How can you use design thinking to reduce the risk of product recalls?

Ler isso me lembrou do dia em que meu avô apertou o botão errado do micro-ondas e a gente quase teve que trocar o micro-ondas. Ele não errou por burrice, errou porque ninguém pensou nele na hora de projetar aquele botão. Empatia, às vezes, é só isso: imaginar que seu produto vai cair na mão de alguém que segura a xícara com tremedeira. Ou que tem pressa. Ou que só queria um café, e não um recall. Design thinking não é sobre ser criativo — é sobre parar de achar que só você está certo.

Utilize a IA para analisar dados e feedbacks da comunidade do LinkedIn sobre o produto em questão. Realize entrevistas com usuários para entender suas experiências, preocupações e expectativas em relação ao produto alimentado por IA. Crie personas detalhadas com base nas informações coletadas para garantir uma compreensão profunda dos usuários.

Focus on Quality Metrics: Incorporating quality metrics into the design process helps track and measure the effectiveness of the design in preventing defects. These metrics can guide decision-making and highlight areas that need attention. For example, Apple uses quality metrics to ensure their products meet high standards

Nice insights! I'd like to add that integrating cross-functional teams early in the process can significantly enhance the ideation phase. Diverse perspectives from engineering, marketing, and customer support can uncover unique insights that might otherwise be overlooked. Additionally, employing advanced data analytics during the testing phase can provide deeper insights into user interactions, allowing for more precise adjustments before full-scale production. Lastly, fostering a culture of continuous feedback throughout the product lifecycle—not just during initial testing—can help in proactively identifying potential issues, ultimately leading to higher quality and customer satisfaction. Exciting times ahead in product development!

Great point! Empathizing with users is truly the foundation of effective design. Understanding not just their needs, but also their emotions and context of use, helps create solutions that are both functional and meaningful. In my experience with product design projects, early-stage user interviews often reveal insights we’d never get from data alone. It’s a crucial step to prevent design flaws and improve long-term user satisfaction.

Um processo de inovação que ignora a escuta ativa é apenas uma aposta. Empatia não é gentileza — é método para reduzir incertezas, validar hipóteses e entregar soluções com real aderência ao contexto do usuário.

To reduce the risk of product recalls, start by understanding user needs and identifying potential issues. Define the problems, then brainstorm and prototype solutions like improving design or quality checks. Test the prototypes and refine them based on feedback. This helps address issues early, ensuring a safer and more reliable product.

Before seeking solutions, it’s essential to deeply understand customers’ needs, frustrations, and expectations. Techniques like interviews, field observations, and customer service data analysis can reveal usability, safety, or quality issues that, if ignored, may lead to product recalls. Applying empathy from the product development stage helps avoid design errors and promotes a user-centered approach — fully aligned with Lean's philosophy of prevention.

I’ve found that using design thinking helps reduce the risk of product recalls by putting the user at the center and catching issues early. I start by empathizing with real users to understand their needs and pain points, then define the core problems that could lead to safety or quality issues. Through rapid ideation, prototyping, and thorough testing-including edge cases and real-world scenarios-I can identify design flaws before launch and build in feedback loops for continuous improvement. This approach not only improves product reliability but also ensures potential risks are addressed proactively, not reactively.

In my experience, Design Thinking is a strategic tool to reduce the risk of product recalls, especially when applied early in the development process. At Crayola, we used empathy-driven design to uncover potential safety and usability issues before launch. By involving quality, R&D, and user feedback during ideation and prototyping, we identified critical risks and made adjustments upfront. This human-centered, iterative approach not only enhanced product performance but also prevented costly recalls and protected brand reputation. It’s about designing with the end-user—and compliance—in mind from day one.

Depois de escutar de verdade, vem a parte difícil: dar nome pro bicho. Porque problema que não tem nome vira fantasma — e fantasma a gente só espanta com reza ou com recall. Definir o problema, pra mim, é igual quando a gente sente dor de cabeça o dia todo e só melhora depois que alguém pergunta: “já tomou água hoje?”. A dor era uma, mas o problema era outro. Quando a gente para e pergunta "qual é o problema de verdade aqui?", às vezes descobre que não era tudo aquilo. E aí você entende: não é sobre inventar o próximo foguete. É sobre não errar o nome da dor.

Identifique potenciais problemas relacionados à segurança, usabilidade e outros aspectos que podem levar a um recall. Analise casos anteriores de recalls de produtos alimentados por IA e aprenda com essas experiências. Envolver a comunidade do LinkedIn para fornecer insights adicionais sobre problemas potenciais.

Um problema bem definido é meio caminho para uma solução eficaz — é nesse ponto que a intuição dá lugar à clareza estratégica, orientando decisões com foco real nas necessidades do usuário e no impacto do produto.

in defining the problem, we need to consider all the stakeholders needs beyond the direct consumers of the product we are designing as well as all aspects beyond performance and cost.. - Stakeholders: a products always related to many stakeholder. for example, a car, not only to its user, but also to people around and environment the car should satisfy the requirements such as maximum emission that the car may emit to not pollute the environments. - Beyond performance and cost: Safety and sustainability are also examples of other requirements that a product should satisfy. if we consider all of these aspects, we can prevent as mush as possible for recall of a product.

With user insights in hand, the next step is to turn those findings into a well-defined problem. Instead of treating symptoms, we aim for the root cause using tools like the Fishbone Diagram or 5 Whys. A poorly defined problem leads to ineffective solutions. When the team clearly understands the risks that could trigger a recall — whether technical, regulatory, or misuse-related — it's much easier to act proactively.

Use design thinking to deeply understand user needs, identify potencial failure points early, and iteratively test solutions to prevent issues before products reach the market.

Design thinking cuts recalls by baking risk prevention into each phase. Empathize via user journey mapping to spot failure risks (e.g., medical device misuse). Cross-functional teams run ‘pre-mortems’ to stress-test concepts against worst-case scenarios. Ideate failsafes: self-diagnosing IoT parts, modular repairs, blockchain-mapped materials. Prototype with adversarial testing (extreme environments) and AI simulations modeling 10k+ use cases. Co-design error-proof manufacturing (e.g., Toyota’s poka-yoke QC triggers). Shift recalls from supply chain fixes to design flaws solved upfront—building resilience into the product DNA.

Facilite sessões de brainstorming com equipes multidisciplinares, incluindo profissionais de IA, engenheiros, designers e representantes da comunidade do LinkedIn. Explore diferentes abordagens para melhorar a segurança, a transparência e a comunicação do produto. Considere a implementação de algoritmos de IA interpretáveis para aumentar a compreensão do funcionamento interno do sistema.

Na fase de ideação, analisar soluções viáveis parra diferentes cenários é primordial para uma prototipagem mais próxima da ideal. Além de considerar personas, fazer benchmarking prévio para descartar práticas com baixa eficácia otimiza tempo, recursos e evita que o projeto fique indefinidamente na ideia, em vez de estar sendo melhorado no mercado.

Fiz uma especialização na área e em uma das aulas usamos LEGO para criar as ideias. Foi muito interessante, experimentação com peças criativas.

Once the problem is mapped out, the idea generation phase begins. At this stage, diversity of perspectives is key. Bringing together people from quality, engineering, marketing, and production helps generate solutions that meet both customer needs and technical or legal requirements. Structured brainstorming techniques, paired with prioritization tools like the Effort vs. Impact Matrix, ensure the team focuses on feasible, high-value ideas.

In the beauty industry, product recalls damage both trust and business. That’s where design thinking steps in. During the ideation phase, we bring together R&D, packaging, dermatologists, and real users to brainstorm beyond just “what’s trending.” We ask, what could go wrong? From ingredient stability to labeling clarity, we generate a wide range of solutions—even the unconventional ones. Ideation isn't about having the perfect answer, but about casting a wide net to minimize blind spots and build a safer, smarter product from day one.

Prototipar é aceitar que a sua ideia, linda e cheirosa na teoria, pode cair no chão como criança tentando andar pela primeira vez. E que tudo bem, porque é assim que se aprende a andar sem meter a testa no móvel da sala. É melhor tropeçar no papelão agora do que escorregar num recall depois. E olha: as melhores ideias que vi nascer foram aquelas que primeiro pareceram idiotas no post-it. Mas alguém teve coragem de cortar, colar, montar com fita crepe... e mostrar pro mundo antes de achar que tava pronto.

Desenvolva protótipos de soluções que abordem os problemas identificados. Utilize ferramentas de simulação para testar os protótipos em ambientes controlados. Colabore com a comunidade do LinkedIn para obter feedbacks preliminares sobre os protótipos e ajuste conforme necessário.

Before making heavy investments in production, we create prototypes to simulate the product’s main features and functionalities. This allows us to detect failures early, drastically reducing the risk of rework and product recall after launch. Rapid prototyping, combined with concepts like Poka-Yoke and FMEA, enables validation of solution robustness and early detection of vulnerabilities.

Once we’ve gathered potential solutions through ideation, it’s time to bring them to life through rapid prototyping. At our hair and skin care lab, this means creating small batches with real ingredients, packaging mockups, and clear usage instructions. We simulate real-world conditions—heat, transit, and shelf-life exposure. These prototypes allow us to identify weaknesses in formulation, packaging leaks, or potential user misunderstandings early. By failing fast and small, we reduce the chances of a costly recall once we scale.

Temos que ter uma abordagem humana, pensando no próximo e suas necessidades, buscar soluções que fogem do tradicional, fazer um brainstorming com a equipe, pensar nas possibilidades para minimizar os erros e possíveis problemas. Ter sempre um modelo de teste e colocar em prática o produto para verificação em campo.

Realize testes práticos com grupos de usuários representativos para avaliar a eficácia das soluções propostas. Utilize métricas quantitativas e qualitativas para medir o impacto das alterações. Incentive a comunidade do LinkedIn a participar de programas de testes beta e fornecer feedback contínuo.

With a prototype in hand, testing it in real or simulated conditions is fundamental. Tests should include both normal use scenarios and extreme conditions that might cause failure. This stage is critical to ensure any adjustments are made before scaling up production.

Testing isn’t just a checkbox; it’s our safety net. We test our skin and hair care prototypes on varied skin types and hair textures, gathering feedback not just from experts, but real users. We listen carefully to what’s said—and unsaid. Did the label confuse someone? Did a fragrance cause irritation in unexpected weather? Testing under different conditions helps us understand the real use case, not the ideal one. This stage ensures our products are as reliable in your bathroom as they are in our lab—reducing recall risk dramatically.

El pensamiento de diseño ayuda a reducir el riesgo de retirada de productos al centrarse en la prevención y la mejora continua. Algunas estrategias clave incluyen: ✅ Comprender las necesidades del usuario: Identificar posibles fallos desde la fase de diseño para evitar problemas futuros. ✅ Prototipado y pruebas tempranas: Validar el producto antes de su lanzamiento para detectar errores. ✅ Iteración basada en datos: Ajustar el diseño según retroalimentación y análisis de riesgos. ✅ Materiales y procesos seguros: Seleccionar componentes y métodos de fabricación que minimicen defectos. ✅ Gestión proactiva de calidad: Implementar controles rigurosos para garantizar estándares óptimos.

Mantenha uma comunicação transparente com os usuários, compartilhando as melhorias implementadas e os motivos por trás delas.

As our merch is produced on demand, I found two processes that work. We get less than one return a year. 1. It is useful to have of a time buffer between when the customer orders and then it is ready to ship. 2. Produce more than one unit per order, especially if the item is popular, in our case the colour & size.