November 27, 2021

Shorten Your Feedback Loops

Happy Saturday and belated Thanksgiving if you're in the US!

This is such an obvious thing, so I don't know if anyone needs to hear this. But I'm gonna say it anyway because it's been on my mind:

Shorten your feedback loops

This is the whole premise of the Lean Startup movement, and something that's fairly obvious to everyone in tech.

With Lean Startups, you want to build a Minimum Viable Product (MVP), so that you can have your users use your product as soon as possible. This leads to quick feedback from your users, which is then used to make a decision on whether to scrap and pivot or improve your product.

I've probably read the Lean Startup book at least two or three times, yet I keep forgetting to follow the advice.

Remember when I shared that I was writing long blog posts and no one was reading it? And it took me 3 months to figure it out? That was a classic example of unnecessarily elongating a feedback loop.

Now that I post content on LinkedIn, the feedback I get comes much more quickly - either as comments and likes on my posts, as sign-ups on the Ops Hacks landing, or the most obvious of them all, dead silence 🦗💀

These are my LinkedIn posts over the past 2 weeks and how they performed, and you can already see that there's great variability in terms of views and engagement.

Being able to get the feedback (metrics) quickly helps me experiment, learn, and improve. For example, here are some lessons that I've taken away for LinkedIn (based on anecdotal evidence, DYOR):

  • Creating posts earlier in the morning tends to get more views and engagement
  • LinkedIn doesn't love non-original content (i.e. sharing someone else's post)
  • Personal stories tend to do better vs. tactical advice

As I continue to test content, format and logistics and get almost immediate feedback, I'll be able to refine my approach and up my LinkedIn marketing game.

Feedback loops in operations

The same principle of shortening your feedback loops applies in early stage startup ops. Whether your startup succeeds or fails depends on how quickly you find product-market fit or a repeatable and scalable growth playbook (depending on the maturity phase of your startup).

You're trying to find an answer to a question that has many hypotheses. These hypotheses have varying degrees of believability and require different amount of resources to test.

Most people (at least certainly me) tend to focus on two things when they're testing hypotheses: 1) probability that a hypothesis will turn out to be true and 2) resources required to test a hypothesis.

I think we should pay equal attention to 3) the length of a feedback loop.

Sometimes we feel so strongly that 1) a hypothesis will turn out to be true, that we'll irrationally trade off 2) resources and 3) feedback loop to test it.

(Hey, if your instinct is good and always on point, then go for it. I unfortunately am not; in fact, my instinct is terrible at times. Case in point - I joined Uber in 2016 and the current stock price is lower than the RSU grant price)

Anyway, some questions we should ask ourselves before we start testing hypotheses:

  • Can you find creative ways to shorten the feedback loop?
  • What is the order of operation in testing the various hypotheses given 1), 2), and 3)?
  • For this project, what's the right tradeoff to make between 2) resources required and 3) length of feedback loop?

Hopefully this is a good reminder of the fact that in startups, time is the most valuable resource - and that we need to be more intentional about how to make the best use of it.

What are your thoughts on shortening feedback loops? Obvious stuff and a waste of time reading about it? Interesting and it's given you something to think about?

Take care and see you next week.


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