For companies involved in a merger or acquisition, the path to success involves recognizing data integration as an opportunity to redefine the customer experience and, by extension, the very essence of the merged entity.
Integrating two companies in a merger or acquisition can bring numerous advantages to the company, its employees, and its customers. By combining the strengths and resources of the two companies, the new organization can be more competitive and in a better position to achieve its business objectives and goals.
However, the process of integration extends far beyond combining physical assets and teams. Prioritizing data integration should be one of the management team’s top imperatives because it enhances decision-making accuracy, streamlines operational efficiency, allows the company to take a customer-centric approach, and fosters innovation.
But data integration is no easy feat. Below, I outline why I champion this initiative and share strategies to guarantee a smooth integration process that will not only elevate people’s experiences using data but also significantly boost financial performance.
See also: The Semantic Layer’s Role in Analytics and Data Integration
Prioritizing Data Integration Out of the Gate
Prioritizing data integration offers a strategic advantage. It lays the groundwork to unite both companies’ customer groups to create a unified data ecosystem that harmonizes all interactions and insights. And it’s essential for delivering consistent, personalized customer experiences and driving customer satisfaction and loyalty in today’s competitive market.
Focusing on data integration also facilitates a smoother integration process. It helps identify and mitigate potential data discrepancies and conflicts early on, preventing operational hiccups that could detract from the customer experience. Addressing these challenges proactively ensures that operational, marketing, and customer service strategies function effectively from the start.
However, acquiring a new customer base also means encountering new audience needs, expectations, and pain points. Integrating these diverse sets requires a well-thought-out data migration strategy. It’s not about merely combining customer data; it’s about understanding each data set and merging them to unlock cross-selling opportunities while effectively serving customers.
Take, for example, Salesforce’s acquisition of Tableau Software in 2019 for $15.7 billion. This M&A stands out as a paradigm of effective data integration enhancing customer experience. This strategic move enabled Salesforce to embed Tableau’s advanced data visualization capabilities into its platform, offering customers a richer, more nuanced view of their data. This integration tailored Salesforce’s customer experience, facilitating more informed and data-driven decision-making processes.
Salesforce’s assimilation of Tableau’s technology exemplifies the transformative power of unified customer data to personalize products and services, refine customer engagement strategies, and optimize operational efficiency. The acquisition didn’t just enhance Salesforce’s capabilities, it revolutionized how companies engage with and understand data.
See also: Real-time Data Integration: A Game-Changer for Mobile App Developers
Best Practices for Developing an Integration Strategy
Mapping out a data integration strategy starts with steps designed to evaluate and enhance the quality of data, select the most suitable integration techniques, and implement robust governance practices to maintain data integrity and compliance throughout the data lifecycle. Here’s an outline of key elements and considerations that form the backbone of a successful data integration initiative:
- Get Teams Involved Early: Successful M&A strategy involves collaboration across various departments, from data, analytics, marketing, and IT teams. Their involvement from the beginning helps companies understand the complexities of merging different data systems. After all, these teams possess the most historical and current knowledge of systems, processes, and data. These teams are your best assets to ensure a strategy is technically sound and aligned with the merger’s objectives.
- Ensure Data Quality: Next, audit both companies’ data. Begin by listing all databases. Doing so helps identify issues with data formats and governance policies, providing a clear understanding of the available data and avoiding potential data disasters. Confirm data sources are compatible with each other before proceeding. Auditing also guarantees the cleanliness and accuracy of your data. As we say in the CDP world, garbage in, garbage out.
- Set Clear Objectives: Once you’ve completed a comprehensive audit, clear objectives for the merger, such as enhancing customer service or streamlining operations, can be set. Setting clear goals can help you stay focused on what’s important.
- Choose the Right Technology and Capabilities: Merging companies bring together a complex array of data that demands careful integration. Select tools and platforms that support the scale and complexity of your data integration needs. Consider using integration tools and platforms that offer flexibility by allowing schema-free data ingestion, which can accommodate various data formats without the limitations of a rigid structure. It’s also advantageous to employ API systems to guarantee effective communication and data exchange between systems to eliminate downtime. Finally, the significance of artificial intelligence and machine learning cannot be understated, as they provide a smart way to eliminate duplicate entries and ensure the accuracy of your customer database.
- Emphasize Data Privacy and Security: Don’t forget to ensure that your tools, practices, and overall approach align with current regulations and data security standards. Your goal is to impress your customers, not make them anxious. Be transparent in your approach and empower your employees and customers to understand what you’re doing and how it benefits them.
- Implement a Phased Integration Approach: Given the complexities of data integration, consider adopting a phased approach. Start with integrating critical data sets that drive immediate value and gradually expand to other areas. Adopting this approach allows for early wins and grants the opportunity to tackle challenges in a controlled manner. Adopting a phased approach allows stakeholders to communicate effectively, align themselves, foster trust, and work collaboratively to address feedback and adapt strategies.
As we look towards the future, the emphasis on data integration in M&A will only grow stronger. It represents a strategic lever for unlocking value, fostering innovation, and achieving competitive advantage in a rapidly evolving marketplace. For companies embarking on this journey, the path to success involves recognizing data integration as more than a challenge—it’s an opportunity to redefine the customer experience and, by extension, the very essence of the merged entity.
