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Data needs to be managed

Data needs to be managed

Master Data Management

Lifecycle management is not just for products. Data also goes through a history, from its creation and processing to its deletion. If you leave everything to your own devices or only act on demand, in the worst case scenario you will be late to market with your products. That doesn’t have to be the case. We explain why lifecycle management processes for master data are of fundamental importance.



When, as happened recently, a pharmaceutical manufacturer has to take back and destroy tens of thousands of packs of medication because the packaging was printed incorrectly – this is no longer just annoying, but can be a threat to the company’s existence. The reason here was as banal as it was fatal: someone in the company had created a material incorrectly in the master data. There was no controlled process for this and the result was incorrect labeling. The mishap took its course.

With a structured creation process for master data, it would not have come to this, but the company had hardly any experience with this. Just like many others. Data is still mostly maintained manually in Excel, without any degree of automation. If someone wants to create a material, other departments often only find out about it in passing. It would be important to immediately enrich the new data record with additional, essential information. For the brand department as well as for production or sales.


The no-gos in data maintenance:

…Inefficient onboarding

Without a controlled workflow, all the necessary steps for data creation and processing are carried out at a snail’s pace. Manual entries and little automation slow down the creation and change process – business comes to a standstill. A digitalized process, on the other hand, can largely automate and therefore speed up the input when onboarding new master data objects.

… Incorrect formats

Another danger without lifecycle management: errors creep in. Incorrect manual entries and a lack of data quality management (DQM) procedures during the data lifecycle lead to information that is useless. If the person in front of the screen is not shown an appropriate request form for entering product data for selection, an incorrect provision format is quickly created, resulting in the supplier being unable to read and process the data record. With clearly structured request forms for the creation, modification, archiving or deletion of master data, on the other hand, information is filled in correctly. This reduces rework or prevents incorrect data from being created in the first place.


„Many companies do not yet have a regulated lifecycle management system for data storage and processing. But you have to realize this: If the individual departments here are not linked by a stringent, automated process, this paralyzes the entire business operation“

– Marcel Röder, IT Consultant Master Data Management

… Extensive cleanup

Once data has been created incorrectly, its cleansing requires a great deal of coordination. Reactive measures are required in the underlying business processes in which master data must be used. One example would be the duplicate material creation. If a purchase or sales request has already been made for the material and a duplicate is subsequently recognized, the effort required to remove it from the system is high, as it is not possible to simply delete a material that has already been used.

… User-triggered task handling on demand

If everything is done manually, master data creation works like this: Person A needs a new material and submits a request (why the new creation? which material?). He maintains the material, then contacts person B from the brand department to add the brand data, consults production manager C, who maintains the production plant, etc. etc. Each of them must therefore be provided with information and data from the previous department. The whole thing is user-triggered and not process-triggered. This makes it difficult to understand where things stand. Verbal agreements are always necessary and the distribution of tasks takes forever.

… No monitoring

A lack of monitoring and reporting procedures is another common mistake. Without clearly defined (system-supported) processes, process runtimes or other KPIs can hardly be recorded. And this also means that the processes are not improved. Adding all these no-gos together, it is not unusual for products to reach the market later than they actually could due to such sloppy work.

How to solve this problem ?

The solution lies in establishing a creation and change process and automated distribution to the right approvers. It must be possible to trace when products are deleted; fast escalation processes are also required. The future lifecycle management process for master data will be mapped in workflow software. There are already predefined fields in the creation screen: New or re-creation? Selection of material type, suitable formats, etc. With the help of these pre-selection options, it is no longer possible to enter anything incorrectly and the onboarding of new master data objects is largely automated.

Proven approach with best practices

SIRIUS works with its customers to determine what such a screen looks like in each individual case, who needs to be involved for which material type for approval, and helps to implement the desired functionalities. We already provide the basic framework for life cycle management: typical processes using coordinated tools and a structured documentation approach. This includes all our project experience in MDM in large companies in the steel, pharmaceutical and chemical industries. So there is no need to create anything expensive on a greenfield site.

And the benefits?

Companies achieve high data quality through defined workflows and the involvement of the right people. This can be further enhanced by DQM measures by automatically checking the data for correctness or by supporting the user in selecting the correct values. Ultimately, a company can create more or customized products per customer and achieve a faster time-to-market with them.

Titelbild: © your_photo/Getty Images

Marcel Röder

Marcel Röder IT-Consultant Master Data Management