You hear about scale all the time. That magical moment when your company really starts to get traction, and you need to start taking what a couple of you were hacking together and blow it out big.
Scale your marketing, scale your team, scale your technology, scale your customer service. But what a lot of tech companies are really doing, especially those in high growth mode, is scaling some kind of process.
This is a process that, in the early stages of growth, may have been performed by 1 person, but now requires 10 or more people just to keep up with rapid customer acquisition and product growth.
While scaling sounds very appealing to an early stage startup struggling to get by, is not something that comes easy – in fact it takes extreme discipline, a commitment to measurement and reporting, flexibility and a relentless focus on driving efficiency.
Over the last several years I have seen scale firsthand – both in my own company, as well as in the rapidly growing venture-backed companies we work with. Through these experiences I have observed avoidable pitfalls when it comes to scaling processes – especially after raising a large funding round or gaining a big new customer.
Pitfall #1 – Not adding enough structure to keep up with growth
“But we’re a startup, we don’t need all that hierarchy, process, structure – it will just slow us down!”
While true to a certain extent, as you get bigger, complexity grows as well. Bob Sutton, organizational behavior expert at Stanford’s School of Engineering, advises companies to put in just enough structure and process to deal with this added complexity. He says, “The reality is you do need more roles, more hierarchy, more process. It’s unavoidable.”
So how do you know how much structure to add, and when to add it?
Kyle Lacy, VP of Marketing at Lessonly, follows the “5 P’s” to scaling: People, Principles, Process, Programs, and Performance.
Kyle Lacy says, “the biggest challenge as a marketing team when you are scaling is the focus on continuous, rapid improvement.” With the “5 P’s” he stresses that the foundation of any strong marketing organization is measure everything (Performance) to discover better ways to reach customers, and that it is critical to align team members with other parts of the organization.
As important as the “5 P’s” are, Lacy stresses that hiring talent is the most important part of scaling: “The most expensive thing a start-up can do is hire bad talent.”
Neil Patel, the man behind success stories like Crazy Egg and KISSmetrics, talks about the right moment to hire. His advice is not to throw labor at growth problems, but rather, to be aware of key triggers that tell you when to bring on people, and when not to.
His advice is to look at hiring for growth through the lens of A) when the tasks being done will generate money, and B) when the tasks to be completed fall under a particular skill set. In this way you can keep complexity at bay as you scale.
Pitfall #2 – Assuming your tech can scale without humans
Speaking of humans, do we even need them anymore? AI and machine learning are becoming more and more common not just in the tech media but everywhere else as well, and it may seem like humans are pretty much going out of fashion.
But anyone building any type of artificial intelligence (and according to Saman Farid AI will be essential to pretty much every tech startup in the near future) will tell you that it may be achievable to get machine learning up to speed on 80% (give or take 10-20% depending on who you’re talking to) of what you want to do, but that last 20% is extremely hard to do with without human intervention.
For one, you need lots of data to train algorithms. And two, so much of what you are likely doing as you disrupt your space is new territory – you’re collecting data, experiencing nuances and learnings along the way that require judgment, insight, and flexibility. All of which still requires humans.
Emily Hurd understands that balancing act between scaling tech and scaling labor very well. As VP of Operations at one of the fastest growing companies in the travel benefits space, Rocketrip, she has scaled multiple functions of their business through a series of funding rounds and the acquisition of large, enterprise customers.
As Rocketrip scaled in the early days, they focused technology resources on customer-facing and/or core product innovations first, and maintained a “delicate balance” of when to build out more product features, and where to add more headcount. She explains, “If there are areas of the business where we can provide coverage with headcount, without sacrificing user experience, we’ll opt to do that while our technology has a chance to catch up.”
Erik Bloch, a director with PatternEx, talks about the relationship between humans and machine learning as well. This is especially relevant in the security space. He stresses that with AI/Machine Learning platforms you want the system to replace people doing repetitive tasks, and allow humans to train the system to help them out so they can do other things.
Pitfall #3 – Getting stuck in “hero mode”
Bloch, who is a veteran of 4 high growth startups, warns that when many startups start to scale, they continue to do things the way they were doing it in the early stages – for example, the CEO or early employees try and continue to work 24/7 and do everything themselves. He stresses that it is critical to bring in the right people at the right time after securing your Series A funding round.
Hurd also talks about the tipping point for leaders to to get work off their plate. She follows a rule that if you find you’re spending 20% of your time on any one area of the business, it’s time to figure out a way to get it off your plate – whether through headcount or technology or both. “And hire good problem-solvers who can make the tasks more efficient; you won’t scale if everyone just clones what you were doing.”
In fact, in the early days Rocketrip’s CEO was even doing some of the manual data processing work himself, but once they started to land large customers the team realized it wasn’t scalable to have everyone do all the extra processing work on top of their regular day-to-day jobs.
The approach that they took to solve this and avoid “hero mode” was two-fold: they developed a dedicated in-house support team that works in shift schedules to cover business hours as well as evening/weekend shifts, and they developed an offshore team to provide 24/7 coverage on back-office processes.
Tyler Leshney, President of ultra mobile, talks about the shift in thinking that occurs between early stages and scale. “It’s so tempting to continue to react the way a start-up would. In the start-up world the wins are dramatic, the losses tragic.
In the scale-up phase victories take longer to materialize and may be even tougher to recognize.” He goes on to pinpoint what is perhaps the single most quality critical to success during the early days of scaling: “All you need is just a little patience.”