How can you use PLM to track customer feedback and improve product performance?

PLM, or Product Lifecycle Management, isn't just a system; it's a strategic approach. It's more than data integration—it's a philosophy that orchestrates a product's journey from inception to obsolescence. It's about synchronizing people, processes, and tools throughout the entire product lifecycle, ensuring efficiency from planning to improvement. PLM isn't a software; it's a strategy for holistic, coordinated, and efficient product development.

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PLM in Retail / Consumer Products industry extends to the design/full definition of products (or SKUs-stock keeping unit). Effective PLM systems intimate the operational flow of brand/product line/assortment planning, product design, materials mgmt/supply chain, product development, sourcing, costing, full bill-of-materials and (selectively) full bill-of-labor. This portfolio may be achieved by PLM or by PLM integrated with support systems that feed or are fed by its execution. Delivery to market (regionality, DTC-Direct to Consumer) should all have an intimacy within or integrated to PLM. PLM is not just a single system, but is best viewed as a vital SolutionScape of systems that have Digital Fluidity from Mind to market

Product Life Cycle Management or PLM helps to deal at every stage of a product development, from the creative design up tp the post-consumer use stage (cradle to grave). Customers′ feed-back is needed at each stage, not only at the creative design stage and this should come not in a linear way but iterative one. Design Thinking offers a good approach to it getting a customer′s feed back based on a prototype will deliver more precise fed-back and help you conceive a better product along its whole lifecycle.

PLM(product life cycle) helps in planing, tracking, configure and traceable different stages of product from initiation to End of program. Also with the feedback from Fields for improvement in current or new program. PLM did not help to design the product as this is done in ALM.

Utilizar herramientas analíticas dentro de la PLM para evaluar el rendimiento del producto ayudará a buscar oportunidades de mejora continua en el dise?o, la fabricación y otros aspectos del ciclo de vida del mismo. En mi opinión es básico escuchar las peticiones que marca el mercado para asegurar el éxito del lanzamiento ??

Customer feedback is crucial while designing the next generation of technology or product that shapes the future. Your demand comes from the end user and they expect the product to work in their favor so it is crucial to not make any shortcuts and ensure every design is done right. Being in NPI some customers are OK with change if that means they have say in what they want in new products. This has its advantages as customers are flexible to ups and downs with some designs that may not be all there yet. It’s crucial when the product goes in full volume that the kinks are out and this will avoid numerous change management tasks to fix down the road.

Customer feedback is your compass in the product innovation terrain. It's not just about validation; it unveils hidden landscapes of needs and challenges. Navigate wisely, for it's the bridge between your ideas and market realities, guiding you through the ever-shifting currents of customer expectations.

One aspect of customer feedback that is important is its relevance to new product design to market timing. Customer feedback pre-market, using Voice-of-the-Customer applications/systems is one way to have relevant timing. Another way of obtaining relevantly timed customer feedback is through Loyalty Apps that track user in-store activity in combination with tracking user / market interaction with on-line products per a given retailer website OR a brand's website + their product's presence in other DTC (Direct to Consumer) website(s). Consumer interest (or non-interest) is a means of feedback, which is equivalent to likes or non-interest in LinkedIn posts. Finally - User Testing services is a very personalized way of obtaining feedback.

Understanding the customers’ expressed and latent needs ensures you’re focused on a real problem that needs solving. Aligning the entire product team around the needs of your customers vastly increases your odds of success.

One of the most important topic. In my experience working for different manufacturers globally, leveraging PLM for customer feedback requires a dynamic approach. Utilizing surveys and reviews informs manufacturing New Product Development teams, guiding market research, idea generation, quality improvement, and product refinement for success. PLM seamlessly integrates diverse insights with product data—whether requirements, specifications, or features. This synergy not only ensures a centralized repository for organized feedback but also facilitates a responsive and human-centered product evolution, fostering a genuine connection between our innovations and the needs of our customers.

Easy. Simply integrate your PLM with a consumer insight platform like InsightSUITE from First Insight. After creating your new concepts in the PLM, send them out for consumer feedback. 24-48 hours later the system can provide simple, actionable data per item, in the PLM UI so data-driven decisions can be made with your target consumers in mind.

Leverage PLM to collect customer feedback, but tread carefully. Relying solely on quantitative data risks missing nuanced insights. Integrate qualitative feedback, diving into the "why" behind the numbers, ensuring a holistic view. Remember, data informs; understanding transforms.

As noted in the prior "add" to this questionairre, leveraging (by pulling in) direct and in-direct customer feedback (personalized product testing; voice-of-the-customer surveys; market appeal/interest via on-line "hits", Loyalty Apps, etc.) should support decisioning in product selection, colorway development, regionality of placement, etc.

Versus using PLM to collect customer feedback, I think of it more as PLM informing the type of research appropriate to where your product and features are in the PLM (generative, concept testing, usability, etc).

As a Windchill PLM Consultant, I had an experience of integrating Quality Function Deployment (QFD) into our approach to customer feedback analysis. QFD serves as a bridge, systematically translating diverse customer feedback into actionable engineering characteristics. By aligning customer needs with specific product attributes, we can precisely prioritize enhancements during the product development phase. This structured method not only enhances our responsiveness to customer expectations but also ensures that our innovations are rooted in the voice of the customer.

Customer feedback, as previously noted, should be able to be analyzed using machine learning / AI algorithms / systems to provide "insights" into decisioning of product adoption, colorway (color trends) selection, regional placement of products, inventory levels per a more learned forecast of sales, etc.

Business analytics and AI bring solutions to analyze consumer behaviors in agile. These tools are more than finding business data; they allow us to understand possible whys behind data and behaviors and try to predict trends and the future to take business actions faster. Currently, these agile tools have transformed the workplace, becoming faster, automatized, and data sharing to manage products and services. From big data to PNL, we can understand consumer behaviors in real-time and enhance strategies and decision-making.

Though it is not a normal feature in the Retail / Consumer Products industry, customer feedback on the reaction to high-interest topics such as sustainability and eco-friendly transformations / adoptions of farm-to-factory, recycled materials using in products BASED directly on customer feedback will yield positive "profile enhancements" of products, product lines, and/or brands. Carbon footprint metrics quarter over quarter; year over year and what has transpired to make it happen / in conjunction with customer feedback is a win-win scenario.

You need a feedback loop. - PLM centralizes customer feedback for comprehensive analysis. - Analyzes feedback to identify trends and direct product improvements. - Prioritizes feedback based on impact and urgency. - Translates feedback into specific development tasks. - Assigns tasks to relevant teams for effective resolution. - Monitors task progress and outcomes. - Integrates customer insights into product development. - Communicates with customers about feedback implementation. - Uses feedback for quality management and continuous improvement. - Employs predictive analysis to anticipate future trends.

PLM makes it easier to track and share data along the product value chain, allowing the sharing of consumer voice into the company to connect stakeholders and consumer needs. In addition, using a standard record of enterprise product data, PLM may let teams collaborate and work together, regardless of their department. Thus, when teams have information at the same time, they work under the same umbrella, finding the right solutions and actionable strategies that answer consumer insights. I think the perfect product fit with customers comes with the PLM approach.

A PLM helps to incorporate customer feedback related to an existing product in the market into new product development. It also helps to track the progress of implementation of such feedback at mid to senior management levels.

Integrar el feedback nos permite identificar, analizar y comprender en profundidad su experiencia, y en base a eso, podemos convertir sus comentarios en acciones concretas que nos permitan hacer que nuestra solución sea aún mejor.

Customer journey mapping is a great exercise to identify satisfaction in product usability and user experience. Over the years, I’ve found that implementing a dynamic customer satisfaction process across the PLM enables quick implementation of enhancements that can drive retention and growth with minimal Investments.

Si ya ha de ser minucioso el proceso de desarrollo, la búsqueda de lograr un resultado eficiente y prolongado en el tiempo, asegurarse de la funcionalidad y mejorara de rendimiento ha de serlo mucho más. Debemos definir como evaluar y modular los indicadores para aumentar la precisión de forma constante.

We have discussed almost all possibilities and outcomes of a PLM in this article, except for possible/potential EOL and Sunset of a product line. A PLM not only helps in contributing to the Product's future enhancements, opportunities and evolution plans, but also gives a transparent indication if the investments done towards the product stands as a Sunk Cost and if it should be withdrawn from the market, without consuming any more funding from the Cash cows/ Stars/ Shareholdings of the company, ultimately leading to competitive disadvantage. Hence, PLM is key contributor, not only in terms of product enhancement, but also for the financial goodness of the company at times of EOL, showcasing no more investments are worth into the product.

Also very important is p&l analysis across the PLM. Driving costs down, delivering efficiencies and scale are important to a product’s sustainability.

Diversity often is a great way to start thinking about innovation. Because it will help us focus on different scenarios and opportunities to rethink what we think we already know.