Mid-Cap Companies and Their Private Equity Sponsors are Finally Ready to See Their Own Data

Mid-Cap Companies and Their Private Equity Sponsors are Finally Ready to See Their Own Data

I have been working with private equity-backed companies and private equity deal teams for almost 25 years. For the last 20, only a small subset of management teams were both interested in extracting real data and insights from their systems and willing to invest the resources, time, and effort in the process. Or they said, they’d like to do it, but don’t have anyone on the team who could take on the challenge.

Now, the tide is turning and everyone seems to be interested, and more willing to make the investment. If they don’t have someone in Ops, Sales, or the CFO’s office who has the in-depth knowledge to lead it, they are more comfortable with some trusted hands leading the way to accomplish these tasks in a manner that teaches their team how to learn, implement, and transfer the knowledge.

The Stax process has always been fast-paced to gather insights and gain quick wins; all to develop a light tech layer so the client can easily keep it going - whether in the initial stages of value creation, mid-ownership, or exit/IPO planning. We have done it for sector and company forecasting, sales and marketing, product and customer profitability, optimization of location businesses, and FP&A to name a few of the practical applications. The process is a bit different for each, as are developing KPIs, working with client teams, and ultimately building the leave behind and training for teams. But the core technical needs and experiential requirements are consistent.

We find the need to be creative about data sourcing (it is everywhere), be vigilant on data cleansing, be both exhaustive and critical when analyzing data, and create lots of cycles for reviewing data with your analytics and cross-functional client teams, and industry experts – early, mid, and late stages. And all along the way, stick with the client to see how they run the operation and what will make the results actionable.

We generally get the client’s initial reads within 6 weeks, deep answers in 8, deploy a built-in analytics platform to the client within 3 months and ramp up training in 4. Just enough time to go from one board meeting to answers by the second to full implementation by the third, and culturally a more data-driven company within a year.

What do I think has changed? Maybe people see and hear more about it from colleagues, they are more worried about the competition, they have someone on their team interested in learning about this because it is so career valuable. I also see a generational shift occurring overall in portfolio ops. Equity sponsors are now hiring data scientists so that they have someone internal who can talk the talk with a specialized consulting firm like Stax. More people have just seen an example and in many cases, the COO or the CFO has a team that can really help get the data and has an interest in bringing this type of learning to their team. All of these are reasons, and as someone who likes data, it’s nice to see these and have more clients willing and able to capitalize on what we have long been providing, but to only a small percentage of private mid-cap companies.

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