Scaling Smart: Lessons from Growing from 15 to 140+ Employees, Twice
In January 2012, I joined a company called TUC Brands, a managed IT services company headquartered in Ottawa. At the time, we had about 15 employees. Within 18 months we had grown to more than 140 employees through a series of acquisitions. It was eventually sold under the name of Fully Managed to Telus in 2022.
Fourteen years later, I find myself in almost exactly the same position.
This past January, I joined a private equity-backed managed IT services company. Nine months later, after a number of acquisitions and bringing the businesses together under our new national brand, Tenom Technologies, we once again have more than ~140 employees across Canada.
There is something interesting about going through almost the same experience twice. The first time around I was much younger, and we were largely figuring it out as we went. Since then, I’ve had the opportunity to experience growth from a few different perspectives. I’ve been an operator, an investment banker advising business owners, an investor, and now I’m back operating a business again. What I’ve learned is that growing a company and scaling a company aren’t necessarily the same thing.
When you are small, you can get away with a lot. Everyone knows each other. The founder knows most of the customers, and employees generally know who does what and if something goes wrong, someone walks down the hall and figures it out. That works with 15 people, but it gets a lot harder with 50 and it definitely doesn’t work with 140.
Here are a few of the things I’ve learned the second time around.
I Was Wrong About HR
One of the first things our private equity partner suggested I do was hire an HR executive. I wasn’t convinced. My previous experiences with HR were mostly around compliance, policies and administration. I had never really experienced HR as a strategic partner to the business, so my view of the function wasn’t particularly high. Adding a senior HR executive also felt like a lot of overhead for an organization our size. Since it wasn’t up for debate, I took their advice and hired one. Wow, I was wrong. Having the right HR leader has been one of the biggest unlocks for us. What I underestimated was how valuable the right HR leader could be. Someone who can advocate for employees and help people find roles where they can be successful, while still understanding where the business is going and the people we’re going to need to get there.
One of the things we did early at Tenom was build the organization chart before we knew exactly who all the people would be. We mapped out the functions we knew the company needed. Service delivery, customer success, internal operations, finance, HR and sales. We then defined what each function was responsible for and what the mission of each role was. Only after we had done that did we start mapping people into the roles. With clear functional roles, we could move towards building the processes.
Build the Factory First, Then Put the People Into It
As we’ve scaled Tenom, one of the things we’ve been trying to move away from is what I call “hero-driven operations” to “system-driven operations”. Every small business has heroes. These are the people who have been around for years and know how everything works. When something breaks everyone knows who to call. They know the customer, they know the system and usually they know some workaround that nobody else knows. Those people are incredibly valuable, but depending on them is also a risk. As we acquired smaller companies, we’ve started asking a pretty simple question. If this person disappeared tomorrow, would this still work? If the answer is no, then we probably don’t have a process. We have a person.
This is one area where AI has been a huge help compared with my experience in 2012. We’ve used AI tools to take our organizational structure and help us think through detailed roles, responsibilities, processes and handoffs. Who owns something, where does it start, what information do they need, where does it go next, and what happens when something goes wrong.
Once we understood that flow, we could then start looking at our systems and data to make sure they supported how we actually wanted the business to operate.
I think back to 2012 when we were building out our Professional Services Automation software. There was a lot of trial and error. You would design the system based on what you thought you needed, maybe get 50 or 60 per cent of it right, then start using it and discover everything you hadn’t thought about. Then you would go back and rebuild it.
Today AI gives businesses the ability to think through a lot of those questions before they start spending time and money building systems.
Don’t Let Sales Be the Tail That Wags the Dog
Entrepreneurs naturally like flexibility and they’re usually pretty good salespeople. They’re also quick to say yes to customers to win the deal, and the result is that they end up with a different contract, pricing models, service standards, and technology. When you’re small, that flexibility can actually be one of your biggest competitive advantages. The problem is that every one of those decisions eventually needs to be supported by somebody else. Eventually the operations team isn’t managing customers. They’re managing exceptions.
I’ve been using an analogy with our sales team that seems to have stuck. Sales are the hunters and the service delivery team are the butchers. Imagine the hunters go out and come back with an elephant, a zebra, a giraffe, a hippo and a bunch of mice. Then they drop everything off at the butcher and say, make sausages. The butcher is eventually going to ask, “how exactly they’re supposed to run an efficient operation with all of these different types of animals?”
So, we’ve introduced the concept of a “hunting licence”.
Our Ideal Customer Profile (ICP) is the licence. If we’re set up to hunt moose, then go find moose. Don’t come back with a bear because you happened to find one, or a deer because it was easy to catch. We’ve built the factory around serving a certain type of customer. That doesn’t mean you never make an exception. It just means the exception should actually be an exception.
One of the biggest lessons I’ve learned is that sales and operations have to be designed together. If sales are incentivized to sell anything to anyone, eventually operations pays the price and resent sales.
Humans Make Mistakes
Billing has been a good example of this for us. Managed IT companies resell a lot of third-party software and licences. Those licences are constantly changing as customers add employees, remove employees, buy devices or change services. Across some of the businesses we acquired, a lot of that reconciliation was still being done manually. That might work when you’re small, but at scale it becomes a nightmare.
If you have thousands of licences changing every month and someone is manually comparing reports and spreadsheets, the question isn’t whether you’ll make a mistake. It is 100% probable.
That isn’t a criticism of the employees doing the work. Humans make mistakes, particularly when we ask them to perform repetitive tasks over and over again. So we assume they will as the baseline, and start looking across the business for areas where people are manually moving information from one system to another, comparing spreadsheets, reconciling reports or checking things that a system should be checking. Instead of asking how we get people to do those things better, we’ve started asking why we’re asking a person to do them at all. I’d rather have our people talking to customers, solving problems and making decisions than spending their day reconciling spreadsheets.
Don’t Automate Chaos
Which brings me to AI and automation. Every business is being told right now that they need to automate and that they need an AI strategy. I agree with both, but I think there is a danger in jumping too quickly to automation. Automating a bad process doesn’t make it a good process. It just means you can now do the wrong thing faster. Before we automate something, we are asking ourselves is whether the process should exist at all. Can we eliminate it? Simplify it? Can we standardize it? Then we can look at automating it. I think that order is important.
Complexity has a way of slowly creeping into an organization. One customer needs something different. Someone creates a workaround. Another person creates a spreadsheet. Three years later nobody remembers why the spreadsheet exists, but everyone is afraid to stop updating it. Multiply that across a company and eventually you’ve created a very complicated business.
Technology shouldn’t be used to help us manage that complexity. It should help us remove it.
The Second Time Around
I’m sure we’re going to make lots of mistakes as we continue building Tenom. We’ve already made some.
But the benefit of doing this for the second time is that I have a much greater appreciation for the things that seem unnecessary when you’re small. Hiring leadership before you think you need it can feel expensive. Putting structure around roles can feel bureaucratic. Standardizing how you do things can feel restrictive, and telling a salesperson that you don’t want a particular piece of business can feel crazy. However, all of those things become increasingly important as the organization gets bigger.
The first time I went through this, I thought scaling was mostly about figuring out how to handle more. More customers, more employees, more revenue, more locations. This time I think about it differently. A big part of scaling is actually about removing dependencies.
The business shouldn’t depend on one person knowing how something works. It shouldn’t depend on the founder making every decision. It shouldn’t depend on someone remembering to update a spreadsheet. And it shouldn’t require ten different ways of doing something that could be done one way.
If I could give one piece of advice to a Canadian business owner going through a similar period of growth, it would be this: don’t wait until you have 150 employees to start building the company that 150 employees will need. By then, you’re already late.
Stephan May is the President of Tenom Technologies, a Canadian managed technology services company.
