Inventory Management Models

Inventory Management Models

Let’s learn more about Inventory Management Models. Inventory management is aimed at deciding the quantity of inputs or resources that need to be arranged, and the time when they need to be ordered, in order to reduce the production costs, in sync to the key requirements. On account of various abnormalities in the production inventory, no particular inventory model is important to the whole variant inventory situations. Therefore, different inventory models have been established to address these specific inventory issues.
An inventory system provides the organizational structure and the operating policies for maintaining and controlling goods to be stocked. The system is responsible for ordering and receipt of goods: timing the order placement and keeping track of what has been ordered, how much and from whom. The system also needs to follow up to answer such questions as: Has the supplier received the order? Has it been shipped? Are the dates correct? Are the procedures established or reordering or returning undesirable merchandise?

The classic inventory model is usually used by organizations to make forecasts on optimum inventory level or for evaluating two or more inventory systems. Nevertheless, inventory models are adopted on the basis of level of uncertainty with lead time or demand situations.

Situation	Demand	Lead time	Type of Model to be adopted
1	Constant	Constant	Deterministic Model
2	Constant	Variable	Probabilistic Model
3	Variable	Constant	Probabilistic Model
4	Variable	Variable	Probabilistic Model

There are two fundamental techniques being employed mostly, to develop inventory reserve estimates, viz. deterministic and probabilistic methods. While deterministic methods involve making a single best estimation of existing inventory reserves on identified engineering, economic and geological information, probabilistic methods utilize the identified engineering, economic and geological information to create a collection of rough stock reserves and their related probabilities. Each categorised inventory reserve indicates the prospect of revival.

The best part about a probability approach is that one can create a model in a better way when provided with values within a bandwidth modeled by an organised distribution density, in comparison to using deterministic figures.

Deterministic models are generally used to depict the optimal inventory of a single item, in the presence of an obscure demand, whereby the inventory builds up at a constant rate to meet an accepted or determined demand. For example, if a contract is received in February with a delivery deadline of December (in a period of 10 months), the product can be manufactured at a rate of 10 per month.

Further, stochastic one time models can also be used for inventory control, when the demand is unknown. These are more realistic models and hence, fetch more relevance, since they take into account factors such as cost of shortfalls, stacking away, arranging for reserves, and accordingly create an optimal inventory plan.

Let us now take hypothetical Deterministic and Probabilistic inventory control conditions:

A deterministic circumstance is basically one whereby the system parameters can be ensured accurately, also referred to as a situation of definiteness as it is known, things will occur as ensured. Further, the information system under consideration should be complete for clear demarcation of parameters. However, such kind of system rarely exists, and if it does, there lies uncertainty most of the times. In a deterministic model, the state of affairs is assumed to be deterministic and hence, a numerical model is produced to optimize on system arguments. As it conjures the system to be deterministic, it indicates that one has complete details about the system.

On the other hand, a probabilistic model depicts an uncertainty situation, which is as a matter of fact more pervasive, yet less comforted. Therefore, people tend to reduce uncertainty. The prototypes of probabilistic inventory comprising probabilistic demand and supply are more applicable in real life situations, though can be troublesome and uncontrollable during analysis.

So, we conclude that in general cases, the suitable inventory plan should be to reduce the costs associated with holding stock of both raw materials as well as finished goods. As for the model to be chosen, it should largely depend on the type of the industry, and you can select to adopt a deterministic or probabilistic model.