M&A Success Is Impossible Without Proper Data Integration

A 7-Step Approach to Integrate Data and Analytics After an M&A Deal

By Leon Ginsburg, Founder and CEO, Sphere Partners

Mergers and acquisitions (M&A) have become the darling of the business world. And for good reason: M&A can be an essential strategy for companies looking to fuel growth and market consolidation.

But ask any tech leader, and they will tell you that a successful M&A requires far more than getting the financial numbers right. One of the most critical components is ensuring a seamless integration of data and analytics from multiple entities.

At Sphere, where our team of experienced tech consultants and expert analysts help clients unleash the power of human and artificial intelligence, we know that maximizing the impact of an M&A begins and ends with data. Read on to learn about the data challenges that crop up during the M&A process — and a seven-step process to overcome those hurdles through data integration.

Data Issues to Look for During M&A

Integrating two or more companies is a monumental task, and while financial and operational integration often take the spotlight, data-related activities are equally paramount.

However, executives leading mergers and acquisitions tend to sideline or outright ignore data challenges that arise during the initial stages post-M&A. That can lead to a series of problems that snowball into catastrophic failures:

  • Inability to Be Proactive. The absence of timely and actionable information with regards to data can paralyze decision-making. The deluge of changes that come with an M&A, combined with a dearth of data, hinders the new company’s ability to effectively respond to both challenges and opportunities.
  • Bad Customer Experience. Data-quality issues post-M&A can tarnish brand reputation and erode customer trust. When your ability to serve customers is compromised, doubts arise about your capacity to uphold promises, maintain trust, and meet their needs.
  • Wasting Time and Resources. Transitioning is already challenging, but coupling it with poor data management exacerbates the situation. Duplicate efforts, manual processes, and inaccurate information drain valuable time and resources.
  • Strategic Blindness. Maintaining an unbiased view of organizational performance during M&A is crucial. Quality data provides the lens through which you can identify success criteria and seize opportunities swiftly using analytics.
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A 7-Step Approach to Integrating Data and Analytics Post-M&A

Having a systematic plan for seamless integration of data and analytics is essential to avoiding the above pitfalls and ensuring a successful M&A. Consider these seven steps to best position your company for a prosperous M&A: 

  1. Evaluate Data Maturity. Acknowledge the distinct data maturity levels of each entity involved in a deal, taking into account factors such as skills, existing systems, data quality, and decision-making practices. By quantifying data maturity, you can set expectations and formulate data-driven strategies.
  2. Commence Data Integration Early. Avoid conflating enterprise technology migrations with the enhancement of analytics capabilities. Kickstart analytics improvements independently of technology integration. Assess the critical data required for insightful business decisions and leverage available data even before systems are fully integrated.
  3. Initiate with Sales Data. Propel your data integration initiatives using customer and prospect data. This data often harbors invaluable insights and can serve as a catalyst for more comprehensive integration endeavors. Harness sales data to unearth cross-selling opportunities and collaborative avenues.
  4. Centralize Data Repository. Establish a singular repository to house all data assets. A data catalog facilitates preliminary analysis of future use cases. This one-stop shop for your data team obviates the need to navigate disparate systems, bolstering efficiency and accuracy.
  5. Harmonize and Govern Data Assets. Create a data warehouse to model disparate data across business lines. This involves high-level information initially, which can be expanded as data maturity improves. Proper data modeling empowers seamless extension as new data assets become accessible in your central repository.
  6. Consider User Adoption. Tailor your strategy to your target audience’s needs. Prioritize business use cases through a data strategy roadmap. Gauge adoption using pre-built “usage dashboards” to identify potential analytics champions across various segments.
  7. Preemptive Action is Key. Rather than waiting for full business integration, initiate the data integration process incrementally. By posing the right questions and progressing systematically, you can rapidly generate valuable insights.

Never Underestimate the Importance of Data in M&A Again

All it takes is one M&A deal that falls apart due to lack of data integration to remind executives that a successful transaction is about much more than numbers on a balance sheet. Just as technology is the cornerstone of modern business, data integration is the linchpin of M&A success. 

By weaving the threads of disparate data into a unified tapestry, you lay the foundation for informed decision-making, enhanced customer experiences, and optimized resource allocation. 

Sphere, on our mission to blend human and artificial intelligence, is here to guide you in all aspects of data integration. Reach out today to discuss how Sphere can help you maximize your M&A success.

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