Best practices for a successful WMS data migration

Data migration is an essential part of a successful WMS implementation. This blog post outlines the best practices, as well as the pitfalls and challenges, so you can perform yours accurately and effectively. A well-planned data migration is worth the effort, as it has a big impact on your business. We will also take the opportunity to introduce our cloud-based, future-focused nyce.logic WMS - a system that can take your warehouse to the next level.

 

What is data migration in a WMS context?

A WMS data migration refers to transferring data from one system, storage or format to another. Some common examples are:

• Implementing a new WMS: migrating data from an existing solution (e.g., an ERP system, legacy WMS, or spreadsheets) to a new WMS
• Upgrading an existing WMS: moving data to a newer version or platform of the WMS
• Consolidating systems: integrating data from multiple systems into a unified WMS
• Changing hosting environments: transferring data when switching between on-premise and cloud-based WMS solutions

No matter the exact nature of the migration, planning and executing it correctly is essential, as you need quality data to take your warehousing to the next level.

 

Why is data migration critical for a successful WMS implementation?

As discussed, quality WMS data is a key factor worth investing in.

Data migration is critical for several reasons, including:

• Accurate inventory management: migration errors can cause inaccuracies in the inventory data, which can lead to misplaced goods, stockouts, overstocking, and an overall inefficient operation
• Operational continuity: errors carried from the data migration can impact the business operation, causing delays, disruptions, and operational downtime, leading to customer dissatisfaction
• System processes and workflows: inaccurate data can lead to misaligned workflows and system inefficiencies, undermining the benefits of the new WMS
• Data integrity and consistency: a successful migration preserves the data quality and allows the WMS to function as expected, providing a reliable output 
• Regulatory compliance: some industries have regulatory requirements regarding record-keeping. Data inadequacies caused by data migration errors can lead to compliance violations, legal penalties, or reputational damage.

Data migration best practices

As you can see above, there are many important reasons to ensure that your WMS data migration goes smoothly. Follow these best practices to ensure a smooth process:

 

Set clear goals and objectives

Having clear and measurable goals and objectives is a critical success factor in a data migration. Define why the project is important, and what it can contribute to the business. What are the goals and limitations of the migration? What data, systems, and processes are included, or excluded for that matter? Involve all relevant stakeholders to create an inclusive process covering as many aspects of the migration as possible.

By thoroughly setting your goals and objectives, you can ensure that the process is successful, efficient, and aligned with organizational needs. You will minimize risks, and utilize the company's resources in the best possible way. Well-defined, measurable goals also provide you with benchmarks to define a successful WMS data migration. 

 

Perform a data audit.

Accurate, consistent and complete data is essential. Perform a data audit before you begin the migration. The audit must identify issues with the existing data and evaluate its quality, preparing it for a smooth transition to the new system. Include applicable data like inventory data, order data, supplier data, customer data, system configurations, historical data, and performance metrics. 

 

Some important things to audit are:

• Accuracy: is the data correct? (e.g., inventory data like stock levels, locations, SKU information, lot, batch, or serial numbers)
• Completeness: are all necessary fields populated? (e.g., are SKUs missing descriptions or attributes? Could these issues lead to errors or other problems?)
• Consistency: is data uniform across systems? (e.g., are product codes standardized?)
• Relevance: is the data still useful, or is it outdated? (e.g., is order history or other logs beyond a certain date needed?)
• Integrity: are data relationships adequately maintained? (e.g., do inventory locations still match bin assignments?)
• Timeliness: is the data current? (e.g., does the stock data reflect recent transactions?)

Make sure to flag all potential issues that are discovered during the audit, such as duplicates, inconsistencies, incomplete entries, and outdated data.

 

Clean and standardize data

After you have audited your data, it is time to review, clean, validate, and back it up. Analyze your findings from the audit to identify what needs to be done to ensure accurate, consistent, and usable data. 

Set standards and validate:

• Establish naming conventions for fields like SKU codes, supplier names, and product descriptions
• Define the rules for field formats, ranges and constraints to validate against
• Align data formats and fields, e.g. measurement units and address formats, and create a data dictionary detailing each field's purpose, format, and relationships.

Clean the data:

• Identify and eliminate duplicates
• Correct typos, inconsistencies and incorrect values
• Handle missing values, e.g. by filling in empty fields or setting up a process for handling them
• Address all other conflicts and potential issues

Choose the right data migration tools

A WMS data migration requires appropriate tools that support both the legacy system and the new WMS. See if the tools have native support for database types, and make sure to verify API support if either WMS relies on APIs for data exchange. Strong data mapping capabilities will facilitate a smooth transition, so be on the lookout for tools with robust data mapping that can translate data from the old system’s structure to the new one.

Vendors can often provide tools or act as the migration solution, but in some cases, external tools are necessary. Ask your vendor about the tools they can provide to ensure a smooth, accurate WMS migration. 

 

Map your data fields accurately

With clean and audited data in place, as well as tools to perform the migration, it is time to map fields between the source system and the target WMS. All WMS systems have data fields, containing information about products, customers, statuses, etc. These need to be properly matched, so they can be smoothly transferred. If fields do not match or somehow get corrupted during the transfer, you risk problems further ahead.

Assess your data fields to understand the source data and define what needs to be migrated. Some practical examples of this could be mapping a “SKU Code” in the old system to a “Product ID” in the new WMS, or splitting a single "Address" field in the old system into "Street," "City," and "State" fields in the new system. These fields may differ between different businesses and WMS systems, and mapping them correctly is essential. With the tools and mappings set up, you have the ability to perform tests or small scale migrations to validate the data.

 

Validate and test your data thoroughly

After the data has been migrated to the new system, it is important to make sure that everything has been transferred correctly.

 

Follow these steps: 

• Set up a validation and testing strategy: define clear, measurable objectives (e.g. accuracy, completeness, integrity, and/or performance) and identify critical data 
• Validate data integrity: perform a pre-migration data validation where you audit source data, assessing the quality of the existing data to identify inconsistencies, duplicates, or missing records
• Test system functionality: plan functional tests to test key workflows and operational scenarios. Focus on core processes that rely on the migrated data, e.g. receiving and putaway, inventory management, picking, packing, shipping, replenishment, and/or cycle counting
• Reconcile inventory and confirm historical data: reconciliation ensures that the inventory in the new WMS matches the physical inventory and the records in the legacy system. Confirm that key historical records like transactions and order histories have been correctly migrated to the new WMS
• End-to-end testing: validate that all integrated workflows, systems, and data functions together as intended from start to finish. End-to-end testing is essential in ensuring that the migration supports all operational workflows, integrations, and business requirements. Simulate your daily operations in the most realistic way possible and, if applicable, test individual components (e.g., inventory management) before running full end-to-end scenarios
• Reporting and analytics: it is critical that the new WMS can keep tracking KPIs and deliver reports. Determine your reporting requirements for the new WMS, identifying key reports, confirming data availability and defining custom requirements. Replicate key reports and compare reports from the new WMS with those from the legacy system to confirm metrics, calculation and formatting
• Gather user feedback: solicit feedback from staff and managers who directly interact with the system. Define feedback objectives, like validating workflows and data accuracy. Make sure to involve users as early as possible and be transparent with the purpose of feedback collection and how it will be used
• Monitor the system performance: monitoring system performance after a WMS data migration is essential to ensure the new system operates smoothly, meets performance expectations, and supports warehouse operations effectively. Address any potential data-related issues promptly to minimize errors, disruptions, and other negative effects 

If you have good data migration tools, validation will be easier. There are several tools available to help with extracting, transforming, and loading (ETL) data while maintaining accuracy, minimizing downtime, and ensuring system compatibility.

 

Challenges in WMS data migration projects

As you can imagine, a WMS data migration project comes with several challenges and pitfalls. Aside from the technical factors we have touched upon, you need to consider the project’s organizational impact. Stakeholder communication and feedback is essential to keep people informed and supportive of the new WMS.

Training and change management is also important, as warehouse staff may resist the new system, especially if the migration impacts their workflow or productivity. There might also be skill gaps that need to be bridged through training and development; identify them early and proactively plan how to handle them effectively. 

Addressing the project’s challenges and pitfalls before performing the migration is worth it, as a failed data migration can prove costly. By having both the technical and organizational aspects covered, you are more likely to achieve a smooth data migration.

 

Conclusion - WMS data migration

Yes, there is indeed a lot to consider when it comes to WMS data migration, but proper planning and execution is worth the effort, as it will ensure that your new system functions optimally. A better, more modern WMS will make your warehouse more profitable by improving things like efficiency, accuracy and safety. 

 

If you are researching data migration, maybe you are on the lookout for a new WMS system? Our nyce.logic WMS uses the latest technology to transform your warehouse, helping you stay ahead of the competition.