By: David P. Anderson, James D. R. O’Neill, and John C. F. Gershon, Department of Economics, University of Maryland The most common problem faced by logistics firms is the inability to predict the impact of their activities on future demand.
As a result, they cannot forecast the future, but rather the present and forecast it to the point where they can predict its effect.
In order to improve their ability to predict future demand, the business must first understand the impact on the present.
However, a key element of this understanding is that, if the business is to make informed decisions about its operations, it must be able to model the effects of those decisions, so that it can make informed choices about its future.
The basic premise is simple: the impact and timing of a decision depends on the outcomes of all the possible alternatives.
For example, suppose a trucker decides to buy a new vehicle and then decides to sell it to a customer.
The trucker can then buy the vehicle at the current price and sell it at a higher price at a later time.
Similarly, if a company decides to invest in a new facility, then the company can invest in that facility and then sell it in the future.
If the trucker and the company want to maximize the future gains, the trucking and the factory need to be able both to anticipate the future demand and to know how much demand will be generated by those future investments.
If these assumptions are true, then if a logistics firm chooses to invest a certain amount in a particular facility, it will generate a certain number of future sales of vehicles that are equivalent to the amount of its current investment.
In other words, the firm’s decisions to invest or not will depend on the future outcome of the facility investments.
In a future post, I will discuss how to implement this assumption, which is also called the “expectational model.”
The next post will explore how to incorporate this assumption into the prediction of future demand into the business’ decision-making.
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