Data has become one of the most crucial factors in the success of companies. It forms the basis for digitalization projects and the automation of business processes. However, not all data is the same. Nothing can run effectively in your company without one specific type: your master data.
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.
Now let’s assume that your master data is completely error-free. What possibilities does it offer? And how can you improve your master data if it needs to be optimized? Find out here.
What Does Clean Master Data Enable?
1. Get the most out of your SAP system
An ERP system such as SAP is by no means an insignificant investment for any company. Most organizations hope to create improved processes and achieve a considerable ROI. Unfortunately, this is often not realized because companies do not fully exploit the possibilities afforded by the SAP system.
Although there are many opportunities for automation, a great deal is still done manually. Processes are far from seamless. One reason for this is that the necessary data is either not available at all or is incorrect – and employees have to bridge this gap with what can sometimes be substantial manual effort.
Your SAP system can only work as well as the existing data basis allows it to. To achieve the full potential and the expected ROI, you need error-free master data.
2. Automate business processes and decisions
Imagine if your processes could run more or less themselves. The Internet of Things constantly provides data that analytics tools can evaluate. Artificial intelligence uses this data to make decisions and initiate the right processes.
All this can happen automatically without much human intervention. This way, you can bid farewell to gut decisions, as everything is based on data and is one hundred percent comprehensible.
Wouldn’t this free up enormous capacities among your employees? They could then devote themselves to other activities, such as optimizing the system or working on new innovations and business models.
3. Use analytics and artificial intelligence
It goes without saying that the vast amounts of collected data do not exist as an end in themselves. In order to use it meaningfully, businesses are taking advantage of analytics tools and artificial intelligence.
These can, for example, provide valuable insights into the behavior of your customers, which allows you to predict sales figures as well as calculate material requirements and completion dates. You also gain insights into which parts of the service customers are not satisfied with and can act accordingly.
All this only works if the underlying data is correct. If it is incorrect, the tools will generate inaccurate results and predictions. These are then used as the basis for decisions that will most likely turn out to be wrong.
4. Exploit the benefits of the Internet of Things
75 billion connected devices are expected to be in circulation by 2025. With the help of sensors, these devices are already exchanging data on a permanent basis, thus merging the physical and digital worlds. For companies, this data opens up a wide range of possibilities for automating and improving their processes while saving precious time and money.
Production example: Machines constantly transmit their workload. If this data is evaluated, recommendations for a more efficient utilization of their capacities can be derived.
Cleaning service example: Sensors transmit the number of people on different floors of buildings. The system uses this data to create a cleaning plan based on the degree of utilization.
The possibilities for using this data are almost endless. However, the Internet of Things can only generate real added value if the received data is linked to the existing master data.
Common Problems with Master Data
Unfortunately, the quality of master data still represents a major obstacle for many companies when it comes to implementing digitalization initiatives. Master data is often…
- scattered in different systems,
- obsolete and useless,
- inconsistent and contradictory,
- stored in an unusable form.
In addition, there is generally no contact person to answer questions. Even a standardized process for creating and maintaining master data is often sought in vain.
Although a study conducted by the Business Application Research Center (BARC) revealed that data quality and master data management have been a priority for decision-makers for several years, initiatives to improve data quality are being launched rather hesitantly. Companies often perceive them to be too overwhelming, costly and unpredictable.
However, it doesn’t have to be this way. Optimizing master data may be easier than you think.
How Does the Optimization of Master Data Work?
The prerequisite for clean, error-free master data is well thought-out master data management in your company. This has the following tasks:
- Establish processes to regularly and automatically check master data for errors and duplicates.
- Regulate internal responsibilities for master data maintenance and specify what all employees involved have to do.
- Implement data governance standards and best practices to ensure high-quality data, security and compliance.
One of the biggest challenges is that ERP applications like SAP do not offer standardized processes for master data maintenance and often overwhelm users due to their complexity. The solution to this is special software, such as EASY Master Data Management. It’s 100% integrated into SAP andbased directly on the SAP Workflow Engine.
A digital add-on solution for master data management ensures transparent processes, improves data quality and reduces administrative effort. Above all, it minimizes costs by shortening the process duration and eliminating errors and indirect process expenses.
There are preconfigured best-practice approaches that can be implemented in the standard system within a few weeks. Our solution usually pays for itself within a year – sometimes even faster.
Are you interested? Learn more about master data management with EASY here.