What is deep-tech valuation and how does it differ from SaaS?
Short Answer
Deep-tech (hardware, biotech, physics) valuations require longer payback horizons, higher risk adjustment, and often government/regulatory validation, unlike SaaS's rapid time-to-revenue.
Full Explanation
Deep-tech (semiconductors, battery tech, aerospace) has fundamentally different economics than SaaS. Differences: 1) time-to-revenue (5-10 years vs. SaaS 1-2 years), 2) capital intensity (£50M+ R&D before first revenue, vs. SaaS £2-5M), 3) regulatory risk (approval timelines, safety certifications, government contracts), 4) manufacturing scale (unit economics depend on volume — marginal cost drops dramatically at scale but startup may be uneconomical). Valuation implications: deep-tech discount rates are 20-30% (vs. SaaS 12-20%) because of execution risk and long development timelines. Time-to-profitability might be 10 years instead of 3. This favours revenue multiples over EBITDA multiples (EBITDA will be negative for 8 years in a deep-tech scenario). For intangible asset valuation: deep-tech relies heavily on IP (patents, trade secrets, regulatory approvals). Valuation methods: Cost Approach (how much to build this technology?) and Greenfield (how long to commercialise?) are more relevant than Relief from Royalty (no comparable licences exist). For founders raising Series A for deep-tech, realistic timelines and risk profiles are important: investors understand deep-tech development is long; mis-representing it as SaaS-speed growth destroys credibility.
Try It Yourself
Related Questions
Fintech valuations emphasise regulatory status, customer lock-in (payment networks), and data assets, with higher discou...
High customer concentration (top customer >20% of revenue) is a major valuation discount for B2B SaaS — contract quality...
Deep tech (AI, biotech, hardware, quantum) valuations depend heavily on proof-of-concept validation, IP strength, patent...
Want to see these concepts in action?
Discover how the Opagio Growth Platform puts intangible asset theory into practice.