Guest Bio
Brian Potter is a senior fellow at IFP and the author of The Origins of Efficiency. He spent over 15 years as a structural engineer and now studies how industries improve, or fail to improve, efficiency over time.
Episode Overview
In this episode of Making Big Shifts, Josh Anderson sits down with Brian Potter to unpack the real mechanics behind efficiency increases. Instead of treating efficiency as a buzzword or a tooling problem, the conversation digs into history, systems, and repetition as the true drivers of cost reduction and performance gains.
Brian shares insights from his background in construction, an industry known for resisting efficiency gains, and contrasts it with sectors that have seen dramatic improvements over time. The discussion connects learning curves, economies of scale, and modern AI tools to practical decisions founders and operators face every day.
Key Takeaways
• Efficiency increases are driven more by repetition than optimization
• Learning curves reduce cost as cumulative experience grows
• Variability creates waste and limits efficiency gains
• Scale amplifies learning only when processes are consistent
• Tools matter, but systems matter more
Favorite Quotes (with timestamps)
“A really important vehicle for making some process more efficient is having a fair amount of repetition.” (07:22)
“The more you do something, the more chances you have to take advantage of economies of scale.” (07:29)
“Costs tend to fall in proportion to the cumulative amount that you’ve done something.” (07:40)
“If you want learning curve improvements, you have to do the same thing over and over again.” (08:20)
Playbook: How to Apply
Step 1: Identify the repetitive core
Audit your operation and isolate the tasks that happen most often. These are the only areas where efficiency increases compound meaningfully over time.
Step 2: Reduce variation before scaling
Variation creates rework, delays, and waste. Standardize inputs, outputs, and handoffs before trying to increase volume.
Step 3: Design for ease of execution
Ask what is easiest for your people, tools, or systems to produce consistently. Efficiency improves faster when execution friction is removed upfront.
Step 4: Scale deliberately
Scale only after repetition is stable. More volume without learning simply multiplies inefficiency.
Subscribe
🎧 Listen to the full conversation with Brian Potter on Making Big Shifts—available on YouTube and Spotify.
Subscribe for more candid conversations with founders and operators rewriting the rules of modern work.
