Original : https://sisunlee.medium.com/growth-culture-c45c5f2834c
Relying on growth experts to reshape product and improve metrics is an incomplete scope of growth. Growth isn’t something that is unlocked with a few great hires. A company’s culture dictates its ability to drive growth more than any individual — it’s having the willingness to ruthlessly focus on impact, let data precede over hierarchy, and embrace experimentations.
To understand why — let’s first define growth.
Growth is about experimentation — testing hypotheses and making ongoing improvements in order to steer the business towards its intended goal as quickly as possible. To do so, teams need to be able to identify and execute against the highest-impact opportunities.
Focus on impact, data, and experimentation are three cultural traits a company needs to drive growth.
Companies must align its resources and priorities towards whatever will move the needle the most. While this sounds obvious, in the absence of clear indicators of impact, people gravitate toward behaviors that are often mistaken as signals for productivity — think emails & meetings. This is a death spiral.
Focusing on impact starts with a clear, measurable goal. What is the one thing that we absolutely need to crush? Which metrics will be used to measure progress? There must be clarity from leadership on what matters and why — which provides clarity for what does not. When employees have varying understandings of their goals, but fail to speak up to question authority, they all end up playing a different ball game. Companies become unable to allocate resources effectively, and motion becomes proxy for progress.
An impact-driven culture expects everyone to solve the most important problems, and avoid wasting time on minor issues. To enable this culture — employee performance needs to tie back to quantifiable impact. Growth is quantitative and definite. Did you win or not? A caveat here is that some projects inherently carry higher risks (bold bets) than others (low hanging fruits), so it’s important to factor this in.
Facebook is a great example of an impact-driven culture.
Accordingly — product orgs were split into growth, engagement, and ads with their respective KPIs measured as MAUs, time spent, and revenue. There’s clarity of prioritization for each org that rolls up to company-wide impact.
https://miro.medium.com/max/1595/0*urIDZFvNpMkoHs4v
There are three parts to establishing a data-informed culture.
Infra — A company must invest in r&d to sufficiently collect, store, and structure all useful data that can help employees derive insights. Data shouldn’t be limited to user engagement logs. It should span further to include all valuable insights, such as customer feedback, market research, etc. Scalability and data integrity are often infra bottlenecks, especially for large consumer-web applications.
Decision — Data driven decisions are much harder to surface and implement. We need to allow everyone to challenge decisions across all levels to let the best data-driven ideas win. This happens in an environment where anyone can refute a CEO’s idea without repercussions. The key is requiring everyone to do the work beforehand and draw data to back up their ideas before bringing them onto the table. This raises the bar for discussions and decision making significantly.
Transparency — To allow data to precede over hierarchy, it must be transparent and accessible to all. Lack of clarity or confidence in data creates friction amongst teams when voting for the best ideas. Everyone should have the same access to sources of truth to derive insights quickly, and get on to the next steps of execution.
The importance of a data-informed culture is that people believe their intuition is right, but are often proven wrong. In the case of Facebook, we launched a zero-rated version of Facebook (Internet.org) in regions across the world without internet access. To reduce bandwidth cost and make Facebook accessible at zero cost for our users, we removed videos from their feed. While this didn’t feel intuitively right, our data showed otherwise. We learned that the utility value of Facebook (being able to communicate with others) in regions without internet access far outweighed the entertainment value (watching fun videos). Data often proves our intuition wrong.