What is information delay?

An information delay is the gap between something changing in the real world and the decision maker acting on a perception of it. It comes from measurement time, reporting cycles, and the habit of averaging recent data. It matters because decisions based on old information can overshoot or arrive too late, which causes cycles and instability.

How it works

The usual way to model it is exponential smoothing. The perceived value moves toward the actual value by a fraction each period: change in perception = (actual − perceived) / delay time. A short delay tracks the truth closely, while a long one lags and smooths out sudden jumps. This is a form of system delay, and it is separate from the physical delay of goods moving along a pipeline.

Information delays are a main cause of oscillation in systems with balancing loops: a manager sees last quarter's sales, reacts, and by the time the reaction takes effect conditions have changed. They also hide the early signs of overshoot and collapse. Reducing the delay, with faster reporting or leading indicators, often helps more than working harder at the response.

Example

Say real weekly demand jumps from 100 to 120 units. The planner's perception uses a delay of 4 weeks. After week 1 perception is 100 + (120 − 100) / 4, which is 105. After week 2 it is 108.75, after week 3 it is 111.6, and after week 4 it is 113.7. The planner is still 6 units behind a month later and has under-ordered about 50 units in total. This is an illustration with round numbers.

How to model it in Machinations

Use a Register for actual demand and a Pool for perceived demand, fed by a Source whose rate is a formula: actual minus perceived, divided by the delay time. Chart the two lines. Play, step the actual demand with a Lever, and change the delay time in another Lever to see the lag.