Sigma & Diglore
Sigma Sigma
Diglore Diglore
Diglore Diglore
I’ve been mapping the logistics of the Maya’s irrigation systems—think of it as a pre‑industrial supply chain optimization. How do you quantify the ROI of such ancient infrastructures?
Sigma Sigma
ROI for ancient irrigation is a simple equation: net benefit divided by total input. In the Maya case, measure water throughput in cubic meters per day, then translate that into agricultural output—tons of maize or beans per hectare. Convert that yield into market value based on current commodity prices, then subtract the capital cost: labor hours, stone, stone quarrying, labor, time lost to irrigation. Finally, divide by the number of years the system remained functional. That gives you a yield‑per‑investment ratio. If the system ran for 200 years and delivered an average of 3,000 tonnes of maize a year at $1.50 per tonne, that’s $4.5 million in gross revenue. Subtract construction and maintenance—say $300,000—and you’re left with $4.2 million. Divide by the original investment of $200,000 and you get a 21‑fold return. That's the ROI, expressed in a metric you can compare against any modern project. If the numbers don't line up, the system is inefficient and needs a redesign—no room for idle speculation.
Diglore Diglore
That’s the textbook approach, but you’re treating a 12th‑century hydraulic network like a 21st‑century corporation. First, you’re assuming a static commodity price of $1.50 per tonne of maize—yet the Maya were trading cacao, jade, and other goods, not selling maize on a global market. Second, you’ve lumped “capital cost” into a single figure of $300,000; that’s a modern estimate of labor and stone. What were the actual labor days, the skill level required, the seasonal constraints? And the 200‑year lifetime you’re quoting—did the system actually run that long without major overhauls? If it only operated effectively for 50 years, the ROI shrinks dramatically. I’d start by reconstructing the actual throughput, the seasonal variation, and the social cost of labor before we talk about dollars. The math looks neat on paper, but the variables are a mess in the real world.