Piermont, part 1 of 1
When companies get into trouble
Behind the numbers in a distressed deal, there are employees, customers, lenders and an owner.
Context
In summer 2025 I was an M&A and restructuring summer analyst at Piermont, a boutique investment bank, working mostly on industrial and healthcare companies. The role came from someone I had first cold-emailed as a freshman and kept in touch with.
The problem
At GreensLedge, the companies had mostly been loans in a pool. At Piermont they were specific companies, and several of them were in trouble. A business under pressure has less time and fewer options, so every analysis has to answer a practical question: what can actually be done, and who does it affect?
What I did
A sale under pressure
The main deal was a sell-side process for a distressed industrial-services company with about $30 million of revenue. I identified more than 10 potential buyers and analyzed five comparable distressed sales. I broke down about $5 million of costs, traced the company’s EBITDA trend, and looked closely at customer concentration: its top three customers made up about 65% of revenue.
- about 65% Top three customers
- about 35% Every other customer
During the process I also tracked more than 50 due diligence requests:1 who had asked what, who owed the answer, and what was still open.
A refinancing
Separately, I worked on a distressed healthcare company carrying about $50 million of debt. I built three refinancing scenarios and benchmarked them against more than 10 precedent refinancings.
Research the team could reuse
Pitch preparation kept starting from scratch. I built more than five reports covering over $40 billion of North American M&A and restructuring activity, and more than 25 comparable companies and precedent transactions. I also researched tariffs, supply chains and friendshoring,2 organized loan and lease data across multiple properties, and put together comparables for industrial real estate tied to electric vehicles.
What I learned
Customer concentration of 65% is a number in a model. It’s also three relationships an entire company depends on.
Piermont was the first time I really felt that the numbers in a spreadsheet belonged to real companies: employees who wanted to keep their jobs, customers deciding whether to stay, lenders deciding how patient to be, and an owner whose company was being sold.
The most valuable work on a live deal wasn’t always the most sophisticated. Keeping track of what everyone was waiting for mattered as much as the model. And by the end of the summer I noticed I was most engaged by the parts of the work that touched how a business actually ran, not the transaction itself.