1. List the elements of a good forecast. Show -The forecast should be timely. -The forecast should be accurate. -The forecast should be reliable. -The forecast should be expressed in meaningful units. -The forecast should be in writing. -The forecast technique should be simple to understand and use. -The forecast should be cost-effective: The benefits should outweigh the costs. 2. Outline the steps in the forecasting process. -1. Determine the purpose of the forecast. 2. Establish a time horizon. 3. Select a forecasting technique. 4. Gather and analyze relevant data. 5. Make a forecast. 6. Monitor the forecast. 3. Describe at least three qualitative forecasting techniques and the advantages and disadvantages of each. -Executive opinions: A small group of upper-level managers may meet and collectively develop a forecast.� It has the advantage of bringing together the considerable knowledge and talents of various managers.� However, there is a risk that the view of one person will prevail, and the possibility that diffusing responsibility for the forecast over the entire group may result in less pressure to produce a good forecast. Salesforce opinions: The sales staff or the customer service staff is often a good source of information because of their direct contact with consumers.� They are often aware of any plans the customers may be considering for the future.� One disadvantage is that they may be unable to distinguish between what the customers would like to do and what they actually will do.� Another is that these people are sometimes overly influenced by recent experiences.� In addition, if forecasts are used to establish sales quotas, there will be a conflict of interest because it is to the salesperson�s advantage to provide low sales estimates. Consumer Surveys: Since it is the consumers who ultimately determine demand, it seems natural to solicit input from them.� The obvious advantage of consumer surveys is that they can tap information that might not be available elsewhere. Disadvantages: A considerable amount of knowledge and skill is required to construct a survey, administer it, and interpret the results for valid information.� Surveys can be expensive and time consuming. � 4. Compare and contrast qualitative and quantitative approaches to forecasting. -Qualitative methods consist mainly of subjective inputs, which often defy precise numerical description.� Quantitative methods involve either the projection of historical data or the development of associative models that attempt to utilize causal variables to make a forecast.� Qualitative techniques permit inclusion of soft (human opinions & hunches) information in the forecasting process.� Those factors are often omitted or downplayed when quantitative techniques are used because they are difficult to quantify.� Quantitative techniques consist mainly of analyzing objective, or hard, data.� They usually avoid personal biases that sometimes contaminate qualitative methods.� 5. Briefly describe averaging techniques, trend and seasonal techniques, and regression analysis, and solve typical problems. Averaging techniques smooth fluctuations in a time series because the individual highs and lows in the data offset each other when they are combined into an average.� A forecast based on an average thus tends to exhibit less variability than the original data.� This can be advantageous because many of these movements merely reflect random variability rather than a true change in the series. 6. Describe two measures of forecast accuracy. -� Three commonly used measures for summarizing historical errors are the mean absolute deviation (MAD), the mean squared error (MSE), and the mean absolute percent error (MAPE).� mean absolute deviation (MAD) is the average absolute forecast error.� mean squared error (MSE) is the average of squared forecast errors.� mean absolute percent error (MAPE)� is the average absolute percent error. 7. Describe two ways of evaluating and controlling forecasts. -A control chart is a visual tool for monitoring forecast errors.� In order for the forecast errors to be judged �in control�, two things must happen.� One is that all errors are within the control limits.� The other is that no patterns, trends, and cycles are present.� A tracking signal is the ratio of cumulative forecast error to the corresponding value of MAD used to monitor a forecast.� It relates the cumulative forecast error to the average absolute error.� The intent is to detect any bias in errors over time. 8. Identify the major factors to consider when choosing a forecasting technique. - The two most important factors are cost and accuracy.� Other factors to consider in selecting a forecasting technique include the availability of historical data: the availability of computer software: the ability of decision makers to utilize certain techniques: the time needed to gather and analyze data and to prepare the forecast; and any prior experience with a technique. What is the use of mean absolute deviation MAD in forecasting?Mean Absolute Deviation (MAD) measures the accuracy of the prediction by averaging the alleged error (the absolute value of each error). MAD is useful when measuring prediction errors in the same unit as the original series[5][6].
How do you use MAD in forecasting?Calculate the mean for the given set of data. Find the difference between each value present in the data set and the mean that gives you the absolute value. Find the average of all the absolute values of the difference between the data set and the mean that gives the mean absolute deviation (MAD).
What role does MAD play in evaluating a forecasting model?MAD measures forecast error in units.
It can, for example, be used for comparing the results of different forecast models applied to the same product.
What is MAD in time series forecasting?MAD. MAD stands for mean absolute deviation, which is the average of the absolute deviations. An absolute deviation is the absolute value of the actual data minus the fitted value (Table 3). The best fitted line should have zero MAD; the larger the MAD, the worse the model.
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