February 13, 2024

This exercise provides you the opportunity to apply several concepts you have learned in Module #3 in addition to Excel skills practice. Learning Objectives: ? Identify trends and patter

This exercise provides you the opportunity to apply several concepts you have learned in Module #3 in addition to Excel skills practice.

Learning Objectives:

· Identify trends and patterns by analyzing data in an Excel line graph

· Compare and contrast the performance and accuracy of five sales forecasting models through forecast accuracy analysis

· Develop conclusions and a forecasting recommendation for a case study issue

· Compute the labor productivity impact due to a demand shock significantly lowering demand below the forecast and make a recommendation on how to address

· Create a chart in Excel and insert the chart in a Word document

· Create a well-written, professional, grammatically correct leadership report

Required Materials:

· Redstone Foods M&M Wholesale Case Study – (Word document)

· Redstone Foods M&M Wholesale Data File – (Excel document)

· Microsoft Excel

Forecasting

Redstone Foods M&M Sales Forecasting Tool
Data Section	2019 Total Sold (Cases)	2020 Total Sold (Cases)	2021 Total Sold (Cases)	2022 Total Sold (Cases)		2021 – 2022 Actual Growth	MODEL #1 2022 Forecast 3% Growth Over 2019 Only	MODEL #1 2022 Forecast Growth Over 2019 Only – Absolute Deviations	Squared Errors	Absolute Percent Error	MODEL #2 2022 Forecast 3-month Moving Average	MODEL #2 2022 Forecast 3-month Moving Average – Absolute Deviations	Squared Errors	Absolute Percent Error	MODEL #3 2022 Forecast 3-Month Weighted Moving Average	MODEL #3 2022 Forecast 3-Month Weighted Moving Average – Absolute Deviations	Squared Errors	Absolute Percent Error	MODEL #4 2022 Forecast Exp. Smoothing	MODEL #4 2022 Forecast Exp. Smoothing – Absolute Deviations	Squared Errors	Absolute Percent Error	MODEL #5 2022 Forecast Exp. Smoothing with Trend	MODEL #5 2022 Forecast Exp. Smoothing with Trend – Absolute Deviations	Squared Errors	Absolute Percent Error	Season Adjusment Factors
January	52598	57487	57342	58012		1.17%	59062	1050	1102500	1.81%	71352	13340	177955600	23.00%	71907	13895	193071025	23.95%	64183	6171	38081241	10.64%	65144	7132	50865424	12.29%	0.89
February	58908	59513	58236	59456		2.09%	59983	527	277729	0.89%	67689	8233	67782289	13.85%	65312	5856	34292736	9.85%	66559	7103	50452609	11.95%	68086	8630	74476900	14.51%	0.91
March	58800	62834	56843	57007		0.29%	58548	1541	2374681	2.70%	63473	6466	41809156	11.34%	61722	4715	22231225	8.27%	68477	11470	131560900	20.12%	70160	13153	173001409	23.07%	0.89
April	69056	76115	72343	60582		-16.26%	74513	13931	194072761	23.00%	58158	2424	5875776	4.00%	57943	2639	6964321	4.36%	65337	4755	22610025	7.85%	65092	4510	20340100	7.44%	1.13
May	64884	67409	65875	58209		-11.64%	67851	9642	92968164	16.56%	59015	806	649636	1.38%	59284	1075	1155625	1.85%	63573	5364	28772496	9.22%	62720	4511	20349121	7.75%	1.03
June	55465	55863	59351	52850		-10.95%	61132	8282	68591524	15.67%	58599	5749	33051001	10.88%	58681	5831	34000561	11.03%	61603	8753	76615009	16.56%	60303	7453	55547209	14.10%	0.93
July	59143	61869	60050	53021		-11.71%	61852	8831	77986561	16.66%	57214	4193	17581249	7.91%	56004	2983	8898289	5.63%	61297	8276	68492176	15.61%	60394	7373	54361129	13.91%	0.94
August	61171	62850	63259	55895		-11.64%	65157	9262	85784644	16.57%	54693	1202	1444804	2.15%	54007	1888	3564544	3.38%	60370	4475	20025625	8.01%	59458	3563	12694969	6.37%	0.99
September	64173	63224	62518	56022		-10.39%	64394	8372	70090384	14.94%	53922	2100	4410000	3.75%	54424	1598	2553604	2.85%	58114	2092	4376464	3.73%	56665	643	413449	1.15%	0.97
October	68265	67351	69002			—	71072				54979				55384				56586				55105				1.08
November	72885	75195	72102			—	74265				ERROR:#N/A				ERROR:#N/A				ERROR:#N/A				ERROR:#N/A				1.10
December	69865	72488	72952			—	75141				ERROR:#N/A				ERROR:#N/A				ERROR:#N/A				ERROR:#N/A				1.14

				Forecast Accuracy			MODEL #1				MODEL #2	MODEL #1	MODEL #1	MODEL #1	MODEL #3	MODEL #1	MODEL #1	MODEL #1	MODEL #4				MODEL #5
Apply Seasonality Adjustment	NO			2022 YTD Accuracy	MAD		6826				4946				4498				6495				6330
Forecast Growth Rate (Target):	3.00%				MSE		65916550				38951057				34081326				48998505				51338857
Forecast Weights:	20%	30%	50%		MAPE		12.09%				8.70%				7.91%				11.52%				11.18%
YTD Aggregate Growth Rate:	-8.05%
				1st Quarter 2022 Accuracy	MAD		1039				9346				8155				8248				9638
					MSE		1251637				95849015				83198329				73364917				99447911
					MAPE		1.80%				16.06%				14.02%				14.23%				16.63%
				2nd Quarter 2022 Accuracy	MAD		10618				2993				3182				6291				5491
					MSE		118544150				13192138				14040169				42665843				32078810
					MAPE		18.41%				5.42%				5.75%				11.21%				9.77%
				3rd Quarter 2022 Accuracy	MAD		8822				2498				2156				4948				3860
					MSE		77953863				7812018				5005479				30964755				22489849
					MAPE		16.06%				4.60%				3.95%				9.12%				7.14%

M&M Sales Forecasts (Cases)

2021 Total Sold (Cases) January February March April May June July August September October November December 57342 58236 56843 72343 65875 59351 60050 63259 62518 69002 72102 72952 2022 Total Sold (Cases) 58012 59456 57007 60582 58209 52850 53021 55895 56022 MODEL #1 2022 Forecast 3% Growth Over 2019 Only 59062 59983 58548 74513 67851 61132 61852 65157 64394 71072 74265 75141 MODEL #2 2022 Forecast 3-month Moving Average 71352 67689 63473 58158 59015 58599 57214 54693 53922 54979 #N/A #N/A MODEL #3 2022 Forecast 3-Month Weighted Moving Average 71907 65312 61722 57943 59284 58681 56004 54007 54424 55384 #N/A #N/A MODEL #4 2022 Forecast Exp. Smoothing 64183 66559 68477 65337 63573 61603 61297 60370 58114 56586 #N/A #N/A MODEL #5 2022 Forecast Exp. Smoothing with Trend 65144 68086 70160 65092 62720 60303 60394 59458 56665 55105 #N/A #N/A

Month

Cases Forecast

M&M Sales Trends (Cases Sold)

Month

Cases Sold

Calcs

January

57342

Yes

January

Jan-18

Jan-19

February

58236

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