Clo Business Decision Making Project - Part I Staples Inc. Lizadora Jones QNT/275 01/25/15 Dr. Ronald Storm 1 2 Staples Inc. Staples Inc. was founded in 1985 and was incorporated on January 23, 1986 and has its headquarters in Framingham, Massachusetts. The company has three major segments: North American Stores and online, North American Commercial and International Operations (Reuters, 2016). The company offers a wide range of products that include: office supplies, business technology products and services, facility and break room supplies, computers and mobility commodities and office furniture under proprietary brands such as Quill and Staples. The company also provides copying and printing services to its retail and delivery customers. It also delivers technology products through its business Easy Tech. The company sells its products to the customers through on line websites: Staples.com, Staples.ca, and Quill.com and through its retail stores, contract sales force and its mail catalogue businesses. Problem In 2015, half of the market value of Staples Inc. was wiped out, the company's shares declined by forty eight percent (Egan, 2015). In 2014, Staples Inc. announced that it will shut down two hundred and twenty five stores in North America. There are a number of factors that have resulted to this. One of them is that the market for its products has reduces drastically over the years this due to a decline in printing. The US government through the Federal Trade Commission was successful in blocking a merger between Staples Inc. and Office Depot, the deal was worth a whooping six billion dollars. It is the second time that The Federal Trade Commission was successful in blocking the merger; it successfully blocked the merger back in 1997. The argument was that the merger will greatly affect competition nationwide hence breaking the anti-trust laws. It is surprising that 3 this was the argument given since Staples Inc. faces stiff competition from retailers like Amazon and Wal-Mart. Identification of research variable The main variable that has resulted to the decline of Staples Inc. is the reduction of printing. This is a quantitative variable. . One of the factors that resulted in a reduction in printing is the increase of use of softcopy documents and the increase of accessibility of electronic devices that users can install word processing programs that they can use to read softcopy documents. It is easier to store documents on a device than carry round hardcopies. In the 21st century global warming has become a great concern for this civilisation. The major cause of global warming is the increase of carbon (IV) oxide levels in the atmosphere. The carbon (IV) oxide traps heat within the earth's atmosphere not allowing it to escape as it should (McKibben, 2007). Trees greatly contribute to the reduction of carbon (IV) oxide in the atmosphere and various groups have campaigned for reduction of felling of trees. Activists are campaigning for a paperless society to protect trees; this has led to promotion of electronic books over hard copy books. The move has greatly affected Staples Inc. since as printing reduces, the products that accompany printing such as staples also reduces. Method for collecting data I will mainly use questionnaires to collect data on the variable. The questionnaires will be delivered to organizations in the printing industry. The questionnaires will help collect various organizations in the printing industry. They include publishers, media houses that print 4 newspapers and the manufacturers of photocopy and print paper. The data will be collected in subtotals of semi-annual figures over a five year period starting from 2015 and backwards. The data will help indicate whether the volume of production of print paper decreased over the five year period. Validation of data I will use the following method to validate the data collected by the method The Exploratory Factor Analysis will help identify data variations for the variable indicated in this study. I can also use it to determine the factors that can provide more information of the variability seen for the data collected. Through the permutation of the projected variables within the elements identified, Exploratory Factor Analysis allows reducing the total number of variables to process and, most importantly, assessing construct by enabling the quantification of the extent to which the items measure the intended constructs. Nevertheless, the empirically endorsed good practices in EFA require making a considerable amount of decisions based upon contextual parameters rather than on clearly predetermined criteria. 5 References References Egan, M. (December 22, 2015). These are the worst stocks of 2015. Retrieved from, http://money.cnn.com/2015/12/22/investing/worst-stocks-2015-oil-energy/ McKibben, B. (2007). Fight Global Warming Now. London: St. Martin's Press. Reuters. (2016). Staples Inc. Retrieved January 22, 2016 from, http://www.reuters.com/finance/stocks/overview?symbol=SPLS.OQ/ Clo Business Decision Making Project - Part I Business Decision Making Project Lizadora Jones QNT/275 Feb/02 Dr. Ronald Storm 1 2 Business Decision Making Project First of all we have to discuss about the data collection. We collected the data for the 50 publisher for the number of paper produced in the given year. After collecting the data for the number of paper produced by the different publisher, we have to use the different descriptive and inferential statistics for the purpose of the analysis of the data regarding the number of paper produced by the different publishers in the years 2011 to 2015. We have to use the ANOVA technique for checking the significant difference in the population average for the number of paper produced for the given five years. The figures of the different publishers for the years from 2011 to 2015 are given as below: (The figures are given in millions) Number of paper produced (million) 3 Publisher ID 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 2011 407 526 144 326 146 461 216 459 173 574 339 172 488 236 422 593 116 390 552 362 657 118 662 293 365 131 667 286 327 309 263 284 466 318 172 622 431 532 635 2012 370 493 125 269 122 370 198 386 95 545 322 114 392 143 393 520 26 326 473 334 605 44 624 257 290 98 613 191 303 265 261 277 382 298 107 536 428 441 611 2013 312 472 92 267 89 290 166 315 72 492 279 37 327 109 366 518 9 322 448 324 569 18 623 210 283 22 562 131 275 206 183 271 317 286 65 530 424 424 540 2014 307 449 69 226 85 254 165 266 37 478 270 23 320 77 361 508 41 274 440 298 529 50 575 161 275 11 535 101 269 175 145 225 292 272 42 528 416 375 509 2015 299 422 55 220 64 250 154 251 10 475 252 3 291 61 332 482 70 273 413 276 506 56 548 159 250 17 534 75 253 169 141 204 265 264 35 505 389 347 485 4 40 41 42 43 44 45 46 47 48 49 50 544 181 397 228 293 458 366 109 182 169 586 535 165 309 131 279 422 271 50 141 163 494 526 161 292 83 274 412 204 15 122 118 459 486 153 268 69 230 398 177 34 113 114 455 480 145 245 57 224 394 163 57 90 85 439 For the given years we have to find the descriptive statistics for the number of paper prints by the different publisher. The descriptive statistics consist of the mean, mode, median, minimum, maximum, standard deviation, skewness, kurtosis, etc. The descriptive statistics for the different given years are summarized as below: Descriptive statistics for number of paper produced in million for the years 2011 to 2015 Mean Median Mode Minimum Maximum Range Variance Standard Deviation Coeff. of Variation Skewness Kurtosis Count Standard Error 2011 2012 2013 2014 2015 363.06 312.14 278.22 258.6 244.68 350.5 300.5 281 267 250 172 370 424 69 250 109 26 9 11 3 667 624 623 575 548 558 598 614 564 545 28351.4453 27947.0616 29381.6853 27507.9592 26095.2016 168.3789 167.1737 171.4109 165.8552 161.5401 46.38% 0.2149 -1.0836 50 23.8124 53.56% 0.1808 -0.9108 50 23.6419 61.61% 0.1797 -0.9628 50 24.2412 64.14% 0.2577 -1.0824 50 23.4555 66.02% 0.2861 -1.0533 50 22.8452 5 From this summary we observe that the average use of the paper is decreasing from the year 2011 to 2015. We have to check this fact by using the ANOVA model. We have to check the claim whether the use of the print paper is same for the given years or not. The ANOVA table is given as below: ANOVA: Single Factor SUMMARY Groups Count Sum Average 2011 2012 50 50 18153 15607 363.06 312.14 2013 2014 2015 50 50 50 13911 12930 12234 278.22 258.6 244.68 ANOVA Source of Variation Between Groups Within Groups Variance 28351.445 3 27947.0616 29381.685 3 27507.9592 26095.2016 Df MS 449879.8000 6824884.300 0 4 112469.9500 245 7274764.1000 F 4.0375 0.0034 2.4085 Level of significance Total SS Pvalue 0.05 F crit 249 27856.6706 Here, we get the p-value as 0.0034 which is less than the given level of significance 0.05 or 0.01, so we reject the null hypothesis that the average number of print papers for the given 6 years is same. This means, we conclude that the average number of print papers for the different publishers is decreasing from the year 2011 to year 2015. Now, we have to study the pattern of time series for the number of print papers for the different years. The time series plots for the given years are given as below: 7 The overall plots for the all years from 2011 to 2015 are summarized in the following graph. From this time series plot it is concluded that there is a relationship between the number of print papers per years and it is observed that the number of print papers are decreasing from 8 2011 to 2015. Now, we have to develop the regression model for the purpose of estimation of the number of print papers for the next years. The regression year is given as below; SUMMARY OUTPUT Regression Statistics Multiple R 0.997348319 R Square 0.99470367 Adjusted R Square 0.994232885 Standard Error 12.26760054 Observations 50 ANOVA Df Regression Residual Total 4 45 49 Intercept 2011 2012 2013 2014 Coefficients 3.858233632 0.028145386 0.046172854 -0.16801231 1.125632977 SS MS F 1271892.649 317973.2 2112.862 6772.231041 150.494 1278664.88 Standard Error 5.37103414 t Stat -0.71834 P-value Significance F 1.43979E-50 Lower 95% Upper 95% 0.47626 -14.67605154 6.959584271 0.057844499 -0.48657 0.628925 0.102177864 0.451887 0.653521 0.127882238 -1.3138 0.195571 0.097311189 11.56735 4.48E-15 -0.144650186 0.088359414 -0.159623924 0.251969632 -0.425580356 0.089555735 0.929638184 1.32162777 By using the coefficients in the above summary for regression model, we can develop the regression equation for estimation purpose of number of prints. 9 References: Schervish, Mark J. (1995). Theory of statistics (Corr. 2nd print. ed.). 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(2008). Statistical Decision Theory: Estimation, Testing, and Selection. Springer