Five common product data manufacturing use cases
For manufacturers, the benefits of implementing product data management systems are various. Below, we focus on some of the most common use cases which highlight why product data management is an essential tool in today’s fast-moving manufacturing environment.
1. Product data and the value chain
Manufacturers generate product data at every stage in the value chain. Operational technology (OT) and connected software enable digital management of various data types, such as engineering data, process information, product development, stock control and product attribute information. As product variants and lines expand, so does the volume of connected product data. As such, storage, structure, systems, and processes are needed to onboard, store, access, share and deploy the data throughout its lifecycle. As manufacturers integrate, piecemeal or wholesale, industry 4.0 into their operating models, ensuring a high degree of product data quality is a key driver behind the added value created.
2. The connected customer
Product-centric businesses operating in an omnichannel environment need to put the customer at the centre of their ‘virtuous circle’ of value generation. Changing customer profiles in B2B- and B2C-focused companies will demand outcome-based adaptations of business models. For instance, as manufacturers become able to deploy 3-D-printing, they will need to adapt to widely varying batch sizes, a higher demand for product customisation and expectations of shorter lead and delivery times. This logic dictates an improved customer experience across eCommerce channels.
There are two other dimensions to the changing profile of purchasers at a time when eCommerce is accelerating at a rate unthinkable even a short time ago:
3. Collaboration with partners
Product data accumulated throughout its lifecycle greatly informs the actions of stakeholders. For industrial manufacturers, this data is gathered from suppliers and fed on to distributors alongside the finished products. If data is leveraged for i4.0, the input (and output) has a major impact on efficiency, quality, costs, and resource deployment. The current 4th revolution in industry relies heavily on absolute efficiency in product data management, as it provides the building blocks underpinning:
4. Mergers and multiple markets
The current operating environment has seen many manufacturers undergo takeovers or have expansion and scaling of operations to cover multiple geographical zones. The complexity of supplier data and system information is exacerbated by this inflowing data being managed in multiple systems and applications, siloed across regions and business units. Without dedicated product information management to deal with this flow of highly specific product data, the risk is that adding, altering, or rectifying data in one system doesn’t automatically mean it will be updated in other systems to reflect the latest changes.Furthermore, several industrial manufacturers operate worldwide, so successfully implementing Industry 4.0 is not limited to specific countries or regions. At the same time, many applications will have close links with local businesses, as customised products often need the capabilities provided by the region-specific manufacturing infrastructure.
5. Regulatory and legal compliance
Finally, a brief mention for compliance. The EU’s GDPR legislation, introduced in 2018, put the global spotlight on data protection and privacy, although behind the scenes, the real importance of managing regulatory and legal compliance data has been growing steadily for some time. The current explosion in dedicated tools for managing this risk at enterprise level means this trend can only continue. Automated processes in modern PIM systems ensure regulatory compliance with various markets and regions, eliminating the need for manual checking and fulfilment.