Holland Mountain’s Billy Dix takes a closer look at some of the opportunities for deal teams to leverage data and build competitive advantage.
Deal sourcing in the Private Capital industry is rapidly shifting from a traditional relationship-driven approach to a data-driven strategy. Many firms are considering how to leverage technology to streamline processes and automate repetitive tasks, freeing up time for the deal team to focus on more value-add activities. For firms looking to make the transition to data-driven deal sourcing, how can a robust data strategy help to build competitive advantage?
Making the shift to data-driven deal sourcing
Private Capital deal flow has historically been generated using the power of networks, with investment teams relying upon the quality of their relationships with advisors and intermediaries to bring high quality deals into their pipeline. CRM systems have helped firms better maintain these relationships but increasingly, GPs relying solely on intermediary relationships for originating high quality deals are being left behind.
The traditional deal team has tended to split its time between a number of key responsibilities. Firstly, analysing target companies and data for screening, identifying which deals should move forward in the pipeline. Secondly, working on due diligence and progressing live deals whilst also supporting portfolio operations and value creation. And finally, maintaining industry relationships with advisors, management team talent and peer groups.
A successful data-driven strategy requires a change of approach. Today, firms are under more pressure than ever and must ensure they have robust business systems and processes in place. The CRM system, which is key to building and maintaining relationships between clients and the deal team, should be configured for the needs of the specific firm, with high rates of user adoption, high quality data with clear data ownership, and platform management governance structures. If these aren’t in place already, your firm is operating behind the curve.
Unlocking the power of data
Assuming that a robust CRM system is already in place, the next step a firm should consider taking is to increase its capacity to collect, organise and access data throughout the end-to-end deal pipeline. Firms may need to consider implementing data lakes and warehouses, as well as layering in the technology required to enable deal times to analyse these increasingly important data sets.
Data sets are readily available to support firms wishing to move to a data-driven deal sourcing approach. Solutions such as FactSet, Pitchbook, Gain.Pro, Preqin, Crunchbase and Sourcescrub provide a means of identifying and analysing companies of interest. There are also data sets within the public domain which can be useful to support analysis of potential deals. These public sources include social media reports, website traffic stats, online reviews and feedback, and management team employment histories.
Analysis tools can be developed in-house or procured from the markets so there are decisions to be made in relation to buy, versus a build option. Proprietary information feeding the system is the key point, not the technology itself. The algorithm will be a ‘black box’ which uses both internal and external data. The output should be a higher volume of proprietary deals and better-informed decision making on prioritisation of targets.
Spend your time wisely on value-add activities
To get ahead, firms will need to ensure that they focus the deal team on value-add activities. Elements of the deal process that can be automated or outsourced to third-parties should be, such as identification of ‘sweet spot’ companies, an initial screening of companies based on size, what industry sector, financials, region, transaction data, etc.
Firms that are reliant on manual analysis will start to see a decline in deal rate compared to their data-enabled peers, who have the capacity to handle a larger amount of data relating to prospective deals. By eradicating manual analysis, investment teams can devote their time to analysing targets that have already been pre-screened. Due diligence can also be outsourced to third-party market experts, reporting back to provide summary intelligence for investment teams to analyse.
When it comes to dead deal data and benchmarking, it’s advantageous for firms to track lost and declined deal data, as well as past and ongoing investments. Declined deal data is proprietary and needs to be leveraged as part of a holistic data-driven approach to deal making. This data is key to enable machine learning algorithms to learn from decisions made across the pipeline, rather than just the successful deals. The benchmarking of successful deals that were identified by a system versus those identified through traditional methods will allow firms to better understand which insights are valuable and which are not, and consequently, incorporate this valuable feedback into the algorithms. Only then can the algorithm give you a true and clear picture of opportunities for future deals.
Build incrementally from solid foundations
Future success relies on embracing the shift from sole reliance on networks, to harnessing the power of data alongside existing relationships. Firms wishing to move to a data-driven approach will need to begin by laying the groundwork in order to gather valuable insights from data and to leverage it to its full potential. Achieving a data-driven approach to deal-making is a step-by-step process and a long-term strategy should revolve around the steps shown in the Digital Maturity Scale. Maintaining the integrity of these systems and the data output requires constant feedback. In order to improve effectiveness over time, investment analysts need to assess and provide accurate feedback on the insights being provided.
The goal throughout should be to build valuable insights from data to leverage the deal pipeline to its full potential, thereby increasing the quality and quantity of deals and overall, achieving considerably better returns.
Billy Dix is head of Holland Mountain’s front office practice, working with leading Private Capital investment and investor relations teams. Billy works with firms across all stages of the digital maturity scale, leading engagements to design target operating models and improve business processes, with expertise in managing CRM system selections, implementations, and delivery of managed services.