Depending on who you ask, a startup has 3 to 7 stages. VCs tend to frame it with broad strokes, either early stage or late stage. Or they might be more granular, defining the stages as each round raised: pre-seed, seed, Series A, etc. Product people tend to frame it around stages of customer value achieved: solution fit, product-market fit, scaling, and the like.
No matter how they slice the stages, none of the frameworks offer clear guidance on how to successfully navigate the stages. Yet, that is exactly what startup leaders need the most. Executives are charged with the responsibility to maneuver the company from one stage to the next. And, in our experience, the hardest move is making the transition from the growth-at-all-costs stages to a profitable, sustainable state. So, we took a pass on our own phases of a startup:
- Phase 1 - Collect the customers
- Phase 2 - ? (High-growth, Scale-up, etc.)
- Phase 3 - Profit
In the beginning, the plan for Phase 1 is straightforward. Put in the hustle, and hope you get lucky. A high-growth startup is almost always burning cash at this point, reinvesting every dollar into future growth.
Phase 3, the profit stage, is clear, too. Mature businesses have established products and processes and go-to-market channels. The game is to look at past data, do your best to factor in market data, and make low-risk decisions. This is why many humans get a "real" job and work for a company at this stage or beyond.
But the time in between, Phase 2, can be a total mystery.
That mystical phase happens when a startup's ARR is in the $50-200 million range. We're well past the MVP. There's usually evidence of product market fit. Go-to-market strategies look repeatable. It’s kind of like being a teenager. They’re starting to look and sound like a grown-up, but they still have a lot of adulting in front of them.
If you find yourself in this stage, don't sweat if you're scribbling notes, making spreadsheets, and finding your profit plans looking rather suspicious. You, my friend, are nestled in the oh-so-common tangle of challenges we see leaders battling with in this peculiar growth stage.
Let's call out the top challenges:
- Scaling - Expanding product, process, and teams without diluting quality
- Strategic - Navigating through strategic dilemmas amidst scaling
- Operational - Maturing operations without losing the startup spark
- Customer and Market - Staying relevant in an expanding and shifting market
- Tech and Security - Driving technological innovation while fortifying security
So now what? Brace yourself; we're going to keep it real and possibly sprinkle in some metaphors about delicious food or 90's pop culture - because why not?
Before we shed light on the challenges, we need to have a moment of real talk.
Getting from Phase 2 to Phase 3 is like going from Good to Great. The difference between good and great companies isn't an incremental change from one to the next. Instead, the great company operates totally differently than the good company.
Making the shift into Phase 3 also requires a change in focus on the leadership team’s part. One of the most common things we have to help an executive with is accepting this truth: The strategies that got them to this point may differ from those that will get them to the next phase. It's like how Facebook started with "Move Fast and Break Things" and then evolved to "Move Fast with Stable Infra."
Some leaders know they need to delegate but don't know they need to change personally in order for that to happen. They may even be the lead advocate for making a change. BUT! Their habits are formed around them doing the role they now need to delegate. So, they need to learn to develop new habits to focus on the responsibilities that need their time now. The challenge is that they often don't realize this. They can be defensive if it's brought up. (I'm not saying that is you. But I am implying that it could be. The good news is, that self-awareness is a strength, so if this is you, that’s totally okay and now you can figure out how to proceed. Ok, whew.)
Now, let’s get back to overcoming the challenges that threaten your startup.
Scaling, while promising, can unexpectedly introduce chaos similar to a toddler barging into your Zoom call — adorable yet inevitably disruptive. How do we navigate through this constructive yet potentially chaotic growth?
Scaling the Product and Tech Teams
You started small, a tight-knit group, everyone wearing too many hats. Now, you need more hats and more heads to wear them. The trick to this challenge is creating a repeatable hiring process that doesn't turn your original team into a faded photocopy of its former self.
The first step is getting clear about who you are. Translation: you'll need things like company values. That you actually live and operate by. And that your teams believe in and operate by. Done wrong, company values can be cringy statements that induce eye rolls or even erode trust. If done right, they can inspire your team, improve culture, and attract talent. It will take you multiple drafts using candid feedback. Consider collecting feedback anonymously if you're not getting unfiltered feedback.
To nail hiring at scale, you'll also need clear hiring protocols. Do you know who does this well? Business Process Outsourcing (BPO) firms go deep into scalable hiring and training. It's too much for us to get into all of the details about how it works in this article. But, from a high level, here's what they do:
- They use AI to screen applications.
- They have a skill test (ahem, a right-sized one that doesn't force candidates to do hours of free work).
- Then, they automate the interviewing scheduling process. Now, they are even doing recorded responses to evaluate a candidate consistently.
- They gather all of the feedback and use tools like AI to score candidates on multiple dimensions.
- Our favorite, extra tip - they use interviews as moments to connect on a more personal level (the EQ stuff, communication style, how they show up), rather than interview questions that elicit generic answers and info they already screened for.
Lastly, it’s important not to hire just because you’re growing. Make sure hiring additional is truly necessary for your needs or for the problems you’re trying to solve. Over-hiring can create a whole other set of challenges & costs, and we saw a lot of those examples play out in many rounds of tech layoffs over the course of 2023.
Product complexity balloons as you race to please a broader customer base. Everyone in the company is dreaming up new features, integrations, and customization options faster than you can say "scalability." Market conditions and technology are also evolving at a rapid pace you must consider and plan for.
You'll need an army of product managers to keep up with the feedback and adapt accordingly. You will also need a well-defined software development process to coordinate their efforts, ensuring your dev team isn't yanked around whenever a new feature idea bubbles up.
Prioritizing enhancements aligning with customer demands and your core product vision takes work. Expanding the team to handle the load requires process updates and quality hires. Our clients tap us to help them derisk the transition. Our product managers come in, establish the new processes, optimize product development operations, and align the teams. And then we can help hire the right full-time roles to take over. And accelerate their onboarding & impact.
And voila! The scaling beast is tamed... well, at least momentarily… hopefully much longer.
Stepping over to the strategic side, our next challenge is a wily one. We have competing thoughts in our heads urging us to pivot when we need to hold steady or telling us to stick to our guns when we need to evolve. What’s the right level of flexibility, how much adaptation is healthy, and how do we figure that out?
Handing Over the Product Reins
You birthed this product. You sang it lullabies in the form of code and marketing strategies. You nurtured it, grew it, and likely had a ton of involvement every step of the way. But now, it's time to let someone else raise it to the next level. Letting go is hard when your product is your baby.
Sometimes, companies have the right person in-house to promote into a CPO or a similar product leadership role. More often than not, they'll need outside help to take over.
A typical pattern we've seen is that companies realize it's time to delegate product decisions when they feel the most pain. The desire for immediate relief is at odds with the reality that it takes time to hire the right person. A fractional CPO or executive product consultant can give a startup the instant relief they need while making it possible to take their time finding the right long-term hire. They can also supplement other product needs within the team during high growth; additional execution help, gap coverage, and onboarding support to name a few. We have also helped clients refine their job descriptions to be more relevant (include culture-fit goals and EQ skills, for example), and even participated in the interview process to increase their chances of making a successful hire.
Maintaining Original Vision vs. Adapting to Scale
As your startup shifts from the innovative, free-wheeling early days into a mature, structure-driven entity, one of the subtler challenges rears its head: The tension between staying true to your original vision and adapting to the realities of scaling. This challenge doesn't just mess with your product; it can permeate your culture, operations, and market positioning.
Your original vision was your north star during those initial stages. It helped you innovate, and differentiate, and probably played a pivotal role in your startup's initial success. Your early adopters bought into it, and your initial team probably joined because they believed in it. The risk? Becoming so adherent to this initial vision that you resist necessary evolution, potentially stalling growth and innovation in the quest to remain true to your roots. Keeping that pioneering spark alive is vital, but not at the expense of becoming rigid or irrelevant in a changing market. Leaders must consistently validate that their original values and solutions still resonate with their customer base.
Whatever the current version of the vision is, it's still important to keep reminding your team - and yourself - about why you started in the first place. Often, leaders feel like they are telling old stories too many times. However, new employees may have yet to hear them or internalize them. Embed these narratives in your internal and external communications. And talk about how and why they may need to evolve openly with your team to keep everyone aligned.
When operational challenges come out to play, they are eager to watch you stumble through their carefully laid traps.
Navigating Larger Bureaucracies
As a startup grows, the decision-making processes that once supported and propelled the company are no longer sufficient. Leaders are generally faced with a new reality: they can't keep up with all of the decisions that need to be made. Where delegation once meant that someone else did the legwork to bring a decision and a summary of the context to the leadership team, now it means handing over more decision-making to the next tier of company leaders.
Turning the decision-making model into a decentralized process may feel like handing over the keys to the castle, but remember: small, independent teams are more nimble than a lumbering giant. The key to maintaining leadership control is to manage by outcomes. There are multiple frameworks for this:
- Peter Drucker was an early advocate of Management by Objectives (MBOs). It's a management approach where managers and employees work together to set, plan, and achieve specific organizational goals. Decision-making is delegated, compared to when only tasks are assigned using a "command and control" management style.
- Google credits much of its early success to its strong adoption of Objectives and Key Results (OKRs), which are basically just MBOs by another name.
- From a product perspective, a roadmap can be managed based on outcomes using the Product Kata or the Opportunity Solution Tree methodologies.
There are pros and cons to any framework, and they should always be examined and applied relevantly within each organizational context. There are risks and nuances in how they’re implemented in each organization, but managing by outcomes and setting clear strategies and goals from the top down are key components in our book. In order to really empower any team, leader, or individual, there needs to be clear, continued alignment on what the business is trying to achieve, from the top down. Ensuring every team is aware of the larger objectives and how their departmental goals, roadmaps & KPI’s impact those objectives is critical. Regularly communicating progress, challenges, shifts, or other conditions that impact the objectives or a team’s ability to achieve them is also critical. None of it is easy, and it requires a lot of organized communication and transparency, but it is achievable. And when it works, it’s awesome.
Managing a Larger Product Portfolio
As a startup grows, it may become the proud parent of not one but a whole lineup of products. Growing startups are quite similar to proud parents; each product line is a unique child vying for attention and resources. The trick to managing this big family effectively is ensuring each member thrives without stifling the others.
To manage a business north of $50 million in revenue effectively, it is essential to diversify its sources of income. Revenue lines like subscriptions, memberships, or transaction fees could be introduced to ensure a stable and multifaceted income. Doing this efficiently requires startups to recognize these avenues and know how to seamlessly integrate them into their current business models without causing disruption.
Andy Grove had a great analogy for the challenge of managing multiple product lines, which he called the Creosote Conundrum. The creosote bush is a desert plant known for stifling the growth of nearby plants by dripping creosote onto the ground, making the area around it inhospitable to other plants. Isn't that a crazy strategy? By making the area barren, it can hog all the available resources. At one point, Intel's main money maker was its memory chip business. It was their flagship product line. Grove astutely recognized that it was like a creosote bush. The emphasis was on the flagship product. After all, it is hard to justify the budget for a new product when its short-term potential is a rounding error for the flagship. It effectively suffocated other promising lines. Fortunately, Grove recognized this issue. He isolated resources and allowed separate teams to focus on nurturing another sapling product line: CPUs. Today, Intel's identity is synonymous with CPUs, not memory chips.
Customer and Market-Related Challenges
We're now in the belly of the beast, my friends. Keeping up with customer and market landscape changes is like being in a Spice Girls song, where you really, really wanna zigazig ah (succeed), but the what and how of zigazig ah are never quite clear, constantly changing, and require close listening to understand. And if you’ve watched the recent David Beckham docuseries on Netflix, this likely has a deeper meaning (Posh Spice’s early patience gets a shout-out here).
Evolving Customer Needs
Ah, customers! Can't live with 'em, and definitely can't live without 'em (note - we love our customers, hopefully, you get the sentiment, here ;) As your customer base gets more crowded and diverse, they'll demand new features, routines, and adaptations that keep them happy. It’s not easy to please everyone, nor should you. But you have to strategize on how and what to address, and what not to, as you grow.
The simplest way to describe this challenge is that a mountain of feedback keeps piling up. In that pile, there is gold. But, it will take your team a lot of time or a smart strategy to sift through what is there and keep up with the pace at which it rolls in.
There are a few ways to deal with this challenge. The first one is to simply ignore customer feedback. Like the unverified and often quoted opinion from Henry Ford, "If I had asked my customers what they wanted, they would have said a faster horse." Similarly, Steve Jobs really did say, "It's really hard to design products by focus groups. A lot of times, people don't know what they want until you show it to them."
It's probably no surprise that we don't recommend ignoring customer feedback. We'd argue that it would totally be possible to come up with the idea of a car if a customer had said they wanted a faster horse. Be that as it may, there are some practical ways to stay up on customer feedback.
First, you should capture it, frequently, consistently, and efficiently. It would be best if you cataloged it in a single place. Multiple tools, such as ProductBoard or Dovetail, can help with this job now. Artificial Intelligence (AI) also makes extracting themes from the feedback much more manageable. There's no excuse these days for not distilling customer feedback into opportunities where you can quantify a high level of impact and effort. Especially since we can pull quantitative data, app analytics, and business data can reveal usage patterns, adoption, and profitability.
Just as you're nailing your product-market fit and go-to-market strategies, competition struts in trying to one-up your moves and woo your customers away with their own flashy steps.
Stay on your toes with continuous market analysis and R&D, ensuring your product offerings stay fresh, innovative, and shinier (or easier to use) than the competition. One great way to do this is to use a Kano model analysis of the features of your competition from their customers that use it. The Kano method categorizes features into four groups: Attractive, Performance, Must Be, and Indifferent. Without going down the rabbit hole of explaining the whole methodology, the goal of the approach is to find the features that your competitors have that are considered Attractive and Must Be features that you don't have. Or that you have a lower satisfaction rating for. Then, you build those features. Jared Spool has a great talk on how to use the Kano model to avoid "experience rot" by removing the features in your product that customers are indifferent to.
Technology and Security Challenges
Phase 2 brings a whole host of other challenges & elevated risks when it comes to data & security. Scaling tech while safeguarding user data is hard work. And a data breach can be an absolute nightmare.
Scaling Technology and Ensuring Security
Growing user bases and product lines means more data types and volume. And, as the old saying goes: mo’ data, mo’ problems. Or something like that. Great song.
Cybersecurity is all about access. Making sure the right people have it, and the wrong people don't. What makes it hard is balancing easy access with hurdles that keep it secure.
Let's not sugarcoat this. You'll need an endless loop of tech audits and a fierce adherence to cybersecurity best practices. It's harder than getting that synchronized TikTok dance right with your friends. And, you'll still lose sometimes because nothing is unbreachable. So get good cyber insurance and always keep data security top of mind.
Managing Tech Debt
Honestly, tech debt is like a troll. It piles up silently, stealthily, until one day, your development team is moving at a glacial pace through a very risky, very deep ocean. We have seen it take down healthy startups.
Generally, this happens because the company has not been sufficiently addressing enough of the tech debt all along. It's almost always the result of a well-intentioned executive or two. It's either because they were trying to move fast, keep the costs lean, or felt like the current software was a good enough cash cow to keep milking it. Or they had a bad experience from a previous refactor or re-platform project. We get it. It's like PTSD for someone who has been through a painful tech project that lasted way too long and didn't generate the value you were hoping for.
The reality is that as a company adds features and its user base diversifies its data universe changes. The information and system architecture need to adapt along with the changing data. It almost always means that reasonable customer requests go unmet eventually because they are too hard to implement in the current system architecture. Companies ignoring that for too long means that the customers start to churn. It becomes a death spiral. Revenue is dropping now. The longer the company delays rearchitecting its platform, the more dangerous it is. There is a point of no return when it won't have the wherewithal to invest in the size of the team and project timeline needed to reverse the trend. The fear of an expensive, risky project often paralyzes a team into inaction. It becomes the reason why the company eventually dies. It's super sad and totally avoidable.
Let's start with what tech debt companies should be addressing. The most deadly kind of tech debt comes from when the way customers think about their data is too far away from how it can be represented in its software. Let's take an e-commerce startup as an example. Suppose this startup initially built its platform to cater to a single country and is now experiencing explosive international growth.
The initial architecture didn't account for different currencies, tax laws, or international shipping. Consequently, international users face a clunky, often confusing purchasing process, with inaccurate currency conversions and unexpected shipping costs.
User dissatisfaction surges, cart abandonment rates skyrocket, and potential international revenue is held back, compromising global expansion efforts.
Fixing the issue may require touching almost every aspect of the software. However, the cost of inaction means leaving all that revenue on the table.
The hardest part is finding a way to talk about tech debt. Some people take issue with the term as a whole. Some engineers are great at connecting technical challenges to business value. Most are as good at explaining business implications as business leaders are technical.
If you're not routinely spending time addressing tech debt, and you're over $50 million in ARR, you almost certainly have a ticking time bomb issue. Do you have a tech debt list? Is it part of your strategic planning conversations (and we don't mean it's brought up and dismissed)? If you answered no to either of those questions, you may need some help. It could be that an outside party is best to get the conversation flowing. Requesting an audit from an unaffiliated third party with specific expertise in the nuances of a platform-type effort is another hot tip for ensuring there's no cognitive bias holding the company back from seeing the actual state of its technology. And how it will limit their success in the future.
A Tale of Triumph Over the Challenges
Despite the analogies and a few parent jokes, hopefully, the learnings are clear. If you've made it to the point where all of these Phase 2 challenges are resonating (aka $50-200 million in ARR) then you're ready to turn them into action and profit. This article is a useful guide for traversing the non-linear path from Phase 2 into the profitable, and hopefully a bit less painful streets of Phase 3.
Naturally, and most likely, a time will come when the level of detail in this 3,700+ word article isn't enough. When that time comes, we'll be here to take your call and answer any questions you might have. Until then, keep evolving, adapting, and hiring great people. Set clear goals, stay true to your company values, and keep your users at the forefront of your mind. Stay efficient, and scale smartly, with the right level of planning and risk. And don’t be afraid to ask for help along the way. It’s a strength, not a weakness.