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Data Integration Pitfalls in Mergers and Acquisitions: Common Mistakes Companies Must Avoid

Data Integration Pitfalls in Mergers and Acquisitions: Common Mistakes Companies Must Avoid

There are many lingering concerns about economic stability, but the drive for merger and acquisition (M&A) is still strong. According to PWC data, 60 percent of corporate business leaders are not planning to delay deals in 2023 to overcome potential economic challenges and volatility. 

M&A is used as a cornerstone for reimagining your business growth. As a matter of fact, business executives who strategically rely on M&A can expand their footprint, improve the quality of their products or solutions, and create stronger market value or differentiation, even when the times are uncertain. However, performing on a successful M&A deal calls for a detailed strategy because mistakes are likely, and they’ll cost you growth and money. 

Companies planning to close a merger and acquisition deal tend to make mistakes related to the technologies such as data integration. A lot of these mistakes can be avoided by leveraging reimagined technological solutions. 

This blog post highlights some of the most common mistakes and discusses how a modern data integration solution that uses AI and self-service can help companies avoid them.

Common Mistakes to Avoid During M&A

  1. Insufficient Data Mapping and Alignment: When companies struggle to map and align data structures, formats and definitions between the merging entities, they run into data inconsistencies and hindered integration. And when businesses strive to integrate and use customer data, decision-making and value generation take a hit. Organizations fail to deliver the value promised to customers and ultimately grow revenue. 
  1. Inadequate Data Quality Assessment: Neglecting to assess and address data quality issues can result in unreliable and inaccurate information. It’s essential to perform a thorough data quality assessment, identify gaps, and implement a data integration approach that offers an end-to-end encrypted environment to use data. 
  1. Overburdened IT teams: With traditional data integration solutions, the responsibility of building data connections and performing other data-driven operations falls on IT. IT teams create custom codes and implement data mappings that take weeks or months. During that time, IT teams struggle to devote their time to more high-value tasks, while business workers wait to deliver value to customers.
  1. Lack of Data Governance: Ignoring data governance during integration can lead to data ownership issues, security vulnerabilities, and compliance risks. Establishing data governance policies, defining roles and responsibilities, and ensuring data privacy and security are critical.
  1. Incompatible Systems and Technologies: Merging companies often use different systems, databases, or technologies, which can pose challenges for data integration. Identifying compatibility issues early on and devising strategies to integrate or migrate data across systems is crucial.

How Can Self-service Data Integration Solutions Help?

Self-service data integration solutions enable companies to maximize the impact of M&As by:

  • Enabling businesses to map complex customer, bi-directional data streams using AI-driven suggestions, making it faster and much more secure than ever. 
  • Providing an end-to-end encrypted environment that allows only authenticated business users to access and use data. 
  • Empowering non-technical business users to implement data connections much more quickly while freeing IT to focus on high-value business priorities.
  • Providing users with a controlled and centralized platform, enabling data access, transformation, and integration while maintaining compliance, security, and data quality standards.

Avoiding common data integration mistakes requires meticulous planning, a collaboration between IT and business teams, and close coordination with business stakeholders. Companies can rely on modern data integration solutions powered by self-service and artificial intelligence to smoothen merger and acquisition and achieve maximum value.