Mastering Controllable Inputs in Product Management

Fireside Product Management

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Last week on Fireside PM, I had the pleasure of reconnecting with an old Google colleague, Chris Vander May. We first crossed paths at the Kirkland office nearly 18 years ago, and since then, Chris has had an incredible career spanning Amazon, Google, Meta, and now his own AI-driven startup, Product Partner AI.

Chris has seen it all—from launching the first version of Google Meet to leading product and engineering teams at Amazon and Meta. Our conversation covered a range of topics, including the key differences between Google, Amazon, and Meta, the power of controllable inputs in product management, and how AI is reshaping the role of PMs. We also delved into how PMs can future-proof their careers, the evolving nature of AI in product management, and the best ways for PMs to leverage AI-driven insights.

Google vs. Amazon vs. Meta: The Cultural Differences

Chris offered a fascinating perspective on how these three tech giants operate differently:

* Google: “Google, in my time, was very much an engineering-driven culture. PMs were peers to engineers, and leadership pushed a 'Why not?' mentality—do the harder thing, even if it's more work.”

* Meta: “At Facebook, the PM was more of an ideas person. The ability to run rapid experiments at scale changed the dynamic. The role of the PM wasn’t necessarily about making the best decision upfront, but rather about trying things and seeing what sticks.”

* Amazon: “Amazon is much more product-led. There’s a strong culture of writing and documentation. You don’t just make decisions on the fly—you write things down to think them through rigorously.”

Chris expanded on these insights by discussing how leadership styles differ at these companies. At Google, the focus was often on engineering-driven innovation, requiring PMs to align closely with engineering teams. At Meta, the emphasis was on creativity and rapid iteration, where launching and learning from experiments was key. Meanwhile, at Amazon, data-driven decision-making and operational efficiency were deeply ingrained in the company culture.

The Power of Controllable Inputs

One of the most impactful topics we covered was controllable inputs, a concept deeply ingrained in Amazon’s culture. Chris explained:

“A controllable input is a metric that you directly influence and that drives business outcomes. Unlike vanity metrics that might look good on a slide deck, these metrics are actionable.”

He gave a fantastic example from Frito-Lay:

“They figured out that the key metric for stocking chips wasn’t total sales, but rather the number of stale bags on the shelf. If there were too many stale bags, they were overstocking. If there were none, they were losing sales. The right number was one stale bag per restock cycle. That’s a controllable input.”

For PMs, this means moving beyond simple engagement or revenue numbers to find the metric that actually drives sustainable growth.

Chris further elaborated that companies often struggle to identify the right controllable inputs because they conflate outcomes with inputs. A revenue target, for instance, is an outcome, but what actually drives it? Identifying and focusing on those drivers—whether it’s reducing onboarding friction, improving time-to-value, or optimizing conversion rates—is what separates strong PMs from the rest.

He emphasized that a good controllable input should have the following characteristics:

* Directly Influenced by the Team: PMs and their teams should be able to take action that moves the metric.

* Closely Tied to Business Outcomes: While it may not be a direct revenue number, it should be something that, when improved, positively impacts the business.

* Quickly Measurable: Metrics that update in real time or within a few weeks allow for faster iteration and learning.

* Resistant to Gaming: Vanity metrics like total app downloads can be manipulated through paid acquisition, but a well-defined input resists such distortions.

Chris also stressed the importance of refining controllable inputs over time. Many teams initially choose the wrong input and need to course-correct. A well-calibrated controllable input should help guide strategic decisions and enable PMs to set clear goals, allocate resources efficiently, and align teams around measurable outcomes.

Another example Chris shared was Amazon’s revenue per thousand opportunities (RPMO) metric for ads:

“Instead of just looking at total ad revenue, we focused on how much revenue was generated per thousand ad impressions. This allowed us to optimize for better targeting and engagement rather than simply increasing ad load, which could degrade user experience.”

He pointed out that these kinds of inputs serve as a north star for product teams, helping them focus on continuous improvements that compound over time.

How AI is Changing the PM Role

AI is transforming the nature of product management, and Chris believes it will lead to fewer but more highly leveraged PMs.

“Right now, we have around 900,000 PMs globally. In the future, I think we’ll see fewer PMs, but they’ll be much more strategic, working across more engineers and leveraging AI to do a lot of the traditional work PMs used to do manually.”

For aspiring PMs, Chris had some direct advice:

* Develop strong judgment. AI can generate ideas, but it can’t (yet) make high-level strategic decisions.

* Talk to customers. AI can process feedback, but it still can’t replace the intuition of a PM who truly understands user pain points.

* Master AI tools. “If you’re not using AI to make yourself 10x more effective, you’ll be replaced by someone who is.”

Chris also discussed the potential impact of AI on cross-functional collaboration. AI-driven insights can help teams make data-informed decisions more efficiently, but it also means PMs will need to refine their ability to translate AI-generated recommendations into actionable product strategies.

What’s Next?

Chris is now leading Product Partner AI, an AI-powered PM tool designed to help PMs be more effective. If you’re curious, you can check it out at Product Partner AI.

For those of you looking to level up your own PM skills, I’ve got a few things going on:

* Maven Cohort: A three-month small-group coaching program where we break down your career like a product, define your OKRs, and build a roadmap to success. Apply at Maven.

* Coaching: If you have a big product decision, job offer, or career move coming up, I offer direct coaching at TomLeungCoaching.com. I also work with company execs to support the coaching and learning of their younger PM teams.

Thanks for tuning in to this week’s Fireside PM! Let me know in the comments—what are your thoughts on controllable inputs in product management?

Until next time,

Tom

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Mastering Controllable Inputs in Product Management

Fireside Product Management

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published 8M ago