Is good master data the foundation of digitization?

Modified: 06-01-2021 Published: 05-18-2021

Man sieht Hände, die ein mobiles Endgerät halten und Datensymbole.

As we’re asking like this, you will surely already guess the answer: Yes, master data is a decisive factor for successful digitization – if you understand how to use it correctly. You can find out why this is the case and how you can ensure good quality master data in this article!


Without a precise overview of your resources, you will quickly reach your limits

Imagine you’re invited to a birthday party and want to bake a cake. You pick out a delicious recipe, roll up your sleeves and start. After you have weighed the flour and cracked the eggs, you realize that half of the ingredients are missing. Now you’ve wasted a lot of food and are nowhere near having a cake.

It’s similar with customs declarations. If you discover that your data is incomplete or insufficient,  while carrying out a customs declaration, you are wasting valuable time and, may even not be able to deliver. Great software, which could actually do everything automatically, is only worth half as much then.

Before we start: What exactly is master data?

It is no different in foreign trade. Nevertheless, we notice that many companies lack an overview of their resources – especially their data. We are mainly talking about master data here. Good master data determines whether your customs processes go smoothly or whether your delivery gets stuck during the trip due to an incorrect number or missing information. But first let’s clarify what master data actually is!

In short, this includes everything that is important from an external point of view in addition to sender, supplier and customer data:

  • Customs tariff number
  • Item names
  • Weights
  • Countries of origin
  • Export control audits
  • Prohibitions and Permits
  • Certificates and similar documents

The whole “customs” complex is therefore an enormously data-driven topic. That is why it is all the more important that you keep the complete master data clean. After all, it wastes time if you first have to laboriously collect all the data for each customs declaration – only to  find out that it is no longer up to date.

A lot of  companies use software for their processes, which is good in itself. Because why shouldn’t we use these tools, to save ourselves a lot of manual work? What is often hidden in the process, however, is that such a tool does not run by itself! There is no such thing as automation and digitization at the push of a button. In order for the software to work as desired, it requires good master data.

With these steps you ensure the quality of your master data

However, like most useful things in life, good master data doesn’t just fall from the sky. Four steps will help you to ensure the quality.


1. Check how good your master data is so far

First of all, you should get an overview of your data sets. The best thing to do is to get an excerpt of all active articles from your ERP system. How many of them are even maintained with customs tariff numbers? Match up similar articles, take a look at retention positions and categories like “Parts of X”. If your company builds aircraft, not all items in the warehouse are automatically classified as “parts of aircraft”.

Data records with rows of invalid customs tariff numbers are typical master data errors! Especially regarding annual changes in the customs tariff, we often experience that these changes are not incorporated. In the system, for example, there may be customs tariff numbers that have been invalid for a number of years. You should definitely avoid that – so take a close look at your master data!


2. Extensively process your master data correctly

Did you notice in the first step that some data is no longer up-to-date? Then in the second step you should process and structure it properly. Incidentally, this step is also particularly important if you would like to enter your master data into software.

Many companies set a very tight schedule for the large digitization project and underestimate the effort that this processing entails. However, saving time on the master data due to a lack of time will be costly for you later – often in the truest sense of the word if an additional payment has to be made due to a lack of information. So take your time for this step!


3. Set yourself a realistic goal

“Digitization” in itself is a very broad term. Therefore, think specifically about what you want to achieve with the digitization of your foreign trade processes. Do you want automated comparisons? Do you need data for reporting? If you know where your actions should ultimately lead, you can work towards them in a more targeted manner. It makes sense to tackle the topics first, that require a manageable amount of effort and create the highest benefit.


4. Ensure continuous quality

Last step: Think about how you can ensure the quality of your master data in the future. Plan the necessary time capacities and randomly check every few months whether all data records are up to date. If you need support with this, please feel free to contact us. We have the necessary software to do this completely automatically.

You might even consider an audit using the AQL method (acceptable quality level per DIN standard). Such an audit has two advantages: You avoid the risk of approaching the matter without the necessary focus in an internal audit – and the results are objective, as they are based on a statistical procedure.

Conclusion: With well-maintained data, you can bypass some of the hurdles of digitization

Good master data is the foundation of digitization. So don’t put off taking a close look at your records for too long. Even if the very first alteration run may be a big project, it will make your foreign trade much easier in the long run. You can find more tips on correcting and changing your master data in the guide. You will also get the most important information about the changes in 2021! Download it and feel free and contact us if you need support with digitization and quality testing.

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