Error-free Product Data is No Coincidence
Our checklist demonstrates how you can systematically improve your product data quality in a sustainable manner.
Tiffany Wiener
12 / 08 / 25·6 Min read
Product Information Management
Product portfolios grow, the diversity of variants becomes richer, and, at the same time, the pressure on companies to release new products faster and more smoothly on the markets increases ever so more. Customers expect comprehensive and personalized product information in multiple languages for their channel of choice. Many companies, however, are still stuck in manual processes involving isolated data, fragmented systems, and tedious release approvals. The consequence: this results in data gaps, unnecessary delays, and higher error rates. Additional factors such as new innovative technologies, artificial intelligence, or lack of expert personnel further magnify this challenge.
A modern Product Information Management system (PIM) helps you in mastering such complexity: It enables you to collect product information in a well-structured way, strategically enrich it, and distribute it to all relevant sales channels. However, only automated, continuous, and scalable processes will turn this into a true competitive advantage. And it is here where a PIM such as ATAMYA comes into play, given its integrated workflow engine and automated central processes from data import to channel-overarching distribution.
💡 What is a Workflow Engine?
A workflow engine is a software component that controls business processes in a systematic and rule-governed way. It creates tasks and automatically forwards it to relevant users or systems using the defined rules, events, or interfaces. In combination with a PIM, it even enables you to control all product-related processes centrally and efficiently – granting you more control, speed, and higher data quality.
Flexible PIM workflows fundamentally change the way how users work with product data in the PIM system – not only on the technical level but, in particular, on the organizational level. Instead of distributing responsibilities within the company to individual persons who then manually edit related data, check it for completeness, or distribute it as tasks to the team upon request, the PIM handles all process steps automatically. This way, work processes are carried out in a more structured and trackable manner as part of a clearly defined workflow. And such workflows can be modelled visually with the established BPMN standard.
Workflows increase efficiency and reduce errors in product data processes. Companies profit from smarter processes since they gain better transparency, shorter process runtimes, scalable procedures, and since they are overall more adaptive.
To allow companies to tap into the full potential of automated processes in PIM, some requirements are to be fulfilled:
Building on a solid strategy concept and clear responsibilities, there are no obstacles left in your way for realizing the automation of product-related processes.
The technological basis for this automation is modelling with BPMN 2.0 (Business Process Model and Notation), a standard for the graphical representation of business processes used worldwide.
BPMN enables you to model processes visually and in a standardized manner, while being intuitively understandable to all teams. In the PIM, you can connect product data processes with BPMN models: every task can be connected with attributes, rules, responsibilities, or external interfaces.
With all this, a continuous, flexible, and traceable process logic comes to life, easily adjustable and scalable anytime.
With a flexible PIM system such as ATAMYA, you can realize and control all sorts of workflows and processes – ad hoc, scheduled, or fully automatically.
Typical real-life scenarios:
1. AI-based Text Generation
Is a product text incomplete, inconsistent, or do you need to create a context-based variant for it? In a PIM, this can be identified automatically to trigger an AI-based workflow so that an optimized text can be generated based on the relevant product attributes managed in the system (e.g., measures, properties, materials). Depending on the specifications provided in the AI prompt, such a text can be factual, emotional, or even humorous. Subsequently, the workflow can also initiate the release or translation of this text.
2. Translation Workflow for International Markets
After the successful release of a text, the workflow can check which of the text’s language variants are currently unavailable and forward this content to a connected translation tool such as DeepL or other service providers. The translated texts are then written back into the system without manual assistance.
3. Automated Datasheet Generation
Datasheets can be generated out of the workflow. Once a product is released, for example, the workflow can automatically trigger the generation of the suitable datasheet or transfer it over to the relevant channels. This saves time and guarantees that all data is always up to date.
4. Intelligent Task Distribution
As part of a release process, an employee receives a task such as ‘Text OK content-wise?’ Depending on the response submitted, the system automatically initiates the next steps: e.g., for releasing it or returning it to technical writers for further review.
Besides the aforementioned practical examples, the ATAMYA workflow engine allows for the realization of many more individual use cases. This way, you can map even complex requirements of your product data management in a flexible and efficient fashion.
Product data processes are becoming more complex rather than simpler: more markets, more sales channels, more content, higher requirements, and more and more new technology. Those who still trust in manual procedures today lose valuable time and potential in their product data processes.
With a PIM system like ATAMYA and an integrated workflow engine, companies automate central product processes, accelerate their time-to-market, secure the data quality, and create a basis for sustainable digital growth.
Author:
Tiffany Wiener
Senior Manager Demand Generation & Partner Marketing
ATAMYA
Error-free Product Data is No Coincidence
Our checklist demonstrates how you can systematically improve your product data quality in a sustainable manner.
These articles may also interest you