Only 26% of organizations achieved data migration within their expected time frame based on the study, "The Impact of Cloud on ERP" which is a survey on the migration from ERP on-premises to the cloud. 90% of CIOs surveyed reported data migration projects extended timelines and budgets due to complexity. Based on the findings the challenges and highest-rated cause of delays were customizations or development that was taken on in order to migrate data.
Another mistake most organizations make is moving all the data from one system to another without considering how much incorrect and incomplete data is in their current database/data structure. Poor data quality can negatively impact business and make it difficult for organizations to make good data-driven decisions. A strategy to migrate crucial data using data quality cleansing techniques will help you achieve a cleaner data migration to the Microsoft Dynamics 365 Finance & Supply Chain Management environment.
At To-Increase, we help organizations fast-track and improve their data migrations to D365 F&SCM using our low to no-code solutions. Therefore, in this blog, we will focus on how organizations can focus on data quality to improve their chances of success during data migration projects to Dynamics 365.
Why is data quality crucial in ERP migrations?
Inaccurate, incomplete, and inconsistent data could lead to data compliance issues. There are several rules that organizations in highly regulated industries need to keep in mind such as HIPAA for the healthcare industry. Some mandates are region-specific such as GDPR rules for the EU region.
Incorrect or missing data can result in issues with customer orders. For example, if the shipping address is incorrect, the delivery will be delayed which can result in unhappy customers and losses for your business due to extra charges.
Poor data makes it difficult to make good impactful decisions for your organization. This could be due to inaccuracies, missing data, and inconsistencies in the data migrated from the legacy ERP.
Common mistakes during data migrations
Underestimating the complexity
Migrating to the cloud and ERP implementation is the major focus and the data migration although a big project is not given as much importance. Companies do not have a strategy or plan when they are migrating data and only realize the complexity when they are neck-deep in the migration. Additionally, they do not plan for what data needs to be migrated and assume they can just move the data as it is. Data migration involves the transformation of data from one system to fit into the rules, business logic, and parameters of the other system. Understanding the way, the Data Management Framework works is an essential skill to be able to navigate the complexities of moving to D365 F&SCM from another legacy ERP.
Lack of a data governance strategy
Lack of data governance can affect data quality. You probably have data from multiple sources and formats that need to be moved to D365 F&SCM, for example, data from multiple legacy ERP systems, or data from other add-on solutions and customizations. A simple lift-and-shift approach that is moving data as is to the new system will not work out for you in the long run. It is a risk-laden approach that can result in a data migration failure. You could have data that is not updated, data duplicates, missing information, and errors. This approach will not work for D365 F&SCM due to the business logic and data entities in Microsoft’s Data Management Framework. If the data entities differ you need to start development or then use a solution to migrate data.
Lack of a migration strategy
A data migration plan helps you identify possible risks in your project and plan for solutions. This requires an understanding of data sources and the relationship of tables across source systems. Dynamics 365 has business logic for dependent data, so you need to follow a data hierarchy while migrating data. For example, if you try to move orders before you move customers into the system, you will receive errors.
Additionally planning for documentation for the project if you decide to take up customizations should be considered to ensure new employees or team members can refer to that in case of any bug fixes.
Not analyzing historical data
When you are moving houses, you need to sort through your stuff and throw out unnecessary junk that has been collected over the years. Similarly, when you are moving data from legacy ERP systems to D365 F&SCM, you need to have a strategy to import relevant and updated data. Sifting through historical data in your old system and finalizing data that needs to move to D365 F&SCM can be messy. Determining how much historical data is needed for reporting and analysis can be difficult without a clear plan.
Inadequate data validation
Testing, testing, and even more testing would be our recommendation to anyone planning a data migration project. Without adequate data validation and testing, errors are sure to pop up in D365 F&SCM when data is not checked internally and externally for accuracy. Inaccurate data translates to incorrect reporting and problems with data integrity. Additionally, when you have inaccurate data in your new systems, it will take a long time to fix any issues caused due to inaccurate data.
Lack of training in data processes
Training and communication are a big part of any data governance project. If the several teams using the organization’s various business systems are not aware of the data structures, data entry processes, and guidelines, you have a lot more data cleansing lined up for you than you had hoped for. This will also increase the timelines for your data migration project.
Best Practices to Ensure Data Quality
Data cleansing
Most organizations have questionable data quality in their legacy systems. Moving to a new ERP is a chance to clean and sort historic data and move data that is valuable. Data errors add risk, delay data migrations, and increase the effort required to complete the project. Focusing on data quality prior to starting the data migration will save your team the headache of managing both tasks simultaneously.
Regular data quality checks
Data quality assessments should be carried out throughout a data migration project and based on Gartner’s recommendation “intensify as initial data conversion tests are run”. When you are moving data from a legacy ERP system to D365 F&SCM, you need to transform it to fit into the data structure of Microsoft’s Data Management Framework. If you have a solution that can help you add data quality rules and validations while testing your data imports into D365 F&SCM, you will have reliable data that you can bank on in your new ERP system. Periodic data cleansing and quality assessments should continue throughout the data lifecycle to ensure data integrity.
Assign roles and metrics
Every step in the data lifecycle can impact data quality. Ensuring that you have roles assigned to employees for data entry, data validation, and data quality checks can ensure ownership and responsibility and improve data quality. Additionally, defining realistic data quality metrics in line with your organization’s goals will help your team define a data governance plan to achieve those numbers.
Phased-wise approach
A phased migration approach will help you “divide and rule” the anticipated data issues and errors that might crop up. Moving from a legacy system to a D365 F&SCM environment involves a lot of complexity and data transformations, doing it all at once, especially if you have a large data migration project involving multiple legacy system consolidations is not the best approach to adopt.
Data migration solutions
If you decide to implement enterprise-ready solutions that can help you with data mapping, data transformation, and data quality rules that can reduce or eliminate development efforts, you are most likely to meet your deadlines and budget and will also save your team a lot of time and stress. A data migration solution can serve as a single source of truth for the technical and business teams that are part of the data migration project and ensure that all stakeholders have visibility of what is going on. If you hire developers or external Consultants to code and customize, it is most likely that only your IT team will be involved.
Data governance
Industries such as pharmaceuticals, food manufacturing, and insurance are highly regulated and have certain compliance guidelines and rules that are mandatory. We recommend working on a data migration strategy and framework in alignment with the larger data governance strategy. Planning and documentation can ensure transparency. If the team is aware of the rules, mappings, and the responsible team members, it is easier to collaborate, retrace your steps, and ensure data consistency.
Are you considering moving to Dynamics 365 F&SCM?
We hope these mistakes and best practices will help you with your data migration project. We have helped several customers move to D365 F&SCM using our Data Migration Solution.
If you are looking to move to D365 F&SCM and looking for solutions that can ease and speed up your migration, our no-code Data Migration Solution can help. Built using the same business logic as D365 F&SCM our solutions can help you clean data while you are testing or moving data.
Our Connectivity Studio solution can help you map data entities using transformations, from multiple legacy systems and move data into multiple companies using multi-threading and parallel processing. Using the Data Quality Studio solution, you can add data quality rules that can check for data validations, data duplicates, and data errors.
Want to learn more about our solutions? Sign up and access our on-demand webinar, “How to Manage Challenging Data Migrations into D365 F&SCM” from the link below.
Rico Lamein
Sumana Samuk
