Objectives and Key Results is a robust framework for setting and managing goals. Originally born and spread from big companies such as Intel and Google, OKRs became one of the most popular approaches to aligning the teams.
Naturally, the question arises: what are the limits of applying OKRs? Is it appropriate to use them for all types of companies or only for some kind of them?
In this article, we'll try to explore what are the limits and best practices on how to apply OKR methodology for startups.
OKR methodology is based on several fundamental principles that we need to remember before considering if it's appropriate or not.
In terms of the process, OKRs usually have a quarterly schedule, each team has 2-4 Objectives, with 3-5 Key Results. Individual Objectives are generally not recommended.
While the big companies that successfully adopt the OKR methodology, early-stage startups operate in a different environment.
For early-stage startups before the Product/Market Fit the main goal is learning and iterating. It's harmful to them to prematurely optimize any processes, as they are not sure yet if the process is the right one at all.
That's why some people argue that OKRs work only for 25+ people teams, and only after the Product/Market fit. For example, Andrew Chen, an investor at Andreessen Horowitz, claims that "OKRs are almost certainly harmful for pre-P/M fit startups."
But is it true? Which of the OKR principles early-stage startups don't want to have? Don't they want to have transparency around the ambitious goals? Don't they want to measure their progress? Don't they want to allow autonomy (even for small teams below 10 people)?
I believe that NO. Any size of the organization would want to have the benefits of the OKRs. The only problem with the standard OKR methodology for early-stage startups I see — that quarterly OKR cycle is too big for the startup. And it seems to be the only objection of Andrew Chen as well.
Here are some tips on how to adopt OKRs for the pre-Product/Market Fit startups based on my experience working with startups at Sommo.
Use shorter cycles
Even as small as 2 weeks if needed. Startup priorities might indeed change fast. But you need at least some level of certainty before turning your ship around.
Be ok to terminate the cycle and the current Objectives
If you figure out the new info and you want to pivot immediately — that's ok for startups. But likely you won't do it too often. It would still be best for your team to finish the goals in most cases and measure the outcome. So that you make data-informed decisions. Unless you finish your iteration and measure the results, you might be repeating the same activities and mistakes.
Focus on learning and validating hypothesis
For early-stage startups, you'd best set OKRs that would allow you to validate your hypothesis as fast as possible. Such Key Results as "talk to customers" or "conduct user interview" would help you do the right thing in your startup.
Having these Objectives written down would help you maintain focus and NOT do the other less-important things. And maintaining focus is essential for startups. So that you don't end up endlessly polishing your MVP with "just this last small improvement." The proper time-bound goals would help you stay on track and focus on what matters.
Some might argue that if you make these changes, it's no longer OKRs. Well, where is the holy unbreakable definition of OKRs? Even organizations that preach OKRs don't use them in the same manner. In Google, every team adopts the methodology for their needs. As long as the main principles are maintained, it is still the same methodology.
Again, OKR is just a framework that should only be used if it helps. In case you're a 3-people startup, sit in the same space and feel like you're all on the same page — you probably don't need OKRs. But as soon as you think that your team might be more focused and aligned — OKRs will help you, regardless of the size of your organization.
OKR is a powerful methodology for aligning your team and achieving great results. When adopted for your context, it works great both for big companies that focus on scale and for early-stage startups that focus on finding the Product/Market fit.
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