View the model
Download the model

A standard approach used in modeling random variables over time is the Markov chain approach. The basic idea is to think of the system as being in one of a discrete number of states at each point in time. The befavior of the system is described by a transition probability matrix which give the probability the system will move to a specified other state from some given state. Some example situations are:

System	States	Cause of Transition
Consumer brand switching	Brand of product most recently purchased by consumer	Consumer changes mind, advertising
Inventory System	Amount of inventory on hand	Orders for new material, demands

Your company is about to introduce a new detergent and you're interested in whether it will clean up in the market. It will be competing against three other existing brands. In this model, we use Markov chain analysis to determine the long-term, steady state probabilities of the system.