Search this site

How small, unmanaged changes create major allergen risk This is one of the biggest fears in food. Because allergen issues don’t usually come from “bad intent”. They come from small changes + weak controls. Common triggers: ingredient substitutions rework use shared equipment changeovers under time pressure artwork not updated supplier formulation drift These issues are heavily scrutinised by: · FSA / Local Authorities (especially where undeclared allergens are involved) · BRCGS / IFS auditors (allergen management is a major focus area) · Retailer audits (they often go deeper than certification audits) Example: A product is labelled “may contain nuts” but the factory starts running a nut product on the same line. If risk assessments, cleaning validation, and label statements aren’t aligned - you’re exposed. Click-PLM helps by connecting ingredient data > allergen rules > claims > label outputs. So when something changes, the system forces the right checks. #AllergenManagement #LabelCompliance #PLM #FSA

"Tailored solutions to drive success in your unique retail market" At Click-PLM, we understand the unique challenges and fast-paced demands of the retail industry. Our tailored Product Lifecycle Management (PLM) solutions are designed to support every stage of your retail product development, from concept to consumer. With a focus on improving collaboration, reducing time-to-market, and ensuring product quality, Click-PLM empowers your team to seamlessly manage product data, suppliers, and complex supply chains. Whether you're currently a large retailer likely utilising a costly, inflexible PLM system, or a small to mid size retailer or brand currently without a PLM , get in touch to discuss how our affordable and powerful PLM solutions can help.

Why removing process friction-not adding effort-is the key to faster product launches It’s not about how many hours your team works. It’s about how much time is wasted: chasing documents re-entering data fixing avoidable errors That’s what slows product launches. Not effort. Inefficiency. The fastest teams don’t work harder -they remove friction. With the right systems: data flows automatically approvals move faster teams spend time on decisions, not admin Because in FMCG, speed isn’t optional. It’s competitive advantage. Where does your process slow down today?

Why informal change control is one of the quickest ways to fail an audit One of the fastest ways to lose confidence in an audit is when changes happen informally: “We swapped the ingredient because it was out of stock.” “We changed the pack size because the customer wanted it.” “We adjusted the process because the line was struggling.” Auditors don’t just care that you changed something - they care: why you changed it what risk assessment was done who approved it whether customers were notified (where relevant) This is often raised by: · BRCGS / IFS auditors (change control, HACCP impact, traceability of decisions) · FSSC 22000 audits (management of change + food safety system integrity) · Retailer audits (they want proof of approvals and sign-offs) Example: A supplier changes the carrier in a seasoning blend > allergen risk changes > label should change > but the artwork doesn’t. That’s a small change that can create a massive compliance issue. Click-PLM helps with structured change control and full audit trails - so you can show the timeline instantly. #FoodCompliance #ChangeControl #PLM #BRCGS

"Driving eco-friendly innovation and sustainable practices across the Product Lifecycle" At Click-PLM, we are committed to helping businesses integrate sustainability into every stage of the product lifecycle. Our platform enables you to track and manage the environmental impact of your products from ingredients to packaging, ensuring that sustainability is at the forefront of your development process. By automatically recognising ingredients with potential sustainability impacts or automatically generating your recycling information for packaging, compliance with sustainability regulations including EUDR becomes seamless, allowing you to meet both customer and regulatory demands while driving innovation in eco-friendly product design.

In today's fast-paced market, companies are constantly seeking ways to enhance their product lifecycle management (PLM) processes. The integration of artificial intelligence (AI) into PLM solutions is transforming how organizations manage their products from inception to retirement. By leveraging AI, businesses can streamline operations, reduce costs, and improve overall efficiency. This blog post explores the benefits of AI-powered PLM solutions and how they can unlock new levels of productivity. Understanding Product Lifecycle Management Product Lifecycle Management refers to the process of managing a product's lifecycle from its initial concept through design, manufacturing, service, and disposal. Effective PLM ensures that all stakeholders have access to the necessary information and tools to make informed decisions throughout the product's life. Key Stages of Product Lifecycle Management Concept and Design: This stage involves brainstorming ideas, conducting market research, and creating initial designs. Development: Here, prototypes are developed, tested, and refined based on feedback. Manufacturing: This stage focuses on the production of the product, including sourcing materials and managing supply chains. Distribution: Once manufactured, products are distributed to retailers or directly to consumers. Service and Support: After the product is in the market, ongoing support and maintenance are provided. Retirement: Eventually, products reach the end of their lifecycle and are phased out. The Role of AI in PLM AI technologies can significantly enhance each stage of the PLM process. By automating routine tasks, analyzing vast amounts of data, and providing predictive insights, AI can help organizations make better decisions faster. Benefits of AI-Powered PLM Solutions Enhanced Data Analysis: AI can process and analyze large datasets quickly, providing insights that would take humans much longer to uncover. This capability allows companies to identify trends, forecast demand, and make data-driven decisions. Improved Collaboration: AI tools can facilitate better communication among teams by providing a centralized platform for sharing information. This ensures that everyone is on the same page and can access the latest updates. Faster Time-to-Market: By automating repetitive tasks and streamlining workflows, AI can help reduce the time it takes to bring a product to market. This agility is crucial in competitive industries where speed is essential. Cost Reduction: AI can help identify inefficiencies in the PLM process, allowing companies to optimize their operations and reduce costs. For example, predictive maintenance can minimize downtime and extend the life of equipment. Personalization: AI can analyze customer data to provide insights into preferences and behaviors. This information can be used to tailor products and marketing strategies to meet customer needs more effectively. Real-World Examples of AI in PLM Several companies have successfully integrated AI into their PLM processes, yielding impressive results. Case Study: Siemens Siemens, a global leader in engineering and technology, implemented AI in its PLM system to enhance product design and development. By using machine learning algorithms, Siemens was able to analyze historical data and predict potential design flaws before they occurred. This proactive approach not only reduced development time but also improved product quality. Case Study: Procter & Gamble Procter & Gamble (P&G) adopted AI to streamline its supply chain management within its PLM framework. By utilizing AI-driven analytics, P&G was able to optimize inventory levels and reduce waste. This not only saved costs but also improved sustainability efforts by minimizing excess production. Implementing AI-Powered PLM Solutions Transitioning to an AI-powered PLM system requires careful planning and execution. Here are some steps to consider: Assess Current Processes: Evaluate existing PLM processes to identify areas where AI can add value. This assessment should include input from all stakeholders. Choose the Right Tools: Select AI tools that align with your business needs. Consider factors such as scalability, ease of integration, and user-friendliness. Train Your Team: Provide training for employees to ensure they understand how to use the new AI tools effectively. This investment in human capital is crucial for successful implementation. Monitor and Adjust: After implementation, continuously monitor the performance of the AI-powered PLM system. Be prepared to make adjustments based on feedback and changing business needs. Challenges of AI in PLM While the benefits of AI-powered PLM solutions are significant, there are also challenges to consider: Data Quality: AI relies on high-quality data to function effectively. Poor data quality can lead to inaccurate insights and decisions. Resistance to Change: Employees may be hesitant to adopt new technologies. It's essential to communicate the benefits of AI and involve team members in the transition process. Integration Issues: Integrating AI tools with existing PLM systems can be complex. Ensure that you have a clear plan for integration to minimize disruptions. The Future of AI in PLM The future of AI in product lifecycle management looks promising. As technology continues to evolve, we can expect even more sophisticated AI applications that will further enhance PLM processes. For instance, advancements in natural language processing may enable AI to understand and respond to user queries more effectively, making PLM systems even more user-friendly. Emerging Trends Predictive Analytics: The use of predictive analytics will become more prevalent, allowing companies to anticipate market changes and adjust their strategies accordingly. AI-Driven Design: AI tools will increasingly assist in the design process, generating innovative solutions based on user preferences and market trends. Sustainability Focus: As environmental concerns grow, AI will play a crucial role in helping companies develop sustainable products and practices. Conclusion AI-powered PLM solutions are revolutionizing how companies manage their product lifecycles. By embracing these technologies, organizations can unlock new levels of efficiency, reduce costs, and improve collaboration. As the landscape of product lifecycle management continues to evolve, staying ahead of the curve with AI will be essential for businesses looking to thrive in a competitive market. To get started with AI in your PLM processes, assess your current systems, choose the right tools, and invest in training your team. The future is bright for those willing to embrace the power of AI in product lifecycle management.

Product Lifecycle Management (PLM) is a critical aspect of any business that deals with product development, manufacturing, and distribution. In a world where efficiency and speed are paramount, understanding how to streamline your PLM processes can lead to significant improvements in productivity, cost savings, and overall success. This blog post will explore effective strategies to enhance your PLM, providing practical insights and examples to help you implement these changes today.