Why Michael Gerber’s ‘E-Myth’ fails in the internet age
The E-Myth Revisited by Michael Gerber is my all time most recommended business book.
It is likely that you have been recommended this book in your favourite business podcast or mastermind. You’ve probably seen a dozen copies of it at your local second-hand bookstore along with other classics like Kiyosaki’s Rich Dad Poor Dad or Jim Collins’ Good to Great.
The E-Myth is somewhat of a cult classic in the business world. It is so because Gerber makes a pretty bold promise. He offers a framework to avoid being part of the 80% of small businesses that fail.
He begins with the humbling truth that ‘being good at your craft/technical role is not the same as being an entrepreneur. Throughout the book, Gerber, tells the story of a small business owner trying to grow her bakery business. He coaches her to not think of herself as a baker, or technician, but rather a manager and entrepreneur.
The book goes further to explain how to structure her company for long-term growth. Gerber calls this the ‘Franchise Prototype’, a framework to help founders think about their business as a franchise, a series of systems, rather than treating your business as a job.
“A real business is one where the founder has created a system so that the business can run itself without their constant presence”.
Now, I really do believe the E-Myth is a great book to help first-time founders understand what it means to be a business owner. To help them frame their business as a system, or what I prefer to term ‘a machine’.
But as of late I’ve been questioning some of the principles and ‘advice’ in Gerber’s book.
The principles were relevant at the time it was published, circa 1980’s. But I don’t think all of them are relevant now. A lot has changed over that 40 year period. Particularly when it comes to human resourcing.
You don’t want to hire the smartest people
In the E-Myth, Gerber makes a pretty profound statement when it comes to building the perfect business model:
“The model will be operated by people with the lowest possible level of skill’’.
He further explains;
“The business model should be such that the employees needed to possess the lowest possible level of skill necessary to fulfill the functions for which each is intended.
It is literally impossible to produce a consistent result in a business that depends on extraordinary people.”
Yeah, let that sink.
I mean, I get what Gerber is saying. You don’t want to hire rocket scientists for your burger restaurant. For starters, rocket scientists are hard to recruit. They’re also expensive because they know their worth.
But most importantly, they’re opinionated. They don’t make good servants because they’ll question everything about your business and how it functions. Rocket scientists are smart, probably smarter than you.
Gerber’s advice is that you don’t want to hire smart people, as you should be the smartest.
Instead, you just want to employ low skilled workers. Workers that will obediently follow an SOP. Workers that won’t question your orders. Workers that will settle for average. Workers that make great factory workers.
In other words, you want to hire drones.
Gerber’s perfect business model is a “cookie cutter’’ one that scales rapidly…like a franchise.
He refers to McDonald's as a perfect case study of a ‘turn-key’ solution to building a wildly successful business.
Last time I checked McDonald’s has a few problems…
The law of leverage
Gerber’s principles are built upon an industrial age business model.
The typical industrial age business has a widget to sell and the only way to grow is to sell more widgets, at scale. The problem is that, because the widget is consistently average, produced by average people doing average tasks, the market will only accept to pay an average price. Therefore, in order to generate a profit, the only lever a manager can pull in the business machine is to manage costs.
Managers are incentivised to drive costs of production down by taking shortcuts, looking for cheaper and faster ways to do things.
Industrial age business models are built on leverage. Leverage of people producing widgets at scale. The problem is, widget manufacturers will cap out at a certain productivity rate.
Finance people refer to this as the ‘law of leverage’, where growth is achieved by ‘duplicating yourself’ using other people’s time, effort, and resources in order to produce a higher return than you could yourself. In other words, scale and growth can be achieved by just building more factories to produce and sell more widgets.
This is why Gerber’s advice is to hire people of
‘the lowest possible level of skill necessary to fulfil the functions for which each is intended’.
Hiring smart people is expensive and you can’t make a decent profit margin on expensive labour that produces an average product.
The industrial age business model is of the assumption that output per person is linear.
The reality is the law of leverage has changed. Drastically.
Exponential leverage
Where industrial age businesses leverage a factory or ‘hard asset’ to generate revenue, today’s most valuable organisations build economic value via a different form of scalable asset that is not humans in factories.
The new model is focused on software and innovation.
Apple, Facebook, Tencent, Google and Netflix — are amongst the world’s most valuable companies. What do they have in common? Well, they don’t sell widgets. A core product of their business models are highly scalable, intangible assets.
The thing is, these assets aren’t easy to make. These companies, therefore, hire the best and brightest to innovate and build new products and ways of doing business.
They don’t follow a rule book because there are no rules — they are writing it as they go.
Algorithmic vs Heuristic work
Of course, exponentially leveraged businesses still rely on people. But what’s different is the type of work these people do. The two types of work can be broadly categorised as Algorithmic and Heuristic.
Algorithmic work involves a process which is defined and the end product is expected. We follow a set of instructions, or an SOP down to the detail, where following this path will lead to a known result. By definition, there are no surprises with algorithmic work because there is a known outcome. The risk of failure is low, to nil.
Heuristic work is the opposite because there is no algorithm. It entails exploring and testing new methods, processes and ideas to create something new. There is no ‘playbook’, hence there is no known outcome. The risk of failure is high.
Algorithmic work includes tasks from manufacturing, selling hamburgers to accountants lodging tax returns. It’s a system of processes that have a repeatable, definable outcome. The ‘perfect business model’ according to Gerber.
Heuristic tasks, on the other hand, might involve launching unmanned rockets into space that return home, writing code that solves a bug in a program to create a new marketing program. Heuristic tasks involve creating something new, bold and different where there is no playbook.
In the industrial age economy, most jobs used to be algorithmic. People in within a very clearly laid-out plan. A standard 9 to 5. There was always a guideline or a formula or a manual that could be followed. Think about how corporations are structured. The path is paved with a ‘career framework’ and the only way to get to the top is to follow it.
However, this model is changing. Algorithmic work is increasingly becoming outsourced to countries where well-trained employees can produce the same kind of results for a fraction of the price. It’s either that, or there is software to replace the need for human work altogether. Algorithmic work is becoming obsolete.
Heuristic work, on the other hand, is driving the new economy.
Heuristic work is the future of work
You can’t build an innovative organisation, filled with people doing heuristic work if you employ drones. Drones are good for algorithmic work, but they suck at heuristic work.
Smart people question things. They want to do things better. They don’t settle for average. They seek to be remarkable, they promote change and growth.
Seth Godin terms these people as Linchpins in his bestselling book Linchpin: Are You Indispensable?
The output is not linear for Linchpins because, through their art, their impact is exponential. A large majority of the work they do is heuristic work.
In summary
Gerber’s ‘perfect business model’ may have been perfect in an industrial age economy. But it’s not anymore. There is no such thing as ‘perfect’ if you’re doing truly meaningful, groundbreaking work.
You can make average things perfect, but they will always just be average.
Doing average work and making average products is an algorithm destined for failure. Because it becomes a race to the bottom. As Seth Godin says:
The problem with the race to the bottom is that you might win.
Work with the imperfections. Try things that might not work. Do work and produce things make a difference.
Build a business that matters.
