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The Glass Slipper Restaurant’s Sales Trends Essay

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Updated: May 5th, 2021

Graph of Data and the 12-Month Moving Average

Table 1. Moving Average Forecast.

Year Month Sales Sales Forecast
2008 January 438
February 420
March 414
April 318
May 306
June 240
July 240
August 216
September 198
October 225
November 270
December 315
2009 January 444 300.00
February 425 300.50
March 423 300.92
April 331 301.67
May 318 302.75
June 245 303.75
July 255 304.17
August 223 305.42
September 210 306.00
October 233 307.00
November 278 307.67
December 322 308.33
2010 January 450 308.92
February 438 309.42
March 434 310.50
April 338 311.42
May 331 312.00
June 254 313.08
July 264 313.83
August 231 314.58
September 224 315.25
October 243 316.42
November 289 317.25
December 335 318.17
2011 January 319.25
Monthly Trend of sales and 12-Month Moving Average Forecast
Figure 1.

The graph shows monthly trends of sales in The Glass Slipper Restaurant in the period of three years from 2008 to 2010. The trend of sales has been fluctuating over the period with the highest and lowest sales being about 450 and 200 respectively. What is apparent in the graph is that the restaurant has a single peak season in a year where it registers the most sales. The peak season occurs in the first three months of the year, namely, January, February, and March, when the restaurant registers sales of over 400. During August, September, and October, the restaurant is at the off-peak season for the sales are between 198 and 243. During April May, June, and July, the restaurant experiences declining sales from the peak period to the off-peak period. In contrast, during November and December, the restaurant experience a rapid increase in sales from the off-peak to peak period. Overall, the graph shows that there is a seasonal variation in the sales of the restaurant according to peak and off-peak tourist seasons.

The 12-month moving average forecast provides a clear trend of the sales over the period of three years. The forecast shows that sales increase gradually over time for they were about 300 in January of 2008 and have increased to about 318 in December of 2010. Overall, the moving average projects that the sales of the restaurant after 12 months would have increased by about 10. The trend line predicts that sales of the restaurant will increase by 0.798 units every month. Therefore, the forecast of sales indicates that the income of the restaurant appreciates yearly, and thus, the value of the restaurant should be plus the projected sales.

Sales Forecast Using Regression

Table 2. Regression Analysis.

Year Month Period (x) Sales (y) x^2 XY
2008 January 1 438 1 438
February 2 420 4 840
March 3 414 9 1242
April 4 318 16 1272
May 5 306 25 1530
June 6 240 36 1440
July 7 240 49 1680
August 8 216 64 1728
September 9 198 81 1782
October 10 225 100 2250
November 11 270 121 2970
December 12 315 144 3780
2009 January 13 444 169 5772
February 14 425 196 5950
March 15 423 225 6345
April 16 331 256 5296
May 17 318 289 5406
June 18 245 324 4410
July 19 255 361 4845
August 20 223 400 4460
September 21 210 441 4410
October 22 233 484 5126
November 23 278 529 6394
December 24 322 576 7728
2010 January 25 450 625 11250
February 26 438 676 11388
March 27 434 729 11718
April 28 338 784 9464
May 29 331 841 9599
June 30 254 900 7620
July 31 264 961 8184
August 32 231 1024 7392
September 33 224 1089 7392
October 34 243 1156 8262
November 35 289 1225 10115
December 36 335 1296 12060
Σ (x) = 666 Σ (y) = 11138 Σ(x^2)= 16206 Σ(xy) = 201538
x̅ =18.5 Ў= 309.39

Regression Equation

y = a + bx

b = Σxy – n x̅Ў/ Σx^2 – n x̅^2

a = Ў – bx̅

b = 201538 – (36*18.5*309.39)/ (16206 -36*18.5^2) = 201538 – 206053/16206-12321= -4515/3885 = -1.16216

a = 309.39 – (-1.16216*18.5) = 309.39 + 21.5 = 330.89

Therefore, the trend line is

y = 330.89 – 1.16216x

Sales = 330.89 – 1.16216 (month)

Prediction of Monthly Sales
Figure 2.

The slope of the regression trend line is not consistent with the trend line of the moving average. While the trend line of the regression is negative [Sales = 330.89 – 1.16216(month)], the trend line of the moving average is positive [Sales = 289.1 + 0.798(month)]. Essentially, the regression line indicates that sales decrease by 1.16216 units every month. In contrast, the moving average forecast shows that sales increase by 0.798 units every month. The reason for the apparent differences is that moving averages considers the overall trend of a year while the regression analysis considers monthly trends. In essence, yearly trends show growth in sales while monthly trends show a decline in sales. Berry (2010) asserts that regression offers instantaneous trends while moving average provides comprehensive trends over a period. Therefore, moving average is appropriate in forecasting sales if offers a comprehensive view of the trend.

Reference

Berry, T. (2010). Sales and market forecasting for entrepreneurs. New York, NY: Business Expert Press.

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IvyPanda. 2021. "The Glass Slipper Restaurant's Sales Trends." May 5, 2021. https://ivypanda.com/essays/the-glass-slipper-restaurants-sales-trends/.

References

IvyPanda. (2021) 'The Glass Slipper Restaurant's Sales Trends'. 5 May.

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