How can you shape the future of product engineering?

Shaping the future of product engineering requires a combination of technological foresight, keeping abreast of the advancement in the industry and where the industry is leading to, knowing and identifying the user base and their preferences , innovation, and iterative development. By following these steps and continually looking to the vision, one can significantly influence the sucess of product engineering and ensure that it's geared towards creating solutions that are beneficial, innovative, and sustainable.

Listen and learn from your production engineers. They know the ins and outs of producing every part of a product whatever it may be. They can improve quality, production yield, production speed, QC, cost base, reduce and even remove waste. In my experience they can and will very often improve final product performance and visual appeal, beyond what designers planned. Consult as early in the NPD process as possible with production engineering it makes significant sense.

Certainly, imagine a bicycle manufacturer. Instead of committing to a full line of bike designs upfront, they start with a basic frame. They produce a small batch, gather customer feedback, and make iterative improvements. This agile approach helps them respond to market shifts, reduce waste, and create bikes that align better with customer preferences.

In my experience I have seen that it is extremely important to be mindful of the end user in any type of improvements and then be keenly aware of the latest technologies and materials available. Be willingly to humbly go back to the drawing board and completely change the way things are done but at the same time going back to the way things have always been done if needed.

With respect to Professional Lighting: 1.Innovation,Invest in R&D for advanced lighting tech. 2.Sustainability,Prioritize eco-friendly, recyclable designs. 3.User-Centric,Understand user needs for intuitive products. 4.Smart Solutions,Embrace IoT for automation and control. 5.Global Reach,Expand internationally while adapting to local requirements. Q1. How can lighting products balance aesthetics and functionality effectively? Q2. What emerging tech trends can impact lighting engineering? Q3. Strategies for entering new markets while respecting local regulations?

My perspective that not all products require physical prototypes due to the availability of advanced design and simulation tools is valid. These tools can assess loads, thermal, electrical aspects, and design before production, saving time and costs. Design thinking isn't limited to physical prototyping; it's about understanding user needs and iterating, which can involve digital simulations or mock-ups. Adapt the approach to the product's specific requirements.

- Design thinking and prototyping are crucial for successful product development - Design thinking emphasizes understanding user needs, brainstorming ideas, and testing prototypes - Prototyping allows for visualizing and testing concepts before investing in full-scale development - Prototypes can take various forms, from low-fidelity sketches to high-fidelity interactive models - The key is to create a prototype that effectively communicates core features - Prototypes gather feedback, validate assumptions, and enable adjustments for a user-centered approach - This iterative process ensures products meet user needs and expectations - Incorporating design thinking&prototyping leads to user-friendly, functional, and validated product designs.

Besides testing prototypes with users, they serve as well to align your team, inform the client and get other stakeholders involved. Prototypes make ideas tangible.

Design thinking and prototyping are transformative tools in product engineering. They shift the focus from mere functionality to user experience. By emphasizing empathy, design thinking ensures products resonate with users' genuine needs. Prototyping, on the other hand, offers a tangible glimpse into the final product, allowing for real-world testing and feedback. This combination not only reduces the risk of costly late-stage changes but also fosters a culture of continuous improvement. In an era where user preferences evolve rapidly, these methodologies ensure that product engineers remain agile, adaptive, and, most importantly, user-centric. Embracing them is pivotal for future-forward product engineering.

Je pense qu'il faut savoir trouver le juste équilibre entre la simulation et le besoin du client. Pour cela on peut tester des prototypes permettant de valider ces simulations lors de tests suffisamment instrumentés pour permettre une analyse du résultat. Cette analyse croisée permet d'améliorer le produit ou ses fonctionnalités.

Data Analysis and Analytics are great and all, but most of the time it needs to ride with context. You can say that as per data, "people who take the stairs live longer, than those who takes the elevator" Context? > Well, if you think about it, the population of people who takes the stairs generally have better lifestyles, like non-smoker, eating healthy, sports-enthusiast, etc.. While the rest, those with conditions, has vices, and other normal people are all clumped in as the "elevator population". > So in context, the data is already skewed, and provides no correlation nor causation of using the stairs gives you longer life, or better life expectancy. Lesson: Context is King - and checkmate. ..quoting Andrew Lacivita on that.

Data and analytics are the compass guiding product evolution. They offer more than just numbers. They provide insights into user preferences, behaviors, and pain points. By harnessing this data, product engineers can move beyond intuition-based decisions, ensuring that every feature or tweak is backed by tangible evidence. This not only enhances user satisfaction but also optimizes resource allocation. Moreover, in a competitive market, analytics can spotlight emerging trends, giving products a proactive edge. Essentially, integrating data and analytics transforms product engineering from a reactive process to a proactive strategy, ensuring products remain relevant, efficient, and user-centric in a dynamic landscape.

Data analytics can be leveraged to gain insights into customer behavior, product performance, and market trends, enabling data-driven decision-making in product engineering.

Absolutely, my perspective aligns with the importance of data and analytics in product development. It's crucial to emphasize that optimizing or developing a product without thorough data analysis is a risky endeavor. Data-driven decisions ensure that you're aligning your product with user needs and market trends, leading to better features, usability, and overall user experience. Data analysis is indeed an integral part of the modern product development process, guiding innovation and growth strategies.

Cloud and DevOps have revolutionized the product engineering landscape. The cloud democratizes access to powerful resources, leveling the playing field for startups and established players alike. It ensures scalability, catering to fluctuating user demands without massive infrastructural investments. Meanwhile, DevOps breaks silos, fostering a collaborative environment where rapid iterations become the norm. This synergy of development and operations accelerates deployment cycles, ensuring products evolve at the pace of user needs. In essence, the fusion of cloud's scalability with DevOps' agility creates a dynamic ecosystem where products are not just built but continuously refined, ensuring they remain cutting-edge and user-centric.

A cloud strategy shouldnt be one where you thrown in more resouces to scale. It should be a well thought strategic approach where you leverage the native PAS services to be resilient and scale while being efficient on the cost and operation support. It is imperative to factor in the cloud securtiy features in the grounds up development and not as an add on.

Data Analysis Matters: Informs decisions Spots trends Ensures competitiveness Understands customers Manages risks How to Perform Data Analysis: Collect, clean, explore data Apply stats/ML Visualize findings What You Find: Insights, recommendations Predictions, risk assessment For example, in retail data analysis reveals seasonal product trends, manage inventory and optimize the marketing plan.

Learning is an ongoing journey, relevant for all ages and across all fields. It's imperative not only for tech teams but also for product groups to stay abreast with the latest technological advancements, such as AI, ensuring they're leveraged in ways that enhance customer experience. Continuous innovation in product design, quality, and novel methodologies is crucial to maintain a competitive edge in the market.

I completely agree with this perspective. In the fast-paced world of product engineering, staying updated with new skills and technologies is crucial. Being open to learning emerging technologies like AI, blockchain, IoT, and more not only keeps you competitive but also empowers you to create innovative and differentiated products. A curious and open-minded approach, along with continuous learning, is indeed essential for enhancing a product's value proposition and innovation potential.

Cultivate a culture of continuous learning and development within the organization. Provide opportunities for engineers to upskill and reskill in emerging technologies and methodologies, and encourage experimentation and innovation.

One of my continuous improvement coaches used to say that learning is a process and not a series of events, and organizational cultures that embrace learning for the sake of improving and advancing become inherently more innovative. As an engineering leader, I have observed that experimental learning (e.g., exposure to hands-on experiences, abstract conceptualization, and active experimentation) is a powerful way to engage the team in a learning rhythm that is continuous and sustained. Finally, teams rewarded for breaking new ground beyond their expertise are more likely to see technical challenges as opportunities rather than conundrums full of uncertainty. Learning as a process is the ultimate engine for product differentiation.

Collaborate with external partners, suppliers, SMEs and ecosystem stakeholders to leverage expertise and resources.Focus on strategic partnerships and alliances to access new markets, technologies, and opportunities for collaboration.

You must be able to succinctly define and describe what you trying to accomplish. Only then will you be able to enlist others to assist in the solution of the problem, design of the product, and marketing of the end result.

Incorporating applied behavioral science into product engineering is a transformative strategy, as emphasized by thought leaders like Matt Wallaert, Amy Bucher, and Stephen Wendel. Wallaert's framework advocates for a comprehensive approach, beginning with 'Behavioral Strategy' to define desired outcomes, followed by 'Behavioral Insights' to understand user motivations, 'Behavioral Design' to craft interventions, and 'Behavioral Evaluation' to assess impact. Leveraging such a process in product engineering can create solutions that are both technologically sound and deeply attuned to human behavior.

Embrace Emerging Technologies- In my career, I've seen the transformative impact of integrating AI and IoT into product design. For instance, a smart home device project significantly benefited from AI algorithms, enhancing user experience & functionality. Sustainability Focus- On a recent automotive project, prioritizing eco-friendly materials and energy-efficient designs not only met environmental standards but also appealed to a growing market of eco-conscious consumers. User-Centric Design- In a healthcare tech venture, involving end-users in the design process led to more intuitive and accessible products, greatly appreciated by both patients and healthcare professionals.

In my experience something that is often overlooked in product engineering is context, how does what we do contribute to the success of the business. Post COVID connection is becoming increasingly important, making sure product engineering teams have a deep understanding of the role their work plays in the business is important.

Get involved in Codes and Standards development in your industry. New product or concept innovation can outpace current testing standards. Often times code change can be reactionary to issues seen in the field. Being proactive will benefit the whole industry.

Robustness. Consider how your product will behave if it is handled by a child. Or an angry teen-ager. Practices like FMEA/FMECA apply here. Murphy is alive and well, as is the Law of Maximum Inconvenience ("if anything can go wrong, it will go wrong at the time when it is most inconvenient/does the most damage"). Imagination is necessary here.