Short-lived PoCs
Constant Feedback from initial users (Lean UX)
Small, highly collaborative founder team
Set the company engineering culture
09 March 2022
This article is part of the series: Bottlenecks of Scaleups
Extracting yourself from a bottleneck may not be easy, but our series will help you navigate the pain points. We’ve identified four phases of a startup’s journey that correspond with some common scaling challenges. It’s overly simple but provides us a framework to show when to adjust your strategy to tackle scaling problems. This was inspired by the great models created by Kent Beck and Simon Wardley.
Phase 1
Experimenting
Phase 2
Getting Traction
Phase 3
(Hyper) Growth
Phase 4
Optimizing
In the early stage, a startup experiments with product ideas to find market fit. They’re focused on building many ideas quickly, so they can test with user groups and trusted experts. The startup has some initial seed funding or are bootstrapping themselves. They would want to collect enough evidence to secure funding for the subsequent phases of growth. The software is lean proof of concepts focused on the product features rather than scalability.
At this point, they have some good initial indicators, some early adopters who are passionate about the product and they had good feedback from industry experts. They have to capitalize on the tailwinds, turning the proof of concepts into an MVP. There’s still a lot of experimenting here. There are likely many directions that the product could go and different types of customers it could be targeting. They have a small, close-knit team that can rapidly decipher feedback and pivot when necessary. Users might be starting to rely on the product, so it has to be performant, available and secure.
We regard the second half of gaining traction to be the beginning of scaling up, and therefore you are considered a scaleup. There is number of measures to use to define a scaleup, the best indicator is sustained headcount growth. The Organisation for Economic Co-operation and Development (OCED) uses 10% yearly employee growth for a “scaler”, and 20% or more over a 3 year period for a high-growth scaler. But they also say “...scaling up being more than “just” a period of rapid growth. Rather, it is the expression of a transformative process that a firm undergoes”.
Hypergrowth is the desired goal for many startups. The initial success has gained steam, and growth is increasing exponentially. There’s no end to stress and demands. The added traffic puts strains on the technical platform. The users are demanding high-quality and new features. An extensive marketing campaign has fired up. The scaleup may be attracting the attention of competitors, incumbents and fast followers. They have to make the company appealing to candidates challenging the talent market. Plus, the scaleup recently secured a lucrative round of funding based on growth projections, so there is investors demanding progress and offering opinions.
The company is definitely in scaleup territory. Typically the definition of hypergrowth is 40% Compound annual growth rate (CAGR). Not all scaleups will reach this level of sustained growth, but will still have significant growth and hit bottlenecks.
At this stage, the startup is still growing, often quite rapidly, but the organization has caught up — they’ve scaled several aspects. There are no longer fire alarms, and we have decoupled product teams performing well. The leadership now has an opportunity to look at the economies of scale across the organization. Some of the choices we made in the previous phases might be hurting. As Kent Beck wrote, “Growing organizations retain the focused urgency of expansion past its usefulness and thus don’t step back to see the need to eliminate process, handoffs, and delay that no longer add value”.
The optimization opportunities are varied. Take the scaleup’s technical platform, for example. It might be fragmented and operational costs may be high. Teams could be wasting time building custom capabilities when there are third-party options. And where people are concerned, there may not be an efficient onboarding and upskilling program. Perhaps their decision-making processes aren’t nailed down, and people are still being micromanaged. And amid all this a scaleup will still have to think about ways to keep users engaged, now that the initial excitement in the company has tempered off.
Phase 1
Experimenting
Short-lived PoCs
Constant Feedback from initial users (Lean UX)
Small, highly collaborative founder team
Set the company engineering culture
Phase 2
Getting Traction
Build & Release MVP, iterate from learnings
Take on pragmatic tech debt
Setup initial foundations - experimentation, CI/CD, API, observability, analytics
Growing team, find initial business seams for correct team topologies
Leadership hired from personal network
Phase 3
(Hyper) Growth
Double down on features to keep up with demand and ahead of competitors
Hardening to handle traffic changes
Invest in data platform for expanded learnings
Rapidly expanding team, hiring, re-organization, new management layers, acquisitions
Split out concerns; platform, design systems, and product teams
Phase 4
Optimizing
Extract out efficiencies; rebuild or buy capabilities for improved efficiency
Pay down tech debt
Team churn; master effective onboarding and delivery practices
What is the next product? Diversify?
This diagram shows some of the initiatives that a company might be focusing on throughout its growth as it transitions from startup to scaleup. It’s by no means complete. However, it illustrates how the scaling strategy evolves. Throughout this article series, we’ll cover what to do at different stages in the growth journey and when to build the foundations for scale. We’ll also use industry case studies to illustrate.
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Bottlenecks of Scaleups
Bottlenecks