Exponentially Growth and Systems Thinking

Every startup and company is obsessed with exponential growth. The key formula defining exponential growth is (1+R)^t , where R is the percentage of growth for each cycle and t is the number of cycles. The (1 + R) implies that we have a cycle where the input gets multiplied (1+R) everytime and this new slightly bigger output is fed back into the system. T is the number of times this cycles happens. T dominates this formula and it is significantly better to have a lower growth rate per cycle but have a huge number of cycles. For instance, a growth rate of 100% for 10 cycles gives 1024 times while a growth rate of 10% for 100 cycles gives an order of magnitude higher return of 13,780 times.

This formula works for one variable but how does it work for systems. Systems have numerous inputs and outputs. Generally, the goal is to optimize one of the output variables. For each cycle, generally one input is the bottleneck as there is a surplus amount of the other variables. Consequently, for each iteration of the cycle, the output of that cycle must help increase the bottleneck by the given rate. As the system develops, different input variables may become bottlenecks due to changes of how the system functions, the growth rate of different input variables, and the marginal utility of how the system functions. The key requirement is that the outputs of the previous cycle help scale the bottleneck by the given rate.