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Author: Eyal Eckhaus, posted on 6/24/2010. in category Logistics

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Abstract: The increased competition and sophistication of consumer demand has forced companies to optimize operations. The company’s agility in response to consumer demand is key to its success, and the ability to predict the demand is critical for effective supply chain management. This article is the first in a series of four articles that outline popular techniques of forecasting demand, designed to meet the needs of both the student and the logistics professional. Purchasesmarte.com also provides some free hands-on utilities for experiencing these techniques.

The increased competition and sophistication of consumer demand has forced companies to optimize operations. The company’s agility in response to consumer demand is key to its success, and the ability to predict the demand is critical for effective supply chain management. This article is the first in a series of four articles that outline popular techniques of forecasting demand, designed to meet the needs of both the student and the logistics professional. Purchasesmarte.com also provides some free online hands-on tools and utilities for experiencing these techniques.

1. Introduction: importance of demand predictions

With the increase in competition, increasingly sophisticated consumer demand, and continuously changing environment, companies are forced to improve their operations. The company’s agility in response to demand has been identified as a key competitive strength, requiring aggressive focusing on supply chain management [1].

In order to properly manage customer needs, forecasting demand is invaluable, and is a key factor affecting success [2]. Obtaining information, such as demand and price, has always been a major commercial objective. Demand information affects production scheduling, inventory control, and delivery plans, while price information affects buyer allocation of purchasing quantities, which in turn affects demand. Demand information is therefore a key factor in supply chain management, with the objective of better matching supply and demand to reduce costs of inventory and stockout, while distorted demand and price information may cause supply and demand mismatches [2].

2. Inventory control and forecasting approaches

Good knowledge about demand enables vendors to maintain minimal inventory levels. Therefore, demand forecasting is a key aspect of inventory control. There are two basic forecasting approaches: assessing future market requirements, and using demand history [3].

Assessing demand requires knowledge about customers, products, and some background conditions that are evaluated by customer surveys and market studies. One method of determining customer demand is assessing potential sales; conversion factors calculated as an expected average demand by item can be a good estimate. Historical forecasting is a basic tool for inventory control that is best used while monitoring environment changes that may require readjustment for result accuracy. Historical forecasting methods are based on mathematical manipulation of historical data [3].

One of the most simple and popular techniques of historical forecasting, is the moving average.

3. The moving average forecasting technique

This is a common forecasting method because it’s simple to apply and understand. It is most successful where the demand fluctuates widely, making it difficult for sophisticated methods to identify demand trends, but can be as easily used when demand exhibits a basic pattern [4]. It is popular for determining market trend changes [5] and is commonly used as a basis for more sophisticated techniques [6]. The shortcoming of the technique is that it doesn’t respond well to changes, it attaches equal importance to all periods, and requires a large amount of data to calculate the average each time [2].

This is performed by calculating the average demand for a constant number of past observations. Example: if we have the following history of demand of 5 months, and define the moving average for 3 months:

Table 1. Example for 5-month demand