3 Ways Data Analysis Can Streamline Mergers and Acquisitions
In modern business, mergers and acquisitions (M&A) are an essential vehicle to drive growth, profitability, and shareholder value. However, delivering a successful M&A project requires careful planning, identification of appropriate buyers and sellers, and above all else, the management of many potential risks. This blog looks at three ways that automating unstructured data analysis can streamline mergers and acquisitions by mitigating risk, reducing manual effort, and driving faster business value.
3 Ways Automated Unstructured Data Analysis Can Streamline Mergers & Acquisitions
1. Reduce time & risk during M&A due diligence
2. Improve post-M&A systems and data integration
3. Enable ongoing data risk management during M&A
According to analyst firm EY, the first half of 2021 saw well over 2,200 global M&A deals with a total value of just over two trillion US dollars. Still, while the analysts may focus on the deal-making aspect of M&A, the most critical work goes on before and after the signing of contracts. Effective execution of activities such as due diligence (pre-deal) and integration of the acquired entity (post-deal) determines both whether a deal goes ahead and whether it succeeds. Each of these areas is time-consuming, full of data, and fraught with risk — until now, that is.
The key to success lies in the automated discovery and analysis of the unstructured data stored with the thousands of documents, spreadsheets, and financial reports that form a core part of any M&A activity. By replacing error-prone manual processes, automation changes how documents and data are analyzed pre-acquisition and integrated post-sale.
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Reduce time and risk during M&A due diligence
One of the most time-consuming and complex areas of M&A is due diligence. This area is also fraught with risk. Due to the volume of documents involved in most M&A activities, there is no practical way to review ALL of them – at least not thoroughly. As a result, many firms “sample” the documents to cover as much as possible. Unfortunately, this sampling leaves the acquiring firm open to missing vital information that could affect the purchase price, identify potential conflicts of interest, or even halt the deal altogether.
There is also a balance regarding how long the due diligence takes to complete. For example, in a competitive bidding situation, investors need to be quick to issue a term sheet. However, if they cut corners on due diligence, what they gain in speed they lose in accuracy — potentially having a significant impact on the contents of that same term sheet.
Automated tools, specializing in the management and processing of unstructured data, remove this challenge. These solutions work through every document, across a range of search parameters. However, unlike simple data discovery tools that look purely for company names or similar terms, AI-infused data analysis solutions can “think” much more like humans. They look for areas of documents that are of interest to the M&A process and flag the most important content for expert review.
This approach does not remove humans from the loop. Instead, it simply identifies which documents are essential for the human experts to review – rather than having them trawl through endless records hoping to find the right ones.
In addition to reducing the time in due diligence, streamlining pre-deal activities through automated data analysis offers reduced and controlled costs and increased coverage of materials. This leads to more accurate valuations and less risk for all parties involved.
Improve post-M&A systems and data integration
Once the ink is dry on a merger or acquisition, the focus shifts from due diligence to integrating systems, processes, and people. Each acquired business will come with its own systems for finance, HR, sales, and more. While running parallel systems might make sense in the short term, in the long run consolidating these systems and their associated processes is top of mind.
Indeed, in the modern business environment, many M&A deals focus on acquiring new technology. Bain & Co claims that over 50% of purchasers seek to profit from the technology acquired, and Accenture says that 80% of companies place a significant emphasis on technology. This approach makes perfect sense — there are numerous strategic benefits to the effective integration of new technologies and systems:
- Access to new technologies
- Exploring the new technologies and software environments gained as part of a merger or acquisition can speed technology adoption and deliver a competitive advantage.
- Modernizing legacy systems
- An acquisition or merger provides a perfect incentive to migrate away from aging and expensive legacy systems.
- Enhanced customer engagement
- Streamlined IT systems in the back office can lead to more effective customer communications, service, and overall engagement.
The focus on technology integration does not make the exercise any more straightforward, however, nor any less risky. Failure to execute an integration effectively can lead to 2-3 times higher ongoing IT costs and 4-5 times higher IT complexity. There are four key tasks that any post-merger integration (PMI) needs to consider:
- Identify what systems exist, their purpose, and their applicability for the new organization
- Integrate relevant systems to create a federated view of documents, data, and processes in the first instance
- Look to consolidate by migrating content and data from source to destination repositories and systems
- Retire legacy systems to reduce cost, complexity, and technology debt
Again, using appropriate tools and technologies to assist with this integration process is critical. The same unstructured data analysis and processing tools used in the due diligence process can help to identify what resides in existing systems and use this information to drive intelligent migrations and integrations. Deploying these systems to the IT teams for all organizations involved early in the process will drive collaboration, increase visibility, and deliver faster and more robust system integration post deal.
Enable ongoing data risk management during M&A
As we’ve seen, risk exists in multiple areas across the M&A process. Of course, any business activity is risky, but the key is to understand the level of risk associated with any activity and mitigate against it wherever possible.
As you move from due diligence to system consolidation, the risk profiles change — but the need to understand those risks does not. For example, during due diligence, risk is focused on ensuring review completeness in as short a time as possible. In contrast, post-integration risk emphasizes system integration, data completeness and accuracy, and process effectiveness.
However, across both these areas, the M&A team has two critical requirements concerning risk management:
- The ability to easily visualize and interrogate the data, documents, and potential risk metrics at any point
- A need for a system to automatically alert them to potential areas of interest or concern
Unstructured data management and analysis tools provide a comprehensive way to address these needs. Standard dashboards offer organizations a consistent view of documents, data, and risk across the whole project. As a result, the newly amalgamated business can focus on rapid and effective integration, access to shared, consolidated technology platforms, and a carefully managed risk profile throughout.
Streamline mergers and acquisitions with automated unstructured data analysis
Mergers and acquisitions provide businesses with tremendous opportunities for transformative growth and innovation. However, they also provide equal levels of risk during the actual M&A process. The sheer volume of documents and data to investigate pre-deal and the technical complexity of integrating systems post-deal make for individually challenging projects. Every M&A deal needs both elements to succeed for the overall objective to be realized.
Human execution of these projects is notoriously challenging, slow, and error-prone. By automating the processing and interrogation of unstructured data, organizations gain access to increased visibility, specific and complete data analysis, and the opportunity to complete the M&A process much faster – so key resources can resume focus on the core business and ensure they’re maximizing the value of the deal.
With the vast amounts of financial and human investment involved in each merger or acquisition, streamlining both pre- and post-deal activities is an ideal way to deliver increased chances of success, which everyone involved can cheer about.