Unveiling a decade of M&A diligence trends: key insights for deal success

The M&A landscape has undergone dramatic transformation over the past decade. Recent research examining virtual data room activity across hundreds of transactions reveals fundamental shifts in how deals are conducted, from the length of diligence periods to the number of participants involved. These findings offer critical insights for dealmakers seeking to optimize their processes and improve transaction outcomes.

The expanding timeline: from 124 to 203 days

Perhaps the most striking finding from comparing M&A activity today with a decade ago is the significant expansion in pre-announcement diligence periods. Ten years ago, the average time from data room opening to deal announcement was 124 days. Today, that figure has ballooned to 203 days, representing a 64% increase.

This expansion accelerated dramatically during the pandemic years. While pre-2020 deals averaged 189 days in the diligence phase, transactions from 2020 to 2022 stretched to 247 days. Several factors contribute to this trend:

• Increased complexity in diligence scope. ESG considerations, climate change impact assessments, and cybersecurity reviews have become standard components of due diligence. These areas received minimal attention a decade ago but now demand substantial time and specialized expertise.
• Market disruption and valuation gaps. Rising interest rates and increased cost of capital have created misalignment between buyer and seller expectations. When parties cannot quickly agree on valuation, diligence periods extend as deals enter holding patterns while expectations recalibrate.
• Geographic variations in market adjustment. Different markets respond to economic changes at varying speeds, with the US typically adjusting faster than European markets. This creates additional complexity in cross-border transactions.

The COVID effect: permanent changes to deal dynamics

The pandemic fundamentally altered how M&A professionals conduct business, with many changes persisting beyond the crisis period.

Building trust in virtual environments

Early in the pandemic, dealmakers struggled to establish trust with counterparties through audio-only calls. The rapid adoption of video conferencing technology proved transformative. Seeing into people's personal spaces, their homes, families, and pets, actually humanized interactions in unexpected ways.

This shift had particular impact in markets where in-person meetings were previously non-negotiable. Countries that once required physical presence for business discussions quickly adapted to virtual engagement, accelerating deal processes in regions where teams lacked local presence.

Reimagining deal team composition

Physical co-location is no longer the primary criterion for assembling deal teams. Organizations now prioritize professional capability, diversity of thought, and specialized expertise over geographic proximity. This has enabled more effective team composition and access to the best talent regardless of location.

Virtual site visits and physical diligence

For industries requiring facility inspections, technology bridged the gap when travel became impossible. Smart glasses and remote video capabilities allowed buyers to conduct thorough physical diligence without ever visiting a site. In one notable example, a buyer completed the entire acquisition of a refinery, including binding agreements, without physically visiting the facility. Operators wore connected devices that allowed remote buyers to direct their movements, requesting specific views and angles in real time.

Data room evolution

Virtual data rooms expanded significantly during this period, not just in document count but in file types. MP4 files containing facility tours, management presentations, and recorded interviews became standard, replacing face-to-face interactions that were no longer possible.

Public vs. private: stark differences in diligence intensity

The research reveals significant disparities between public and private company transactions:

• Timeline differences. Public company deals average 125 days in the pre-announcement phase, while private deals extend to approximately 230 days.
• Information volume. Private deals contain nearly 3,000 more files in data rooms compared to public transactions.
• User participation. Private deals involve more than 100 additional users on average.

These differences stem from several factors. Public companies face greater regulatory requirements for transparency and information disclosure. This creates more preparedness and often means substantial information is already publicly available, reducing what needs to be shared in the data room. In some jurisdictions, legal constraints limit what public companies can share, even under NDA, if it constitutes material non-public information.

Private companies typically have fewer regulatory obligations, less established disclosure practices, and may rely less on external advisors. Smaller private companies often lack the resources and infrastructure for comprehensive information preparation, extending the time required to gather and organize materials.

Cross-border complexity: an additional month of diligence

Cross-border transactions add an average of 30 days to the diligence timeline. This extension reflects several challenges:

• Language barriers. When original documents exist in languages other than English, sellers typically refuse to provide translations to avoid reliance issues. Buyers must either find team members fluent in the source language or engage specialized translators.
• Local regulatory requirements. Each jurisdiction brings unique regulatory frameworks that require specialized expertise and additional review time.
• Expanded advisor networks. Cross-border deals often require multiple advisory firms with jurisdiction-specific expertise, increasing coordination complexity and communication overhead.
• Foreign direct investment regimes. New national security and foreign investment screening processes have emerged across many countries in recent years. These regimes, some still in their infancy, create uncertainty and require extensive engagement with regulators. Advisors and dealmakers are still learning how these frameworks apply, leading to extended timelines as parties navigate unfamiliar regulatory territory.

The Goldilocks effect: finding the optimal diligence period

Research reveals a “happy medium” in diligence timelines that correlates with both higher deal success rates and lower premiums paid by buyers. Neither rushed diligence nor excessively prolonged processes produce optimal outcomes.

Balancing thoroughness with speed

Achieving this balance requires discipline and focus:

• Targeted information requests. Generic, off-the-shelf diligence questionnaires waste time and frustrate management teams. Requests should be tailored to the specific business, focusing on what truly matters rather than checking boxes on irrelevant items.
• Clear materiality thresholds. Establishing appropriate materiality levels from the outset prevents teams from spending time on inconsequential matters. The water cooler contract in a large-scale operation simply does not merit attention.
• Understanding value drivers. Investing time upfront to understand what makes the business tick, what the real drivers are, and where risks likely hide enables more efficient diligence. This requires combining sector expertise with specific knowledge of the target.
• Defined scope and parameters. Setting clear boundaries for the diligence exercise prevents scope creep and speculative investigation of tangential issues.
• Deal lead accountability. The deal lead must maintain focus on what matters, set the pace, and ensure all team members understand the strategy and timeline. Without strong coordination, diligence can drift.

Managing information overload: the growing user base

The number of users accessing virtual data rooms has increased 64% over the past decade. This growth reflects several trends:

• Increased specialization. As diligence has become more sophisticated, covering more areas in greater depth, teams have grown to include specialists in narrow domains. Rather than generalists, deals now involve experts in specific aspects of ESG, cybersecurity, regulatory compliance, and other focused areas.
• Geographic distribution. The ability to assemble teams globally means organizations can involve the best people regardless of location. A team might include specialists from multiple continents, each contributing expertise in their area.
• The coordination challenge. Larger, more distributed teams require significantly more coordination. Deal leads spend substantial time in alignment meetings ensuring everyone works toward common objectives and understands the timeline.

Finding the right balance between accessing necessary expertise and maintaining manageable team size represents an ongoing challenge. The temptation to expand teams is high when virtual access makes it easy, but coordination costs increase with each additional participant.

Deal leaks: timing and intentionality

Analysis of deal leaks reveals important patterns:

• No correlation with data room opening. Contrary to what might be expected, leaks do not correlate with virtual data room launches. The introduction of multiple users to confidential information does not appear to trigger leaks.
• Correlation with announcement timing. Leaks cluster much closer to the announcement period, suggesting they are often strategic rather than accidental.
• Intentionality. The data indicates most leaks are deliberate rather than inadvertent disclosures.

Leak prevention and response strategies

While preventing determined leakers is nearly impossible, organizations can take steps to minimize risk and prepare for potential leaks:

• Technical and behavioral safeguards. These work well for preventing unintentional leaks but cannot stop someone intent on disclosure.
• Pre-planned response strategies. Public companies should engage PR firms early and develop response scenarios. Having a strategy on the shelf, ready to deploy if needed, enables faster, more effective responses.
• Scenario planning. Consider different leak sources and severity levels. A speculative inquiry requires different handling than a major publication announcing they are running a story the next day.
• Tailored messaging. Communication strategies should differ by audience. Shareholders need to hear about financial metrics and value creation. Employees need to understand what the transaction means for their roles and future. Preparing audience-specific messaging in advance enables more effective crisis response.
• Buyer alignment. When selling, particularly in industries with significant employee populations, engage potential buyers in discussions about leak prevention. Help them understand that leaks undermine their ability to present themselves effectively as the new owner and motivate the workforce. Aligning interests can reduce intentional leaks from the buyer side.

Optimizing seller preparation

One often-overlooked factor in diligence timeline is seller readiness. Many sellers enter processes unprepared, lacking organized information and clear data room strategies.

• Pre-launch preparation. Time invested organizing information before launching a process pays dividends. Well-prepared data rooms enable buyers to move more quickly and efficiently.
• Curated information. Simply uploading every document is not helpful. A transportation deal that includes every individual land permit for a long road network creates noise rather than insight. Thoughtful curation focuses buyer attention on material information.
• Controlling the timeline. Sellers who invest in preparation can better control the diligence timeline, reducing the time buyers need for analysis and keeping deal momentum.

The promise and challenge of AI in M&A diligence

Artificial intelligence represents the next frontier in M&A process optimization. While excitement about AI's potential is widespread, actual implementation remains in early stages.

Three key AI applications

• Deeper insights. AI can process unstructured data including voice, video, and natural language to extract strategic and valuation insights that would be difficult or impossible to gather manually. This enables more comprehensive understanding of targets.
• Automation. AI can automate labor-intensive, repetitive tasks such as contract review, report generation, and initial document analysis. This frees professionals to focus on higher-value analytical work.
• Forecasting and prediction. AI can help predict outcomes based on regulatory changes, technological developments, and potential customer or competitor reactions. This enhances strategic decision-making.

Current state of adoption

Most organizations remain in experimental phases:

• Efficiency applications. Early use cases focus on time-saving tasks like transcribing management presentations or generating first drafts of limited-scope reports.
• Contract review. Law firms are exploring AI platforms that can review large contract sets, identifying key provisions and issues much faster than manual review. For example, analyzing 50 customer contracts for specific terms and risks could be reduced from 50 hours of junior lawyer time to minutes.
• Shadowing approach. Organizations are testing AI outputs against traditional methods before relying on them, similar to the cautious approach to self-driving cars. Trust must be built before AI becomes a primary tool.

Barriers to broader adoption

• Confidence gap. While practitioners understand AI's potential applications, skepticism remains about making decisions based on AI-generated information. The gap between understanding capabilities and trusting outputs must be bridged.
• Testing and validation. Organizations need frameworks for testing AI tools on real deals, likely running parallel processes initially to validate accuracy and reliability.
• Evolving sophistication. Current applications focus on basic efficiency gains. More sophisticated uses in forecasting and strategic analysis remain largely aspirational.

The consensus among M&A professionals is that AI adoption will accelerate significantly over the next five years. The question is not whether AI will transform diligence processes, but how quickly organizations can build the trust and frameworks necessary to leverage its full potential.

Practical recommendations for deal success

Based on a decade of data and insights from experienced practitioners, several recommendations emerge:

• Invest in preparation. Whether buying or selling, time spent preparing before launching formal processes pays dividends in efficiency and outcomes.
• Maintain competitive tension. Keep diligence timelines under control to preserve deal momentum and competitive dynamics. Extended processes often signal problems.
• Build focused teams. Prioritize the right expertise over team size. More participants create coordination overhead that can outweigh benefits.
• Leverage technology strategically. Virtual data rooms, video collaboration, and emerging AI tools enable more efficient processes when used thoughtfully.
• Plan for contingencies. Have response strategies ready for potential leaks and other disruptions, even if you hope never to use them.
• Set clear materiality thresholds. Focus attention on what truly matters rather than pursuing comprehensive review of immaterial items.
• Embrace virtual engagement. The shift to distributed teams and virtual interaction is permanent. Organizations that optimize for this reality will have competitive advantages.
• Monitor the timeline. Be conscious of how long diligence is taking. Extended timelines often indicate underlying issues that need to be addressed.

Looking forward

The M&A landscape will continue evolving. Regulatory complexity is unlikely to decrease. Information volumes will keep growing. New areas of diligence focus will emerge.

Success will belong to organizations that combine technological leverage with disciplined process management. AI and other tools will help manage information overload, but human judgment, strategic thinking, and relationship building will remain central to deal success.

The expansion from 124 to 203 days in average diligence periods over the past decade need not continue at the same pace. As AI tools mature, as professionals become more adept at virtual collaboration, and as best practices for managing complex, distributed diligence processes become more established, the trend may stabilize or even reverse.

The key is maintaining focus on what truly drives deal value while leveraging technology to handle the expanding universe of information and requirements that modern M&A demands. Organizations that master this balance will be best positioned for success in the decade ahead.