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








