# Project analysis

Projectanalysis

Issue3

Theproject analysis team has also been mandated to analyse a proposalfrom the marketing department aimed at eliminating phone orderingsystem now operating at Diatribe Company. The marketing departmenthas analysed the performance of its new on-line shopping methodologyas compared to the existing techniques of retailers shopping at theCompany’s warehouse and phoning in their orders and consequentlyprovided the information provided in appendix 1.

Inworking out descriptive statistics in the excel spreadsheet using theanalysis data provided, the information provided in table 1 below wasobtained.

Table1.Descriptive statistics

 INTERNET   PHONE   WAREHOUSE               Mean 12515.8 Mean 11538.23 Mean 12137.86 Standard Error 118.626 Standard Error 100.3188 Standard Error 105.4272 Median 12505 Median 11526 Median 12059 Mode #N/A Mode #N/A Mode #N/A Standard Deviation 786.8757 Standard Deviation 665.4396 Standard Deviation 699.325 Sample Variance 619173.3 Sample Variance 442809.8 Sample Variance 489055.5 Kurtosis -0.42374 Kurtosis 0.336031 Kurtosis 1.456416 Skewness -0.14536 Skewness 0.106273 Skewness 0.946477 Range 3291 Range 3143 Range 3279 Minimum 10689 Minimum 9958 Minimum 10816 Maximum 13980 Maximum 13101 Maximum 14095 Sum 550695 Sum 507682 Sum 534066 Count 44 Count 44 Count 44 Confidence Level (95.0%) 239.2321 Confidence Level (95.0%) 202.3121 Confidence Level (95.0%) 212.6142

Itis very clear that the mean sales achieved through selling thecompany’s products on-line were higher as compared to warehouse andphoning sales. Sales through phoning lagged behind others with amean of \$11538.23 thousands. At 95% confidence level, the mean salesin both cases are within the normal population mean. However, thestandard deviation is higher in on-line sales as opposed to the othermethodologies.

Assumingthat the sales operations have a normal distribution, and assumingthat the mean for warehouse sales is also representing the populationmean µ, we can find out whether there is a significant differencebetween the sample mean for on-line sales and phoning sales relativeto the mean for warehouse sales by calculating there Z scores [ CITATION Owe81 l 1033 ].

TheZ score for on-line sales is (12515.8 – 12137.86)/ 786.88 = 0.4803.

TheZ score for phoning sales is (11538 – 12137.86)/ 665.44 = -0.90145.

TheZ scores show that phoning sales are within the normal limits of thepopulation mean but on the lower side of the mean hence giving anegative Z score. On the basis of these results, the company needsto improve phoning sales or avoid it altogether.

Lookingat the statistical values obtained by the analysis team, it is goodto conclude at 95% confidence level that the use of on-lineoperational techniques in selling the company’s products is betterthan using phone in placing orders and achieving related sales.

Otherthan the decisions based on statistics, tnvrstar in their article inhubpages have indicated that the freedom of choice is higher inon-line shopping than visiting a nearby shop or warehouse to make achoice [ CITATION tnv14 l 1033 ]. Tnvrstar has also mentioned that freedom of choice is higher on-linebecause if you do not like the price of an item, you can switch toother on-line services or you canfollow the same procedure in a normal shop or warehouse but it wouldtake more time and energy to do so.

Suchfactors would therefore favor the use on internet services as opposedto conventional operations and these would result in higher sales. Privacy is also crucial to many of us who may not wish to buy someitems in public. On-line services would offer a platform whereprivacy is guaranteed and you can buy any kind of product fromon-line web store anonymously to maintain your desired privacy asalso stated by tnvrstar [ CITATION tnv14 l 1033 ].

Thereforethe marketing department of the company is justified in recommendingimmediate elimination of phone ordering system from the operations ofDiatribe Company.

Furtherinvestigations by the team involved finding a correlation betweenwarehouse selling verses phone selling and also warehouse sellingversus on-line selling. Figures2 and 3 show the relationship thatwas obtained in these cases.

Figure2: warehouse verses on-line sales

Figure3: warehouse verses phoning sales.

Aquick assessment of the two graphs shows that slope in figure 2 isgreater than the slope in figure 3.

 SUMMARY OUTPUT Regression Statistics Multiple R 0.06545 R Square 0.004284 Adjusted R Square -0.01942 Standard Error 671.8712 Observations 44 ANOVA   df SS MS F Regression 1 81565.03278 81565.03 0.180689118 Residual 42 18959256.69 451410.9 Total 43 19040821.73       Coefficients Standard Error t Stat P-value Intercept 10782.3 1781.222831 6.053312 3.32891E-07 X Variable 1 0.062279 0.146511832 0.425075 0.672951688
 SUMMARY OUTPUT Regression Statistics Multiple R 0.16496716 R Square 0.027214164 Adjusted R Square 0.004052596 Standard Error 785.2796124 Observations 44 ANOVA   df SS MS F Regression 1 724562.2307 724562.2307 1.174971 Residual 42 25899890.93 616664.0697 Total 43 26624453.16       Coefficients Standard Error t Stat P-value Intercept 10262.7664 2081.884191 4.929556816 1.34E-05 X Variable 1 0.185619901 0.171242285 1.083960667 0.284566

Foron-line sales, the regression line is y = 0.1856x + 10262.77 asopposed to phoning sales regression line equation which is y =0.0623x + 10782.3. The gradient in the first case is three times thegradient in the second case implying a better relationship andperformance by on-line sales. The R squares obtained indicate thatthe relationship between on-line sales and warehouse sales is higherhence giving more reason as to why dropping phoning sales ispreferable. Phoning sales are also challenging and as MaRS haveindicated in their article on sales basics, staying positive, beingpersistent and listening and adjusting to customers responses are thepersonal ingredients for success [ CITATION MaR09 l 1033 ]. However, these could be the more reasons why phoning sales are notfavored.

References

MaRS. (2009, december 6). MaRS sales basics. Retrieved October 3, 2014, from MaRS website: http://www.marsdd.com/sales-basics

Owen, F., &amp Jonnes, R. (1981). Statistics. London: Butler and Tanner Ltd.

tnvrstar. (n.d.). hubpages. Retrieved october 3, 2014, from hubpages website: http://www.tnvrstar.hubpages.com/hub/on-lineshoppingtips

Appendix1

 Internet Phone Warehouse 13361 9958 11692 12302 12123 10816 10874 11498 13224 11856 11051 12099 11239 11459 11900 12224 11030 14095 12753 11856 11517 12683 12308 12062 12466 11496 12263 13980 13006 13558 12503 11896 12210 12134 11726 11907 10689 11858 12488 11907 11621 12481 13576 11808 12234 12143 11554 11655 12507 12654 11450 13574 12079 11987 11696 11102 12383 13036 11277 12734 11887 10989 12200 12526 11332 12075 11582 10450 11993 11988 10392 12289 12004 11080 11779 12175 10488 11842 13674 11926 12698 13221 11371 12775 13297 11917 13044 13546 11490 12550 11920 11167 11690 12288 11087 11572 13827 13101 11778 13083 10594 12413 13248 12090 14052 12724 11132 11374 11951 11582 11684 13550 11563 11713 13001 11096 12056 11520 11075 11053 12888 12214 12211 12711 11751 11020 11935 11867 11827 12646 12568 11623

Allvalues in \$ thousands.