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rear-view mirror. What are the conditions that would have to exist for driving a car that are analogous to the assumptions made when using exponential smoothing?
2. What capability would an organization have to have to not need forecasts?
3. When a new business is started, or a patent idea needs funding, venture capitalists or investment
bankers will want to see a business plan that includes forecast information related to a
loss
4. Discuss how you would manage a poor forecast.
5. Omar has heard from some of his customers that they will probably cut back on order sizes in the
next quarter. The company he works for has been reducing its sales force due to falling demand and
he worries that he could be next if his sales begin to fall off. Believing that he may be able to convince his customers not to cut back on orders, he turns in an optimistic forecast of his next quarter
sales to his manager. What are the pros and cons of doing that?
6. Give three examples of unethical conduct involving forecasting and the ethical principle each violates.
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- Two independent methods of forecasting based on judgment and experience have been prepared each month for the past 10 months. The forecasts and actual sales are as follows:arrow_forwardThe following are sales revenues for a large utility company for years 1 through 11. Forecast revenue for years 12 through 15. Because we are forecasting four years into the future, you will need to use linear regression as your forecasting method. Note: Enter your answers in millions. YEAR 1 2345 5 6 7 8 9 10 11 Period 12 13 14 15 REVENUE (MILLIONS) $4,865.7 5,072.3 5,507.7 5,738.2 5,495.4 5,198.7 5,087.0 5,111.5 5,559.7 5,740.4 5,868.4 Forecastarrow_forwardThe following table shows predicted product demand using your particular forecasting method along with the actual demand that occurred: FORECAST ACTUAL 1,480 1,530 1,380 1,480 1,680 1,580 1,730 1,780 1,630 1,680 Compute the tracking signal using the mean absolute deviation and running sum of forecast errors. Note: Negative values should be indicated by a minus sign. Round your "Mean Absolute Deviation", "Tracking Signal" to 2 decimal places and all other answers to the nearest whole number. Period Forecast Actual Deviation RSFE Absolute Deviation Sum of Absolute MAD TS Deviation 1 1,480 1,530 -50 -50 50 50 50.00 -1.00 2 1,380 1,480 -100 -150 100 150 75.00 -2.00 3 1,680 1,580 100 -50 100 250 83.33 -0.60 4 1,730 1,630 100 50 100 350 87.50 0.57 5 1,780 1,680 100 150 100 450 90.00 1.67arrow_forward
- K Following are two weekly forecasts made by two different methods for the number of gallons of gasoline, in thousands, demanded at a local gasoline station. Also shown are actual demand levels, in thousands of gallons: Week 1 2 3 4 Forecast Method 1 0.95 1.05 0.97 1.20 Actual Demand 0.68 1.05 0.96 1.00 Week 1 2 3 4 Forecast Method 2 0.82 1.21 0.88 1.17 The MAD for Method 1 = thousand gallons (round your response to three decimal places). Actual Demand 0.68 1.05 0.96 1.00 Save Darrow_forwardThe most naive forecast can is quite valuable in leading to an organization’s success because it is most widely understood by senior managers. True or Falsearrow_forwardDic 2 - Time Series Analysis and F eBook Problem 6-01 (Algorithmic) Consider the following time series data. Thm Week 1 2 3 4 5 6 Value 20 13 15 11 19 13 Using the naïve method (most recent value) as the forecast for the next week, compute the following measures of forecast accuracy. a. Mean absolute error. If required, round your answer to one decimal place. b. Mean squared error. If required, round your answer to one decimal place. c. Mean absolute percentage error. If required, round your intermediate calculations and final answer to two decimal places. % d. What is the forecast for week 7? If required, round your answer to two decimal place.arrow_forward
- Can you please solve all parts of the question manually. Thank you!arrow_forwardThe worksheet Hudson Demand Case Data in MindTap provides the number of visits over one year from January to December (52 weeks). Chart the data and explain the characteristics of the time series. How would you forecast future demand for customer visits? What criteria will you use to determine a “good” forecast? What methods would you use, and why? What is your final recommendation with respect to a forecasting method? Note:- Do not provide handwritten solution. Maintain accuracy and quality in your answer. Take care of plagiarism. Answer completely. You will get up vote for sure.arrow_forwardGive typed explanation Part 2: Using exponential smoothing, the forecasted demand for period 5 using the smoothing constant determined in image= ?arrow_forward
- ontrast the reactive and proactive approaches to forecasting. Give several examples of types of organizations or situations in which each type is used.arrow_forwardThe following table shows the actual demand observed over the last 11 years: Year 1 2 3 4 5 6 7 8 9 10 11 Demand 6 8 4 7 11 7 13 12 10 13 8 This exercise contains only parts b, c, and d. Part 2 b) Using the 3-year moving average, provide the forecast from periods 4 through 12 (round your responses to one decimal place). Part 3 c) Using the 3-year weighted moving average with weights 0.10, 0.30, and 0.60, using 0.60 for the most recent period, provide the forecast from periods 4 through 12 (round your responses to two decimal places). Part 4 d) Mean absolute deviation for the forecast developed…arrow_forwardThe following table shows the actual demand observed over the last 11 years: Year 1 2 3 4 5 6 7 8 9 10 11 Demand 7 9 6 10 12 7 12 12 9 9 8 Part 2 Using exponential smoothing with α = 0.30 and a forecast for year 1 of 6.0, provide the forecast from periods 2 through 12 (round your responses to one decimal place). Part 3 Provide the forecast from periods 2 through 12 using the naive approach (enter your responses as whole numbers).arrow_forward
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