. But, after 40 years of optimisation, an argument which requires you to fire 3 of the remaining 4 people to generate a positive RoI is unlikely to fill anyone with enthusiasm.

Problem 3: It’s not all the same

Because tech folk don’t understand the real world, they think everyone in an accounting department is a fungible unit of resource – that is, any one of them can be interchanged with any other one of them.

Even thinking that shows how naïve and out-of-touch tech folk are.

The reality is, if you have a four person team in the structure outlined above (sales ledger, purchase ledger, payroll and someone in charge), you almost certainly have four entirely different personality types and skillsets, none of which you can eliminate entirely from your business.

A good sales ledger person is likely to be more like a salesperson than an accountant. They have to sell, persuade, cajole, and encourage payments out of their customers in a way that a tech solution of just sending one Dunning letter after another could never hope to do.

I’ve only worked with a small number of truly exceptional credit controllers over the years and the people who do this well are an incredibly rare breed. However, good credit controllers accelerate your cash flow like nothing else on earth. You would need to be insane to get rid of one of those, if you’re lucky enough to have one.

Your purchase ledger person will be very focused on transactional processing, but they play a key role in managing your expenses. Particularly in making sure your expenses are correctly categorised – if they are wrong at this stage, any downstream reporting will be incorrect, so they need a level of focus and attention to detail which most people outside accounts departments don’t have.

They also have to deal with a barrage of suppliers wanting to be paid, queries internally and externally, balancing supplier statements to the purchase ledger accounts and more.

This sounds like the sort of thing tech would be good at, but it isn’t particularly as there is a lot of fine judgement involved. To give one simple example, buying a pen would have an entirely different accounting treatment depending on whether that pen was something for your warehouse team to sign delivery notes with, an antique Montblanc pen you’ve bought as an investment, or one of a batch of pens you intend to sell in the normal course of business as a stationery supplier.

Machines aren’t going to guess the right account code between those scenarios just based on the knowledge that a pen has been bought any time soon.

If you have a dedicated payroll person, you’re running an organisation with a large and complex payroll. That requires deep expertise in HMRC’s ever-growing and ever-more-complex rules and regulations which nobody can pick up instantly, and tech solutions can’t understand the nuances, and oddly inconsistent rules, involved in our tax system.

They will also be creating a range of legally-required returns to a variety of official bodies and fending off queries from your staff who don’t understand their payslip or think they’ve been underpaid or overpaid.

Because of the legal and financial consequences of getting this wrong, if you outsource this area of your business to an AI robot, I hope you enjoy prison food.

Finally, your “person in charge” is compiling all the reports, doing the monthly accounts, liaising with the auditors and dozens of other things. Anyone who thinks this is a purely mechanical process either doesn’t understand nearly enough about how accounts are prepared or they’ve worked with a lot of third-rate accountants.

While of course, some of this is relatively mechanical, it’s often in the process of doing the mechanical work that you notice anomalies which require further investigation before you can be sure the accounts are right. A tech tool which just reports the numbers as they find them is of very little use at this stage in the process – human insight is what you really need at this stage.

Which, by definition, is something you can’t get from something, er, a non-human.

So, when accounts departments have shrunk to perhaps 20% or less of the number of people they would have had before computerisation came in, any new tech service has to justify an RoI from removing people who are, to a large extent, un-removable because you need them, and their respective skillsets, within your business.

And if you don’t have an accounts department which looks like that, whoever has been running it clearly hasn’t been doing a great job over the years. In this scenario, you don’t need a new tool. You just need to make sure you’re getting the value out of the tech you already have and your costs will drop away instantly, without any further investment in new tech.

All the benefit of using the tech you already have better flows straight to your bottom line.

All the areas where you bring in a new system are taking away from your bottom line and, in the absence of offsetting cost-savings, represent a drain on your bottom line, not an addition to it.

In a nut-shell

I realise this looks different if you’re some Silicon Valley wunderkind who doesn’t know what they’re doing, but every AI pitch for “transforming my accounting system” looks the same.

They provide zero functionality over and above what I already have with my existing tools.

They offer no realistic cost-saving opportunities because we’re not in the 1980s any more and I’ve got an accounts team of just 4, not one of 20.

If I really pushed it, I might get that down to 3 (at the cost of some significant loss of valuable skills), but then a tech solution has to cost significantly less than one full-time person’s salary, or there’s no RoI on the investment.

I genuinely believe you’d be insane to get rid of a £30k salary to spend £100k on a tech solution, but tech people don’t understand how accounting departments really work, so they think spending £100k on tech “will make you more efficient”.

It doesn’t. At best it’s a naïve misunderstanding. At worst, it’s an outright lie.

And given that one of my fundamental operating principles is not to deal with naïve people, idiots, or liars in any field, that makes the tech co’s sales pitches hard to take seriously.

It’s not that I’m against tech or don’t think there are further efficiencies out there somewhere. I spent most of my career from the 1980s onwards implementing new systems and driving efficiencies to improve bottom line performance. So I’m not against the principle of this at all.

But on a practical level, AI solutions which claim to transform accounting departments just don’t.

Their “solutions” are inefficient, packed full of additional risks, generate no real-world cost savings anywhere which isn’t still using quill pens, and delivers no meaningful features which aren’t already available to an averagely-competent accounts team through their existing systems.

One day, in light of evidence to the contrary, I might change my opinion. But right now, despite ketamine-fuelled tech CEOs’ claims, there is no compelling case to replace any accounting system with an AI one.

And an even less compelling case to add it in as an extra layer on top of systems which can already do everything you need and which you’re already paying for.

If you really care about your bottom line, think twice about you fall for the tech cos’ sales pitches. They are mostly not true – your only job is to decide whether they are deliberately lying or if they just don’t know what they’re talking about.