Infor M3 Data Migration: 5 Common Problems and The New Ultimate Solution

Data migration isn’t an option for enterprises – it’s an integral aspect of remaining competitive in the digital age. However, the data migration process of transferring your data from a legacy ERP system can pose significant problems for Infor M3 customers. During the shift to cloud services, many enterprises struggle to hit deadlines and maintain peak performance levels.

 

In this article, we’ll explore common obstacles that enterprises encounter during data migration, and we’ll consider the game-changing new data migration solution from Syniti and implemented by Doppio.  

 

5 Pain Points Enterprises Face With M3 Data Migration

Before you can devise a successful data migration strategy, it’s vital to understand the challenges ahead. Here are five problems that M3 customers face when moving enterprise data:

 

     1. Performance and productivity take a hit

Typically, enterprise data is based on long loads, comprising millions of records. Despite the availability of advanced data migration tools, many enterprises still handle large data sets in spreadsheets. 

 

The concept of performing API calls from a spreadsheet works fine on a small scale where you have an easy path to migrate. However, if you’re dealing with large volumes, running multiple API calls, and using a defined set of rules, this approach will quickly run into trouble.

 

Enterprises operating this model will inevitably suffer significant performance issues, which can be detrimental to company-wide productivity in the short-term and may deter future data migration efforts long-term.

 

     2. Time constraints for large-scale data migration

Another byproduct of large data sets is the time required to perform data migration. Even in the age of automation, data migration tools can’t circumvent the clock entirely, so analysts must deal with slow, tedious methods and multiple iterations on larger projects.

 

Currently, you must perform several iterations in data migration and wait for a review of each version. If revisions are needed, it may trigger a full restart of the whole process.

     3. Poor configuration of existing data infrastructure

The way that you configure M3 has a massive impact on how the system operates in the background. For example, let’s say you are loading data for a large enterprise that has 120 warehouses. Every single item you bring into the system creates many separate records.

 

This setup is far from ideal, as analysts would much rather the ability to extract the precise data needed at that moment, like a single part file for a single warehouse. With this type of solution, all other files can be loaded later, enabling faster, more flexible data migration at a granular level. 

 

     4. Differences in data structures 

Data must be transformed before it will work in Infor M3. Traditionally, if your enterprise moves data to the cloud from a legacy Infor ERP or third-party system, your team must do some groundwork.

 

For example, in an SAP system, data may be structured for items in a certain way, which isn’t the same as Infor M3. Before you can proceed with your data migration process, you’ll need to create a vast database that may consist of thousands of lines of code to transform the data into a suitable format for M3.

      5. Differences in machines during the data migration process

If you don’t use the same machines throughout each stage of the data migration process, you can expect a lot of errors. Besides that, you may find it challenging to work with the database structure due to distinct variations between the machines used in development or testing compared to those in production. 

 

Typically, this situation requires analysts to cleanse data, often with custom-coded tools. Doing this enables you to incorporate useful features like the ability to call APIs directly with Java queries. However, as your enterprise scales, you should seek a more sustainable solution.

 

The Data Migration Solution For Infor M3 Customers

Syniti and Doppio want to offer M3 customers the means of performing a faster, easier data migration that tackles these problems head-on. The ideal data migration strategy will do the following:

 

Reduce the data migration process into a reasonable amount of time, from days to hours. Minimizing time will enable enterprises to quickly get into the cloud and stay on track to hit project deadlines. 

 

Enable Infor M3 multi-tenant to facilitate multi-threaded APIs. By running several API calls simultaneously, you can improve performance across the board, saving time, and optimizing data quality.

 

Allow for precise extraction so analysts can identify and extract specific objects or data items without running entire loads every time. This feature will not only save time and costs, but it will streamline data operations to make enterprises more productive.

 

Syniti has a viable data migration solution for Infor M3 customers, which comes in the guise of data migration templates. By considering the essential steps involved in moving data to M3 from any third-party ERP, such as SAP or Oracle, we can create a step-by-step framework that mitigates the normal pain points. 

 

Infor plans to sunset the Adage product in the near future, leaving many process manufacturing customers with the challenge of data migration, and no straightforward way of migrating their master data. This is the ideal use case for Doppio’s templatized solution to simplify Adage to Infor M3 data migration. 

 

Doppio and Syniti Are Providing a Standard for Data Migration

Currently, there is no standard for the M3 data migration process. As such, many companies dive headfirst into a painstaking trial-and-error cycle, where they invest countless hours and dollars. 

 

Any conglomerate or a large enterprise that is still moving millions of records from third-party platforms like SAP to M3 through spreadsheets will know that it’s not a sustainable or scalable approach.

 

Syniti and Doppio Group are providing the standard that M3 customers so desperately need. With a templatized framework for any transition path, you have a pragmatic way to manage and move your data. Ultimately, this enables your enterprise to achieve a successful and smooth data migration.

 

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