📌 Digital Product Lifecycle Management Summary
Digital Product Lifecycle Management, or PLM, is the process of overseeing a digital product from its initial idea through development, launch, updates, and eventual retirement. It involves planning, designing, building, testing, releasing, and supporting the product, as well as collecting feedback and making improvements. PLM helps teams coordinate work, reduce errors, and ensure the product meets users’ needs throughout its life.
🙋🏻♂️ Explain Digital Product Lifecycle Management Simply
Think of digital product lifecycle management like taking care of a pet. From the moment you get it, you plan for its needs, help it grow, keep it healthy, and eventually say goodbye when the time comes. In the same way, PLM means looking after a digital product at every stage, making sure it is useful and up to date until it is no longer needed.
📅 How Can it be used?
A team uses PLM software to track every stage of a new mobile app, from concept to ongoing support.
🗺️ Real World Examples
A software company uses digital PLM tools to manage the development of a new online learning platform. The process starts with gathering requirements, moves through design and coding, continues with user testing, and finishes with regular updates based on user feedback. The PLM system keeps all information and tasks organised, so everyone knows what needs to be done and when.
An electronics manufacturer uses digital PLM to coordinate the release of a smart home device. The team tracks hardware and software versions, manages updates, ensures compliance with regulations, and handles customer support, all within a single PLM platform to maintain quality and consistency.
✅ FAQ
📚 Categories
🔗 External Reference Links
Digital Product Lifecycle Management link
👏 Was This Helpful?
If this page helped you, please consider giving us a linkback or share on social media! 📎 https://www.efficiencyai.co.uk/knowledge_card/digital-product-lifecycle-management
Ready to Transform, and Optimise?
At EfficiencyAI, we don’t just understand technology — we understand how it impacts real business operations. Our consultants have delivered global transformation programmes, run strategic workshops, and helped organisations improve processes, automate workflows, and drive measurable results.
Whether you're exploring AI, automation, or data strategy, we bring the experience to guide you from challenge to solution.
Let’s talk about what’s next for your organisation.
💡Other Useful Knowledge Cards
Team Communication
Team communication is the process of sharing information, ideas, and feedback among members of a group working together. It helps ensure that everyone understands their responsibilities, goals, and any updates that might affect their work. Good team communication reduces misunderstandings and helps teams work more efficiently and effectively.
Secure Federated Learning Protocols
Secure Federated Learning Protocols are methods that allow multiple parties to train a shared machine learning model without sharing their raw data. These protocols use security techniques to protect the data and the learning process, so that sensitive information is not exposed during collaboration. The goal is to enable useful machine learning while respecting privacy and keeping data confidential.
Attack Vector Analysis
Attack Vector Analysis is the process of identifying and understanding the various ways an attacker could gain unauthorised access to a system or data. It involves examining the different paths, weaknesses, or points of entry that could be exploited by cybercriminals. By studying these potential threats, organisations can strengthen defences and reduce the risk of security breaches.
Help Desk Software
Help desk software is a digital tool that organisations use to manage and respond to customer or employee questions, issues, or requests. It helps teams organise incoming queries, assign tasks to the right staff, and track the progress of each case. This software often includes features like ticketing systems, knowledge bases, and automated responses to make support more efficient.
Intent Shadowing
Intent shadowing occurs when a specific intent in a conversational AI or chatbot system is unintentionally overridden by a more general or broader intent. This means the system responds with the broader intent's answer instead of the more accurate, specific one. It often happens when multiple intents have overlapping training phrases or when the system cannot distinguish between similar user inputs.