Everything You Need to Know when Running a Factory

An M&A advisor or investment banker helps you run a sale process — they identify buyers, run the auction, and negotiate terms. They cannot change the multiple you receive; they can only optimize the process to achieve the market multiple for a business like yours. ConTech changes the multiple by building the platform layer that shifts your buyer comp set from hardware manufacturers (6×) to software-enabled platforms (12×). The two are not alternatives — they are sequential. ConTech builds the platform and the metrics over a 3-to-5-year period; your banker then runs the process using those metrics to justify a premium multiple. If you hire a banker before you have the platform metrics, you will receive the market multiple for a hardware company. If you build the platform first, you compete for the software-platform multiple.

A CTO or CDO is a headcount solution — you add a senior executive who then needs to hire a team, choose a technology direction, build relationships with vendors, and manage a multi-year roadmap. The median time from CTO hire to production platform is 18–36 months, the fully-loaded cost of a qualified industrial CTO is $300k–$500k per year, and the execution risk is high because few CTOs have both industrial domain expertise and platform-layer building experience. ConTech is a project-based solution with a defined scope, fixed pricing, and a delivery track record. The platform we build can then be handed off to an internal technical lead for ongoing management — you get the platform outcome without the headcount risk and without the 18-month runway before you see anything production-ready.

Generic AI tools are powerful but require your team to know how to prompt them and provide context each time. They have no memory of your workflows, no connection to your ERP, and no understanding of your product catalog or pricing rules. ConTech is configured for your business — it knows your parts, your customers, your pricing, and your document formats. It runs automated workflows that don't require anyone to prompt it — it fires when triggered by an incoming RFQ or a dealer portal submission. For industrial businesses, the difference is between a smart assistant who needs to be briefed on everything versus a trained system that knows your business and runs autonomously within defined guardrails.

Building in-house is theoretically possible and practically very difficult for industrial businesses. It requires: machine learning engineers ($150k–$250k/year each), at minimum 12–18 months to build a production-quality workflow, ongoing model maintenance and infrastructure management, and deep domain expertise in both AI and industrial operations. ConTech gives you a production-grade platform in 6–12 months for a fraction of the cost of one ML engineer's annual salary, with domain expertise already embedded. The 5–10 industrial companies per year that successfully build in-house typically have exceptional CTO or CDO leadership, strong internal data infrastructure, and a multi-year runway to invest. For everyone else, buying is faster, cheaper, and lower execution risk.

AI tools will continue to improve, but so will your competitors' use of them. The companies that are building platform layers now are accumulating the NRR history, recurring revenue percentage, and customer engagement data that will change their valuation comp set in 3–5 years. By the time you start in 18 months, early movers will have 18 months of platform data maturity that is directly visible in their enterprise value. The valuation multiple impact of a platform layer is not primarily about the technology — it is about the demonstrated track record of recurring revenue and customer retention that the platform generates over time. Every month you wait is a month of NRR history you will not have in your data room when your exit process runs.