Cutting Edge Individual Case Assignment, QNT 5160, Fall 2018 Semester
File No. 2 (Monthly Data for 2014 and 2015)
			Actual	Employee
			Call	Head
	Year	Month	Volume	Count	Notes
	2014	Jan	24,015	62,120
	2014	Feb	25,203	62,152
	2014	Mar	23,589	62,138
	2014	Apr	27,454	68,343	Centex corporation acquired 4/1/2014
	2014	May	28,120	68,120
	2014	Jun	28,321	67,987	Dental insurance plan changed effective 7/1/2014
	2014	Jul	29,021	67,956
	2014	Aug	26,954	65,342	Printer division sold to Arconet Corporation 8/1/2014
	2014	Sep	26,456	65,380
	2014	Oct	27,120	65,432	Major tax law changes signed into law by U.S. President
	2014	Nov	26,954	65,423
	2014	Dec	27,321	65,650	Year-end bonuses announced on 12/10/2014
	2015	Jan	26,456	65,620
	2015	Feb	27,450	65,610
	2015	Mar	31,435	75,231	Paxton Enterprises acquired 3/15/2015
	2015	Apr	33,124	75,201
	2015	May	32,432	74,978
	2015	Jun	31,901	75,012	New employee insurance deductions in effect starting 7/1/2015
	2015	Jul		80,000

Use the above excel sheet to answer the below questions

Question 3b (10 points):

Apply Linear Regression to predict call volume from head count using the appropriate Excel template. Assume the headcount in July is 80000. Using this headcount number, show your forecast below and attach the completed Excel template.

Call Volume Forecast for July 2015 (Causal Forecasting based on head count of 80,000): __________

Question 3c (10 points):

Calculate the Mean absolute deviation value of the Exponential Smoothing model (Question 3a) and the Average Estimation Error of the Linear Regression model (Question 3b). Explain the difference between these two values.

Mean absolute deviation of Exponential Smoothing model, alpha=0.5: ______________________

Average Estimation Error for Causal Forecasting model based on headcount: __________________

Explanation of the difference in values:

Question 3d (20 points):

Considering your answers to Questions 3a, 3b and 3c and all the factors that have been described above, prepare your best forecast for July 2015. Show your forecast value below and explain and justify how you came up with this forecast. Finally, provide your recommendations to Mark on how to modify forecasting process and improve its accuracy.

Call Volume Forecast for July 2015 (My forecast): _________________