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A growth mindset leads to resilience and adaptability. It's about celebrating failures as opportunities for growth and learning. Using AI tools can play an important role in cultivating a growth mindset by analyzing data trends and patterns and help us identify areas of improvement and innovation. With advanced AI's capabilities today, we can look for growth opportunities, even in the face of adversity. A growth mindset, coupled with AI-powered insights, can be a force for driving positive change and achieving lasting success, if implemented ethically.

Many of the most successful apps today did not begin with their current form in mind. This is what drives me to consistently adopt a growth and opportunity mindset. Instagram began as a whiskey app (Burbn). Twitter originated as an internal team collaboration tool. The list goes on. It's crucial for product leaders to possess a flexible mindset, pivoting when necessary and building in directions where the data and research shows user needs and market trends. As a product leader, its even more critical to take ownership and responsibility for your team to allow them to see the growth opportunities and optimism that came from your previous efforts.

I agree. Moreover, when we use the phrase "fail fast" and the plethora of tools that allow you to experiment, we deliberately embrace failure.. "Calculated risk" carries a similarly positive meaning.

Failures should not be seen as setbacks, but rather as opportunities for learning. They offer invaluable insights into what isn't functioning as expected, which in turn aids in refining and enhancing product strategies. It is crucial to thoroughly analyze each failure, identifying its root causes and comprehending the circumstances that contributed to it. This approach often uncovers gaps in our knowledge, skills, or processes, which can then be addressed to avoid future similar failures. If we find that a specific approach or product feature consistently underperforms, we should not hesitate to pivot. Adaptability and agility are key and a readiness to alter our course as needed, based on lessons learned from our failures, is crucial.

Failure isn't the end. It's an opportunity for growth. You can wallow in your sadness or dust yourself off and move on. Most people fail. The ones who ultimately succeed don't let individual failures hold them back.

In my experience as a Founder-CEO & CPO, embracing a growth mindset is pivotal for refining product strategy. When faced with failures, viewing them as opportunities for learning and improvement is crucial. I've found value in conducting thorough post-mortems, dissecting what went wrong, and extracting actionable insights. Teams can collectively pivot towards innovative solutions by fostering a culture that encourages feedback and open communication. Remember, a growth mindset fuels resilience and propels continuous improvement, laying the foundation for robust and adaptive product strategies.

One should adopt a growth mindset because it enables individuals to embrace challenges, persist through setbacks, learn from criticisms, and find lessons in others' successes. By believing that abilities and talents can be developed through dedication and hard work, individuals with a growth mindset are more likely to bounce back from failures, view setbacks as opportunities for learning and improvement, foster creativity and innovation, and experience greater satisfaction and fulfillment in their careers.

In my PM role, I view failures as learning opportunities. If a new feature doesn't resonate with users as expected, I analyze the user feedback and performance metrics to understand the shortcomings. In my experience, adopting a growth mindset is pivotal. Rather than seeing failures as setbacks, I see them as stepping stones to improvement. For example, a product launch that didn't meet expectations became a catalyst for reassessment and a more strategic pivot. Things that I've found helpful include fostering a culture that encourages experimentation. It's essential to create an environment where team members feel safe taking calculated risks. Regular retrospectives after launches help identify what worked and what didn't.

I believe that learning from failure and making necessary pivots involves adopting a growth mindset as the foundational step. Embracing a growth mindset means acknowledging that abilities and skills can be developed through effort, feedback, and continuous learning. This perspective reframes failure as an opportunity for personal and professional growth, steering clear of fixed mindset pitfalls like blaming others, denying responsibility, or succumbing to discouragement. Cultivating a growth mindset entails practicing self compassion, welcoming constructive feedback, and acknowledging and celebrating progress and achievements.

Adopting a growth mindset means embracing challenges, viewing failures as opportunities for learning and growth, and believing that abilities and intelligence can be developed through dedication and hard work. In a healthcare startup, we faced challenges with user engagement and retention for our app. Instead of seeing this as a failure, we adopted a growth mindset, viewing it as an opportunity to learn, improve, and find innovative solutions to address the underlying issues and better meet the needs of our users.

The Five Whys technique is a problem-solving method that involves asking "why" repeatedly to uncover the root cause of an issue. By delving deep into the causes of a problem through iterative questioning, this approach helps to identify underlying factors and address core issues effectively. Originally developed by Sakichi Toyoda for Toyota, this technique aims to prevent recurring defects or errors by peeling away layers of symptoms to reveal the fundamental cause. It is a simple yet powerful tool used across various fields like engineering, management, and healthcare to improve processes and decision-making by focusing on the primary cause of a problem.

In my product management role, I employ the 5 Whys technique to dig into the root causes of issues. For instance, if there's a drop in user engagement after a feature release, I repeatedly ask "why" to uncover reasons beyond surface-level explanations. In my experience, the 5 Whys technique is a powerful tool for problem-solving. It goes beyond addressing symptoms and delves into the core issues. E.g, by asking why users aren't adopting a new feature, we discovered it was due to a lack of intuitive onboarding rather than disinterest. I've found it helpful to include involving cross-functional teams in the 5 Whys process. Different perspectives enrich the analysis. Additionally, framing questions carefully is crucial to avoid assumptions.

After multiple failures I experienced that the best way to learn from failure and pivot effectively, use the 5 Whys technique. By repeatedly asking "why," you uncover root causes. For instance, if a product launch fails, ask why until you identify issues like understanding customer problems or validating assumptions. This approach reveals hidden gaps and errors, preventing their repetition in the future and enabling more informed problem-solving for successful pivots.

The 5 whys technique involves asking "why" multiple times to dig deeper into the root cause of a problem or failure, helping to identify underlying issues and address them effectively. When our healthcare app experienced low user engagement, we used the 5 whys technique to investigate the root cause. We asked "why" multiple times to uncover that the lack of personalized content and features tailored to individual user needs was a significant factor contributing to the issue. This insight enabled us to refocus our efforts and prioritize developing personalized and relevant content and features to improve user engagement.

Testing assumptions with experiments involves designing and conducting tests to validate the beliefs or expectations you have about your customers, market, or solution. This process is crucial for product innovation as it helps in verifying ideas, learning from customers, and avoiding investing resources in products that may not meet market needs. To test assumptions effectively, you need to clearly define your assumptions and hypotheses, prioritize them based on importance and uncertainty, design experiments using methods like surveys, interviews, prototypes, A/B tests, and more, execute the experiments ethically and reliably, collect relevant data, and analyze the results to draw conclusions about the validity of your assumptions.

In my role as a CPO, I emphasize the importance of testing assumptions through strategic experiments. It's not just about relying on intuition; rather, it's a proactive approach to validate or challenge our hypotheses. By incorporating iterative experiments into the product development cycle, we gather valuable data that guides decision-making. This method not only mitigates risks but also fosters a culture of curiosity and innovation within the team. In my experience, treating assumptions as hypotheses to be tested ensures that our product strategies are grounded in real-world insights, driving more informed and successful outcomes.

Tester des hypothèses est primordial pour gagner du temps et de l'argent. Par exemple si nous voulons développer une nouvelle fonctionnalité pour notre produit nous avons différentes options: développer en interne ou utiliser une API/SDK d'un prestataire externe. Vous pouvez tester cette nouvelle fonctionnalité en utilisant une API externe le temps de voir si celle ci fonctionne et répond à votre hypothèse. Une API est plus facile à intégrer que de développer toute une fonctionnalité. Vous gagnerez donc du temps et à la fin de l'argent. En fonction du résultat vous pourrez garder l'API ou supprimer l'API et développer la fonctionnalité en interne ou bien arrêter cette nouvelle fonctionnalité si elle ne répond pas à vos attentes.

In my PM role, I validate assumptions through experiments. For instance, if we assume users want a gamified feature, I'd design a limited release and analyze user interactions and feedback before a full-scale implementation. In my experience, testing assumptions is pivotal. It prevents investing resources in ideas that may not resonate with users. For example, assuming a demand for a certain integration, we ran experiments to find out the actual user interest, avoiding potential development efforts on a low-impact feature. I've found it helpful to include setting clear hypotheses before experiments. It provides a focused approach to testing assumptions. Additionally, using A/B testing or pilot releases helps gather real user data.

Testing your assumptions with experiments involves designing and conducting controlled experiments or tests to validate your assumptions, hypotheses, and proposed solutions, helping to reduce uncertainty, validate ideas, and make informed decisions. To address the low user engagement issue, we conducted A/B tests to evaluate the impact of different content types and personalized features on user engagement and satisfaction. By testing our assumptions through experiments, we were able to identify effective strategies to increase user engagement and tailor our app to better meet the needs and preferences of our users.

User feedback is key, with the caveat that companies who have committed to a path often find themselves in an innovator's dilemma position that makes it hard to change directino. Feedback from existing customers may drown signal from the broader market and from prospective customers.

Knowing when to pivot in product management is an art. It usually boils down to a few key signals. For instance, if your product isn't gaining traction despite multiple iterations, or if user feedback consistently points to dissatisfaction, it might be time. Deciding to pivot is no walk in the park. It requires a delicate balance between commitment and adaptability. There's an emotional attachment to the original plan, and acknowledging that it's not working can be tough. Keep an ear to the ground for user feedback and market shifts. Regular check-ins on metrics and user sentiment help spot the need for a pivot early on.

Learning from failure often means pivoting, or changing your approach, based on what you've learned. This move can save time and money, steering you towards creating something valuable for your customers. Pivoting takes guts and flexibility. You need to be clear about your goals, ready to let go of your first idea, and open to exploring new options. It's all about adapting smartly to meet customer needs and achieve your business aims.

Pivoting involves making a significant change to your product, strategy, or business model based on insights and learnings from failures, experiments, and changing market conditions, helping to realign your efforts and focus on more promising opportunities and directions. Based on the insights and learnings from our experiments and the 5 whys analysis, we decided to pivot our healthcare app by focusing on developing personalized and interactive features tailored to individual user needs and preferences. This significant change in our strategy and product direction enabled us to better address the underlying issues contributing to low user engagement and improve the overall user experience and satisfaction.

L’utilisation d’une boucle de rétroaction est cruciale pour apprendre des échecs. Ce processus inclut la collecte et l'analyse des retours d'expérience et des interactions utilisateurs. Par exemple, l'analyse des commentaires utilisateurs aide à identifier les problèmes d'une fonctionnalité, guidant les améliorations nécessaires. Si une fonctionnalité reçoit des avis négatifs, cette méthode permet d'ajuster rapidement. Elle encourage une culture d'amélioration continue, essentielle pour s'adapter aux besoins des clients et aux marchés en évolution. Une gestion efficace de la boucle de rétroaction renforce la résilience et l'innovation.

Post a feature launch, I'm not celebrating prematurely. Instead, I'm knee-deep in user feedback, metrics, and insights from the support team. This loop ensures our decisions evolve based on continuous learning. Experience shouts that a feedback loop is the heartbeat of successful product management. It's not a one-shot deal. After a feature release, the loop kicks in. Metrics and feedback tell the tale. It's about shaping the product journey based on what users are saying & doing. Automation is a must! Tools that aggregate user feedback, track real-time metrics, and streamline the process make it a breeze. Making the loop a team effort, involving devs, designers, and support, ensures a 360-view.

A great book that touches more on this is Sprint: How to Solve Big Problems and Test New Ideas in 5 days by Jake Knapp. His processes have helped me save many hours across early stage startups when resources and dev time are scarce.

Using a feedback loop involves continuously gathering, analyzing, and acting on feedback from users, stakeholders, and data to monitor progress, identify areas for improvement, and make necessary adjustments and refinements to your product, strategy, and approach. To ensure ongoing improvement and alignment with user needs and preferences, we established a feedback loop by regularly collecting and analyzing user feedback, monitoring key metrics, and adapting our app based on insights and learnings from the feedback and data to continuously improve and enhance the user experience and overall product quality.

Continuous learning means learning from previous learning, so it is necessary that you have strong and regular documentation and constantly update them.

A "failure" could show you the need for a new product that you may not have thought of before. It could show you a problem that other people may be facing as well and may require a simple solution. Think "Airtasker".

Learnings are everywhere - not just in the failed experiments. You should look for opportunities to learn even when an experiment plays out just how you hypothesised. Usually, when ‘winning’, the common reaction is just to move on to what may at the time seem obvious as the next iteration. But this is the perfect time to dig deeper and learn more. - Have you established causal relationships? - What happened to secondary metrics, and why? - If you dig deeper into experiment cohorts what behavioural differences do we see? - Are there other surfaces where what you learnt here could be applied? - What other teams might benefit from what you learnt?