Last week during one of Serac’s internal team meetings, I wrote the question “Does this scale?” on the whiteboard. For context, we were talking about streamlining internal operations generally and how we can consistently add value to our portfolio companies specifically. For example, at any point in time at least 30-40% of our portfolio companies (port cos) are raising capital. We asked ourselves how efficient it is for us to make one-to-one introductions for our port cos to outside investors. It’s not difficult to do with a concentrated portfolio but will likely be less efficient as the portfolio grows. Instead, is it better for us and our portfolio companies if we teach them how to run a streamlined fundraising process so they can tactically and strategically source and attract the right investors for themselves? We concluded that the best long-term solution is a combination of both—providing investor intros and teaching, with the latter of the two being easier to scale.
The interesting part about operating a business that invests in other businesses is navigating the uni-directional flow of data and people. The world is flooded with and has access to data about everything—even useless information. Our ability to measure anything we desire can be useful, but it can also be a massive distraction at the same time. Sometimes having too much data and relying on it too much can cause us to devalue the benefit of human intuition, connection and relationships.
According to an article published by Madeline Shi, Senior Private Equity Reporter at Pitchbook, ‘AI is helping accelerate private equity dealmaking, but not necessarily making it better.’ The investment bankers she interviewed in the article stated that the automated tasks in their due diligence processes generate more questions, but the questions don’t provide deeper insights. The consensus was that AI is a helpful tool to scan more deals, but it hasn’t replaced the “actual deal-making process” (source).
The danger of relying solely on LLMs that source data from public data lakes is the slow degradation of human intellect and a company’s competitive advantage. Steven Bartlett said on one of his podcast episodes that AI will eventually (and maybe inevitably) push society to the mean or average part of the statistical bell curve. The simple example he gave was that if you take someone who is a very poor writer, that person can use AI to vastly improve their writing. This person instantly goes from very bad to average. On the other hand, if you take someone who is already a great writer, AI will radically change (or suggest changes) to their writing that puts them on par with everyone else. The last thing a great writer wants is to go from great to average.
I believe it’s the same in business. Companies that overly rely on data and the outright removal of the human touch in their processes run the risk of becoming “average” because the customer experience suffers. In the book, Unreasonable Hospitality, the author (Will Guidara) said that at times the restaurant he managed struggled with providing exceptional customer service and staying profitable as a business because they refused to compromise giving every customer a world-class dining experience, which was costly. He and his team eventually figured out how to achieve both—exceptional service and profitability—but it was not easy and it did not happen overnight.
In the same vein, I’m convinced that in this rapidly evolving AI-driven future, the companies that win will be those that never lose sight of the importance of the customer experience. Using technology to enhance a customer’s experience is great. In contrast, using technology solely to acquire more customers and giving them a sub-par experience is bad. In the first scenario, customer growth will likely be slower, but long-term profitability per customer will likely be higher and customer attrition will be significantly lower. In the second scenario, customer growth will likely be faster, but profitability per customer will be lower and attrition will be higher.
Finding the balance between using data and automation and maintaining a focus on the customer experience is and will always be the defining characteristic of the next generation of great companies.
So, back to my original question—”Does this scale?” Perhaps the question is not “Does this scale?” but “Should this scale?” I believe the simple answer is “yes” and “probably not.” Any process that does not detract from the customer experience, yes; scale it and automate the heck out of it. On the other hand, any process that detracts from the customer experience, do not scale it. At the end of the day, the customer experience is everything. My hope is that in this AI-driven paradigm that we are living in, we never lose sight of that.
