What is ‘Growth Thinking’? Part I: Introduction

The concept of a growth team is a bit of a trendy topic in the startup/tech world. But it is a popular idea for good reason: companies like Facebook, Airbnb, Uber, and others have attributed significant improvements in their business metrics thanks to work done by growth teams.

What is a growth team? Growth teams are typically interdisciplinary, data-driven teams whose work touches marketing, product, engineering, and data science. Growth teams apply the scientific method to quantifiably improve business metrics — whether it is engagement, retention, conversion, or acquisition — often using tactics like experimentation and A/B testing. Growth teams are amorphous and flexible and are organized differently at different companies. In this series of posts, I won’t be trying to define what a growth team does; instead, I will focus on why good growth teams are successful.

There’s a lot of reasons why the model of a cross-functional, high-paced team focused on scientifically improving business KPIs works. One of them is the unique problem-solving toolkit used by growth teams around the world; I call this “growth thinking.”

Growth is a tool: In knowledge work our tools are the processes we use to approach and solve different types of problems. — Andrew Chen

Growth teams are typically composed of members with different expertise, like marketing, design, engineering, and product management. Everyone on the team brings different perspectives and experiences to the table, including different problem-solving toolkits (this is one of the many reasons why diversity is so important).

When a plumber shows up to a job and an electrician shows up to a job, they come with entirely different (physical) toolkits. In the knowledge economy, your problem-solving framework is your toolkit. Someone from a design background not only brings their design skills, but their domain’s specific method for creative problem solving. The value of an interdisciplinary team isn’t just the skills that each individual contributes, but the variety of problem-solving frameworks that come from having diverse backgrounds and perspectives.

A growth team’s one goal, eponymously enough, is to grow the company. But growing a company is a notoriously hard problem. Because of the diversity of roles and backgrounds on a growth team, growth teams are especially equipped to take on big challenges: they have lots of different problem solving tools in their toolkit, all on a single team.

Interdisciplinary work is when people from different disciplines work together. An antidisciplinary project isn’t a sum of a bunch of disciplines, but something entirely new. — Joi Ito

The way that successful growth teams think and work isn’t simply the same as the standard way of thinking from each of its member’s domains; something new arises when all of these different problem solving frameworks are mashed together. Joi Ito, the director of MIT’s Media Lab, describes the difference between “interdisciplinary” and “antidisciplinary” work: “Interdisciplinary work is when people from different disciplines work together. An antidisciplinary project isn’t a sum of a bunch of disciplines but something entirely new.” Growth thinking is more than the sum of its parts — it is its own problem solving framework. Growth thinking is not just interdisciplinary, but an antidisciplinary approach to growing a company.

Growth thinking may be new, but it isn’t original. In the spirit of Kirby Ferguson’s Everything is a Remix, growth thinking is a copy, a transformation, and a combination of several other powerful problem-solving frameworks, like design thinking, Eric Ries’ “Lean” framework, data-driven decision making, agile software development… the list goes on. These frameworks are themselves mashups and transformations of other theories that came before them.

In this series of posts, I’d like to compare and contrast how growth thinking intersects with other problem-solving frameworks, and share how I’ve thought about growth at DataCamp.

Continue to Part II: Lessons from Design Thinking