Best ERP Data Migration Practices

Aug,18,2022· read

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The probability of your organization drowning in a sea of data is extremely high. Company information, employee information, supplier and vendor documents, and customer service information - the list goes on and on. Given the massive amount of data flowing through your organization, timely and efficient processing must be one of your top priorities. ERP data migration practices are integral to your enterprise resource planning implementation plan.

Incorrect data directly impacts the bottom line, so data integrity is critical to providing the most accurate projection of a company's health status. Inaccurate and inconsistent data can become an ineffective indicator of how your business performs if fed into an ERP system. If you do not deal with data efficiently before implementing your ERP system, you risk not only a failed implementation but also the failure of your entire organization.

Let’s have a deep dive into all these concepts:

 

 

Overview of NetSuite Data Migration

NetSuite Data migration is a methodical and phased approach to transferring data between (multiple) systems that uses a specific migration methodology. The business decision to change the ERP landscape is frequently the impetus for data migration.

Data migration is an activity that adds value to the organization. Furthermore, an end-to-end data migration exposes an organization's entire data landscape in a novel way. Going through the migration process in this manner can reveal many unknowns in organization data and data relationships and enable mapping of the entire organization data landscape. Furthermore, data migration aids in the identification of data owners and can be an improvement or a solid starting point for establishing data governance within your organization.

 

 

Did you Know?

It is important to note that data migrations are inherently complex. Internal controls that assure the completeness and accuracy of the data selected for migration are critical. A solid and extensive data reconciliation framework with checks and balances is critical for verifying the completeness and accuracy of the migrated data. According to NetSuite experts in Australia, data migration consumes 15-25% of the project implementation budget.

 

 

What are the ERP Data Migration Challenges?

Challenge 1 - ERP's Integrated Nature

The first Data Migration challenge arises from the integrated nature of ERP and the requirement for a single data source, as it necessitates input and collaboration from multiple business areas. This work must be carefully coordinated and managed.

Challenge 2 - Understanding Data Migration Activities

Data Migration in ERP implementation entails much more than simply extracting and loading data from legacy systems into the new system. Typical ERP Data Migration activities include:

  • Extraction
  • Collection
  • Cleaning and harmonization
  • Testing
  • Loading
  • Transformation
  • Retention and archiving

Each of these activities must be thoroughly understood and then meticulously planned.

Challenge 3 - Involvement of Business

Although technical involvement is essential, many Data Migration activities necessitate business input and effort. This is not always recognized; as a result, the appropriate resources are not permanently assigned, or the time required from the business owners is not always adequately factored into the project plan.

Challenge 4 - Modifying Data

Many ERP projects require modifying specific data (revised numbering systems, different analysis groupings, and so on) as part of the migration process to the new system. Decisions about the nature of these modifications are usually made during the project's design stage, and the work required to collate and structure the data begins after that.

Challenge 5 - Historical Data

The amount of transactional and historical data to be migrated can vary depending on the project, the business, the client, and the vendor. If this is not addressed early on, it can lead to disagreements, delays, and even budget overruns.

 

 

Top ERP Data Migration Practices

Top ERP Data Migration Practices

Addressing the above-mentioned challenges requires an hour and demands the implementation of the best ERP data migration checklist or strategies. In fact, employing the following best practices for data migration in NetSuite can assist businesses in avoiding errors and maintaining the overall ERP project's timeline. Here are the top data migration strategies:

1. Give data migration priority

Data migration requires a lot of labor, which is easy to underestimate. If you don't prepare properly, data migration might cause your entire deployment to be delayed. Getting started quickly and with appropriate resources is critical to prevent it from becoming a bottleneck. Create mechanisms for removing and cleaning data from different sources as the implementation gets underway.

2. Consider using the data for larger commercial purposes

Analyze your current data in-depth before beginning the migration, consider how it will be utilized within the ERP system, connect it to the architecture of the ERP database, and establish rules for converting the information to the database structure throughout the NetSuite data migration services. By evaluating the company's data, an ERP solution offers the chance to get superior real-time insight into the operation. Therefore, consider how each department and organization should use the information for decision-making while transferring.

3. Delegate accountability for data governance

Assign responsibilities to your team and clearly define who oversees what data is another best data migration strategy. For instance, the group will have to choose whether redundant customer data is accurate and need to be added to the ERP system. Additionally, this is an excellent moment to designate someone to oversee compliance with any rules that apply to your company. A slip-up might cost you money considering the CCPA and GDPR's new laws.

4. Early review of the upload template

To upload data into the new ERP application, format the data extracted from the old ERP to match the upload template provided by the new ERP. Examine the template early on to determine the degree of difficulty of the required formatting.

5. Recognize the complexities of data mapping

You must also consider the data types in each system as part of the data mapping process. For example, you may have a customer ID in one application that accepts alphanumeric characters but only numeric characters in another. You must decide how to accommodate this difference during this case's mapping and migration process.

6. Use data with caution

In the hope that you'll need it someday, you could be tempted to hoard data and import every bit from your outdated systems into the NetSuite ERP Implementation system. However, not all historical information is necessary to be instantly available or helpful. In fact, integrating every piece of historical data might be detrimental, decreasing system efficiency and making it much harder for users to locate the data they want.

You might not need to transfer specific data if no one on your team can provide a strong argument for why they need it in the new system. If it is required for analysis or other applications, some firms may choose to preserve past data that they do not move in a separate system.

7. Consider what to do with ‘Non-Migrated’ data

If you migrate only some data, you must decide what to do with the data that remains in your old ERP application. Here are a few possibilities:

  • If you intend to keep using the old ERP, you should make everyone's permissions read-only. This will prevent new entries while allowing you to refer to older data when needed. If the application is read-only, your legacy ERP vendor may offer a reduced fee for continued access.
  • If you do not expect to need the data in the future, you may want to simply archive it to spreadsheets for future reference. Consider the volume and complexity of the data in the old ERP before selecting this option. These factors influence whether using a spreadsheet is a viable option.
  • You could create a database to store the data as a third option. This can be useful if you think you'll occasionally need access to the data but not regularly. Because someone will have to set up a database and migrate all the data that was not migrated to the new ERP system, this will become a separate project. You may also need to create a small application or reports to make data extraction from the database easier.

 

Wrapping Up!

Designing and executing a solid data migration process is cutting-edge, requiring highly skilled personnel such as VNMT experts and mature processes at the very least. Recognizing the significance and complexities of data migration and acting accordingly is essential for executives looking to have 'control' over their professional company. It is critical to recognize that data migration is not only an IT function but also (and more importantly) a business requirement that significantly impacts a company's daily operations.

When will the data migration be considered successful?

It is an excellent question to ask yourself. During the planning phase, the level of ambition for data migration is defined and designed. Data migration will prove beneficial in a variety of ways, including:

  • Data modeling entails identifying and mapping data relationships (referential integrity) due to data landscape exposure.
  • Data Governance entails the selection of data owners as well as the associated roles and responsibilities.
  • As a result of the (partially) renewed IT architecture, there is less idle search time and a smaller data footprint.

In all cases, data migration in ERP implementation can be viewed as a growth enabler that improves organizational efficiency, data governance, and regulatory compliance.

FAQs

Database migration can be divided into three approaches: big bang data migration, trickle data migration and zero downtime migration. 

These steps are as follows: discovery, data enhancement and cleaning, proof of concept, test migration, and production migration. These phases each include five ETL processes: analysis, extraction, transformation, loading, and validation. 

Poor planning and analysis of project scope can result in incorrect data migration in ERP implementation. Inadequate business engagement with project management can also result in a migration that does not meet the needs and requirements of the business.