"Old school" dealmaking depended on networking and relationships to both source and close deals. But knowing the right people isn't enough anymore. It's time for new school thinking.
Companies "including private equity firms "are increasingly adopting data-driven decision-making to transform all areas of their business. It gives dealmakers the ability to more strategically, objectively, and proactively drive investment opportunities.
But what is data-driven decision-making? And how do you ensure it becomes a consistent best practice at your firm? Let's dive in.
Just like it sounds, data-driven decision-making is the practice of using data to guide and inform decisions. Effective data-driven decision-making depends on the quality, breadth, and depth of information available. However, the best decisions are usually made by examining and integrating data from multiple relevant sources.
Most data-driven decisions in dealmaking revolve around a firm's investment thesis. By utilizing data, firms are able to better develop their initial investment criteria, find target companies that fit, and refine both their theses and portfolio over time.
Data-driven decision-making also makes it much easier to manage and address many of the other important challenges and opportunities that firms face. Let's take a look at some examples.
Example #1
It's time to find a new addition to your portfolio. Luckily, one of your team members comes back from a conference with what he considers a hot lead. Everything seems right: The contact is eager and the conversations the two had were productive.
You decide to do a little digging and pull up some data on the target company. From what your data source tells you, half their staff has left in the past 6 months and revenue is down. Worse still, it looks like the founder has been shopping for a while and several other firms have already turned down a potential deal. Whether you decide to move forward with the opportunity or not, you now can approach the conversation in the right way to make the best decision for your firm.
Example #2
One day, a team member approaches you with the name of a company. You've never heard of them, but from what information she gives you, they're a profitable, bootstrapped company with a new patent and positive signs for the future. The best part? They fit your investment thesis perfectly and fill a gap in your firm's portfolio.
How did she find such an opportunity? By inputting your firm's requirements into a private company intelligence platform that scoured its database for potential fits. Now your team can start the process of vetting and securing this "hidden gem" before any other firm catches a glint!
Example #3
Your firm acquired a high-tech company last year, and so far, things have gone swimmingly. The board is even starting to think about taking it public. But all of a sudden, an alert goes off. Things are starting to take a turn for the worse: revenue is down, employee attrition is climbing, and so is customer churn.
All these data signals point to something awry. After further investigation, you find the problem. Luckily, your firm was able to catch the downward trend and address it before it was too late.
As these examples show,being data-driven has many benefits and advantages for private equity firms.While there's really no downside to becoming a data-driven firm, here are five of the main benefits of data-driven decision-making for dealmakers:
Operational efficiency: The old adage is right: "Time is money." Using data to drive decision-making means your firm will spend less time on the wrong tactics and more time on things that you know work because you have the data to prove it.
Higher IRR: With data comes insights that you can use to tune your investment theses to pinpoint the most profitable deals with the highest propensity to close. Focusing sourcing efforts on these targets results in more transactions and higher IRR.
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More consistent performance: Gone are the days of waiting for intermediaries to pass you a deal that may or may not align with your firm's needs. When your shop becomes fluent in data, you can proactively identify and systematically vet opportunities, which translates to more accurate forecasts and predictable outcomes
Deeper and stronger relationships: Being able to spot top targets early on in their life cycles and knowing precisely when to reach out allows dealmakers to build trust and rapport with companies over time. Once they're ready to transact, these firms are top of mind.
Advantage over your competition: Consistent data-driven decision-making leads to deep domain expertise and unique market perspectives. Not only does this type of proprietary advantage help firms identify the right deals faster and earlier than the competition, but it's also appealing to current and potential portfolio companies.
Becoming data-driven requires change. And if you've ever tried to change the way someone works (even yourself), you know it's a difficult endeavor. But when it comes to altering the way people make fundamental decisions and approach deals, failure isn't an option.
This transition must be done in a way that sets your firm up for success from the beginning "without disrupting current business. Here's a 5-step framework to help you implement data-driven decision-making in your private equity firm.
To become a data-driven firm, the entire organization needs to be aligned. Your firm must create a plan for how departments "from accounting to business development and beyond "are going to meet their goals by using data. While this overarching directive must come from the top, success ultimately requires data expertise to determine tactics that map back to your firm's goals, what impact these tactics are expected to have, and how to measure success.
If your firms' stakeholders don't have strong quantitative analysis capabilities, consider hiring a data analyst to help. Hiring a data scientist as your firm becomes more invested in this way of thinking can be the right approach. This blog post will help you decide when it's the right time to bring a data scientist on board.
As we mentioned earlier,data-driven decision making requires data from across multiple relevant sources. But that's not all. Firms must also have somewhere to house and organize this information, as well as the tools to transform data insights into action. For all of these systems to work seamlessly together and effectively support data-driven decision making, dealmakers must place time, effort, and thought into building the right tech stack.
While every tech stack is unique, there are 4 core components every data-driven firm should consider:
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Just because a new paradigm is starting in your firm doesn't mean you have to make sweeping changes. In fact, you shouldn't. Start with collecting a specific set of data for a particular endeavor. Depending on your firm's maturity level, this initial venture may even be as simple as using a private company intelligence platform to find your next investment opportunity.
Once you're able to finish the first project, do a post-mortem and determine what went well and where your teams could improve. Then, iterate with the next project and keep expanding and refining your processes until being data-driven becomes second nature.
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One way to combat the resistance that typically comes with change is by celebrating successes whenever possible. Because you started this process by creating an organizational plan and mapping tactics to important goals for your firm, it should be straight forward to use the data that results from those projects to show how data-driven decision-making is providing value.
The key will be to communicate these successes on a regular basis. Tout the early wins, such as detailing time savings in deal sourcing. Then, consistently reinforce qualitative results such as "this deal could only have been found through data-driven methods" and quantitative ones like "deals driven by data have brought in $3m this quarter." These efforts will help to sway any resistant members of the firm.
For your firm to truly adopt data-driven decision-making you must test and iterate. The entire point of data is to gain clarity and get closer to the correct answer. But just because you make a decision with that data doesn't necessarily mean it's the right path forward. And even once you find the right path, it will eventually need to be reevaluated and updated.
What's important is that no matter what the result of a decision is, you are still getting more data on which to base future decisions. The great success you'll find with data-driven decision-making is that instead of placing your faith in unfounded beliefs or anecdotal evidence, you have undeniable truths that your firm can use to continuously improve and achieve more.
"Old school," opportunistic dealmaking doesn't cut it in today's fast-paced and highly competitive market. Data-driven decision making is no longer optional for firms"it must be understood, embraced, and honed by every person in your organization. Only then will your firm be able to take a strategic, proactive, and differentiated approach to finding and closing deals.
Taking control of your deal flow is possible. To learn more about how data-driven decision making can help and the ways leading firms achieve success, download this free five-step playbook.
