Product thinking involves going beyond user requests to address core problems and needs. It involves understanding users, predicting future needs and business goals, and crafting solutions that can scale.
In today’s world, software and games are like ongoing partnerships, selling dreams of future features and partnerships. Product thinking helps companies sell minimum viable products (MVPs) and creates mental models that keep the entire team on the same page.
Please share your experiences and success stories to help others understand and use product thinking effectively.
Product thinking is a combination of science and art, involving collecting data, listening to team members, and understanding customer needs. The product manager is responsible for connecting these dots and creating a cohesive vision. Product intuition is crucial, and the MVP approach is like dating before marriage. The MVP should be strategically planned and not just a season pass to an evolving experience. Effective product managers have a good technical understanding and are not just passing off execution to engineers. They must be knee-deep in the process to make informed decisions and guide their team effectively.
@WhitneyChard, what do you consider to be a solid technical understanding?
Technical understanding for ML product management varies depending on the organization and function. Understanding the model, metrics, and user experience is crucial for effective ML product management. The model’s objective function is affected by the user’s experience, and the model’s attributes should be included in the model. Communication is essential for engineers to take the project seriously, and trust is not a replacement for knowledge. Large corporations, like Google, expect technical expertise, but not all FAANG firms have the same standards. Meta PMs have a lower technical bar compared to other PMs, making it essential to understand the subject matter and communicate effectively with engineers.
After just finishing an inspired session, I’ve been thinking about this once more.
Product thinking, in my opinion, needs strong leadership at all levels as well as a strong corporate culture that values taking risks, making investments, and coming up with new ideas.
In the absence of that, product management becomes the execution of executives’ pet projects, for which they are ultimately not held responsible when their investments fail to generate commercial value.
The individual is proficient in UX and business needs metrics but lacks technical background as a PM. They have some architecture knowledge and have learned from their company’s developers and tech leads. They feel they could benefit from higher knowledge in data science but are unsure of the degree. They work in insurtech and want to expand their knowledge to other industries. They are considering focusing on gaps in their knowledge.
What did the workshop (session) entail? It helped, right?
I concur that effective leadership is the key to aligning product thinking with the goals of the company and making the benefits obvious.
The ability to translate concepts into concrete, accessible actions that other people can use or at the very least begin to understand is the key to success.
Given that my team has met its overall gross profit goals, Product Management is currently reluctant to disturb engineering. The difficulties are evident, though, since market fit and adoption continue to be elusive, if not downright frightening.
Balancing short-term gains with long-term viability is a complex and challenging task. Engineers must address cognitive load, use ability, and mental modalities to improve product performance. The lead PM is working on team culture and maturity, but fostering change is a formidable task. Navigating these intricacies requires perseverance and a keen eye on goals. Despite hurdles, the pursuit of alignment between profitability and sustainable growth holds the promise of future success. Keep pushing forward!
Anyone interested in machine learning should start with Andrew Ng’s course. But I believe it’s crucial to acknowledge that the subject of Gen AI is rapidly developing and sometimes be difficult to understand. To better comprehend the subject, it could be a good idea to concentrate on machine learning’s fundamentals and work with Kaggle data. Additionally, I’ve discovered ChatGPT to be a helpful tool for learning about machine learning and producing code quickly.
Even though I frequently use ChatGPT, I’ve never used it to learn the fundamentals of coding. I’ll check out Andrew’s course. Will now!
Thank you so much!
The product manager role was once a creative one, aimed at understanding the market and building innovative products to provide clients with novel solutions. However, many companies have turned this role into a glorified project manager, focusing on client feedback and filling sprints. This has led to the SaaS industry becoming full of mediocre products that will die a slow death once they hit the market. The founders often claim they had a bad GTM when the product was a duplicate of an existing one. Launching a cyber security SaaS suite in 2023 is seen as a failure in business and life.
This comment is nice.
This forum is undoubtedly unbiased.
I agree with the first statement, and if my position ever changes to fit the second, I’ll start looking for a new job.
I’m not sure where the notion that a product is only focused on meeting customer demands originated. From my perspective, the task is to offer business value (often cash or a precursor to revenue), which USUALLY entails fulfilling user requests but can also involve undertaking highly controversial actions if necessary (for example, Adobe switching to a subscription model).
In order to address your question, I would say that the core of product thinking is to start with a business purpose and move backward from there, taking into account any pertinent limitations such user behavior, technology, the legal environment, and so forth.
@MarcoSilva, in product creation, it’s important to separate what users say they want from what they truly need, just like Steve Jobs said.
What does knowing your customer on a ‘deeper level’ even mean?
Knowing your consumer better entails having a more thorough and nuanced awareness of their demands, prejudices, behaviors, motivations, preferences, and challenges. This goes beyond superficial demographics and interactions, allowing for the creation of products, services, and experiences that resonate with customers and address their underlying needs. This involves thorough research, meaningful conversations, and data analysis to uncover insights.
Product thinking is crucial in understanding user needs, even if they don’t know it yet. The Jobs to Be Done (JTBD) method helps by identifying the user’s main tasks and turning these tasks into Job Stories. These stories help understand why the user wants what they want. To turn these Job Stories into features, first draw out solutions for the user’s needs, make mockups, test them on the customer base, and keep checking designs against the Job Stories. This ensures that the feature answers the user’s needs, not just what they asked for. Additionally, “How Might We” or “Can We” questions help keep the team focused on the main questions from the Job Stories. This approach helps in product thinking and encourages continuous learning and asking. The goal is to create features that answer the user’s needs, not just what they asked for.
@JesusRojas, the Jobs-to-Be-Done framework is useful for improving product management skills. It’s often overlooked when discussing a product. The speaker is looking to refresh their knowledge and use the framework without a project manager. They are also excited to read about Intercom’s implementation of the framework and its flavor, as they admire their holistic approach to product development. The speaker appreciates the reminder and the support provided by their VP.