Salesforce is a powerful tool that can transform the way a business operates. It can help companies streamline their sales, marketing, and customer service processes, leading to increased productivity and improved customer satisfaction. However, migrating data to Salesforce can be a complex process that requires careful planning and execution.
I have been in a lot of projects where Data Migration was a big and continuous challenge, from deciding who is responsible for data cleansing to mismatch between old and new system making data mapping near impossible.
In this blog post, I will discuss five common mistakes to avoid when planning for Salesforce data migration.
- Insufficient Data Analysis
Data analysis is a critical step in the data migration process. It involves identifying the data that needs to be migrated and determining the best way to transfer it to Salesforce. Insufficient data analysis can lead to incomplete or inaccurate data migration, which can have serious consequences for the business. Moreover, it can result in data loss, which can impact customer relationships and business operations.
To avoid this mistake, businesses should conduct a thorough analysis of their data before beginning the migration process. This should involve identifying the types of data that need to be migrated, determining the quality of the data, and deciding on the best way to transfer it to Salesforce. It is essential to involve all stakeholders in this process to ensure that all data is captured accurately.
- Lack of Data Mapping
Data mapping is the process of matching data fields in the source system to those in the target system. It is a critical step in ensuring that the data is migrated accurately and completely. Failure to map data correctly can result in incomplete or inaccurate data migration, which can have a significant impact on business operations.
To avoid this mistake, businesses should create a comprehensive data mapping plan that identifies all the data fields that need to be migrated and how they will be mapped to Salesforce. This should involve working closely with the technical team to ensure that all data is mapped accurately and completely.
It’s important that during the mapping process you not only take into account what is on the page layouts, but also old fields no longer visible and fields used in any automation processes.
- Inadequate Testing
Testing is a crucial component of the data migration process. It involves validating the data after it has been migrated to Salesforce to ensure that it is accurate and complete. Inadequate testing can lead to data loss or data that is incomplete or inaccurate. This can have a significant impact on business operations and customer relationships.
To avoid this mistake, businesses should create a comprehensive testing plan that includes a range of scenarios that test the data migration process thoroughly. It is essential to involve all stakeholders in the testing process to ensure that all data is validated accurately.
Testing of course needs to happen where possible in the sandbox and in small sample batches of data first. It is important to establish if the info goes through as expected and what happens with any automation processes. Think carefully about any auto emails that get send out as part of processes. Importing hundreds of rows of data can trigger major process chains, which can grind your system to a hold as well as flooding people’s inboxes with unnecessary messages. Temporary de-activating processes might be a key outcome of your testing!
- Poor Data Quality
Poor data quality can have a significant impact on business operations, customer relationships, and the success of the data migration process. It can lead to data loss, incomplete data migration, and inaccurate data. Poor data quality can also result in low user adoption, which can impact the ROI of the Salesforce investment.
To avoid this mistake, businesses should conduct a data quality audit before beginning the migration process. This should involve identifying any data quality issues and developing a plan to address them. It is essential to involve all stakeholders in this process to ensure that all data is of high quality and accurate.
Here I have often seen a challenge to whom is responsible for the quality. It should be a two way processes. The business knows (or should know) what correct data is, whereby the Salesforce project team can help in speeding up the process with automation tools and pre-check data before loading.
- Lack of Data Governance
Data governance is the process of managing the availability, usability, integrity, and security of data used in an organization. It involves establishing policies and procedures to ensure that data is used correctly and consistently across the organization. Failure to establish a data governance framework can lead to data loss, inconsistent data, and poor data quality.
To avoid this mistake, businesses should establish a comprehensive data governance framework before beginning the migration process. This should involve identifying the people, processes, and technology required to manage data effectively. It is essential to involve all stakeholders in this process to ensure that all data is governed effectively.
Conclusion
Salesforce data migration is a complex process that requires careful planning and execution. Failure to plan adequately can lead to data loss, incomplete data migration, and inaccurate data. By avoiding the five common mistakes discussed in this blog post, businesses can ensure a successful data migration to Salesforce. It is essential to involve all stakeholders in the data migration process to ensure that all data is captured accurately and completely. With proper planning and execution, businesses can realize the full potential of Salesforce and transform the way they operate.
Test twice, Load once
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