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Home Discover our latest blogs Discover our latest blogs Avoiding data migration pitfalls in your new ERP implementation
Data & AI
4 minutes reading

Avoiding data migration pitfalls in your new ERP implementation

Hundreds of millions going up in smoke, years of work for nothing: everyone knows the stories about failed ERP implementations. According to Gartner, even about 7 out of 10 ERP projects fail to achieve the set goals. One of the key success factors is data migration. Within this domain, we explain in this article, there are numerous challenges. The good news? Thanks to three ingredients, as an organization you are able to migrate cleaned and controlled data in a manageable way.

Kevin Stolk

Kevin Stolk

June 05, 2024

The need for a data migration 

Is your current ERP system legacy, are you switching to another vendor's system, or do systems need to be integrated into the holding company's ERP system due to a merger or acquisition? Then you can't get out of a data migration. Currently, it is extra topical. For example, at SAP, where the end-of-life of SAP R/3 and SAP ECC 5.0 and 6.0 is fast approaching. Organizations running on these need to switch - with some urgency - to a more modern system. 

In data migration, transferring data one-to-one from the source systems to the target ERP is not possible. Cleaning, data mapping, transforming, enriching: these processes are all necessary for a successful migration. After all, the ERP must be fed with correct, complete and up-to-date data that matches your business processes and goals and is tailored for the new system. 

Unprecedentedly high failure rate  

According to Gartner, 55 to 75 percent of ERP projects ultimately fail to meet their objectives. There are functional shortcomings, for example, or the performance is disappointing. The research firm states that a quarter of the projects are delivered much too late or not at all.  

A well-known example is the failed SAP S/4HANA implementation of a large supermarket group, which wasted seven years and 500 million euros. The main cause was in the data area. SAP works by default with sales prices, the concern with purchase prices. Adapting the ERP to the unique business processes and price management logic of the supermarket group proved too complex. The 30-year-old ERP is still running. 

Complexities in data migrations 

It's a striking example of complexities surrounding data migrations. Other potential stumbling blocks are:

  • poor data quality
  • insufficient understanding of, for example, different data formats and dependencies between data (sets)
  • poor data governance  
  • errors in data mapping (or linking data fields between a source and target system)
Data is certainly not the only source of ERP failures. For example, ineffective project teams, inadequate testing and integration problems are also major causes.  

More knowledge, better tools, less chance of failure

Fortunately, every failure yields lessons. Since the 1979 launch of SAP R/2 - considered the world's first "modern" ERP system - many studies have been conducted, methods developed and best practices distilled. Technology is also fueling the ERP evolution. The current generation of tooling for data migration and data quality significantly increases the success rate. 

In addition, ERP implementation and data migration have become fields in their own right with dedicated positions such as data migration specialist and ERP data architect. Thanks to training courses, conferences, (online) knowledge sharing and project experience, they know all the methods, best practices and challenges.  

Result: the chances of a successful ERP data migration have become ever greater. On paper. After all, you have to face all the challenges. 

Three common pitfalls

Challenges in data migrations around ERPs that we often see in practice include:

#1 Every project requires a custom approach 

Every ERP implementation and data migration requires a unique approach, which must comply with the frameworks we outline in our white paper. Important factors include the existing and future data structures, the amount of customization, and the specific business processes and goals. As are data quality, integrity and volume.  

And then there are a lot of peripheral issues, such as compliance and compatibility with the IT landscape. This interplay is far too complex to automate, no matter how clever AI is today. Only with data migration specialists in the lead can you arrive at a migration plan that covers all these aspects. 

The pitfall? Often the data migration is left to the ERP system implementation partner or an IT person "who is handy with data. However, chances are that they do not have enough focused expertise on data migration and data quality.  

#2 Business is not sufficiently embedded 

ERP implementations and data migrations are, at their core, primarily business projects. So the business aspects must come first. Thorough business knowledge is required for a successful data migration. The specific processes, strategies, needs and logic of the business? It all has to be firmly embedded in the data migration. 

Here we see a gap between implementation and data migration professionals. Implementation specialists are primarily technically proficient and skilled within the domain of their own ERP; the expertise of data migration specialists includes both data and business (and to a lesser extent technology). 

The pitfall? If the importance of data migration expertise is not sufficiently understood, one mainly looks at what needs to be done technically with the data to get the ERP system working. Technology is important, but not the primary goal. That is to ensure that the data ensures that the business can work optimally after going live. 

#3 Clash between implementation and migration requirements

The supermarket chain case shows that the (business) data side can place demands on the (technical) implementation side. The reverse also happens. For example, when data must be transformed because of technical limitations. 

The pitfall? People often choose the easiest solution: data transformation. However, does this solution not fit well with the business processes or does it damage data quality? Then this "quick win" leads to problems in the longer term. 

Even more challenges

These three examples come from our white paper on data migration around ERPs, in which we describe many more pitfalls. 

Risks of faulty data migration 

Fortunately, non-optimal data migrations most rarely lead to failed ERP implementations. Other risks of data migration failures are a lot more real. Consider data loss, incorrect information, system failures, operational disruptions and compliance issues. These errors often have a major impact on the business. 

Three ingredients for success 

Technology-oriented data migration is the fast track, business-oriented data migration the good one. After all, once your ERP system is in place, you want it running on high-quality data that seamlessly connects to your business. 

Over time, more and more knowledge has been gained and shared within the field and better methods, best practices and specific data migration tools have been developed. To increase the success rate of your ERP data migration, we explain in this article on the ideal data migration process, you need three ingredients:

  1.  Data migration specialists with knowledge of business, data (migration) and technology.
  2. Proven methods and techniques.  
  3. Advanced tooling that can be configured to meet all the requirements from the data migration plan.

Cegeka Data Solutions' data migration specialists have over 20 years of experience with - and a proven track-record in - complex (ERP-related) data migrations. Thanks in part to our in-house developed tooling, called the Smart Data Migration Suite, we can always guarantee a managed and controlled data migration.

Want to know more?

Want to know more about the challenges, best practices, benefits and steps to take for a successful ERP data migration? Then download our white paper Data migration in ERP implementation: from headaches to Grand Prize.

Kevin Stolk

Kevin Stolk

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