Question

These questions are from Hospitality Managerial Accounting course. Topic: Forecasting Methods

True or False: 1. Moving average can be said to be a type of weighted moving average.

True or False: 2. Trend is a repeating pattern in data.

3. Exponential smoothing method is just like weighted average, except that _______ are determined by a smoothing constant, alpha, and the number of periods considered is infinite.

Answer 1

Some Applications of Forecasting:
Forecasts are vital to every business organization and for every significant management decision.
We now will discuss some areas in which forecasting is widely used.
Sales Forecasting
Any company in selling goods needs to forecast the demand for those goods. Manufactures need to know how much to produce. Wholesalers and retailers need to know now much to stock. Substantially understanding demand is likely to lead to many lost sales, unhappy customers, and perhaps allowing the competition to gain the upper hand in the marketplace. On the other hand, significantly overestimating demand also is very costly due to (1) excessive inventory costs, (2) forced price reductions, (3) unneeded production or storage capacity, and (4) lost opportunities to market more profitable goods. Successful marketing and production managers understand very well the importance of obtaining good sales forecasts.
For the production managers these sales forecast are essential to help trigger the forecast for production which in turn triggers the forecasting of the raw materials needed for production.
Forecasting the need for raw materials and spare parts
Although effective sales forecasting is a key for virtually any company, some organizations must rely on other types of forecasts as well. A prime example involves forecasts of the need for raw materials and spare parts.
Many companies need to maintain an inventory of spare parts to enable them to quickly repair either own equipment or their products sold or leased to customers.
Forecasting Economic Trends
With the possible exception of sales forecasting, the most extensive forecasting effort is devoted to forecasting economic trends on a regional, national, or even international level.
Forecasting Staffing Needs
For economically developed countries there is a shifting emphasis from manufacturing to services. Goods are being produced outside the country (where labor is chapter) and then imported. At the same time, an increasing number of business firms are specializing in providing a service of some kind (e.g., travel, tourism, entertainment, legal aid, health services, financial, educational, design, maintenance, etc.). For such a company forecasting “sales” becomes forecasting the demand for services, which then translates into forecasting staffing needs to provide those services.
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Forecasting in education environment
A good education institute typically plans its activities and areas concentration for the coming years based on the forecasted demand for its different activities. The institute may come out with a forecast that the future requirements of its students who graduate may be more in particular sector. This may call for the reorientation of the syllabus and faculty, development of suitable teaching materials/cases, recruitment of new faculty with specific sector-oriented background, experience and teaching skills. Alternatively, the management may decide that the future is more secure with the conventional areas of operation and it may continue with the original syllabus, etc.
Forecasting in a rural setting
Cooperative milk producers’, union operates in a certain district. The products it manufactures, the production capacities it creates, the manpower it recruits, and many more decisions are closely linked with the forecasts of the milk it may procure and the different milk products it may see. Milk being a product which has a ready market, is not difficult to sell. Thus demand forecasting for products may not be a very dominant issue for the organization. However, the forecast of milk procurement is a crucial issue as raw milk is a highly perishable commodity and building up of adequate processing capacity is important for the dairy. The milk procurement forecast also forms an important input to the production planning process which includes making decisions on what to produce, how much and when to produce.
Ministry of Petroleum
The officials of this crucial ministry have to make decisions on the quantum of purchase to be made for various types of crude oils and petroleum products from different sources across the oil-exporting nations for the next few years. They also have to decide as to how much money has to be spent on development of indigenous sources. These decisions involve/need information on the future demand of different types of petroleum products and the likely change in the prices and the availability of crude oil and petroleum products in the country and the oil-exporting nations. This takes us back to the filed of forecasting.
Department of Technology
The top officials of this department want to make decisions on the type of information technology to recommend to the union government for the next decade. But they are not very clear on the directions which will be taken by this year rapidly changing field. They decided to entrust this task to the information system group of a national management institute. The team leader decided to forecast the changing technology in this area with the help of a team of information technology experts throughout the country. This is again a forecasting problem although of a much different type. This field of forecasting is known as technological forecasting.
Forecasting is the basis of corporate long-run planning. In the functional areas of finance and accounting, forecasts provide the basis for budgetary planning and cost control. Marketing relies on sales forecasting to plan new products, compensate sales personnel, and make other key decisions. Productions and operations personnel use forecasts to make periodic decisions involving process selection, capacity planning, and facility layout, as well as for continual decisions about production planning, scheduling, and inventory.
As we have observed in the aforementioned examples, forecasting forms an important input in many business and social science-related situations.
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6.3 Defining Forecasting:
A forecast is an estimate of a future event achieved by systematically combining and casting forward in predetermined way data about the past. It is simply a statement about the future. It is clear that we must distinguish between forecast per se and good forecasts. Good forecast can be quite valuable and would be worth a great deal. Long-run planning decisions require consideration of many factors: general economic conditions, industry trends, probable competitor’s actions, overall political climate, and so on.
Forecasts are possible only when a history of data exists. An established TV manufacturer can use past data to forecast the number of picture screens required for next week’s TV assembly schedule. But suppose a manufacturer offers a new refrigerator or a new car, he cannot depend on past data. He cannot forecast, but has to predict. For prediction, good subjective estimates can be based on the manager’s skill experience, and judgment. One has to remember that a forecasting technique requires statistical and management science techniques.
In general, when business people speak of forecasts, they usually mean some combination of both forecasting and prediction. Forecasts are often classified according to time period and use. In general, short-term (up to one year) forecasts guide current operations. Medium-term (one to three years) and long-term (over five years) forecasts support strategic and competitive decisions.
Bear in mind that a perfect forecast is usually impossible. Too many factors in the business environment cannot be predicted with certainty. Therefore, rather than search for the perfect forecast, it is far more important to establish the practice of continual review of forecasts and to learn to live with inaccurate forecasts. This is not to say that we should not try to improve the forecasting model or methodology, but that we should try to find and use the best forecasting method available, within reason. Because forecasts deal with past data, our forecasts will be less reliable the further into the future we predict. That means forecast accuracy decreases as time horizon increases. The accuracy of the forecast and its costs are interrelated. In general, the higher the need for accuracy translates to higher costs of developing forecasting models. So how much money and manpower is budgeted for forecasting? What possible benefits are accrued from accrued from accurate forecasting? What are possible cost of inaccurate forecasting? The best forecast are not necessarily the most accurate or the least costly. Factors as purpose and data availability play important role in determining the desired accuracy of forecast.
When forecasting, a good strategy is to use two or three methods and look at them for the commonsense view. Will expected changes in the general economy affect the forecast? Are there changes in industrial and private consumer behaviors? Will there be a shortage of essential complementary items? Continual review and updating in light of new data are basic to successful forecasting. In this chapter we look at qualitative and quantitative forecasting and concentrate primarily on several quantitative time series techniques.
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