Article: Beyond Relationships - A Data-Driven Approach to Sourcing

Summary

Our latest kicker.cloud insights focused on navigating digital transformation in the private finance industry, highlighting key starting points for adopting new technologies. This month, we’ll dive deeper into the topic by exploring the first step in the M&A lifecycle and one of the most critical aspects of M&A professionals' work: sourcing new opportunities. While private finance remains a highly relationship-driven business, we discuss how data can increasingly enhance the sourcing process and empower professionals to expand and strengthen their networks. By leveraging proprietary data combined with AI-driven technologies, professionals can increase their chances of identifying and capturing better targets before their competitors.

Adopting a Data-Driven Approach to Sourcing

In M&A, significant value is created in the early stages of the deal process: sourcing and screening potential targets. Whilst relationships remain crucial for securing deals, M&A teams are recognising the power of data to enhance their sourcing capabilities. Using methods like pattern recognition and AI copilots, professionals can identify opportunities faster, allowing them to spend more time evaluating promising targets as opposed to searching for them. Data-driven insights enable teams to prioritise their pipeline efficiently and focus their efforts where most impactful. Ultimately, a data-driven approach helps M&A teams to get through dealflow faster, and allow for timely decision making during these critical early stages of a deal.

The main objective of a data-driven strategy is to reduce manual searching, automate repetitive data entry tasks, and enhance human decision-making. This involves combining proprietary data, such as communication and performance metrics, with external data sources to generate faster and more accurate insights. Sourcing represents an ideal starting point for a data-driven approach due to the new ways of generating unique insights from internal and external data. The combination of relevant data sources and smart analytics can allow teams to identify opportunities ahead of their competitors, use resources effectively, and increase chances of success.

Today, most M&A teams still manage their pipeline by manually summarising notes, updating statuses, and scheduling meetings. The next frontier in data utilisation will introduce continuously learning AI copilots that assist teams in manual tasks as well as in deeper analysis on why some deals succeed whilst others don’t.

Practical Examples of Data-Driven Sourcing

When beginning to adopt new advanced technologies for sourcing, consider these initial areas where the latest technologies can offer value instantly:

• Finding of relevant targets by utilising internal and external data: Curating a list of potential M&A targets based on various data sources. This list will then be enriched with insights from internal data, resulting in highly relevant and bespoke suggestions for possible M&A opportunities.

• Cultivating existing relationships with copilot features: Outsource your relationship management to self-learning assistants that are always on top of your relationship status and suggest when it’s the right time to make moves.

• Automated initial analysis for screening: Employing targeted analysis from public sources such as financial data and news, whilst also incorporating internal data for automating the initial analysis of a potential target.

The M&A industry is at a pivotal moment. Those who embrace data-driven practices will be better equipped to navigate challenges and capitalise on emerging trends. By taking control of their data, M&A professionals can supercharge their operations by focusing only on value add tasks.

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Author: Eljas Pajamies