🔥𝟗 𝐋𝐞𝐬𝐬𝐨𝐧𝐬 𝐟𝐫𝐨𝐦 𝟗 𝐘𝐞𝐚𝐫𝐬 𝐨𝐟 𝐃𝐨𝐢𝐧𝐠 #𝐓𝐞𝐜𝐡𝐧𝐨𝐞𝐜𝐨𝐧𝐨𝐦𝐢𝐜 𝐀𝐧𝐚𝐥𝐲𝐬𝐢𝐬 𝐟𝐨𝐫 𝐒𝐭𝐚𝐫𝐭𝐮𝐩𝐬🔥

After nearly a decade of working with deep-tech and biotech startups, I’ve seen what separates those who scale successfully from those who struggle. Here are 𝟗 𝐡𝐚𝐫𝐝-𝐞𝐚𝐫𝐧𝐞𝐝 𝐥𝐞𝐬𝐬𝐨𝐧𝐬 every founder and investor should know:

1️⃣ 𝐓𝐡𝐞 𝐛𝐞𝐬𝐭 𝐭𝐢𝐦𝐞 𝐭𝐨 𝐝𝐨 𝐚 𝐓𝐄𝐀 𝐢𝐬 𝐞𝐚𝐫𝐥𝐲, when you still have time to course-correct, not when investors start asking tough questions.

2️⃣ 𝐀 𝐩𝐫𝐨𝐜𝐞𝐬𝐬 𝐭𝐡𝐚𝐭 𝐰𝐨𝐫𝐤𝐬 𝐢𝐧 𝐭𝐡𝐞 𝐥𝐚𝐛 𝐫𝐚𝐫𝐞𝐥𝐲 𝐬𝐜𝐚𝐥𝐞𝐬 𝐚𝐬 𝐞𝐱𝐩𝐞𝐜𝐭𝐞𝐝; yields shift, costs creep up, and bottlenecks appear.

3️⃣ 𝐓𝐞𝐜𝐡 𝐟𝐞𝐚𝐬𝐢𝐛𝐢𝐥𝐢𝐭𝐲 𝐚𝐧𝐝 𝐞𝐜𝐨𝐧𝐨𝐦𝐢𝐜 𝐯𝐢𝐚𝐛𝐢𝐥𝐢𝐭𝐲 𝐚𝐫𝐞 𝐭𝐰𝐨 𝐝𝐢𝐟𝐟𝐞𝐫𝐞𝐧𝐭 𝐭𝐡𝐢𝐧𝐠𝐬, just because you can make it doesn’t mean you can make it profitably.

4️⃣ 𝐒𝐭𝐫𝐨𝐧𝐠 𝐮𝐧𝐢𝐭 𝐞𝐜𝐨𝐧𝐨𝐦𝐢𝐜𝐬 𝐦𝐞𝐚𝐧 𝐧𝐨𝐭𝐡𝐢𝐧𝐠 𝐢𝐟 𝐲𝐨𝐮 𝐫𝐮𝐧 𝐨𝐮𝐭 𝐨𝐟 𝐜𝐚𝐬𝐡, fundraising and financial strategy determine whether you make it to scale.

5️⃣  𝐒𝐨𝐦𝐞 𝐒𝐭𝐚𝐫𝐭𝐮𝐩𝐬 𝐖𝐚𝐧𝐭 𝐕𝐚𝐥𝐢𝐝𝐚𝐭𝐢𝐨𝐧, 𝐍𝐨𝐭 𝐭𝐡𝐞 𝐓𝐫𝐮𝐭𝐡. The best clients are the ones who use TEA to make strategic decisions, not just to impress investors.

6️⃣ 𝐈𝐧𝐯𝐞𝐬𝐭𝐨𝐫𝐬 𝐭𝐚𝐤𝐞 𝐓𝐄𝐀 𝐬𝐞𝐫𝐢𝐨𝐮𝐬𝐥𝐲 𝐰𝐡𝐞𝐧 𝐢𝐭’𝐬 𝐢𝐧𝐝𝐞𝐩𝐞𝐧𝐝𝐞𝐧𝐭; numbers that are “too good to be true” usually are.

7️⃣ 𝐅𝐞𝐞𝐝𝐬𝐭𝐨𝐜𝐤𝐬 𝐬𝐮𝐩𝐩𝐥𝐲 𝐚𝐭 𝐬𝐜𝐚𝐥𝐞, 𝐰𝐚𝐬𝐭𝐞 𝐦𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭, 𝐚𝐧𝐝 𝐬𝐮𝐩𝐩𝐨𝐫𝐭𝐢𝐧𝐠 𝐢𝐧𝐟𝐫𝐚𝐬𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞 𝐜𝐚𝐧 𝐦𝐚𝐤𝐞 𝐨𝐫 𝐛𝐫𝐞𝐚𝐤 𝐚 𝐬𝐜𝐚𝐥𝐞-𝐮𝐩, anticipate them early to prevent costly surprises.

8️⃣ 𝐀 𝐓𝐄𝐀 𝐢𝐬𝐧’𝐭 𝐚 𝐨𝐧𝐞-𝐭𝐢𝐦𝐞 𝐞𝐱𝐞𝐫𝐜𝐢𝐬𝐞; it should evolve alongside the technology, market conditions, and scale-up challenges.

9️⃣ 𝐓𝐡𝐞 𝐦𝐨𝐬𝐭 𝐬𝐮𝐜𝐜𝐞𝐬𝐬𝐟𝐮𝐥 𝐟𝐨𝐮𝐧𝐝𝐞𝐫𝐬 𝐮𝐬𝐞 𝐓𝐄𝐀 𝐟𝐫𝐨𝐦 𝐭𝐡𝐞 𝐛𝐞𝐠𝐢𝐧𝐧𝐢𝐧𝐠.

Would love to hear from other founders and investors, what lessons have you learned about scaling technology? 🚀