#547 Why OKRs Fail: Radhika Dutt on Building Teams That Think, Learn, and Adapt

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Mehmet: Hello and welcome back to a opposite of the CT O Show with meed today. I'm very pleased joining me Radhika Dutt she's author of radical product Thinking. We're gonna talk today about a topic, which in my opinion is very important about, you know, [00:01:00] how we measure success. I don't want to steal much from. My guests usually Radhika.

I keep it to them to introduce themselves. So tell us a more about you, your background, your journey, and what brought you to, to write the book and do what we do today. 

Radhika: Uh, it's so great to be here, mammoth and good to meet you. Uh, so my background is that I'm an engineer by training and I studied engineering at MIT.

Uh, my first startup was right out of our dorm rooms at MIT. Uh, and you know, it all sounds glamorous, but I can assure you it really wasn't, uh, it wasn't glamorous because we made so many mistakes. Uh, and, uh, what do I mean by these mistakes? You know, these are mistakes that are so common in the startup world.

Uh, it's now what I call product diseases. They're diseases that make good products go bad. And I'll give you one example of a product disease that we had caught, uh, our vision. Uh, and this was back in 2000, our vision was [00:02:00] revolutionizing wireless. And now, you know, I still wonder 25 years later what we actually meant.

Um, while we had this big, fluffy vision, right? The reality was we just weren't clear on what is the problem we are setting out to solve? Why does it need to be solved? Um. Without that sort of clarity, the way we measured success was by how much fundraising we had done and you know, how many big logos of customers we had on our website and so on.

Right. Uh, but my first book, radical Product Thinking, which came out in 2021, it's about these product diseases and how you can avoid them, uh, by. Uh, very systematically translating your vision into everyday actions. And it's a way of building world-changing products that gives organization a step-by-step process that provides, you know, clarity on vision.

How do you translate it into a strategy and so on. What I found was, and this is what is leading me to [00:03:00] write the second book on why goals and targets don't work. After reading my first book, a lot of people came to me and said, you know, I really like this long-term approach you're talking about. I like that you're.

Talking about how to think long-term, balance it against the short-term business needs, how to avoid vision, debt, et cetera. But my company is just driven by goals, targets, um, it's driven by OKRs or objectives and key results, and I find that. I can't think long term that I have to keep driving towards these short term numbers.

And so what do I do in that scenario? And this question came up so often and it made me realize that, you know that for a long time I'd been the one feeling like goals and OKRs. Don't work, but I couldn't articulate it, but I thought it was just my problem. And so hearing these comments made me realize, okay, this isn't just me.

Like this is a very common thing that happens. Um, and so what do we do instead? [00:04:00] And that what, uh, that's what led me to work on this next book that I'm working on. 

Mehmet: Great Ika, you know, like in your introduction you mentioned something, which, uh, stuck with me and I'm sure you're gonna, we are gonna have, uh, a lot of, uh, points to discuss with you.

You mentioned about these fluffy things and you mentioned about like, uh, and, and I will come back to the OKRs and, and the other stuff, but yeah, starting from here. And I, you know, while preparing with, with the information that I had and, you know, reviewing some of your work, um, I've seen, like you've said, like many systems are designed to motivate that, that actually they, they kill motivation.

Now. This is, for me, it's like, um, you know, something that. Should stop everyone because especially in today's world, and you gave the example of, you know, the wireless and you know what we're trying to do. Why do you think Radhika, this keeps happening again [00:05:00] and again and again? Um, is it like a human nature?

Is it like, uh, you know, we like to be. I would say kind of trapped by these things. What do you think? Really the motive for us to always believe that? Yeah, like let's do this, let's be, let's get the fundraising, let's get the logos on the website, and then we figure out like, actually, you know, we are in CAD of era, I would call it similar to era race, if that makes sense.

Radhika: Yeah. Um. There are two reasons I see for, uh, because you touched on a few topics. One is the motivation aspect, right? So we'll talk about that. But the other aspect that you talked about is why do we measure success in this way? Uh, where it's so many vanity metrics as I call it, you know, vanity metrics of how much fundraising have we done, um, how many logos we have, et cetera.

Um. In terms of motivation, the first thing is [00:06:00] there's always this misconception we have that we need to motivate people. That motivation isn't an intrinsic thing. You have to give people and drive people with that motivation, extrinsically, um, that is the first misconception. And so, because we wanna try and push this motivation on people, we think, oh, I need a really inspirational vision statement.

Um, and this inspirational vision statement is what's gonna keep my team together? You know, in our case, that inspiring vision statement was supposed to be revolutionizing wireless, right? Because we wanted to sound big for our team, but. When you have these big vision statements, whether it's, you know, uh, something like revolutionizing wireless or reinventing warehousing, um, I've heard things like, um, uh, contributing to human progress by empowering people to express themselves.

What does that even mean? Right? Um, when you have a vision like that, you no longer have a filter. Basically [00:07:00] anything goes, if you hold up a feature against a vision, like empowering people to express themselves and thereby creating human progress, like any feature will go, um, I could be a dance studio to match this vision.

I can be a company that makes, uh, post-its so that people can express themselves better. Um, it could be, you know, a fashion brand. Anything goes when you have such a broad vision. It's not motivating, it's just confusing. But this is what we think we need. Um, so that's the first piece of it. And then there's a second piece of it, which is because we have these fluffy motivation or, uh, vision statements, um, we also think, well now I need goals so that I can tell you exactly what I need you to achieve.

So then to basically make up for these foundational cracks, we then set goals like band-aids on top of these foundational cracks, and we say, okay. I wanna define the [00:08:00] impact I need you to create. You know, here's the goal that you have to hit. And that's the other piece of the extrinsic motivation that we try to drive.

And again, it creates the wrong sort of mentality, uh, and the performance theater where you create the incentive for people. Ta-da, I've hit the number you wanted, but it's not whether or not you've solved the problem. 

Mehmet: Right. Uh, if you allow me, like also something, which I spotted it and I gonna talk about, you know, the, the performance, which are like the short terms with you now is.

Uh, it's, it's kind of human nature to think that if we did something one time, it and succeeded. So whenever we repeat it, it's gonna succeed everywhere. And this is, you know, um, I discovered this late, but I was happy that I discovered, but they're not is when people, they talk about the first principle, right?

And, uh, I've seen this multiple times. Ika, when a company starts very well, you know, they [00:09:00] have a very good start and then someone. And, and that's why I don't call myself consultant because I unfortunately the word start to get associated with such things. Uh, a consultant comes and tell them, Hey, like if you take the framework that X company did, you're gonna guys rock, right?

And then here I gonna talk with you about, uh, KPIs and all K or all OKRs, right? I know, and by the way, uh, even I have a friend that we, we, we, we use the same term. Like we say, like these guys like worship, these, you know, KPIs and O OKRs, but from you as expert and someone who, who work on this, uh, Radhika, what do you think fundamentally is broken and why team, do you think?

What teams in general, they use them? In a wrong way. I would say, 

Radhika: first of all, it's not that they use them the wrong [00:10:00] way. This is actually what a lot of KR experts say. They say, if goals aren't, or if OKRs aren't working for you, you are using them wrong. Mm-hmm. And it's really not you. It's not that you are using them wrong.

Here's the fundamental issue with OKRs. What happens is OKRs. Give people the incentive that you have to hit all of these numbers. And so the incentive it creates for teams is I wanna show you that I'm a high performer, and to show you that I'm a high performer. I'm gonna show you that I've hit these numbers.

So let's take an example. When you set, let's say the OKR, that we wanna grow the business and, uh, one key result is get to 20,000 signups by, uh, the end of this quarter. Well, you know, when you set a number like that, I'm gonna wanna show you that I've hit 20,000 signups. Like, you know, you set me a target, I'm a high achiever.

I will do it. [00:11:00] So I go get those 20,000 signups. But you know what? It makes me look less deeply at what did I do to get those 20,000 signups? Maybe I threw a bunch of money into doing paid advertising to be able to get those 20,000 signups. I didn't build sustainable sales channels that actually cost less.

Or maybe it was that I got those 20,000 signups. But I wasn't, uh, removing all the bot signups, et cetera, because hey, it helps me hit my number. And honestly, the last piece of this is not even malicious. It can be subconscious. It can also be that I hit the 20,000 signup number and I'm happy, and I say, great, I'm done.

But then if I look underneath and say, how did I get those 20,000 signups? Maybe I discover actually. It's not the target segment of people that we are targeting at all. I know that it was a bunch of students who signed up and they're not gonna convert to anything else. This [00:12:00] is a product for managers.

It's just students happen to sign up because that's, you know, whatever sales channel got them into it. My point is when you set targets, people are showing you the good numbers. Whereas what you really want is you want them to look at the bad numbers. You want them to look at, Ooh, you know what? This is not the right target segment.

What went wrong? What do I do instead? What can I learn from this? You want them to play detective and that whole muscle for experimentation, the learning for the learning, the reflection, and the adaptation. That muscle atrophies with OKRs because everyone wants to focus on the positive numbers on proving that things are working as opposed to questioning what is really working, what is not working.

Mehmet: Uh, and, uh, just as a follow up, Rika doesn't, I'm wondering why people, they don't figure out that, uh, you know, this is contradictory, for example, with something like design thinking because, you know, [00:13:00] um, you need to have these. Um, mistakes recorded and followed up, and then you try to go and improve. And this is the story of every startup, every company, you know, whether it's like, uh, you know, whether it's Google and other, I'm saying Google because we know, like Google, they have set the rise on the OKRs.

Um, and, and this again, my point. We, maybe it worked for them, don't get me wrong. Right. But doesn't necessarily mean it's gonna work for, for, for you, you know, I mean, in the way you described it. Now, my question to you is, why do you think. Um, leaders, uh, believe that, uh, rigor equals more metrics. Mm. You know, like, but they, they have this itch.

Is it because this is how they were taught? Someone told them this? What's your opinion? 

Radhika: Uh, two things I wanna touch on first, you mentioned the Google example. You know, there's often this [00:14:00] belief that it does work at Google because Google has been evangelizing OKRs. I've talked to so many. Uh, anonymous Googlers, and you know what they said?

They go like, oh, OKRs. That's our secret tool for actually making our competitors fail. We evangelize OKRs just to make them use it and fail. 

Mehmet: That's funny. 

Radhika: So, so it doesn't work necessarily at Google. Um. And, uh, there's actually a really great example even at Google where they set OKRs and how it led to perverse incentives.

Uh, in fact, John Doer talks about Google and this example where Pichai, when he was leading Google Chrome, he had set OKRs. And actually John Doer talks about this as a fantastic example of exactly how she, you should set OKRs. So what was the example? He said, you know, Pichai set the KR. Of building the best web browser.

And then the key result in the first year was get to 10 million, um, users, [00:15:00] and they didn't get to that number. Then the next year he doubled down getting to 50 million users and they got to, you know, something like in the range of 20, and he was like, yeah, you know, that didn't go well either. Third year he said a hundred million users, and kaboom, they got to 111 million users and that was apparently proof of OKRs.

Succeeding. You know what? Yes, Kaboom. Indeed. They go to 111 million users. But how did they get there? They got there through anti-competitive practices. They made it mandatory for all of the manufacturers to install Google Chrome as the default. I mean, that is how you got to it. And European Commission hit them with the biggest fine to date, um, of many billion dollars.

And it was their biggest, biggest fine for these anti-competitive practices. This is what I mean, that we hit targets, but not because we've actually solved the problem. In this case, it worked for Google. Why? Because they had the monopoly and they [00:16:00] could drive that com. Anti-competitive behavior. Now let's go to the second question that you had, which is why do leaders then believe that this works?

Right? Right. And the answer to that is. Goal setting is so entrenched in corporate Psyche. We've been told for decades. For decades that goal setting is how you build big businesses. Um, and so we've really absorbed this and we think this is the only way to do it. So let's go back to why do we think this is the way.

Where does this idea come from? Like, why did we come up with goal setting and not, let's say, I don't know, um, setting puzzles in the, in, in the corporate world and the answer dates all the way back to 1940s to Peter Drucker's work in management by objective. Basically Peter Drucker, he came up with this revolutionary idea of management by objectives.

Let's set targets together with our employees. It was revolutionary for that, [00:17:00] for that time, and over time, other leaders adapted that. So Andy Grove at Intel, the legendary CEO. Took management by objectives in the late seventies and he called it OKRs. And then in 2018, this was what was evangelized by Google and uh, John Doer.

So we think this is a new idea, um, and if it's works for Google, it should work for us. So I understand why leaders think this works. But I want to show, peel back the curtain to show reality on this. Yeah. Let's look at 1940s. What was the problem that Andy Grove was solving? So I did some research. He had been working with General Motors at the time, and the problem statement with General Motors was that he was working with primarily.

A workforce that was doing repetitive tasks. There was no automation and there's one right way to do things on the assembly line. There's one right way to [00:18:00] install tires to screw in this, like there's one right way. And in that scenario. Goals work. This is what research shows when you have a repetitive task, like when you're lifting weights in the gym, when you are, uh, stuffing envelopes for a campaign, if it's a repetitive task.

Goals work really well. To drive someone to achieve those numbers. Right? And this is why his scenario at General Motors in the 1940s worked. Now let's take the same scenario and think about the workforce today. Everything that can be automated and more has already been automated. We have a workforce that is not working on repetitive task.

Every problem they work on is typically a complex problem that's more like solving a puzzle. And yet we're using goals. So what happens even on the manufacturing floor at Boeing, you've seen the kind of quality issues when you have production targets. [00:19:00] Um, and it's because everything that's been automated has been already, 

Mehmet: uh.

That's make a lot of sense. I cannot tell you, you know, uh, one thing also, this is why personally, you know, uh, and, and you mentioned about how this was working for 1940s in manufacturing. Uh. With known factors, right? So as you said, like, yeah, we, we know exactly, you know, how the assembly works. So if we try to say, yeah, like we want to get 40 of this per hour, let's say 40 cars.

Right, so we know exactly what's the process, and then either you add, you know, more people on the, on the line, you add additional production lines, whatever. Now this is why myself, I'm, I call myself the anti playbook guy, especially I work in sales also as well, and every time they used to bring us.

Without mentioning, of course, with respect to, to, to, to [00:20:00] every person in this, because I know also they put efforts in this. It's not like to, you know, put them down. But, um, I get your point, which, uh, I am advocate of it. It's about the knowns and the unknowns and for example, that's why I tell people, like when you try to bring any KPI or measurement of.

Success for sales organizations specifically, and this applies to startups 'cause I, I have like, love for them and I want to succeed. So I tell them guys, don't go bring a playbook. Whether it's o OKRs, whether it's like any other framework because you don't know you have unknown factor. You don't know like what's, uh, if are the market conditions the same, that when these people came up with this framework, it's still applicable.

Second thing, geographies. Um, people, right? So not all people, they react the same way. Now, saying all this radical, you know, and, and you see like, I'm trying to, to, to take it from a big problem, which is, it is. [00:21:00] Some people might be listening and saying, okay, we get it. What's the solution? And I know like you propose a radical shift, you call it OH Ls.

Objectives, hypotheses, and learnings. Tell us a little more about it. 

Radhika: And by the way, mammoth, I love what you said about. Uh, frameworks. I am usually really against frameworks, right? Um, and I know I, I offer frameworks, but at the same time, why am I so against it? Because I feel like exactly what you said, frameworks they have, they're, it's like physicists saying, oh, this ha, this is a great solution and it works for spherical cows in vacuum.

And you go like, I don't have spherical cows and it's not vacuum. How does this work for me? Um, it doesn't, right? And so to me. A framework isn't great unless it creates a mentality or a mindset that, uh, that is shifted and a framework brings about a mindset shift that yields better results. If a framework is just a [00:22:00] process, it's just more work, and this is why I don't like OKRs.

So let's talk about what is the mindset shift I'm working on bringing about and OHL sounds dry. So once we talk about the mindset shift. The framework starts to become more obvious. So the mindset shift is, instead of goal setting, it's one of puzzle setting and puzzle solving, because that is more the nature of our work these days.

We are solving puzzles at work. It's really complex puzzles. And so to bring about this mindset shift from goal setting to puzzle setting, let's take an example of how this framework works. And you know, you mentioned sales, so I'm gonna look at a sales example right now. Traditionally, the way you would do it is you would just set a target for sales, which is, you know, you wanna achieve X million, uh, in, in terms of sales targets by the end of this year.

Instead, a puzzle would look like this. I would still maybe talk about, well, we want to get to X million in, uh, [00:23:00] sales. But I see a problem and the problem I see is sales grew in the last three years. Uh, they've really stalled in this last year. And I don't know what is happening. This is the puzzle. If I knew all the answers, you know, this wouldn't be a puzzle.

So here are some open questions I have. Is it that the market has fundamentally shifted that maybe with AI there's something happening and we haven't really figured out how to adapt to this market? Maybe it's that our messaging was resonating for the early adopters, but our sales message is not resonating for the mass market or maybe the product.

Uh, the problems with, you know, our product and what we have built, that it resonated for our early adopters, but it's not meeting the needs of the mass market. And so I ask these open questions and the summary of the puzzle is how do I solve this puzzle to then get back to that growth trajectory? So now I have aligned the team.

We've [00:24:00] talked about what are the questions we honestly don't know answers to? And there might be, as a leader, different pieces of the puzzle that different functions take away. Now that we've set the puzzle, let's look at how we solve the puzzle. So the puzzle setting, by the way, is the objectives. Mm-hmm.

And now, um, I, I've changed the name by the way, of the framework. I now call it Ola instead of o hls. Easier to say it. Ola And the. OLA stands for objectives, hypotheses, learnings and adaptations. Mm-hmm. And so the last part of this, the puzzle solving, is the hypotheses, learnings, adaptations, and it translates into three questions.

Three really easy questions, right? First one, how well did it work? What do I mean by this? Whatever your first attempt is at that puzzle. When you try it, how well did it work? And you notice the difference between goals versus this approach. I'm inviting the good and the bad. When I [00:25:00] ask how well did it work, I'm not asking a binary question, did you or didn't you hit this target?

It's really an open question. How well did it work? Let's look at the sales example. Maybe what I tried is, you know, from the sales angle, um, I was managing to get meetings, but maybe. When I'm trying to approach the mass market, my messaging wasn't resonating. So I'm trying this new messaging and my hypothesis was this new messaging, how well did it work?

Well, it turns out this is working. I'm getting meetings with those decision makers. So great. That's the answer to the first question. Second question, what have I learned? What have I learned from this? Not just numbers. Don't just tell me I got X numbers of meetings, here's my sales pipeline, blah, blah.

What have you learned? And the answer to this may be, you know, great, I'm getting those meetings, but I'm finding that here in the mass market, there's an extra group, uh, [00:26:00] beyond the decision maker that needs to approve. And I'm, I've traditionally just never targeted this group. I don't know how to talk to them or what drives them.

So that's my learning. What have I learned? Then comes the third question. So based on how well it worked and what have I learned, what will I try next? Like if I had a magic wand, what will I ask for? This is the adaptations. And so in this third question, maybe the answer is, I'm going to create a webinar to address this group that I've never talked to before.

I might also create materials that the decision maker can easily forward to this group, um, to get them to buy in. And now by the way, you notice that in how I adapt, it's already setting up that next puzzle. 'cause now I can try this out and see how well did that work, what did I learn from that, and what will I try next?

And so what this offers is a way of setting a puzzle and then solving a puzzle. But. You know, how's this different [00:27:00] from Lean Startup? You're not just focusing on experimentation. You have to stay in the exploration space and asking questions for a little bit longer to really understand and define what is the puzzle before you just jump into experimenting.

Mehmet: Um. And I think this iica can be applied in, in, in, in any organization, regardless of the size, because now we are not. Uh, and I like the flexibility, which is the last part. And now I'm, I'm happy you corrected me. You call it now, Ola, which is the, uh, the adaptation, which I think this is where, um. The importance is like, it's not a rigid framework.

Playbook, you know, people, they love, and again, back to your intro, I'm going back there. People, you know, we, we, we like to be attached to these things and um, especially now with the age of AI and everything is changing around us. So we need this, uh, you know, adaptation Now [00:28:00] saying ai, and I know like we are not talking about the tech itself.

Um, have you seen like, you know, organizations who are trying also to. Put as goals, we want to be in the ai. Um, maybe we want to, to, to adapt it, uh, as, as a technology or we want to create something with it. Um, have you seen any results by, you know, using your framework, they get maybe a better understanding on how they need to plan these and how they need to measure their success rather going with like.

Other frameworks or older models like the OKRs and and, and KPIs and so on. 

Radhika: Oh, what you say so resonates because there are so many companies right now that are thinking about, you know, uh, ai, uh, and, and also thinking about AI first. You know, there's so much fomo. Yeah. This fear of missing out, like everyone who's saying AI first, like now it makes you think, oh, I need to do this too.[00:29:00] 

Um, and so there, in terms of this puzzle setting and puzzle solving. In my own experience in working with consulting, uh, with companies in my role as a consultant, right? What we do is if we use ai, it is very deliberate. We've defined the puzzle well enough that we realize. To solve this piece of the puzzle, we really do need ai.

If there isn't a real need that this would help truly solve this problem, then there isn't a real need for ai. This is something that numbers are showing us right now in the economy, that there's such a huge, uh, outpouring of investment in ai. That in many ways, that is what is floating the economy, and yet most companies aren't yet seeing a return from it.

And so in terms of a framework. The real question is what is the problem you're solving? Um, you know, I mentioned vision at the very beginning, right? Right. In the radical part thinking book, I talk about vision and [00:30:00] strategy. Here's a framework for a vision so that you don't write, you know, just, uh, BS visions like, uh, being the leader or revolutionizing wireless.

So here's a vision statement in a fill in the blanks format, and I'm gonna fill this out in. Um, for a startup that I had in 2011, sold it in 2014, and I'm not gonna tell you anything about the startup. I'll just tell you the vision today. When amateur wine drinkers want to find wines that are, that they're likely to like, and they wanna learn about wine in this way, they have to find attractive looking wine labels and find wines that are on sale.

This is unacceptable because it leads to so many disappointments and it's hard to learn about wine in this way. We envision a world where finding wines you like is as easy as finding movies you like. On Netflix, we are bringing this about through a recommendations algorithm that matches wines to your taste and an [00:31:00] operational setup that delivers these wines to your door.

Now in an AI first world, right? I would've probably jumped into, you know, better AI so that we can give you personalized recommendations and learning about wine, right? But what you'll notice about this vision is we focused first on the problem statement. Who has that problem? It was amateur wine drinkers.

It's not the people who are so snobbish and know about wine. Uh, and in which case, they're gonna feel like your recommendations do nothing for me. I'm too well-versed in wine to learn from your algorithm. Right. So we were targeting the amateur wine drinker then. You know, if you look at what is the problem we were talking about exactly what the problem was.

These people sort of choose wines randomly based on attractive looking labels. Why is that unacceptable? What is the world we envision, you know? We didn't even talk about AI or machine learning at that time. We still were talking about the problem, which is the personalized recommendations, et cetera. So my [00:32:00] point is, as you think about what is your vision, uh.

Your vision isn't ai. Your vision is not AI first. The only place you talk about ai, where you finally earned the right to talk about AI is when you've defined the problem so well. You know, you've understood the problem. You've talked about why the current, why the status quo is absolutely unacceptable, and then finally, how you're solving the problem.

And AI may feature if that is in fact the right approach. 

Mehmet: Um, you know, it's so simple, but I don't know. Me included, sometimes we, we fall in this trap, right? And I tell people, you know, if you want to see something, uh, on stage, done perfectly, uh, I know. Whether you like or not, fan or not, but, uh, I tell people like, go and watch, uh, Steve Jobs introducing the iPhone.

Because if he started saying like, Hey, we have, like, uh, if he started with the CPUs and [00:33:00] you know, all the, no one would get it, but he, he was telling the story like, why? Actually people were not even aware about the problem, but he was like, I, I, this is a scene I can't forget, which is, you know, saying about the keyboard and how it's not UI friendly and you know, all this and we stuck and then we need something better.

And I always tell people, now back to the AI thing, like if you start, if, if I, I, I'm telling everyone if I see a pitch deck starting with Wei, the we are the AI for this. I'm telling them, no thanks, but no thanks because. I'm not sure what you're doing, guys. Like, uh, I just, before I, I came, uh, to record this, uh, episode with, youre like, I saw someone sent me like, we are the AI for trading.

So what, like, you know, uh, but this is, again, this is important for founders and or like entrepreneurs who are listening to us to understand this now. [00:34:00] For getting everyone on the same page. So I know usually there are two approaches of doing this, so it's either coming from up to down from the management all the way down, or vice versa in case of Ola.

Like how, you know, have you seen it working in a better way? Is it like, you know, CEO come and say, Hey, like. I want to set this up in my company and I want everyone to be on the same page. Or is it like, no people from down, they start and then it goes all the way up to to the top management. 

Radhika: Yeah. Uh, this is such an interesting question also because I've tried and made mistakes and so let me share my learnings along the way.

Sure, 

Mehmet: please. 

Radhika: So, my first mistake was going only top down. So, you know, a company that I've been working with. I first talked to the leader and I said, you know, let's not use OKRs or targets. Here's why. And I gave him all of this rationale that I gave you [00:35:00] earlier in our podcast, right. Um, and it turned out like it was really just hard for him to accept as a leader because, you know, it's the only thing they know, like goal setting is the only method that they know.

So even when I introduce a new approach, yeah, it sounds good, but it sounds downright scary because I've never tried this before. And you know, there's this fear that if I'm doing this puzzle setting and puzzle solving, am I basically letting my team off to the playground and I'm telling them, you know, off you go.

Play. When you're done, come back and let me know how it went. Puzzles have this, um, connotation. Like is it just fun and games that my team is off to go do. So there are two things. First of all, to know as a leader. Which is puzzles is not just fun and games, it's incredibly rigorous because people are measuring more than what they would just with OKRs 'cause just KR measurements.

And those targets are not enough to be able to give me an honest answer to what have you [00:36:00] learned? I expect a lot of measurement and you should be able to tell the story about exactly what's happening. And if I ask a couple of questions and you don't know the answer, it tells me how deeply have you looked at the puzzle?

Right? And so puzzle setting and puzzle solving is very rigorous, but. To be able to introduce this into organizations. I've had to both talk to leaders, but then introduce this to teams so they didn't drop OKRs on day one. I introduced this to the product team and I was able to say, okay, from now on, just so that we understand it for ourselves, you know what is happening with the product.

If you're thinking about a feature, let's think about it as a puzzle. Let's talk about what were we solving for, and then let's talk about the puzzle solving in this way of how well did it work, what have we learned, what will we try next? So I introduced this approach at this maritime company and you know, the team started to come back to me with those answers.

And then, by the way, instantly I started getting a better sense of. Like, who's really good at solving [00:37:00] these puzzles innately, who needs more handholding with this new approach of puzzle solving? Right. Um, and then just in a, in the span of like two such presentations, uh. It shifted the mindset altogether.

Mm-hmm. Now, people were thinking about experimentation, learning, adaptation. They were thinking in this way when they were releasing new features. And that was really powerful to see this mindset shift from within. Right. And then as teams got more comfortable in presenting in this way, in the safety of our group, then.

Um, I introduced this approach, uh, at a management level where in the monthly business reviews, we started presenting this information of how well is it working, what have we learned, what will we try next? Uh, and now it's become more normalized. You know, even when we do a design sprint, we talk about the learnings from the design sprint as here's the puzzle.

Here is how well did we learn? What if we, [00:38:00] or how well did it work? What have we learned? What will we try next? And sometimes, by the way, in the course of a design sprint, here's the puzzle we thought we had. We talk about our learnings and then we realize we were completely wrong about what the puzzle actually looked like.

That it wasn't a jigsaw puzzle, it was actually a Rubik's Cube, for example. 

Mehmet: Um, I had to go one thing. Uh, and here, you know, as I was telling you before the actual recording. So I have a lot of startup scale up, uh, people who listen and, you know. I, I advise them also sometimes. So one of the things, for example, about uh, mainly OKRs is people's and any other, other similar methodologies.

I would say, um, people consider them that they might slow a little bit. For example, you know, in OKRs, other than filling all the things that the templates and all this, it's like done on quarterly base. And I know some companies even they, they. Extend this [00:39:00] now, if I am into a very fast moving, and I think everything nowadays is fast moving, uh, vertical, can I apply ola in, you know, speed, that allows me also to keep competitive to make sure that I'm doing what I'm I'm supposed to do, whether getting new features in my product, going, finding more customers, et cetera.

Radhika: Yes. And both. Uh, yes, you can do it very quickly and you can also see results from it really quickly. Mm-hmm. Um, I'll talk about results in a moment, but in terms of speed, one of the things about OLA is whether you're a startup or a scale up, you know, there isn't all the. Process burden where O OKRs require you to constantly monitor is this red, yellow, or green.

It's not about seeing red, yellow, or green. This becomes a mindset, a way of working where you're constantly seeing from every part of your [00:40:00] team, you know, whether you're thinking about marketing and. Did this campaign work or you know, did this sales outreach work, all of these things, you start to think about it in very quick cycles, right?

Sometimes that cycle might be in the span of even a day, because I tried something, I already can see, you know, are people clicking on this or not? It might be the span of a week. I've figured out the answers to how well did it work? What have we learned? What will we try next? In other cases it might be a longer cycle.

Depends on the size of your experiment, right? And so that is the power of this approach. It's very flexible that it's not about just quarterly goals or targets. You do the cycle as just depending on what is the size of your experiment and it, it's more of a mindset than just process of doing this quarterly.

The second thing is about success. What you'll find is two things. One. We talked about motivation at the very beginning of this [00:41:00] podcast. Puzzles are like catnip for your team. Whereas, you know, especially if you have a high performing team, everyone likes solving puzzles in your high performing team.

Whereas goals and targets are an extrinsic driver. Goals and targets about, you know, someone else telling you. You have to hit this number. Whereas when you talk about a puzzle, it's more like, uh, and I do this in workshops all the time. I ask people to tell me how they feel this difference. And like puzzles create this internal drive.

It's more like, I want to solve this puzzle. You know, you mentioned all these questions. Darn it. I, I want to know what is the answer to these questions, right? And so it's a lot more of a driver. And the second thing is because it's a driver and you never get complacent. You know, at the end of solving one puzzle, you're like, oh, but that just unlocked this next puzzle.

Now I wanna know what's the answer to that. So I'm constantly figuring out the next puzzle and the next puzzle, and that's what drives continuous results. [00:42:00] And so this company that I've been working with for the last two years, you know, when I joined, uh, this company. When I started working with a team as a consultant the first year, uh, when they were using OKRs, sales had stalled at the time.

Hmm. And in taking this approach, we doubled sales in 2024, and then we doubled sales again in 2025. Not only did we use this puzzle to expand the market that we were addressing, we also used it to address the needs of our early adopters. And by doing that, we dropped churn from 26% to 4%. So we were basically able to use this approach for different kinds of problems within, you know, the product or who we were targeting, et cetera, and we were able to drive real results.

Mehmet: Uh, you know, that make complete sense to me. And, uh, I think, um, you know, uh, [00:43:00] it's a pragmatic approach also as well, if I want to think about it from a logical perspective, right? Because I want my high performing team members to be focusing on what matters. Solving hard problems. This is why they are there, right?

And, you know, I don't want my team to be dragged in. As you mentioned at the bringing repetitive tasks, you know, things that doesn't move the needle, right? This is what, what we say now, saying this Ika. Now imagine like the whole company now have the buy-in, but still they have some stakeholders that, again, if I might use the the word they want to see.

Dashboards, KPI dashboard, whether they are like shareholders, investors, whatever. So now what's the radical shift, if I might say it this way, in communicating this with, you know, everyone who is outside [00:44:00] the organization in terms of course, like, you know, shareholders, investors, and, and so on. 

Radhika: Yeah. So, um, there are two pieces to this.

So one is, you know, there's a company, uh, called ITX in the us. Um, and the way they work even with their board is instead of just setting targets with the board, what they do is they talk about puzzles at a board level. Mm-hmm. They talk about, you know, what are the initiatives, what are the problems we're trying to solve?

What are the problems this year that we're setting out to solve and the initiatives. That they're going to take on and how they expect them to solve those problems. So it's exactly this puzzle setting and puzzle solving sort of mindset, even at a board level. So instead of just talking about targets, they have different leaders in the organization facilitate these sorts of workshops where they're puzzle setting and puzzle solving.

So that's the first thing. The second thing is, right, even in the sales example, uh, [00:45:00] that we talked about. We do care about metrics and numbers. We want to know, uh, you know, in terms of sales, are we achieving higher sales? Even with this company that I told you about, you know, it's not like we weren't measuring, we were measuring, we wanted to see sales.

You know, sales had doubled year over year, two years in a row. Customer turn decrease from 26% to 4%. So we're constantly aware of all the numbers and KPIs, but. The way we drove these results wasn't by just focusing on those numbers. To give you an analogy, this is like playing football, right? And being so obsessed with the scoreboard that I'm constantly just looking at the scoreboard as opposed to actually playing the game.

What you need people is to go play the game and to play it well, and by doing that, they're not just looking at the number of goals. They're thinking constantly about who has the ball, right? And how are they, how are they passing? How well are they passing to [00:46:00] each other? They're looking at all of these other things that are, you know, that are the leadership level.

You might not even just notice, but you are looking at all of these details, right? And so the mindset shift that you wanna bring in as a leader. Is this sort of constant puzzle setting and puzzle solving, and to the board, to shareholders, you present in the way that either, first of all, resonates with them.

So you might share with them numbers, but you might also share how well did it work, these initiatives we took on, what did we learn? What are we going to try next? Um, based on the, our learnings in 2025, for example, what are we going to do in 2026? You might take this approach and share this even at a board level, but most importantly at a team level, use this approach with your teams so that based on the level of knowledge, skills and experience that different people have, different teams have.

You introduce this approach to them and you'll get the real [00:47:00] answers from the trenches in terms of how are things actually going, not just fake answers based on like what you want to hear. You know, you'll get the real answers. It's not just the 20,000 signups that they'll tell you about. They'll actually tell you, you know, we're getting these signups, but it's not the right target.

What if we try this in terms of sales? Instead, uh, or, you know, maybe the product. Uh, it turns out we need to make these big tweaks because here's what we're actually finding, not just numbers to say, Hey, this grew, so all is good. 

Mehmet: Right. Ika, what do you think the role of, uh, ecosystem builders also would be in having this, again, shift from?

OKRs to, TO, to all. And making sure that also when they suggest something to the new generation of founders, that they don't let them fall in the same traps that. People before them fell into, in my opinion, [00:48:00] I've seen it by the way. It's not like I'm just, you know, giving compliment, you know, to what you said, just for the sake of it.

'cause I've seen it beforehand. So what us and me, I'm, I'm considered as an operator. Sometime also as well. There are probably like also a lot of, uh, incubators, accelerators, and everything in between. So how we can, how we can be part of this change. 

Radhika: Oh, I so appreciate and love this question, uh, so sincerely, because you know, very often this pressure to just show numbers comes from above, you know, from investors.

And it turns out, you know, it's not good for investors either, because then you'll see exactly what they. Want you to see, um, very often as investors, one way you can, we can bring about this shift is if we can be real partners. We're inviting the answers, the honest answers to both the good and the bad.

You [00:49:00] know, there's one investor here that I particularly like working with. His name is Michael Mark. Um, and he's an angel investor. And with him, you know, I felt like. He was, when he invests in a company, you know, it's with this idea that, look, I have faith in you as an entrepreneur. It's not that I have faith in necessarily your business model.

I feel like you are going to evolve your business model. You're gonna learn from it. And you know, because of that, I feel like. He's one of those investors to whom you talk about, you know, how well did it work? What have I learned? What will I, what will I try next? And you might get really interesting feedback.

He's super smart and will be your partner in that. I think that's the approach that we can take as leaders, as entrepreneur, or as. Um, as mentors and as investors, right, where we can be that partner to whom, uh, in invest, uh, entrepreneurs will share this sort of honest truth. And the last thing I'll say is, you know, it is so rare for an entrepreneur to [00:50:00] be able to share honestly what is happening.

Very often you just hear this startup language that honestly, at this point I feel allergic to. That, uh, entrepreneurs will go like, oh, we're killing it. We're crushing it. It's like, oh, please just tell me the truth in terms of how is it actually going? You know, I'm here for you. I really wanna know the real answers.

And just across the board, when I find that the culture is all about, we're killing it, crushing it, et cetera. Nobody is telling the truth in terms of how things are actually going. Why don't we all talk about like, how well is it going? What have we learned? What will we try next? And you'll get actually insightful conversations as opposed to the hubris and the blah, blah.

Mehmet: Yeah. And part of it is Radhika from my humble, uh, experience. It's ego, right? It's, uh, again, the so-called, uh, I call them the fathers of the playbooks and the frameworks. When, when you try to. You know, ring the bell, raise the flag, whatever that is, you know, make [00:51:00] a noise. Like, hey, like we have something wrong here.

And then you see this pushback from the founder, you know, themselves, the founders also. Why? Because, oh, like we brought this. We can't be wrong at the moment. Of course. And when you try to confront and not, not in a aggressive way, of course, like confront them, like, Hey, but look like, as you mentioned, like we were doing it this way, it was working fine.

Since we shifted the messaging, we start to see things going in the wrong direction. Oh no. Like see these guys, they have worked with this company and this company and these companies, for example, they are like. I don't know, uh, unicorns and decos and and so on again. And by the way, it happens in hiring, by the way, as well.

I've seen it where I see people, you know? Yeah. Because this guy, he was like, high performance guy in this company, I'm gonna hire and tell them I sold this movie before. That doesn't work necessarily all the time, unless the guy. I've seen it. If he, I, [00:52:00] I, you know, maybe I learned from you something today, Radhika probably we sometimes, when we try to remove the ego, try to remove, you know, the emotions a little bit and think logically.

Yet at the same time. Give it the feedback to ourselves. I think we're using Ola and indirectly, this is what I discovered because, uh, and you mentioned you are an engineer, and I think this is what an engineer always try to do is like we try to go and do the diagnosis first and then we go and. Trying to come up with the solution.

Like I worked as a, a technology consultant for a long time, and I understand this, um, radical really like, it's, it's an amazing discussion. Uh, and we are almost close to, to to, to its end today. If you want to leave the audience with like, one final advice, whether they are like founders, entrepreneurs, or maybe they have established business and they are looking for better way to, to measure [00:53:00] success.

Final words from you and where people can get in touch and learn more. 

Radhika: Um, so one thing I'll say is whether or not your company uses OKRs and has all these KPIs and targets. Even if you feel like I have no ability to change that, you can still use this puzzle setting and puzzle setting approach with ola, right?

You can make your own work less soul sucking, um, and you can make it more puzzle driven and you can do this within your sphere of control, whatever that sphere of control is. So if you are a CTO, you know, you could use this with your engineering teams and engineering managers. If you are a product manager, you know, you could do this even with your small group, uh, who, wherever your sphere of control is, you can apply this approach of defining the puzzle and then solving it.

And one thing that I've learned from my own experiences. You know, when you sometimes find that we, you are just using, [00:54:00] um, vanity metrics to measure, uh, success, it often means that the puzzle isn't clear enough. So spend some time really defining the puzzle with your team. That's what creates alignment.

And the second piece of alignment comes from solving the puzzle because as you talk about how well did it work, what did we learn? What will we try next? It creates so much alignment that you know exactly where you are and what needs to be done next. Um, so, so that's the power of this. Regardless whether your company uses OKRs or not, you can do this puzzle setting and puzzle setting shift.

And in terms of how to reach out to me, um, and connect and learn more. You can download the free toolkit. Uh, go to radical product.com. Um, and if you go to toolkits, there's the o l's toolkit, although the new name is Ola, I'll change it on on the website eventually. Um, but I'll share a link for show notes.

Um, and also, you know, as you use this framework, you're welcome to reach out to me on LinkedIn. I'll send a link to that too. So reach out to me on LinkedIn. [00:55:00] Tell me about your experience. I'm in the process right now of writing my second book, so as you use this approach, if you wanna tell me your story, it might just make it into the book as a case study.

So you are welcome to reach out. 

Mehmet: Great. I will make sure that, uh, you know, the links that Ika mentioned, they will be available in the show notes. Uh, you can get them uh, through. The podcasting app you're listening to. So, uh, no, no issues in this Rika. You know, I really enjoyed the conversation. Again, this is, you know, uh, eye-opening.

Uh, I would say, uh, it's provoking in a positive sense, of course. And I think like, uh, every leader, every founder, they should be. Today reviewing what, what they have done before with whatever is the OKRs or any other, uh, performance metric they use or framework they use and consider ola because, you know, really it's, it's something which more human.

And I like when you said it's not like soul sucking a hundred percent with this. [00:56:00] Uh, and just, just like fun fact. I know like even the people who sometime they show you and they talk about, you know, these things when you go out with them, right. Get them on a coffee or beer or whatever after work and just listen to the stories.

They hate it. We know, we know it. So, so there's always guys a better way to do things. Don't over complicate your lives and just check, uh, radical's work and, uh, you know, again, uh, looking forward when your book is out. So. Of course, like we can also help you in promoting that Ika with with pleasure. And yeah, feel free to get in touch with her and I will put the links again in the show notes.

And this is how I end my episode. This is for the audience. If you just discovered this podcast by luck, thank you for passing by. I hope you enjoyed If you did, so give me a small favor. Subscribe and share it with your friends and colleagues, and if you are one of the people who keeps coming again and again, thank you very much.

I'm repeating myself at the end of each episode, but this is a huge success not [00:57:00] because of me, because of my guests, of course, including Edika and the audience having us on the top 200 Apple podcast charts since Fab Till today. We are. Not all the countries, but every week we are in a different countries.

But in October, 2025, we crossed like 12 countries simultaneously. I'm still waiting for my American friends to get in the US top, top 200 podcasts, John. But we made it to the uk, we made it to Germany, we made it to Australia, New Zealand, and many other places in the world. So I'm waiting you guys, and as I say, always stay tuned for any of his work very soon.

Thank you. Bye-bye.