This list is far from exhaustive, but it indicates the extent of the data needed for the end-to-end lifecycle management of the product on its journey from maker to end user. Obtaining that can be complicated for designers, marketers, retail sales forces and product distributors. Moreover, in the majority of cases, how data is stored and made accessible can create several risks in the supply chain.
Manufacturers: adopting product information management to support digitisation
Focusing on the importance of product information management usually emphasises its importance for marketing – providing high-quality, customer-facing and rich product data for customers and end users, we’re talking about the wide range of information generated about their products. The following list illustrates as such;
- Manufacturing Data: bills of materials, ingredients, manufacturing processes.
- Dimensional Data: capacity, volume, length and so on.
- Performance data: test standards and results, environmental performance, (including certification), hazardous materials, compatibility with other products.
- Cost data: procurement and purchasing.
- Logistics data: key warehousing information, materials handling, multi-unit packaging, inventory.
- Identification data: GUIDs, Bar Codes and other Unique Product Identifiers.
Product information and manufacturing
To respond to the rapidly changing habits and attitudes of customers and the outlook for ‘market shakeout’ of the weakest, the entire supply chain model needs to evolve. Apart from the impact of changing requirements on retailers and distributors, the key players in this area are manufacturers. At the start of the value chain, they generate a great deal of rich product data which goes unused. This at a time when distributors need to respond to retail demand for consistent content as retailers, in turn, are increasingly pressured by customers to deliver better shopping experiences.
Therefore, the design and implementation of a PIM solution has different demands depending on your requirements. What ultimately determines the pricing range is how much each factor impacts on the complexity of your circumstances. At Start With data, we have devised our own High-Level Scoping questionnaire for your PIM Initiative. Your responses will allow us to talk to you in greater detail to scope your precise requirements. We can then present this PIM pricing range split up over the 4 principal cost aspects.
The digitisation of manufacturing
Digitisation of the supply chain allows companies to respond to customers whose expectations are evolving. It works together with the intents of Supply Chain 4.0 which is driving innovative approaches to product distribution and reducing time to market considerably. These services are based on the use of advanced forecasting approaches such as predictive analytics of internal processes, like demand for raw materials, and external ones such as rapidly shifting market trends.
There is likely to be greater demand from industrial customers for increasingly customised products as industry 4.0 enables widespread use of 3-D printing and short production runs. The trend towards micro-segmentation means mass customisation will finally be feasible. Customers can be managed in more granular clusters, with a specific range of appropriate products offered to each segment.
Industry experts concur when it comes to how MDM and PIM capabilities will enhance efficiency and customer experience; an end-to-end master data management solution alongside a common data platform for product information management (PIM) allows for complete visibility throughout the information value chain….”{This approach to} excellence-in-data-management supports process optimisation initiatives and has a direct impact on the bottom and top line.” (1)
Putting the cart before the horse
Market observers in several manufacturing sectors warn about the dangers of thinking you can simply spend your way towards i4.0 maturity. Mun-Gu Park, partner at KPMG in South Korea and i4.0 country leader remarks; “Driving true and sustained value from i4.0 demands the integration of automation, data, advanced analytics, manufacturing and products, in a way that unleashes unique new competitive advantages.” (2) All these values and qualities can be driven by applying a consistent and robust approach to product information management.
How product data adds value to to the industrial manufacturing sector
Investments in digitalisation are increasingly needing to extend beyond the bounds of IT to include key operations technologies (OT) like track-and-trace solutions, asset management and digital twinning. The Chief Digital Officer (backed by the CEO) has a helicopter view of technology and operations and is best placed to drive these innovations. Many large companies in a range of sectors have demonstrated the value of adopting this broad strategic vision in leading the way towards digital transformation.
Powering value with PIM
Processes
B2B purchase paths can be complex, making it more challenging for manufacturers to offer a consistent, high-quality digital customer experience. To facilitate improvement, there are a number of process optimisation tools offered by a product information management system. Whereas data was previously stored in silos and not all information could be leveraged to achieve the optimum results, the tools available nowadays allow for a truly integrated planning process.
- Manufacturers can use mapping exercises to understand customer behaviour, such as mapping paths from sales teams, procurement, R&D teams and heads of manufacturing.
- PIM system tools can automatically adjust targets to match shifting demand or supply chain disruptions.
- Automated processes provide real-time updating of product master data. Using reliable master data on supplier lead time allows for use of predictive analytics regarding materials requirements.
- Data from suppliers, service providers and distributors can be shared in a cloud-based master data repository to ensure that every stakeholder is using accurate and up-to-date information to steer processes and make decisions based on the ‘single source of truth’.
Governance
To reach the desired integrated process optimisation, manufacturers need to address the importance of data governance. All processes in the supply chain need to be clearly aligned throughout the company and, equally important, this data alignment must be extended to their various partners – suppliers, distributors, retailers, marketplaces and so on. A centralised data governance framework ensures that data structure, management and policies work in harmony rather than being siloed and fragmented across different partners.
Solutions for manufacturers
Rather than starting with the technology solution and working backwards to the business case, focus first on what added value is the objective. Maximising this value will depend on the choice of tools you make. Interconnected technologies have enormous capabilities and need to be integrated at the level of product and value-chain;
- Real-time integrated supply (and demand) chain management, with all trading partners integrated.
- End-to-end track and trace capacity for products, using smart labels and digital signatures.
- Production planning with a feedback loop from customers leading to greater efficiency in asset use.
- Digital quality assurance frameworks, with digital twinning creating an environment for easy product testing.
Conventional IT and Operating Technologies are converging and the focus is on optimising throughput, demand forecasting flexibility, productivity and return on assets. Industrial tools are becoming smarter while the role of automation and data management is becoming normalised. The clear road ahead is integration among stakeholders in the value chain regarding factors and decisions that will affect industrial transformation and adapt to differences per region, priority, type of manufacturing, company and regulatory frameworks.