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Mind the Product

Podcast

How to prioritise your work for impact – Nacho Bassino (Product Leadership Coach)

AI governance

Perplexity lawsuit sends warning to product managers

B2B product management

Artificial Intelligence (AI) & Machine Learning (ML)

Building Product Teams

Business Strategy

Data Driven Product Management

Digital Transformation

Diversity and Inclusion

Minimum Viable Product

OKRs

Prioritisation

Product Design

Product Research

Product Development Process

Product Ethics

Product Discovery

Product Leadership

Product Management Career

Product Strategy

Stakeholder Management

🌎 <a href="https://www.mindtheproduct.com/world-product-day/" style="color:#FFFFFF;text-decoration:underline;">Happy World Product Day!</a> Be sure to celebrate product, yourself, and your peers today! 🎉

Why teams often struggle with OKRs: A conversation with Jeff Gothelf

Lessons from my first year as a Prod Ops Manager

How Google makes AI work at Enterprise scale – Miku Jha (Director, AI/ML and Generative AI, Google Cloud)

5 ways to invent and simplify as an AI/ML product manager

Gregor Ilg

<blockquote><p>&#8220;There is a way to do it better. Find it!&#8221; <cite>Thomas Edison</cite></p></blockquote>
<p>Here’s the thing with innovation, you can&#8217;t just tell people to be innovative. A great idea doesn&#8217;t always come when you&#8217;re sitting at your desk between 9:00am and the end of your working day. Here at etventure we’ve tried various approaches to innovation in the last few years, and what we’ve learned is that success cannot be planned. You have to embrace uncertainty and understand that the majority of your decisions are based on assumptions. You have to invest skillfully to test these assumptions. The smarter your investment in testing, the better your chances of product success. Here’s what we’ve learned based on our experience of adopting a testing mindset and seeing your way through innovative product development.</p>
<h2>Product/Market fit Cannot be Planned</h2>
<blockquote><p>72 percent of innovative software projects are not successful. <cite><a href="https://www.infoq.com/articles/standish-chaos-2015">Chaos Report 2015</a></cite></p></blockquote>
<p>While this is not surprising, I’ve always found that people intuitively assumes that it only applies to everyone else. Obviously that&#8217;s not true, even projects that were executed by the book can fail, at least from an economic point of view.</p>
<p>So it’s very important to define your measurements for success, especially when building new products. In the end it is almost always about finding product/market fit. You want to build a solution that matches your business goals with customer needs. Finding this match is the ultimate challenge in innovative product development, and it’s nearly impossible to plan this entirely in advance.</p>
<p>So the success of an innovative project should not be measured in terms of software quality, revenue or  ROI, but rather in the knowledge gained. Not every attempt will automatically lead to financial success. Instead, many small tests have to be carried out in order to find your way towards product/market fit.</p>
<h2>Reduce the Costs of Failure</h2>
<p>So the calculation is quite simple. The less effort, money and reputation it takes to test a certain assumption, the more options you get to adapt, expand, discard or completely rebuild the product.</p>
<p>At this point, it is very important to acknowledge that finding success is not about the initial idea. Ideas are a dime a dozen. Social networking was not a unique idea (did you ever make friends on Myspace?). Online shipping was not a unique idea (did you ever order groceries from WebVan?). Making the internet searchable was also not a unique idea (remember Altavista?). All of these ideas satisfied a specific customer need, but still many of these companies didn’t succeed.</p>
<p>From what we experienced it’s the implementation that ultimately makes the difference. And by that I mean not just the implementation of the software but the whole process by which an outstanding product is developed step-by-step from many good and bad ideas.</p>
<p>There is no way the Facebook project team could have known exactly beforehand what would and wouldn’t work. Every new feature is a bet and requires an investment. And the less money you need to test an assumption the more bets you can make.</p>
<p>As an aside, I think that much-cited startup maxim &#8220;fail fast, fail often&#8221; makes the wrong emphasis. The goal is not to lose as many bets as fast as possible, the aim is to reduce the costs of failure in order to increase your total amount of bets.</p>
<h2>Prioritize Investments</h2>
<p>Usually it is not enough to test as many assumptions as possible to find product/market fit. You must also have an understanding of how to prioritize your investments.</p>
<p>Most assumptions about a product fall into one of five categories that should be addressed in the right order. Skipping one of these categories can cause you to miss the target completely.</p>
<h3>1. Interest</h3>
<p>Find out if anyone is actually interested in the product idea. Are there people already trying to solve the problem? Do they want to test your solution or would they recommend it to others?</p>
<h3>2. Reachability</h3>
<p>In the B2C area this can be tested quite easily, through, for example, targeted ads or by handing out flyers. In B2B, the question of reach is sometimes much more difficult to answer. Here, legal, political or structural constraints must also be taken into account. In any case, the best product is worthless if you don&#8217;t have access to the target group.</p>
<h3>3. Willingness to pay</h3>
<p>This is not just about monetization, but about whether users are willing to invest in the product. This could be money &#8211; or time, attention or reputation. A Facebook referral can be used as an indicator of willingness to pay. In any case, you should be aware of the added value of your solution in order to set the right measurement criteria.</p>
<h3>4. Technical Feasibility</h3>
<p>I would advise that you don’t invest in digitization until the cost of handling processes manually is higher than the cost of developing a digitized solution. As long as you handle things manually you can easily change course. Once you build software you are invested.</p>
<h3>5. Scalability</h3>
<p>Only when you have built a digital solution and are beginning to pile up numbers in terms of traffic, downloads or active users, should you start to think about scaling. There is no need to build an infrastructure that handles 100,000 users if you are still struggling to get the first 100. Yes, that probably means you will have to rebuild stuff. But rebuilding something because you know you need it is much better than building something to find out you actually didn’t need it from the beginning.</p>
<h2>Focus on Outcome not Output</h2>
<p>Finally one of the most important and at the same time most difficult to implement realizations: Focus on outcomes not on outputs. The release of the first software version is no reason to celebrate. For us, once we’ve acquired our first customers, received the first payments or validated our first assumption, then it’s time to celebrate. The software in itself is worthless if it doesn’t create the desired outcome.</p>
<p>And while I’m at it I would like to explicitly state that the software is not the product. The combination of processes, customer approach, business model AND software is the product. Even though Uber has a very handy app, it would not be nearly as successful if you had to wait 30 minutes for a driver.</p>
<p>So please keep in mind that building an innovative product is so much more than just executing software specifics. By applying the testing mindset you’ll enhance your chances of success.</p>

core/freeform

Hypothesis and Testing

The journey to product experimentation by Split

Progressive product development: release products that deliver by Split

Surveillance art, dying phones, and fake likes – Dries Depoorter at MTP Engage Hamburg

Understanding and executing effective research

What’s stopping teams from running experiments by Cameron Savage

How to be a better data-driven product manager

Product’s role in experimentation culture by Terry Lee

Stay Humble or Be Humbled — Case Studies from the Experimentation Trenches by Anthony Rindone

The Testing Mindset – How to Find Product/Market fit

Gregor Ilg

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