Data is a fundamental part of PLM system
The fundamental elements of PLM data is related to product design, manufacturing and support. From the early beginning product lifecycle management strongly emphasized the importance of data and data management for successful PLM implementations.
PLM is focusing on solving manufacturing business problems. The key manufacturing problems are related to how to control a product cost and optimize business. When 70% of a product cost defined during the design stage, the reliance on the design data becomes more than important. Therefore, very often, CAD data management has core influence about any decisions how to manage data in PLM systems. At the same time, if a system is locked in the engineering department, an ability to provide a complete view on product cost and process optimization is very limited. The connection between design & engineering and rest of the business is the most challenging piece of a successful PLM implementation.
PLM systems with CAD roots
PLM software was born as a natural extension of CAD businesses. It initially started as data management for design and engineering. Later on it grew up to a function that capable to manage product development processes and provide information about product to downstream processes. Connection to CAD (design) data provided an important information to drive product lifecycle in an organization. However, deep CAD connection, made a bad service for PLM by creating an additional level of complexity and increasing software dependencies. On a business level, it is not uncommon for vendors to use CAD-PDM and PLM dependencies to protect their business assets and impose an additional level of competitive advantage. I will talk later about it in the chapters about CAD-PLM integrations.
CAD agnostic PLM systems
Is it possible to create a PDM/PLM software disconnected from CAD data and design roots? Companies were looking for answers on this question for the last two decade. Many of these companies went out of business or were acquired by CAD or ERP vendors. The idea of focus on product development processes without having deep roots in CAD, seems attractive to people these days too. I can see some renaissance of these ideas influenced by modern technologies (the Internet, cloud, SOA, etc.).
PLM and Legacy Data
Legacy data it painful. Speak to anybody in the business of PDM/PLM implementation and they will tell you that managing and importing an existing (legacy) data is complicated, time consuming and very expensive task. It can easy cut your implementation profits and to increase project time.
Legacy data problem is much bigger and not limited to PLM domain. Business intelligence, tackling legacy systems top priorities for CIO. Legacy data is the information stuffed in file cabinets and Excel spreadsheets or buried in antique data management systems company built and/or acquired for the last two decades. These systems are sitting in corporate data centers or (sometimes) under the desks of employees.
The years of CAD / PDM / PLM implementations, heavy customization and product modernization created a unique system landscape. It is overloaded with data, historical systems and complex implementations. It is rare situation that company implemented only one system. To maintain multiple systems is expensive. To make changes in existing implementations is complicated. It slows business and blows up IT budgets. This is why to cut legacy system can be a priority for many IT department in coming years.
The demand for data in manufacturing companies is skyrocketing. Modern manufacturing is heavily dependent on product data, cost, suppliers, service, regulation, customer activity. This is another reason to bring PLM data management.
The traditional PLM business practices is to come with new solution and try to ignore the existence of legacy data. Very often it becomes a problem of customers, implementers and service providers. PLM systems should put “data management” as a priority and able to scale up with growing data management needs.
Data and Control
The ugly truth of enterprise software – it is about how to control the data. It is part of every enterprise software solution. The long term value of customer is defined by how deep customer will be dependent on data management by enterprise system – PLM is one of them. It is all about what data you manage, how do you keep your customers accessing and processing this data.
The data control is an interesting element of PLM technologies. I expect PLM system to pay more attention in the future on how to manage fundamental PLM assets, to provide control to data from upstream and downstream processes. PLM data management will play even more significant role in a future foundation of manufacturing competitiveness. It is a foundation for manufacturing competition and core element of value proposition for customers in a digital world.
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