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Reference Data: Smoothing Out the Bumps in M&A

Reference Data: Smoothing Out the Bumps in M&A
Nowadays, organizations continue to leverage Mergers and Acquisitions (M&A) to increase market share, expand product offering, reach more customers, increase revenue, improve margins, and reduce cost. The recent trends of consolidation across every industry show no signs of slowing down. In fact, according to S&P Global Market Intelligence, just in the first quarter of 2021, M&A transactions recorded $989B globally! This is an increase of 81% YoY and the highest deal volume in the last 4 years, despite the pandemic!

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Mergers & Acquisitions do not automatically generate all these desired benefits. In fact, these mergers bring complex architectural and data challenges. Just because two companies use the same kind of transactional/ERP system does NOT mean that the two systems can be easily merged. It becomes just as difficult to merge two similar ERP systems as it is to merge two dissimilar transactional systems. Why is this? The difficultly arises due to the DATA and the ecosystem. Do we have the same data? Structures? ERPs? Code representations? Financial hierarchies? What’s the governance model? What are the best practices to follow? Do we need all the systems and how do we make all of this work together?

Culture, people and other non-tangible factors have some impact, but by far the greatest challenges result from the differences in the underlying data.

According to Harvard Business Review, multiple studies show that the failure rate for mergers and acquisitions (M&A) sits between 70 percent and 90 percent. How can these percentages be improved? According to Accenture, companies that took the time to properly integrate their systems following a merger were able to reduce costs of key business functions by as much as 40%.

Organizations must achieve synergies across the merging companies while reducing cost, as quickly as possible. Let’s examine some challenges. For most all M&A scenarios, a set of consolidated financial statements is an early requirement. To produce accurate financial statements, the chart of accounts (COA) hierarchies must be rationalized. This task requires involvement from accounting, finance, and management teams. The consolidated financials are essential to start the process of estimating and generating synergy targets. The consolidation requires a process and straightforward tools to support. The tools must be:
  • Secure
  • Flexible
  • Enable “what-if” changes with ease.
  • Provide different effective start and end dates

The tools must support mapping/aligning the COA at any level in the COA hierarchy or at the lowest level of codes. The newly mapped codes must be extended against the previous year’s transactions to generate financial statements.

A good reference data management tool can help achieve this. In fact, good reference data provides a strong foundation for the overall data management strategy that should be in place with a merger or acquisition.

Let’s consider a real-world case study. Several years ago, three large telecom companies received approval for merger. The combined companies operated over a dozen different billing systems. Cost estimates to merge the dozen plus billing systems were in the hundreds of millions of dollars and would take years to implement. This was a huge challenge which would make achieving the key goals of improving ailing customer service and reducing complexity to the end customers difficult if not impossible. As a result, the service codes, billing codes, channel lineup, and other similar codes had to be both aligned and rationalized at the same time. Alignment and rationalization would be straight forward efforts if there was one common billing system used across companies, geographies, and brands. Additionally, the merger would be considered a failure if it required hundreds of millions of additional dollars invested and years to wait.

The newly merged company immediately formed a task force with key stakeholders from the acquired companies. The task force agreed on a process to submit, analyze, justify, and approve code rationalizations. To support the newly agreed process, the task forced required a tool that would easily enable the process from code submission to approvals and enable the dozen plus billing systems to operate “as is.” The tool must be secured, web-based, economical, easily to use and deploy. The tool must allow multiple old codes to be retired and replaced by fewer, simpler codes.

By supporting these needs, the new process and tool were implemented in a matter of months versus the previous years’ long estimates. Across the enterprise, business users were able to submit code rationalization requests to the task force via the tool’s web front end. The new codes, effective dates, impact analysis, and cross-organizational approval were all done via the same web browser-based tool. Once the effective date occurs, the tool works with other systems to facilitate the code promotion process. Detailed history was maintained in cased a future change or roll-back became necessary.

To summarize, M&As can be an important part of a company’s growth, but they come with some complex challenges. As the gathering and usage of data explodes across every aspect of business (and life), a successful M&A requires a strong data management and governance strategy. Good reference data should be core to this strategy and provides a strong foundation to build upon. A good RDM tool becomes important to help manage it.
Portrait of Jignesh Kothari

(Author):
Jignesh Kothari

Jignesh is a Senior Data Solution Architect at Teradata. He has experience building, designing, implementing and selling enterprise software solutions providing high value business outcomes across various industries.
  View all posts by Jignesh Kothari

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