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Roots of the Feature Factory (1/n)

Published: March 27, 2017

What are the roots of the feature factory approach?

You can often trace it back to how efforts are funded, and how managers/team members are incentivized…


I expect everyone to advocate passionately for their ideas! What should we do? What should we build? Where should we go? If you want your project funded, you better be ready to make the pitch! We need a bias for action here.

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I’m not sure we actually agree on the desired outcome here. I advocate for us exploring what success would look like and building a shared understanding of the problem. How would we know if things were working? How will we inspire novel solutions from the team? Ideas are kind of cheap…


But what does that get us? I need to report to the board on what we plan to do, and how we will spend their money. Face it, people want solutions and they love a good plan. If we don’t get our annual project list done soon, we’ll look completely unprepared. You’re up against some big players here in terms of finding resources and funding. So what’s your plan? Just high level please … I don’t need the nitty gritty.


Well, we’ve got a list of things that have a decent shot of driving the outcome you and I discussed. Some are small, so we’d like to try those first. Some are bigger and riskier. Again, I’m not sure we all agree on the desired outcome…


What about the machine learning one? That was really good…


Um, yeah, well that one is pretty big. But …


But if you want the resources, you’ll need to be think big and be bold. “Just trying stuff” doesn’t really resonate. And you’ve got to consider optics as well. Sales has been chomping at the bit for something new. It’ll give you a chance to build some bridges with the data science team as well … and everyone knows they are in demand. A partnership!

Unless there’s a story, I’m not sure we can get you the engineering resources you need. You need a win here to advance your case…


Of course I want the team to win, but sales having something new is a different outcome, right? What about our current product makes it hard to sell?

We had discussed the outcome of reducing churn, and very few people are churning because we aren’t using ML here. I don’t want to add all of that complexity either… ops will get killed trying to maintain it all.


Oh, you have a lot to learn! You have to figure out which game you’re playing. OK, so the machine learning thing… we discussed that after the offsite last week and…

Sound familiar? How many issues can you spot?

There’s no silver bullet to defeat this kind of thinking. You have to be prepared to fight and show results. In my experience, the only way to change this mindset is to show that the alternative “works”. Elaborate planning and big batches are frequently a proxy for trust and confidence. Perhaps…

  • Propose experimenting with incremental outcome-based funding
  • Stay on message. Continuously report on outcomes. It will put pressure on other teams to do the same
  • Use projects as a trojan horse for missions. Remove feature names from project titles. Stick with the desired outcome If you are a leader/executive and you’re reading this, take a hard look at how you incentivize your team, and the degree to which your current planning process promotes batch sizes and silver bullets.

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