Mergers and Poor Data Management
When two companies merge, it can can have incredibly lucrative results. However, due to poor data management, there can be numerous challenges that lead to merger failures. Understanding the pitfalls and addressing them well before a merger occurs saves considerable time, money, and valuable resources.
Differences in Data Usage
One of the most difficult things about a merger can happen when both companies aren’t handling data management in the same way. For instance, one company may be up-to-date with a cutting-edge data management system while the other may be using an antiquated platform. When this occurs, the task of getting the data from both companies working symbiotically can be tedious.
While there are vendor solutions for migrating data, using different platforms could lead to more problems than solutions. For instance, data that has already be interpreted by a different enterprise can cause inaccurate data transfer during the merge.
Tips for a Successful Data Migration
Indexing
Document all the data that is involved. This can be achieved by simple indexing. Make sure to include all storage locations that are both onsite and offsite.
Validation
To limit process failures, validating data is necessary. You’ll need to create workflows that allow you to manually review information such as addresses, phone numbers, and other calculations.
Capture and Extraction
Be sure to extract all digital forms of data. All archives, backups, emails, cloud systems, and other forms of storage should be validated.
Data Management Standardization
Ensure that all formats are similar by transforming the data that was acquired in different formats to a standard format.
How To Prepare for Data Cleansing and Data Standardization
A data audit is the first and perhaps the most important step you have to perform before engaging in a data cleansing and data standardization process. In short, it will help you identify the most common issues associated with the quality of your data.
Security and Permissions
Take steps to ensure that the data is protected when sharing with other people. In some instances, you may need to redact certain information, but make sure that you keep the original copy, as well.
