“Everybody talks about the art of M&A. And I get it, I'm not denying it…but I think our industry truly lacks the science/the lessons learned that we could transfer to others and say, ‘Hey, why don't we standardize this? Why don't we know that these are certain things that you should look out for in a deal, and approaches that you can take to make sure deals go smoother?’” - Kison Patel, CEO of M&A Science
In this Expert Insights Series interview, Jon Thompson hosts Kison Patel, Founder and CEO of M&A Science and DealRoom. M&A Science is a community of progressive practitioners committed to refining the M&A processes. The platform is renowned for its virtual roundtables, annual summits, and a popular podcast with a 50K+ following. DealRoom, under the M&A Science umbrella, offers a comprehensive M&A lifecycle management platform. This innovative software, alongside the M&A Science Academy, equips professionals with training and resources to excel in their roles.
Kison's journey in M&A began with the creation of DealRoom software in 2011, laying the foundation for what M&A Science would become. His contributions to the field also include his book, Agile M&A, which outlines an agile framework for M&A execution and is a testament to his understanding of the complexities and nuances of M&A transactions. Prior to these endeavors, Kison was part of the Forbes Technology Council and served as a partner at Transatlantic Investment and Advisory, a boutique M&A firm.
Jump to a Section:
- Taking a Scientific Approach to M&A
- M&A Data Insights and Performance Metrics
- The Role of Command Rooms and Virtual Data Rooms
- AI in M&A - Data Management for the Next Decade
Taking a Scientific Approach to M&A
While acknowledging the inherent art involved in M&A – characterized by the nuanced and experiential aspects of deal-making – Kison believes a more empirical and standardized approach is possible.
M&A, often perceived as a field driven by intuition and experience, has significant potential for systematization, and Kison believes the lessons learned through hard-won experience should be distilled into a standardized set of practices and principles.
By identifying key factors and metrics that contribute to successful deals, M&A teams can develop a common knowledge base. This shift towards a science-based methodology is not about undermining the importance of the 'art' aspect – the creativity and negotiation skills that are crucial in deal-making. Rather, it's about complementing these with a robust framework that can guide decisions and strategies more effectively.
“When you buy a company, you don't know anything about it (you may think you do, but you really don't). And you will get really far and actually sign LOI without actually knowing a lot about that company… If you can take a project management approach to be very iterative, like having these deliverables in not only the diligence report, but just how we're going to integrate this company, how we're going to extract value out of it… If you're running an Agile process, you can deliver far better results.”
With this outlook, M&A teams can not only improve their current practices but also contribute to the evolution of the field, making it more efficient, reliable, and predictable.
M&A Data Insights and Performance Metrics
“When you're working on a deal, and you feel like it's hard and a pain in the ass to get the data - that starts souring the relationship. And I feel like that's what ends up triggering not doing the deal. The more access you get, the more you can get your analysis and get comfortable doing the deal.” – Kison Patel
When it comes to M&A, the significance of high-quality, well-organized data cannot be overstated. It’s crucial for presenting compelling narratives that can increase the value and speed of a transaction. As Jon puts it, “clean, comprehensive data facilitates faster sales at higher valuations.”
Data provides insights into the dynamics of a deal, enabling stakeholders to understand not only the financials but also the operational, cultural, and strategic fit.
Real time data insights allow for measuring performance metrics throughout the M&A journey. From the initial stages of identifying potential targets to the final stages of post-merger integration, performance metrics help to monitor progress, identify potential risks, and ensure that the deal stays on track. These metrics are often tailored to the specific objectives of the transaction, providing a clear picture of how well the deal is aligning with the strategic goals of stakeholders.
In the post-merger phase, data aids in the integration of the entities. It enables management to align processes, systems, and cultures, and to track the realization of synergies that were identified during the due diligence phase. In essence, data acts as a guiding light through the process of merging two entities.
The Role of Command Rooms and Virtual Data Rooms in M&A
“You want to have one central place, a single source of truth. And something designed for running an M&A process. I've seen way too many deals utilizing Excel, email, or series of PowerPoints cobbled together to run the M&A process. That's a very old school way of doing M&A. If you're emailing an Excel tracker, back and forth… this is 2023, you should see a therapist and get some help because that is highly inefficient.” – Kison Patel
In the landscape of mergers and acquisitions, a 'command room' is essential. DealRoom, an M&A lifecycle management platform, serves as a centralized hub for pipeline management, strategic decision-making, and data management, essential for the efficient execution of M&A activities.
Additionally, FirmRoom, a virtual data room by M&A Science (and similar BI platforms), are transforming the way M&A transactions are managed. They provide secure, cloud-based repositories for sensitive data, facilitating seamless collaboration and information sharing among stakeholders. The use of these tools signifies a shift from traditional, manual data handling methods to more agile, technology-driven approaches.
Artificial Intelligence in M&A - Data Management for the Next Decade
“Look at M&A - it's slow moving. Step one, get people off Excel. Step two, we can look at AI. So, I see a lag, like a 5–10-year lag for a lot of the cool things you'll see in other industries before it hits M&A.” – Kison Patel
Kison and Jon discussed a slow adoption of AI within the M&A sector, projecting a delay of approximately 5-10 years before its full adoption.
This prediction underlines the cautious, yet inevitable, embrace of advanced technologies in an industry traditionally reliant on more conventional methods. Additionally, Kison highlights skepticism within the industry, “The M&A finance world and people in corporate finance, are hyper skeptical about AI. More than any industry I know of - super skeptical.”
While there may be immediate opportunities to streamline and templatize processes (e.g., distilling a diligence summary report), it will likely be a while before AI disrupts the industry due to the time it will take to build up and train data within a private environment.
Connect with Kison and M&A Science
About Blue Margin
Blue Margin increases enterprise value for private equity-backed, mid-market companies by serving as their fractional data team. We advise on, build, and manage data platforms. Our strategy, proven with over 300 companies to-date, expands multiples through data transformation, as presented in our book, The Dashboard Effect. Download your copy here and get weekly insights on our podcast.