Question

National Scan, Inc sells radio frequency inventory tags. Monthly sales for a seven-month period were as...

  1. National Scan, Inc sells radio frequency inventory tags. Monthly sales for a seven-month period were as follows:

Month Sales (000 units)

Feb.       21

Mar.      20

Apr.       17

May       22

Jun.       20

Jul.         24

Aug.       22

  1. Plot the monthly data on a sheet of graph paper.
  2. Forecast September sales volume using each of the following:

(1) The naive approach

(2) A five month moving average

(3) A weighted average using .60 for August, .30 for July, and .10 for June

(4) Exponential smoothing with a smoothing constant equal to .20, assuming a a March ­forecast of 19(000)

(5) A linear trend equation

  1. Which method seems least appropriate? Why? (Hint: Refer to your plot from part a.)
  2. What does use of the term sales rather than demand presume?

PLEASE LIST ALL STEPS

Homework Answers

Answer #1

(a)

Graph:

(b)

Forecast

1) Naive Approach - In this, forecast is equal to actual value of previous period which is Aug Sales.

Hence, Sep = 22

2) Five month moving average = Average of last 5 months = Average (Apr,May,Jun,Jul,Aug) = (17+22+20+24+22)/5 = 21.00

3) Weighted average = 0.6*22 + 0.3*24 + 0.1*20 = 22.40

4) Exponential smoothing:

Apr = Mar forecast + 0.2*(March actual - March forecast) = 19 + 0.2*(20-19) = 19.2

May = 19.2 + 0.2*(17-19.2) = 18.76

Jun = 18.76 + 0.2*(22-18.76) = 19.41

Jul = 19.41 + 0.2*(20-19.41) = 19.53

Aug = 19.53 + 0.2*(24-19.53) = 20.42

Sep = 20.42 + 0.2*(22-20.42) = 20.74

(c)

The least appropriate method is the naïve approach. Naïve approach assumes that the next period demand is the same as pervious period. In such case, we should get a flat line on the graph sheet. However, we see that it is not the case. Thus the least appropriate method is the naïve approach.

(d)

Sales and demands are similar. However sales presumes that these numbers will be sold irrespective of the demand. This means the demand could be more than this values but the numbers of sales will be achieved.

ALTERNATIVE METHODS FOR (a) and (b)

a) The graphical plot of the actual data is shown below. Use the grids to create the label and mark the intervals. Then plot the points. The image on your graph sheet should look similar to the image below.

b) Forecast for the various methods are shown below

  • Naïve approach takes the value of the previous period.
  • The five month moving average takes the average of the previous five periods as the forecast value for current period
  • The weighted average value is obtained by multiplying the respective weights against the previous months
  • The exponential smoothing uses the formula
  • F(t) = alpha*actual(t-1) + (1 – alpha)*forecast(t-1)
  • In order to calculate linear trend we need to use linear regression. And use Y=b + aX to forecast the data. Here we have used the regression option from data analysis to find the value of b = 18.85 and a = 0.5.

The formulas for each of them are shown below

Know the answer?
Your Answer:

Post as a guest

Your Name:

What's your source?

Earn Coins

Coins can be redeemed for fabulous gifts.

Not the answer you're looking for?
Ask your own homework help question
Similar Questions
National Scan Inc. sells radio frequency inventory tags. Monthly sales for a seven-month period were as...
National Scan Inc. sells radio frequency inventory tags. Monthly sales for a seven-month period were as follows: Month Sales (000) Units Feb 19 Mar 15 Apr 12 May 28 Jun 17 Jul 24 Aug 28 b. Forecast September sales volume using each of the following: SHOW WORKS!!!! (1) The naive approach. (2) A five month moving average. (3) A weighted average using .60 for August, .10 for July, and .30 for June. (4) Exponential smoothing with a smoothing constant equal...
National Scan, Inc., sells radio frequency inventory tags. Monthly sales for a seven-month period were as...
National Scan, Inc., sells radio frequency inventory tags. Monthly sales for a seven-month period were as follows: Month Sales (000)Units Feb. 17 Mar. 20 Apr. 14 May. 22 Jun. 21 Jul. 25 Aug. 29 (3) Exponential smoothing with a smoothing constant equal to .10, assuming a March forecast of 15(000). (Round your intermediate forecast values and final answer to 2 decimal places) Forecast _______
National Scan, Inc., sells radio frequency inventory tags. Monthly sales for a seven-month period were as...
National Scan, Inc., sells radio frequency inventory tags. Monthly sales for a seven-month period were as follows:      Month Sales (000)Units   Feb. 15   Mar. 15   Apr. 10   May. 27   Jun. 15   Jul. 23   Aug. 28     b. Forecast September sales volume using each of the following:      (1) A linear trend equation.(Round your intermediate calculations and final answer to 2 decimal places.)     Yt thousands        (2) A five-month moving average. (Round your answer to 2 decimal places.)        Moving...
National Scan, Inc., sells radio frequency inventory tags. Monthly sales for a seven-month period were as...
National Scan, Inc., sells radio frequency inventory tags. Monthly sales for a seven-month period were as follows:      Month Sales (000)Units   Feb. 16   Mar. 19   Apr. 11   May. 22   Jun. 19   Jul. 24   Aug. 21     b. Forecast September sales volume using each of the following:      (Fill in the blanks) (1) A linear trend equation.(Round your intermediate calculations and final answer to 2 decimal places.)     Yt __________thousands        (2) A five-month moving average. (Round your answer to 2...
this question how The Naïve approach =20 National Scan, Inc., sells radio frequency inventory tags. Monthly...
this question how The Naïve approach =20 National Scan, Inc., sells radio frequency inventory tags. Monthly sales for a seven-month period were as follows Monthly Sales (000 units) Feb……... Mar……. Apr…….. May……. June……. July…….. Aug…….. 19 18 15 20 18 22 20 a) Plot the monthly data on a sheet of a graph paper b) Forecast September sales volume using each of the following (1) A linear trend equation (2) A five-month moving approach (3) Exponential smoothing with a smoothing...
The monthly sales for Yazici Batteries, Inc., were as follows: MONTH SALES January 20 February 21...
The monthly sales for Yazici Batteries, Inc., were as follows: MONTH SALES January 20 February 21 March 15 April 14 May 13 June 16 July 17 August 18 September 20 October 20 November 21 December 23 Plot the monthly sales data. Forecast January sales using each of the following: Naive method. A 3-month moving average. A 6-month weighted average using .1, .1, .1, .2, .2, and .3, with the heaviest weights applied to the most recent months. Exponential smoothing using...
Trends and Regression Calculate the Linear Trend Line for the following data Using the Liner Trend...
Trends and Regression Calculate the Linear Trend Line for the following data Using the Liner Trend Line, what sales do you forecast for July 2016 (plot the values) Using the Linear Trend Line, what sales do you forecast for July 2017 (plot the values) Comment on the quality/reliability of your forecasts - what concerns should you have regarding the accuracy of your linear trend line forecast? Select an alternative Trend Line that you think best fits the historical data. Make...
Consider the following data: Monthly Profit of a Gym Month Jan-12 Feb-12 Mar-12 Apr-12 May-12 Jun-12...
Consider the following data: Monthly Profit of a Gym Month Jan-12 Feb-12 Mar-12 Apr-12 May-12 Jun-12 Jul-12 Aug-12 Sep-12 Profit ($) 6,400 6,153 5,454 5,277 5,395 6,198 7,919   6,364 6,068 Step 3 of 5: Determine the exponentially smoothed forecast for the next time period using a smoothing constant, α, of 0.35. If necessary, round your answer to one decimal place.
Month time Sales Jan 1 200 Feb 2 203 March 3 210 Mar 4 218 April...
Month time Sales Jan 1 200 Feb 2 203 March 3 210 Mar 4 218 April 5 230 May 6 245 Jun 7 346 Jul 8 376 Aug 9 389 Sep 10 231 Oct 11 200 Nov 12 189 Dec 13 155 Jan 14 178 Feb 15 193 Mar 16 192 Apr 17 201 May 18 212 Jun 19 367 Jul 20 391 Aug 21 401 Sep 22 204 Oct 23 201 Nov 24 183 Dec 25 145 Jan 26...
Year Month Return Year Month Return 2006     Jan 3.95 2008     Jul 3.29 2006     Feb 3.77 2008...
Year Month Return Year Month Return 2006     Jan 3.95 2008     Jul 3.29 2006     Feb 3.77 2008     Aug 4.62 2006     Mar 5.29 2008     Sep 4.81 2006     Apr 3.77 2008     Oct 5.16 2006     May 4.47 2008     Nov 3.69 2006     Jun 5.2 2008     Dec 5.15 2006     Jul 3.9 2009     Jan 5.29 2006     Aug 4.33 2009     Feb 3.19 2006     Sep 4.41 2009     Mar 3.89 2006     Oct 5.14 2009     Apr 4.48 2006     Nov 3.24 2009     May 5.27 2006     Dec 4.13 2009     Jun 3.93 2007     Jan...
ADVERTISEMENT
Need Online Homework Help?

Get Answers For Free
Most questions answered within 1 hours.

Ask a Question
ADVERTISEMENT