PLM – Managing products, how hard can it be?

According to Volvo, a single car model is comprised of 30,000 hardware components that can be configured in 1,000,000 different ways depending on customer preferences. A car also has 100 communication buses that transmits information, 200 control units (computers), 400 different functions like GPS, seat heating, wipers, brakes etc., these functions are realized by 2,000 different software components, making sense of 10,000 different signals from all over the car.



It’s easy to say that a car is a complex product consisting of hardware, software, electronics as well as various related services. All different parts need to be developed, manufactured, supplied, assembled, delivered and maintained, all in a well-coordinated way. In addition, should this car be sold in different configurations to different markets and different customer needs? This is no simple task. It requires control of data and information with a vast amount of cross-functional collaboration. This brings me to PLM which stands for Product Lifecycle Management, and as the name implies, is all about managing products through its lifecycle. Glancing at the different parts above, working with anyone of these areas related to the product, you operate within the PLM ecosystem. Product complexity together with an increased pressure from globalization and competition concerning pricing, quality, time-to-market and service offerings, makes PLM even more relevant than ever. We need to control our product data in an efficient way to be successful.

The acronym PLM is well known within the engineering and manufacturing departments of most companies but is far from commonly used company wide. We do understand the importance of managing information about our products throughout the full value chain, yet we don’t do it. One reason could be that the PLM software vendors historically only focused their offerings on processes within engineering departments. This legacy strategy mainly includes CAD (Computer Aided Design) integration, BOM (Bill Of Material) management and basic workflow support. A 2019 CIMdata survey confirms that the scope of PLM hasn’t changed much in most companies and still focuses on capabilities related to engineering departments. A problem with PLM today is that it hasn’t evolved in the pace needed to meet the demands of modern-day products and is still mainly managing hardware for a small part of the lifecycle. A car is no longer merely comprised of mechanical components but has evolved, yet management and mindset often remain the same.

Products are of course already managed through-out its lifecycle today but at a too high of a cost and without the coordination through the full lifecycle. Product information is segmented and handled manually leading to a high amount of waste and lack of end-to-end traceability. Organizational silos occupied with their own responsibilities without sufficient knowledge of what’s going on in other departments. Up to 50% of product development and commercialization resources alone are wasted as there are no specific need for what is produced and stored. The main challenges managing product information lies in the complexity of processes and systems, siloed organizations and people wanting to control data and tools. Companies are inherently afraid of change and complexity which keeps data sharing down to manual transfers which is both error prone and makes traceability extremely hard. Modern companies are required to become data driven and stop taking decisions based on gut feeling or emotion. Relying on spread sheets, documents, mail and knowledge only existing in the head of employees is a poor strategy that will make you fall behind competitors quickly.

PLM as a concept has the ability to be the glue that bind the many functions that contributes to a product, ensuring a seamless flow of product information, a digital thread, between—engineering, design, manufacturing, customer success, sales, marketing, operations, finance, legal, and more. Product information should not only support the decisions about what gets built but should also influence all aspects of how it gets built, operated and maintained. To become data driven, the right product information needs to be in the right place at the right time in the right format.

Looking at the Volvo car example, PLM as we know it isn’t good enough anymore. But what is required? A few examples of what is tasked for PLM to solve the coming years: easy traceability and access of all relevant data across domains and full lifecycle, impact analysis where all items affected by a proposed change are identified, real-time reports where data is combined from all needed application from anywhere in the lifecycle, unify data models between applications and making sure they can be changed and enhanced with new objects and relationships effortlessly. Some companies are on the right track. What do they have in common? Let’s dig a bit deeper in the next article.


Marcus Ohlin is a Management Consultant and Business Analyst at FiloProcess, an independent Swedish consultancy firm passionate about realizing the value of product information.