Shota Ishii joined me on The PE Data Guy to talk about what happens when PE-backed manufacturers cannot answer a basic question: which products are actually making money? He has spent two decades building systems that give companies a clear picture of where their cash goes, and we got into why that gap exists and what it takes to close it.

We covered working capital, data architecture, and what mid-market companies need to do right now to get their data in order before AI can do anything useful for them. Shota shared an example of a $400 million metal company that found $80 million in working capital improvements once they had the right transaction-level visibility.

Chapters:

1. 00:00 - Understanding Capital Efficiency
2. 06:42 - The Journey to Becoming a Robo CFO
3. 20:55 - Amazonifying Legacy Industries: The Need for Real-Time Data
4. 31:51 - The Importance of Data Strategy in Mid-Market Companies
5. 35:18 - The Future of AI in Mid-Market Companies

Guest Information

Shota Ishii is the founder of Proximo Tech, where he works with PE-backed manufacturers on capital efficiency and working capital. He studied applied physics and AI and has a background in quantitative finance, hedge funds, and corporate innovation. He is based in Japan and can be found on LinkedIn.

Companies Mentioned

1. Proximo Tech
2. Moody's
3. Blackstone Credit
4. Amazon
5. Snowflake
6. Databricks
7. AWS
8. Google Cloud
9. Salesforce
10. OpenAI

Websites Mentioned

1. Proximo Tech
2. LinkedIn
3. Snowflake
4. Databricks
5. AWS
6. Google Cloud

Key Takeaways

1. Clean, granular data at the transaction level is the foundation for improving working capital.
2. The cost of not building a data platform grows over time as competitors who do build one move faster.
3. Data is a company asset. Without structure and governance around it, AI cannot make use of it.
4. Mid-market companies often underestimate how affordable modern data tools actually are.