Companies often utilize Mergers and Acquisitions (M&A) to enhance value or capabilities. A recent survey by a Big 4 consultancy revealed 47% of CFOs aim for M&As to drive growth this year. However, increased deal activity also brings multiple challenges. M&As are risky, making value preservation vital. Executives often commit to ambitious synergy goals during initial planning, which can be difficult to achieve. Business leaders are thus trying to leverage technology to modernize their approach to M&As. But before we dwell into how technology can reshape M&A, let us first understand different phases of a M&A lifecycle. The M&A lifecycle typically includes the following steps:
Technology has already revolutionized valuation, due diligence and integration phases of the M&A lifecycle, playing a pivotal role in the success of a transaction. 69% of global executives already employ data analytics for M&A deal analysis. In due diligence, advanced software automates the review of vast legal, financial, and operational data, expediting the assessment of risks and critical information. During negotiations, collaboration platforms and virtual data rooms facilitate efficient communication and information sharing. Post-merger integration becomes smoother with the assistance of project management tools and communication platforms, enabling teams to coordinate efforts seamlessly and realize synergies. Finally, data analytics tools provide valuable insights for post-merger evaluation by measuring KPIs against initial projections, aiding in identifying areas of improvement. However, it's essential to recognize that despite tech's widespread influence, the deal sourcing phase remains reliant on human expertise, investment banker’s network and industry knowledge, as finding the right target often demands a human touch and an in-depth understanding of market dynamics.
However, deal sourcing partners such as GrowthPal, are at the forefront of this movement and use advanced data analytics and cutting-edge machine learning algorithms to revolutionize deal sourcing assessment, to increase the probability of successful transactions.
This article explores the evolving role of technology in M&A deal sourcing. We delve into various aspects, including the changing landscape of deal sourcing, the use of data analytics to identify potential targets, and the impact of AI and machine learning. Learn more as we highlight the benefits and practical applications of embracing technological advancements in different M&A strategies.
In traditional deal sourcing methods in M&A, businesses primarily relied on personal networks, industry conferences, and professional intermediaries such as investment banks or brokers. These methods involve building relationships, attending industry events, and relying on word-of-mouth referrals to identify potential acquisition targets. For example, executives leverage their personal connections within the industry to gather information about potential targets.
In hiring an investment banker for business expansion, incentives are crucial in determining the banker's motivation for achieving the best outcome. It's important to consider that a banker's incentives may contradict yours, if not being paid to represent you as most Investment bankers take mandates from sell-side. This conflict of interest can negatively impact your outcome as an organization. Investment bankers often prefer sell-side assignments due to the higher likelihood of completing transactions and receiving fees. By focusing solely on the sell side, bankers avoid favoring any specific buyer mandates.
Additionally, companies would conduct manual research and analysis to evaluate the financial performance, market position, and strategic fit of potential targets. Companies use research platforms to identify potential acquisition targets by applying relevant filters, such as company revenue, employee size, service or product offerings, and geographical presence. However, the data on these platforms is often inaccurate, missing, or outdated, which makes it difficult to shortlist and screen potential targets.
While these methods have been effective to some extent, they often lack efficiency and scalability. These methods also mean that you are missing out on targets outside your or the Investment Banker’s network as well as targets who are opportunistically looking for acquisitions but are unaware that you are on the lookout. The introduction of technology and data analytics has disrupted these approaches, enabling businesses to leverage advanced algorithms and AI tools for faster and more data-driven deal-sourcing processes.
According to a survey conducted by Deloitte of 500 business leaders, more than 80% of the respondents believe that data analytics would play a bigger role in mergers and acquisitions in the future. One of the fundamental drivers of this evolution is the rise of technology and its integration into deal-sourcing processes. The advent of powerful data analytics tools, machine learning algorithms and artificial intelligence has transformed the way deals are sourced, screened, evaluated, and executed. These tools enable dealmakers to efficiently process vast amounts of data, identify potential targets based on specific criteria, and generate actionable insights, all with increased speed and accuracy.
Instead of manually sifting through piles of information, companies can now leverage advanced analytics to extract meaningful insights from complex datasets. By applying machine learning algorithms, dealmakers can identify patterns and trends that may not be immediately apparent to the human eye. This data-driven approach allows for more accurate and objective decision-making, reducing the risk of overlooking critical information.
Disruptive deal sourcing combines readily available data across research platforms and online databases like Traxcn, Crunchbase, Owler, Apollo, etc. with advanced algorithms to build a highly rich, curated and qualified top funnel of targets. By utilizing such platforms and leveraging AI/ML models, dealmakers can access a wider pool of potential targets, overcome geographical limitations, and streamline the deal-sourcing process. With access to rich datasets and sophisticated analytical models, dealmakers can not only get access to a much wider pool of targets for acquisitions and strategic investments but they can also uncover valuable insights and patterns that were previously hidden - and all of this at just a fraction of the cost of hiring an Investment banker. Disruptive deal sourcing platforms like GrowthPal can boost your Corporate Development team’s productivity 3x and save their efforts multifold.
Data driven insights not only help in identifying attractive investment opportunities but also in assessing the potential risks and synergies associated with a transaction. By leveraging data and analytics, dealmakers can make more informed decisions and increase the likelihood of successful outcomes.
The rise of big data and sophisticated analytics has given dealmakers the ability to uncover valuable insights that were previously hidden. By analyzing the available data thanks to the digital footprint companies leave in the current technology era, market trends, and industry benchmarks, dealmakers can gain a deeper understanding of a target company's performance and potential. This insight goes beyond traditional financial metrics, allowing for a more comprehensive assessment of the risks and synergies associated with a transaction.
The application of data and analytics in deal sourcing allows wider access to a potential target from different geographies which was not possible before. It also enhances the decision-making process. Dealmakers can make informed judgments based on quantitative evidence rather than relying solely on intuition or gut feelings. By considering a wider range of factors and evaluating multiple scenarios, dealmakers can better assess the viability and potential outcomes of a deal. This data-driven approach increases the likelihood of successful transactions and reduces the chances of costly mistakes.
Finding targets through internal networks and recommendations restricts your capacity to have the broadest market perspective. The development of technology has enabled organizations to use a new, "disruptive" formula for deal sourcing: "DATA x TECHNOLOGY + ANALYST TEAM." This deal sourcing formula, powered by GrowthPal, combines data, technology, and human expertise to provide Corp Dev teams with a continuous pipeline of qualified targets.
The formula starts with a rich, comprehensive and intelligent database of 2Mn+ companies across tech-enabled sectors and geographies. This database is a highly curated database of startups and new-age businesses, collated from over 60 data sources. It provides intelligence on these companies, including their private financials, growth metrics, and competitive landscape.
At the second level, an advanced AI/ML algorithm is leveraged to scan the entire universe of startups and new-age businesses to find matching targets in accordance to your inorganic requirements. It is at this level that the platform is able to find all the matching targets under the sun against your mandate in accordance with your target’s revenue, employee size, geographic presence, technology skillsets, or other parameters. This layer brings the shortlist into thousands of potential targets. But how do you know which of these targets are keen on getting acquired i.e., the founders have the intent to exit?
This is where the final screening by a dedicated team of analysts is done. The last mile screening and shortlisting is done by the analyst team that reaches out to these matched targets to validate the data and intelligence on your behalf. They speak with the interested founders directly to gauge their intent for acquisitions or strategic investments. A rigorous process allows us to deliver only "Ready to Transact" leads directly in your inbox with advanced data & intelligence on potential targets for your review & approval to highly improve the probability of a successful transaction.
The advent of big data has revolutionized the deal-sourcing process. Companies now have access to a wealth of information from various sources, including market data, financial reports, industry reports, and social media. By harnessing the power of big data analytics, dealmakers can identify potential targets based on specific criteria, such as revenue growth, market share, customer demographics, and competitive positioning.
Big data and advanced analytics is used by businesses like GrowthPal to find possible targets for deals faster with higher accuracy. GrowthPal employs a large database of over 2 million companies and leverages the power of extensive and diversified information to increase the efficacy and efficiency of the target discovery process.
Accurate and comprehensive data is paramount in deal sourcing. Companies need reliable and up-to-date information to assess potential targets accurately. This information is often not available on online and research platforms, and it can be invaluable for assessing the financial health and strategic direction of a potential target. Technology enables the collection, analysis, and validation of vast amounts of data, ensuring the accuracy and completeness of the information used in the deal-sourcing process. Target details like their revenue, revenue by customers, revenue by geographies, technological skills team-wise, active projects, service or product offerings, team size, geographic presence, cash flow, etc. are very important while shortlisting targets. Unavailability of these data points or inaccurate data can often result in unwanted targets sipping in your pipeline which might consume a lot of your team’s bandwidth. These data points can also help dealmakers identify potential risks and opportunities associated with targets, mitigating the chances of making ill-informed decisions.
In conclusion, the role of technology in deal sourcing is evolving rapidly. The use of data analytics, AI, and machine learning is becoming increasingly common, as businesses look for ways to improve the efficiency and effectiveness of their deal-sourcing processes. These technologies can help companies to identify potential targets more quickly and accurately, and to assess their financial health and strategic fit more thoroughly. Companies like GrowthPal exemplify the synergy between data-driven technology platforms and human analysts thereby increasing the probability of a successful transaction as they are able to mitigate a lot of risks with their rigorous three layered screening process. To learn more about the data driven recommendation engine, contact us.
Your email address will not be published. Required fields are marked *