How big opportunities are hidden under apparently meaningless things.
A long time ago I heard a story about a McKinsey consultant who helped the firm save millions by proposing to replace chocolate cookies the company made available to its employees free of charge for a healthier alternative.
Crazy, right? How is it possible that just getting rid of some cookies could generate so much money?
Although subtle, the assumptions were pretty straightforward:
Chocolate cookies contain lots of calories, which can make people gain weight.
Weight is a risk factor for diseases and it's taken into account in health insurance premiums calculation.
Health insurance costs are paid by the company.
Therefore, by replacing chocolate cookies with something healthier and less caloric, the company could save money on health insurance premiums.
Do these assumptions make sense? If so, are they powerful enough to really save millions?
The truth behind the cookie hypothesis
One way of getting closer to the truth is using market sizing techniques, used by business consultants to quickly figure out a number that might be relevant to business decision-making.
Examples of estimation exercises:
How much profit does the local bar in your neighborhood make?
How many gas stations are there in your country?
How many people go through the Guarulhos airport every day in São Paulo?
How many chickens are there in the world?
How many vehicles does the town hall of São Paulo need in order to have at least one car patrolling all the corners of the town every 5 minutes maximum? (This one I got from my last round when interviewing at McKinsey)
I had a lot of fun doing estimation exercises when I was preparing myself for the selective process of big consultancy groups before graduating from Business School.
I especially recommend the Crafting Cases market sizing course and the Guesstimation books if you are interested.
I was enjoying myself so much while estimating things that I started to go beyond the exercises from the books and create my own challenges whenever I saw an opportunity.
It has been a long time since then, so why not do an example with our millionary cookie hypothesis for the good old times?
The first step is to place the most important variables and establish the mathematical connection between them as MECE as possible.
A high-level breakdown of the total savings in USD/year for avoiding the infamous chocolate cookies could look like the following:
Please note this is not an exhaustive breakdown and in a real project consultants go much deeper.
There are a few key things we are not considering for the sake of simplification, for example:
The chocolate cookie is a global thing (we could use a % of the offices that offer high-caloric snacks or even a breakdown per country for a more accurate estimate)
Cookies are being eliminated and not replaced by anything else less caloric, which is inflating savings (and maybe we should consider something that has 30% of the calories as a replacement, for example)
Something I learned in the past is that sometimes it is not necessary to get to the exact number to make a decision.
Just understanding the upper and lower boundaries, the order of magnitude, or the main levers inside the model is usually enough to provide the necessary insight to decide on something.
So, let's keep it going. After structuring the problem and creating our mathematical model we need to attribute values to the root variables and run some calculatations.
A quick Google search can give you the number of calories of each cookie and the average hourly rate McKinsey charges its clients.
For other numbers like the average number of cookies someone eats a day, I came up with my own rough estimate.
If we wanted to be more precise, weighted averages usually get to more realistic assumptions, but they won't change the order of magnitude here.
The blue boxes below represent root values while the orange boxes are merely the product of pre-existing root variables.
The key takeaway here is that YES - it is reasonable to say that a large corporation can have a million-dollar impact with a dietary change.
Almost 10 million dollars considering our assumptions in the example above, and excluding all the employees that are not consultants.
These excluded employees could represent a meaningful impact on the total savings adding some more million to the end result, given that all other employees who are not consultants account for 75% of a consultancy workforce and usually spend 5 days in the office, which would make them eat much more cookies.
This is not a big surprise, given the scale of a global corporation.
In fact, to save a single million, McKinsey would need to find a way to save only $25/year or ~$2/month per employee given its 40 thousand people workforce.
It doesn't sound much when framed like this, right? Maybe simpler than calculating insurance cost savings would be to find a slightly cheaper food provider.
The second key takeaway is that most of the savings in our model do not come from insurance premiums but from presumed revenue losses due to absenteeism.
This might be a strong assumption given that consultancies charge their clients a flat fee and a sick day from one employee should not directly impact the revenue.
However, it's safe to assume that if the employee was not on sick leave he would be probably working on something else that could add value to the firm, which means there is a real impact here.
Another strong assumption behind this is the link between weight gain and absenteeism.
Although there is not a lot of research in this field, a quick Google led me to this article that shows findings to support this claim, especially for the already overweight population.
But even if absenteeism does not happen, the increase in health insurance premiums alone is adding up to 1.5 million/year in our example, supporting the thesis that the cookie diet can have a million-dollar impact.
Digging specifically into insurance savings
One key assumption on the insurance premium savings is the additional yearly cost per kilogram for the insurance.
I admit this is a tough one, given that this is not directly factored into how companies charge for premiums and therefore not a good number to use.
Much likely the relationship between weight and insurance cost is not linear and it would not make sense to use it like this, but might be good enough for our back-of-the-napkin estimation.
In addition to this, knowing how much each additional kilogram can increase health costs sounds like powerful information to have, so I decided to have fun being creative and trying to figure it out anyway.
In case you are curious, I got to this number by doing the following extrapolation:
Data shows that lifetime medical costs can be reduced from 20-50% given a 10% weight loss.
Considering our average weight gain of 5kg represents ~6,25% of the weight of the average consultant who has 80 kg, I'm assuming we can reduce the lifetime costs of this consultant in equal proportion, or up to (6,25/10)*[20 to 50%] = ~[12.5 to 30%].
If insurance costs can be reduced in the same proportion as the medical costs, then we just need to factor in the average price of insurance paid by McKinsey.
This can vary heavily by country but let's use the ~6k/USD year according to this market survey
It is likely that McKinsey insurance is above the average, but I'll ignore it given that other countries probably have cheaper insurance than the US and hopefully these differences will offset one another a bit.
Finally, I'll use the 12.5% lower boundary of the insurance cost reduction and multiply it by 6k, which gives us $750/year or $150 per each of the kilograms we are considering in the model.
That's definitely not the best way to run this estimation, but the important thing is that this exercise led us to a model of the problem, making very clear which are the main levers that affect it and how much.
Playing with the numbers, we can easily see that is reasonable to say the consultant's diet can lead to a 6 or even 7-figure impact on the firm, which might have sounded like an exaggeration at the beginning of this article.
I don't know if this is a true story, but is a story that always stuck in my mind, making me not only hungry when I think about all those cookies but also wondering about what other big opportunities are hidden behind the daily trivial small things we live with.
Beyond the cookie jar
There are more explicit examples of small things that add up big that don't require us to do crazy estimations to get an idea of their impact on our lives.
Household chores are a good example, demanding more than 500 hours a year from the average UK citizen according to research.
Of course, we all need to prepare something to eat and do other duties, but couldn't we really cut some of these hours? If so, how much more efficient can we get?
My favorite (or least favorite) example is ironing.
I'm strongly in favor of the movement pro-stop-ironing clothes, as I understand that ironed clothes look good, but only because there is a social construction behind them.
After all, we tend to perceive with strangeness those with a wrinkled outfit but that would be purely normal if we all did it.
So why do we sustain the collective burden of the ironing ritual?
The average Brit wastes 1 hour every week with ironing alone. And although the average can vary significantly according to the type of clothes one wears, the method, country, season, and other variables it is likely that most people take around that.
This means 52 hours per person/year, and more than 50 billion of humanity's hours if we assume only 1/8 population irons its clothes on this average.
Imagine how much we could do with 50 billion hours every year!
In Britain alone, 28 million people are currently working on an average salary of 16 euros an hour, adding up to more than half a billion dollars of impact in one single country.
Obviously, not all of them would work one extra hour a week if they didn't have to iron but you get the point.
In fact, curiously, economically speaking that would probably mean a decrease in GDP because there would be no more need to produce iron, purchase it, deliver it, use electricity, etc.
Nevertheless, we could all use our 52h hours/year to consume something else, produce something else, or just do something better with our time.
That's one of the reasons pushing GDP growth does not necessarily mean we are living any better.
Another thing I find annoying, although sometimes relaxing, is washing up dishes.
For this reason, I decided to investigate if it would make sense for a hypothetical individual to buy a dishwasher:
Provided that an average new dishwasher costs $1,000 and one individual makes $30/hr and spends on average 1h30/week washing up, the payback for the dishwasher happens in less than 6 months if he were able to completely replace the time spent washing working and getting paid for it.
However, this individual would still need to spend time using the machine, which means he would not save 100% of the washing-up time.
So, how much time (and money) can a dishwasher save?
Even if it saves only half of the time of manual washing, the 1-year payback is pretty fast and worth it given the 10-year life expectancy of the machine.
Maybe I will elaborate a bit more on that and cleaning robots in another article, but it sounds like a great deal if you have room in your house, make more than $15/hour, and can buy a machine for under $1k.
Finally, one example of the overlooked impact of the minutes we waste every day went viral when some brilliant mind shared the following layout on the web:
I loved this so much!
Once you start looking at the small numbers behind every day's activities, you realize the compounded power of the small changes.
What to do with all of this info? Should I stop eating cookies?
There are 2 key lessons in all of this:
1. Small changes can play a big difference in one individual's life.
2. One small change, in the context of a large group of individuals can easily add to millions, billions, and trillions of economic impact.
I'm not planning to stop eating cookies, but before writing this article, it was not clear to me that eating a pack of cookies once a week could lead an individual to gain 5 kg at the end of the year.
Of course, we shouldn't take this literally given numerous variables such as differences in metabolism, caloric spending, etc but you get the idea.
On the other hand, I can clearly see the impact of some small habits compounding in my routine:
I enjoy listening to music while working out or doing my morning walks, but when the content does not require my visual attention, I sometimes listen to Udemy videos. In 2023 alone, I've listened to more than 100 hours of technical content this way without having to stop doing what I was already doing.
By taking 20 minutes after I wake up and before I sleep, I'm able to dedicate almost 5 hours a week to reading, which is equal to one book a week on average. This adds up to 50 books a year, which I've done in the past (check out some of my book reviews here).
Can you imagine how different the world would be if we could slightly improve the health of millions of people by replacing cookies with something better, or having them exercise for 30 minutes a day?
Have any other ideas about small things that compound big?
Would love to hear them in the comments below.
Yorumlar