Throughout the development and distribution of a product, data is generated – this renders valuable information. Intelligent product data management makes targeted use of the value of this data. But how does it work? The quality of product data management is already determined while the data is being collected.
What is product data management?
Product data management (PDM) is a complex term. To simplify matters, it can simply be broken down into its three components: Product, data, and management.
The product stands for more than just an object, a thing, or a service. The basis of product data management is a product model, which ideally is represented by the product life cycle.
The data represents all relevant information about the respective product. This data has different functions at the different points in the life cycle. They do not always have the same relevance.
The management of data is designed to ensure that the quality of product development is enhanced at every stage of the product life cycle, starting with product data entry.
Product data management is therefore about making all product-relevant data available as efficiently as possible during the development, as well as in later phases of the product life cycle. The uniformity of the data is of utmost importance. It must be ensured that all authorized users can rely on working with the most recent data set.
Prior to the turn of the millennium, it was common to use the term engineering data management (EDM) instead of product data management.
The advantages of a standardized PDM system
The more complex corporate structures are, the more important product data management becomes. Dispersion and duplication of product-relevant documents not only delays workflows, it is also a source of particularly dangerous errors. A “single point of truth” for all product data avoids data duplicates and incorrect information.
Uniform handling of product data has many advantages:
Management of current product data in a central location
Fast retrieval of different product data without the risk of duplication
Acceleration of processes throughout the entire product lifecycle
The implementation of a comprehensive PDM system is therefore decisive for success. For example, product data management significantly reduces the rate of returns if the consumer always has access to consistent and non-contradictory information about the product he has purchased. Ideally, the potential buyer will not find any outdated information on any offer page.
PDM for the growth phase of a company
The expansion of a business and the development of new product ranges are not always synchronized with communication processes within a company. In many cases, internal company structures do not keep pace with economic expansion.
This leads to conflicts, for example between the production, design and purchasing departments, between branch offices and external partners. Designers who are assigned similar tasks may work with different versions of the same file. Supply shortages result in dissatisfied customers.
Uniform product data management prevents typical problems in the growth phase of a company. Clear standards for uniform communication regarding product data are important here.
PDM and PLM
Product data management is an important part of product lifecycle management (PLM). The latter stands for a comprehensive corporate concept that optimizes control over the respective processes during the lifecycle of a product and uses information in a targeted manner — for example, for sales promotion. Because this control depends on the quality and scope of data, PDM focuses on the collection, quality and availability of this data. In manufacturing and design, in particular, small errors in data entry can have serious consequences.
The following is an example of the potential danger: Employee A and employee B are both working, at the same time, with different dimensions of a small screw that is part of a technical object. Product data management therefore focuses on uniformity, timeliness and quality of product data.
Product data management with artificial intelligence
AI is already able to help with the entry of product data — for example, with a list of entry suggestions. This list of suggestions can be continuously updated and optimized with the help of information from the actual application as well as from Big Data. Today, these methods are used by providers who are active in the outsourcing sector for product data entry.
PDM software provides support for companies that are facing new challenges in light of ever-shorter product life cycles. Artificial intelligence secures a range of requirements for professional product data management. These include:
Central data preparation for the entire company
A continuous flow of information that can be used uniformly in the various departments
Increased efficiency of different processes
To this end, PDM meets the requirements of standardized product data feeds and enables categorization according to individual wishes.
PDM is not possible without reliable product data entry
In product data management, each and every data entry counts. One wrong number can be enough to question the validity of an entire data set. This is precisely why assigning individual company employees to the comparatively monotonous task of entering product data is not productive. This leaves companies in a classic dilemma:
If only one employee is entrusted with entering product data, errors will accumulate due to the uniform nature of the work.
If several employees are entrusted with data entry, this creates shortages in other areas.
The internet can provide a means of solving this resource problem. Individual product data management tasks can be selectively outsourced on crowdworker platforms: Several people whose qualifications are guaranteed are involved in a project. Breaking down complex tasks into clearly defined microjobs ensures not only fast but also high-quality results, because each individual entry is subjected to a rigorous reviewing process.
Product data management remains of utmost importance throughout the entire life cycle of a product: From the idea, through development, to market maturity and beyond. The quality of the results depends on professional data collection. Outsourcing guarantees precisely this quality. Tried-and-tested security precautions ensure correct data entry — and outsourcing product data management also has clear advantages in terms of speed.
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