One of the most powerful principles of systems thinking is that the structure of a system determines the patterns of behavior we observe over time. Trying to change behavior without altering structure is like treating symptoms without curing the cause.
Before addressing the specific case of the smallpox epidemic among the Aztecs, it is important to introduce the basic epidemiological model known as SIR (Susceptible – Infected – Recovered). This model helps explain how an infection spreads through a population over time by classifying people into three main categories:
Susceptible (S): Individuals who have not yet been infected but are at risk.
Infected (I): Individuals who have contracted the disease and can transmit it.
Recovered (R): Individuals who are no longer contagious, either because they have developed immunity or have died.
This article explores how the technique of normalization enables system dynamics models to begin in equilibrium, allowing hidden feedback structures to surface clearly. Using the story of People Express, it shows how the clash—or harmony—between visible decisions and invisible dynamics can define a company’s destiny. Financial results are revealed as deeply tied to service capacity, reputation, and employee engagement. Scaling wisely, it argues, requires more than growth—it requires systemic clarity.
One of the most powerful principles of systems Este artículo explora el principio fundamental del pensamiento sistémico que establece que la estructura de un sistema determina su comportamiento. A través del caso del programa estadounidense TANF (Asistencia Temporal para Familias Necesitadas) —que ofrece apoyos económicos, alimentos básicos y servicios asociados— se ilustran tres configuraciones estructurales distintas que generan comportamientos radicalmente diferentes. Este análisis está orientado a propósitos educativos y muestra cómo una comprensión profunda de las estructuras permite intervenir de manera más efectiva tanto en sistemas sociales como organizacionales.
The prey reproduces exponentially (αx) unless subject to predation. The rate of predation is the chance (βxy) with which the predators meet and kill the prey.
Predator
dy/dt = δxy - γy
The predator population growth δxydepends on successful kills and the reproduction rate; however, delta is likely be different from beta. The loss rate, an exponential decay, of the predators {\displaystyle \displaystyle \gamma y}γy represents either natural death or emigration
