Product Agility

Phil Hornby: Empower to Succeed: How to Make High‑Quality Decisions in Product - Productized 2025 TalkInTen

• Saloni Seth-Watkins, Phil Hornby, Ryan Lane

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Welcome to another brisk Talk in Ten recorded live at this year's Productized conference. In this episode, Phil Hornby (founder of For Product People) explains why empowerment in product teams really means the ability to make decisions that stick — and how to raise the quality of those decisions.

Key topics discussed:

  • What a "high-quality decision" is and why it’s distinct from a "good outcome."
  • Evidence-informed decision making: combining quantitative data, qualitative insight, and expert judgement.
  • Practical tactics: decision logs, Amazon-style memos, and setting a "best-before" date for revisiting choices.
  • How to evaluate decision quality without falling into the blame game.
  • Where AI fits — as a tool to inform decisions, not replace human accountability.

Guest bio:

Phil Hornby — Founder, For Product People. Phil runs workshops and talks, helping product teams make better decisions by combining structured thinking, evidence, and practical frameworks. He focuses on turning tacit product judgement into explicit, defendable choices that teams can commit to and act on.


Thank you to our partners at Productized for hosting such an inspiring event and to our sponsors Bobcats Coding — a Budapest-based digital product studio specialising in AI engineering and end-to-end product development. Download their AI economics guidebook at bobcatscoding.com.

Host Bio

Ben is a seasoned expert in product agility coaching, unleashing the potential of people and products. With over a decade of experience, his focus now is product-led growth & agility in organisations of all sizes.

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Welcome to the Product Agility Podcast where we explore the ever changing world of product leadership and org design, helping you navigate complexity and build better outcomes for your people and your customers. This week we're coming to you live from Lisbon for the third year in a row at the Productize conference where I'm grabbing 10 minute conversations with product thinkers, leaders and innovators from around the world. These quick fire chats are all about what's shaping our industry right now, from AI and product strategy to the human side of building great products. Now a huge thank you goes out to Bobcatz Coding for making this Lisbon series possible. Bobcats is a Budapest and Lisbon based digital product studio specializing in AI engineering and end to end digital product development. They're also on a mission to educate the market, exploring a new topic every six months and this fall is no exception. Their latest AI economics guidebook is out now and you can download it for free@bobcatscoding.com now here's your talking 10. Hello and welcome back. Still on day three of the wonderful productized conference here in Lisboa. We are the Product Agility Podcast and I am salonie Seth Watkins. I am not Ben Maynard, who's having his voice is probably having a well earned break today. I think we're on number 22 now. I'm looking at Srin, our producer. So yeah, we're still going. We're still going. Next to me, I have the wonderful Ryan, who's the CTO for Bob Katz coding. Hi, good to be here. And we are interviewing Phil Hornby this morning who's a founder of For Product People. That's correct. And your talk and workshop, which you've also done, is called Empower to Succeed Decision Making in Product. Now you've been on the podcast before. That's true. We were looking at this earlier. I think you did something about. What did you talk about last time? Something to do with features or something. It's probably roadmap. Roadmapping. Okay. But it could be decision making. The kind of two gel together. Perfect. So tell us a little bit about your workshop and the talk you're about to do. So the talk I'm about to do is fundamentally anchored on this key premise that empowerment is something we're all told we should have in product teams. But what does it really mean? Empowerment is really the ability to make decisions that stick. But no one's actually ever been taught how to make a good decision. We just assume we're still alive. So we made some decisions. We didn't die so they must be alright. And so we go into these jobs and we're expected to make these quite consequential decisions without any really formal background or understanding of how to go about it well. And so there's a concept of a high quality decision that we're going to talk about in the talk and it's really got multiple parts, but it's like it's framed well. We consider options, we kind of justify it, we bring together the evidence to support it, we tell the story about it, we actually commit and take action. And these things all come together as a chain in terms of high quality decisions. Now I want to stress a high quality decision doesn't mean it's a good decision with a good outcome because you can still screw it up even if you do it well. Now you increase the odds of getting a good outcome by creating a high or taking a high quality decision because you're basically loading the odds in your favor. You're doing the due diligence. But some new information might come in tomorrow that invalidates what you thought you knew or the world changes. A black swan event happens. It can still all go wrong, but you've got a much higher chance of being successful. There is no way of guaranteeing a good outcome. A good decision. There's always a chance of it going wrong, but you can make it a much better chance. That helps you if you make it a high quality decision decision. And there's a core tenant I believe in of what I call evidence informed decisions. Most people these days talk about being data driven. What BS Data tells you? Nothing. Data needs to be interpreted. Data needs to be looked at and understood. And we have the quantitative side. Now we all do discovery, we go and talk to customers, we do interviews. That's the qualitative side. So that's another form of evidence. That's why I talk about it as evidence informed. We've got two lots of evidence. Data, quantitative and anecdotes or stories that are more qualitative that help us understand the data. But then we are product people, I hate to say it, but as product people we are paid to have opinions. We are paid to have a perspective. We have intuition. We have spent years trying to understand our markets, understand our customers, building up tacit knowledge. We need to bring that tacit understanding and make it explicit so people, we expose it and say this is why we have this opinion and bring those three together because sometimes you just can't have data. Tony Fadel in Build talks about accepting that some decisions are opinion driven. The first creation of the iPhone or the ipod just had a ton of opinion based decisions in there. And yes, it might have gone wrong. We love looking at the success stories out there and how they made that opinion based decision. It could have gone wrong. There were other companies like he was actually part of a company called Magic Leap which was a spin out of apple in the 90s that tried to create the iPhone. It all went wrong. The technology wasn't there, the need was there, but the opinion was we can do this, we should do this. It went wrong and that's always a possibility. But we've got to. They understood the market and the customer need, they just couldn't create it. The technology wasn't right. And understanding that you're going to make some opinion based. We are all human at the end of the day and AI isn't going to take away the decision or AI shouldn't take away the decision. It's about working with say tools like AI to help us make better decisions. But ultimately there's a classic IBM quote, computer can't be held accountable, a human can. Even asking AI to make a decision is a decision. You are delegating that decision, you will be held accountable for delegating. So you're still making the decision, you're still accountable. And so as a human, let's understand that and let's make sure we create a high quality decision that we can stand behind and that we can get other people on board with as well. That's fascinating. Are there processes that you embed this framework inside of or is this more of like a value proposition? So this is kind of a generalized framework to decision making. And I'm not the person who created this. This comes out of some guys in the US in fact, and some other stuff from Ravi Meta as well I've just mentioned there, but I'm bringing it together. But it's a generalized way of thinking about how to make high quality decisions. Like you need to look at options. Like Matt Lemay in his Impact first product Teams book talks about don't just consider one scenario, it's not a yes or a no. Or don't even just have two. It's not an either or have a minimum of three scenarios you're considering because often you'll find a better option by doing that. And it might be take one from one, one from the other or parts from each of them. But that contrasting and considering which ways to go and what matters and knowing the actual context of what matters as well helps you then make the Right choice in your context? Because there is no. In fact I just use a bad phrase. I said the right choice. There is no such thing as one right answer. There is an answer that you are happy with as an organization based on what you know. But there can actually be four, five good answers. You've got to pick one. Do you have a perspective on, on, on tracking these decisions? So if there's, you know, if we all put so much additional thoughtfulness into the decision making process, is there an analogous way of evaluating them in the long term over different time. Time. Time frames? How do you, how do you look about evaluating decisions retro. Retroactively. So a couple of things are going to put one, I like to keep decision logs like a list of all the decisions I've made. In fact, typically most decisions I drive to bring the clarity end of writing a one to six page or Amazon style memo. And so that document lives and I can go back and revisit it and like I'm working on one right now. I just got some more information in this morning. Ah, I need to tweak a little bit. 90% of it's still valid but one part is not valid anymore. So we're going to go back and revisit it as a team. But I think there's also a. You can almost set a best before date on any decision. When are we going to revisit it? Because one of the things that creating clear decisions gives is teams the ability to run and execute. But if they, if you're constantly revisiting that decision, then they never know when they are going to get redirected. Like it's the classic. Every month we have a new strategy, a new vision. Well, teams just don't commit. They just carry on with what they were doing before because they know next month it'll change, the next month it'll change. So if they know when it's valid to be revisited now, maybe there are certain triggers or maybe it's time horizon based. You can set what are the criteria for when we're going to go back to this and we'll reevaluate it. You could also look at evaluating decision quality. The problem is that what you find is people tend to fall into the evaluating was it a good decision or a bad decision? As opposed to did I make a high quality decision? And that subtlety is important. We will all make bad decisions even when we make them high quality, but we'll have a higher chance of doing a good decision if you go back and revisit it and evaluate it. Was it good or bad? It tends to form into that classic blame game area, which is what you're trying to avoid. It's like we all got on board based on the evidence that we had in front of us and the opinions that we all had and aligned on. Let's move on. Let's not go back and judge did we make a bad decision. Let's look at whether we can make a better or higher quality decision next time. I love that because we're so, we're so used to these days putting things into this or that binary and, and that's sort of the instinctive management decision of that, you know. And what you're saying, if I've heard it correctly, is true empowerment. We have to go into that. We have to really explore that. And I like this thing about high quality versus good or bad. So I think introducing that kind of vocabulary does change the whole nature of this, this decision making. So, yeah, you've got to be open to failing. Yeah. People use throughout the terms like feel, feel fast, fail often. Yeah, I actually hit the phrase feel fast. Yep. It's learn fast is my preference. It's like I haven't failed if I. Learned, which was probably how it was probably meant in the first place. So. No, that's been wonderful. Thank you very much. I hope that's given you some preparation for the next. So for your, your talk next. Thank you for your time this morning, Phil. And thank you again to my co host, Ryan. And that's another talk at 10 and we'll see you on the next one. Thanks, Bye.

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