Where is There Massive Cost Take-Out Opportunity?
How can we identify industries with high human decision making costs?
It was established that the current output of humans in the knowledge economy is decision making. How is the economic value going to be created via AI?
To understand where AI has the potential to take out significant costs, we first need to identify industries where human decision making constitutes a substantial portion of overall costs.
G&A Lens
Theory: General and Administrative (G&A) expenses, which often include the costs of human decision making, can serve as a useful indicator.
Industries such as finance, healthcare, consulting, logistics, and retail all have high G&A percentages, often ranging between 15% to 25% of revenue. The human component in these industries typically includes strategic decision making, planning, managing complex projects, or customer engagement.
Sales Lens
Theory: Sales involves significant costs due to customer acquisition, outreach, and relationship management.
Industries such as consumer packaged goods, retail, pharmaceuticals, technology, and consulting all have high sales spend, often ranging between 10% to 25% of revenue. These industries rely heavily on direct customer engagement, market differentiation, and aggressive client acquisition strategies, which drive higher sales and marketing costs.
Communication Complexity Lens
Theory: Communication complexity arises when multiple departments need to collaborate.
Industries such as healthcare, finance, logistics, and technology have high communication complexity, often accounting for 5% to 10% of revenue1.
Regulatory Compliance Lens
Theory: Compliance costs are high in industries with heavy regulatory burdens due to the need for meticulous reporting and monitoring. AI can automate compliance checks, reduce manual auditing efforts, and ensure adherence to regulations.
Other Lenses: High Process Complexity, High Decision-Making Complexity, High Customer Service/Sales
Which industries rank highest under each lens?
Note: This is a very high level pass; I have more detailed analysis I will share overtime
Drivers are not MECE or similar order of magnitude
https://avasant.com/report/communications-system-support-staffing-ratios-2023/