Demand Planning / Karl Knapp.

Format:

Book

Author/Creator:

Knapp, Karl, author.

Series:

SAGE skills: Business.

SAGE skills: Business

Language:

English

Subjects (All):

Demand (Economic theory).

Physical Description:

1 online resource.

Place of Publication:

Los Angeles, CA : SAGE Publications, Inc., 2024.

Summary:

Companies need to predict the future to be able to plan for it. Prediction is difficult but essential for an effective operation. Organizations use forecasting methods to predict a wide variety of eventualities. These include customer preferences, social trends, demographic trends, and technological advancements, but the most common and critical forecast businesses make is of demand. The need to forecast the future is based on the simple fact that responding to either increases or decreases in demand takes time. EaziBikes is like any company in that it needs to forecast demand in order to plan. There are several ways and elements involved when attempting to make a forecast. In many small to midsized organizations, forecasting is based on the opinions of either key sales force members or executives. This type of forecasting, based on opinion, is called qualitative forecasting. While it can be useful, its quality depends on the experience and judgment of those on whose opinion it is based. Before we get into the specifics of a more rational approach, we need to consider the worst possible approach so that you don't repeat it. A common approach to qualitative sales forecasting is to solicit the professional opinions of those closest to the markets and customers, the salespeople. If you have experienced and knowledgeable salespeople, they often have excellent insights into the direction of the markets they serve. As such, asking their opinion and forecast for sales can be a good idea. For an organization that has salespeople representing various regions or districts, having the salespeople individually create a forecast and then summing them together is called composite forecasting. Composite forecasts can be quite accurate because even if one salesperson's forecast is incorrect, the errors tend to cancel out when taken together. Those that underestimate sales are offset by those that overestimate them. Given knowledgeable salespeople, this can be a useful approach. Two problems can occur, however. First, if the salespeople are working on commission, especially if they receive a bonus for exceeding their quotas, there can be a built-in bias for them to underestimate the forecast. With a lower forecast-and lower goals-they can more easily earn bonuses. Even if the salespeople are unbiased in their forecasts, there is a second problem. Often management doesn't like the forecasts provided by the salespeople. Management often has an incentive to increase sales, especially if the company is publicly traded. Publicly traded companies are notorious for their relentless drive to increase revenue and increase profits. Shareholder focus is often on short-term profits. This creates an environment where managers are driven to relentlessly increase sales. Managers' incentives may cause them to reject the salespeople's forecasts and substitute their own. This is especially the case if the salespeople provide forecasts that aren't in line with shareholder expectations or management goals. This can be the case even if the forecasts are credible and accurate. Given the built-in incentives that can work at cross-purposes, managers can pull rank and change the forecast to meet their own goals. This is the worst possible case. Asking for input from the salespeople creates the expectation that they will be listened to, especially if they have tempered their bias to create an accurate representation of future sales. If you are going to ask for employee input and opinion, it should be valued and used. If not, any future requests for input will be met with either scorn or outright rejection. In this Skill we focus on forecasting methods that are more reliant on data than opinion. While opinion-based forecasting is often used, it should at the very least be supplemented by forecasting based on historical data or factors that are correlated with prediction of demand. The best companies in the world base their decisions on facts and data wherever possible. In this Skill we examine the historical sales of EaziBikes' three product lines, serving adults, young adults, and kids. We will use these data to create forecasts to be used in the creation of an operations plan.

Notes:

Description based on publisher supplied metadata and other sources.

ISBN:

1-0719-5151-3

9781071951514

OCLC:

1456885538