Finding Deals by Tracking Deals: How A Data-Driven Approach Can Improve Deal Management

There was a time when the keys to effective deal management were the experience and instincts of the players involved in the deal. Operating by “gut feel” worked well—or, at least, it seemed to since there was no other method to compare it to. 

The tools for ingesting and analyzing data simply weren’t available to firms.

The Deal Management “Game” Has Changed

First, “game” is in quotes because it’s used facetiously here. Deal management is no game, especially since many millions of dollars (and sometimes billions of dollars) are at stake.

Today, successful firms have replaced gut feel with a data-driven approach to deal management. 

They’ve had to for a couple of reasons. First, savvy stakeholders are no longer willing to bet on someone else’s instincts—even if that someone is a highly regarded industry veteran. They want the firms they collaborate with to provide advice that’s based first and foremost on facts.

This isn’t to say that other, qualitative factors aren’t important. A portfolio company founder’s experience and personality, the company’s team chemistry, and other attributes can and should be part of the decision-making calculus. But stakeholders are, understandably, more focused on data today than ever before.

The second reason that Firm A has adopted a data-driven deal management strategy is that Firm B did so months ago. Fail to optimize your operations and you’re effectively handing deals to Firm B (or Firm C, or…). And they’ll gladly take them!

Deal Management and the New Post-Pandemic Reality

The COVID-19 pandemic was another driver behind the move to data-driven deal management. Being unable to meet in-person forced stakeholders to look for other criteria on which to base their decisions, and collecting and analysis of data weren’t slowed at all by the crisis.

In fact, private equity pros who were spending less time on planes and in boardrooms had significantly more time to amass and leverage information, so the flow of data actually accelerated during the pandemic. With firms and stakeholders the importance of easy access to high-quality data, the flow rate will only continue to increase.

Beyond “Big Data”: The Rise of AI, Machine Learning, and Other Tools

The recognition of the vital role that data and deal tracking can play in deal management has been followed by a movement to get more out of that data. Artificial intelligence (AI), machine learning, scoring, and other predictive analytics are enabling firms to anticipate trends and make even better investment decisions.

These additions to the data-driven approach to deal management are having a positive impact in many areas of firm operations, including:

  • Sourcing investments
  • Performing due diligence
  • Choosing targets
  • Monitoring investments
  • Assisting portfolio companies post-investment creating value

And the sources of the data that supports these activities can be surprising. For example, with seed and early-stage companies that don’t have a track record that can be analyzed, some firms are building data models that look at things like social media signals to get a sense of the organization’s potential.

Those signals might previously have been dismissed as irrelevant. But with improvements in how data is collected and analyzed, they may prove to be very useful. Social media signals can also be predictive at the individual level—pointing to product managers, developers, and others who might be interested in starting their own company or who already are planning to do so.

Connecting with them while they’re actively and eagerly looking for strategic partners can open the door to a long and lucrative relationship in some cases. Years ago, these thought leaders and trendsetters would not even be on anyone’s radar until they already had established key relationships.

4 Steps for Developing Data-Driven Deal Capabilities

Data-driven deal management isn’t something that happens overnight. There are four critical steps firms have to take to get there:

  1. Prioritize the acquisition of high-quality data. You can’t succeed with just any information. You’ve got to obtain or develop clean, accurate data. Like they say, “Junk in, junk out.” So, in that sense, having little to no data is probably less damaging than bad data.
  2. Get the right systems and people in place. Outdated data management methods (think shared spreadsheets) have to go. You need the right, purpose-built technology to get value from your data. Similarly, you need team members who either have data management experience or are willing to develop it. It sounds harsh, but the reality is that people who insist that “the old approach to deal management is the best approach” are only going to inhibit your progress.
  3. Continue to leverage industry experience. Adopting a data-driven deal management approach doesn’t mean you should ignore the skills and insights of your team members. Data may be “driving” your approach, but you still need the experience of your people to help with navigation.
  4. Don’t settle for “good enough.” Technology evolves. Companies evolve. Markets evolve. Firms that have optimized their data-driven deal management processes today and then assume they can turn their attention to other initiatives inevitably find that those processes become outdated much faster than they expected. Then they’re playing catch-up. On the other hand, firms that keep a watchful eye on technology, their data sources, and their processes continue to be leaders in their area of expertise. 

Data-Driven Deal Management: A Permanent Shift in the Requirements for Success

The idea of “finding deals by tracking deals” isn’t a fad. It’s a solid strategy that’s here to stay. And the sooner you immerse yourself in data-driven deal management, the sooner you’ll differentiate your firm and move to the front of the pack.

Differentiate With Data
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