At the beginning of each year, a sales manager meets with sales representatives to discuss the sales objective for their territory. This year, the sales representative is expected to achieve the prior year's sales plus ten percent. This objective is known as the Multiple Choice payback point. sales quota. return on investment. break-even point. territory's profit.

As a supply chain manager for a company, you are tasked with forecasting the demand for a particular product. To assess the accuracy of your forecasting model, you decide to calculate the Mean Absolute Percent Error (MAPE) for the past seven months. Below is the data representing the actual demand and forecasted demand for each month: Month Actual Demand  Forecasted Demand  1 1000 1100 2 900 1200 3 1300 1400 4 1100 700 5 2000 1700 6 1500 1200 7 1600 1500   What is the Mean Absolute Percent Error (MAPE) for the seven-month period?    Question 1 options:   a)  20.68%   b)  17.66%   c)  18.38%   d)  19.44%

Market Company’s policy is to have 30% of the next month's sales on hand at the end of the current month. Projected sales for August, September, and October are 26,000 units, 21,000 units, and 31,000 units, respectively. How many units must be purchased in September?

Suppose a firm has had the following historic sales figures. Year: 2016 2017 2018 2019 Sales $3,400,000 $4,650,000 $3,300,000 $2,900,000 What would be the forecast for next year's sales using the naïve approach? Answer is complete but not entirely correct. Next year's sales $ 3,550,000 2020 $3,500,000

For Mother’s Day, the handbag buyer planned a point-of-sale promotion at 25% off for straw handbags. Here is a record of what sold during the promotion: 100 handbags with an original retail of $49.00 200 handbags with an original retail of $39.00 Calculate the following: Total markdown in dollars for the promotion. Total sales generated for the Mother’s Day event. Total markdown percentage for the Mother’s Day sale event.

i need the answer quickly

Tasty Bread Company has monthly demand for one of its products as follows: March= 520; April=490; May=550; June=580; July=600; August=420. Compute the three-month moving average for July.

Given the following data, use least-squares regression to derive a trend equation: Period Demand where y Demand and x = Period. 1 10 2 12 3 5 4 13 5 12 6 11 D The least-squares regression equation that shows the best relationship between demand and period is (round your responses to two decimal places):

The 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…

The 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).