Material master data management. In many companies, this issue is still treated like a household chore: everyone knows it has to be done, but no one wants to roll up their sleeves and get stuck in. This at least is the parallel suggested by a study conducted by the Business Application Research Center (BARC). It concluded that although master data management is highly prioritized by most decision-makers in companies, it’s often severely neglected in day-to-day corporate practice.
Master data management is at least as useful (and necessary) for successful digitalization as doing the dishes or dusting are for a tidy home. In fact, many digitalization initiatives can only be truly successful with a pool of tidy master data. And as we all know, data is the golden nugget of digital transformation.
Clean SAP logistics processes – It’s All About Costs
Let’s take a look at a practical example. Imagine a mid-sized industrial plant manufacturer with several subsidiaries in various countries. This company uses five SAP® systems, in which around 15,000 material master records are created year after year, providing an essential basis for numerous business processes.
One area where master data is particularly crucial is the supply chain. If errors creep into this master data – which isn’t out of the realms of possibility given the 15,000 material master records created per year combined with poor data management – this can have drastic consequences for the processes in the supply chain. For example, wrong decimal points could mislead planning, an incorrectly set parameter could block a complex procurement process, while an outdated address could lead to supply bottlenecks that paralyze the entire production process.
This list makes it crystal clear that poor material master data is not merely a flaw in the system; it can quickly become a sensitive cost factor. This applies not only to worst-case scenarios, but also to the daily bread and butter operations with master data. To illustrate this point, our plant manufacturer from the example above spends around 1 million euros per year on process costs for material master data management.
Why Master Data Management Causes Problems
Unlike transaction data, master data has an indefinite lifespan. Companies must ensure that all data is handled correctly throughout its respective lifecycle. In other words, it must be entered into the system, maintained, stored and backed up there and then deleted in a controlled manner at the end.
These extensive requirements are what makes master data management so complicated. If a company’s processes aren’t sufficiently adapted to these requirements, this will inevitably lead to quality-related issues: the material master data record will be untidy, incorrect and prove unreliable in many processes.
Efficient management of master data and services – Recognize Challenges
To understand why material master data causes such major problems for organizations, we have to look at the fundamental challenges associated with master data management:
- Error-prone data entry. Material master data is entered and maintained in the system across many points in the company. This is often still done manually and by people with varying degrees of qualification, i.e. normal project employees who have simply completed a crash course in SAP. It’s not long before they become overwhelmed by the program’s complexity.
- Coordination of data entry. There are hardly any companies in which all processes are fully digitalized. As a result, people from different departments exchange information about data via email, chat, telephone or in direct conversation, all while using various document types. This is time-consuming, costs money and consumes resources.
- Unclear structures. The data entry process and structure of data management evolve along with the company. Employees come and go, business units are reorganized, branches are opened and closed. If master data management doesn’t keep up with the times and adapt to these changes, it becomes inefficient and results in poor data quality.
- Long, non-transparent process runtimes. Data management with chaotic processes will also end up blocking other business processes in the company at some point. As a result, granting approval could be delayed while no one really knows what the problem is.
- Redundant master data. It’s not always incorrect data that causes problems. Even duplicate data records, such as for a supplier serving different locations, can quickly become sand in the gears, e.g. because old master data was used for a return instead.
How to optimize your material master data – Step by step to a successful project
In this white paper you will learn how to start a project to optimize your material master data in SAP and thus create a solid basis for your future business success.
How Can Material Master Data Be Optimized in SAP?
If companies want to tackle these challenges, they must improve their master data management in a targeted, coordinated manner. In our experience, individual isolated measures are simply not sufficient. For this reason, we recommend you rethink your entire material master management process. Ask yourself whether it might be more sustainable to roll up your sleeves and start restructuring your material master data entry processes. The alternative? A highly stressful patch-up job of turning bad processes into less bad processes. When approaching the optimization of your material master data, your first step is to define the general requirements that the process should meet. These include:
- Flexibility: data entry should be based on material types and genuine requirements, not the other way around.
- Automation: reduce manual entries as much as possible, as these are error-prone and require lots of coordination.
- Speed: reduce lead times so that downstream processes can be triggered more quickly.
- Transparency: clever monitoring of all processes shows you weak points and responsibilities, facilitates troubleshooting and promotes learning processes.
How to Implement Your Goals with EASY Material Management
In an increasingly digitized world, processes can also be automated and linked together. Thus, subprocesses dealing with master data management on the one hand and total processes such as change management or production preparation on the other can be mapped in SAP® Logistics. As a result, cycle times are reduced, processes can be monitored and optimized in real time, and personnel resources are freed up for profitable tasks. In addition, cross-department and cross-location cooperation is greatly simplified.
EASY Material Management for SAP® Solutions was specifically developed to address the aforementioned problems and requirements. The software solution is fully integrated with SAP and fits seamlessly with your existing IT infrastructure. EASY Material Management enables you to set up your material master data anew in your existing system environment, and transfer it to a sustainable process.
From the kick-off to the go-live, optimization with EASY Material Management only takes about eight weeks. After this, all systems are set up and employees trained. At the end of this period, master data can be created and maintained more easily and without duplicates. As a company, you reap the benefits of enhanced data quality with clear responsibilities and shorter lead times in master data management. This way, the question of who will do the housekeeping in the future is largely resolved.
What About the Costs?
Optimizing master data management with EASY Material Management soon becomes an easy win, as the investment costs are recouped very quickly thanks to significant cost savings and increased productivity. Our customer from the plant engineering sector, with 15,000 material master records per year, successfully reduced its process costs of one million euros by 75% by migrating its systems to S4/HANA.
Drivers for Digital Material Master Process in SAP
Master data is basic information about all operationally relevant objects such as customers, suppliers, employees and products. All other data in the company can only be used in a meaningful manner if it is linked to the correct master data. We have learned from experience that unclean master data is one of the primary reasons why digitalization initiatives fail.