Questions for Case Study III
1. Per the average product sales demographic per store outlined on page 2 of the case study, how was the Ban Boredom strategy intended to enhance financial performance of each store? Analytically, using the data in Exhibit 4, perform a single regression analysis between Future Controllable Contribution and the Ban Boredom Score? In terms of gauging the intended financial performance of the strategy what should be your expectation for such an analysis? Did your analysis meet this expectation? If not, what might be some of the financial reasons why the strategy is not effective?
2. How was the Companies implementation strategy different between the Ban Boredom Strategy and the Cause You Just Can’t Wait Strategy? (See page 3). Do you feel the companies approach was appropriate for each? Based on the high reliance on Crew and Mgr. Skill in successfully implementing the Ban Boredom Strategy, perform a regression analysis and compare each against the Ban Boredom strategy, does your analysis support the company expectation? How does Cause You Just Can’t Wait Strategy influence Crew Skill and the success of Ban Boredom?
3. Prepare a multiple regression analysis using the data in Exhibit 4 and split the stores based on those stores with a Crew Skill above the Median, and those below. How do the results differ and what may this indicate regarding the success of the strategy? For those stores with a relatively low Crew Skill what might you implement to enhance these skills?
4. Comment on the company’s use of the balance scorecard to evaluate employee performance and identify operational improvements. How was the variable compensation of store management linked to financial performance, do you feel this is a solid plan, what might you do to enhance it?
5. Perform a regression analysis comparing Future Controllable Contribution with population, per captia income and number of competitors. What does this analysis indicate? Given the fact that 30 of the 75 stores are located in u
an areas and the average rent on a 2,100 square foot store is $49,000, how might this analysis influence how the company negotiates with landlords, and how changing geographic store locations could enhance performance?
Due Date:
Sheet1
Store # Futrure Controllable Contribution CYJCW Score Ban Boredom Score Crew Skill Manager Skill Population Income Competitors Y^ Y Y^
1510 $23,000 84.93 71.43 2.35 2.2 17,754 $27,084 6
1711 $25,419 88.8 75.00 2.87 2.52 8,966 $47,712 2
1514 $21,164 95.41 117.86 2.93 3.85 21,550 $22,935 4
1507 $24,637 95.42 85.71 3.09 4.23 16,926 $25,744 5
1513 $22,695 83.28 92.86 3.10 2.41 16,381 $38,252 1 Y^ = b0 + b1*X1 + b2*X2+b3*X3+b4*X4+B5*X5+b6*X6
1709 $22,314 91.37 78.57 3.10 3.63 13,297 $17,308 7
1710 $22,273 96.36 117.86 3.20 4.16 19,808 $34,333 3
1573 $22,734 78.63 67.86 3.23 4.04 14,859 $8,182 5
1579 $18,871 92.85 121.43 2.80 2.59 10,532 $8,181 7
1577 $18,007 83.93 121.43 2.85 3.28 3,747 $18,036 3
1586 $17,874 90.59 135.71 2.88 3.12 3,014 $22,384 3
1544 $20,200 96.56 135.71 2.89 3.07 10,923 $32,042 3
1515 $17,897 88.93 128.57 3.10 2.81 11,160 $14,589 7
1704 $20,886 96.65 125.00 3.11 3.52 3,151 $18,198 3
1537 $21,373 95.86 125.00 3.16 3.95 1,116 $23,056 2
1598 $38,573 87.14 67.86 3.34 3.21 19,809 $23,550 6
1512 $44,141 92.2 114.29 3.37 2.85 26,519 $29,411 6
1543 $43,364 85.91 119.93 3.63 3.57 8,177 $10,746 4
1558 $40,403 90.58 82.14 3.64 3.43 20,624 $18,850 7
1702 $43,222 90.14 110.71 4.05 3.71 3,265 $18,197 6
1570 $46,308 92.19 110.71 4.20 3.17 3,126 $55,416 1
1568 $40,576 81.74 78.57 4.38 2.69 14,653 $52,821 3
1560 $47,453 96.19 135.71 3.27 3.6 17,808 $21,034 3
1503 $42,776 82.14 128.57 3.28 3.4 9,695 $15,091 4
1546 $44,599 88.75 125.00 3.44 3.55 3,218 $18,467 4
1516 $45,936 95.48 128.57 3.63 3.91 14,186 $14,153 5
1547 $44,054 90.63 125.00 3.65 3.33 8,870 $15,279 4
1542 $42,128 79.67 128.57 3.68 3.07 9,697 $12,258 5
1517 $45,481 91.28 135.71 3.80 3.66 6,898 $15,749 6
1566 $46,280 94.79 128.57 4.40 3.42 8,491 $12,388 4
Questions for Case Study III
1. Per the average product sales demographic per store outlined on page 2 of the case study, how was the Ban Boredom strategy intended to enhance financial performance of each store? Analytically, using the data in Exhibit 4, perform a single regression analysis between Future Controllable Contribution and the Ban Boredom Score? In terms of gauging the intended financial performance of the strategy what should be your expectation for such an analysis? Did your analysis meet this expectation? If not, what might be some of the financial reasons why the strategy is not effective?
2. How was the Companies implementation strategy different between the Ban Boredom Strategy and the Cause You Just Can’t Wait Strategy? (See page 3). Do you feel the companies approach was appropriate for each? Based on the high reliance on Crew and Mgr. Skill in successfully implementing the Ban Boredom Strategy, perform a regression analysis and compare each against the Ban Boredom strategy, does your analysis support the company expectation? How does Cause You Just Can’t Wait Strategy influence Crew Skill and the success of Ban Boredom?
3. Prepare a multiple regression analysis using the data in Exhibit 4 and split the stores based on those stores with a Crew Skill above the Median, and those below. How do the results differ and what may this indicate regarding the success of the strategy? For those stores with a relatively low Crew Skill what might you implement to enhance these skills?
4. Comment on the company’s use of the balance scorecard to evaluate employee performance and identify operational improvements. How was the variable compensation of store management linked to financial performance, do you feel this is a solid plan, what might you do to enhance it?
5. Perform a regression analysis comparing Future Controllable Contribution with population, per captia income and number of competitors. What does this analysis indicate? Given the fact that 30 of the 75 stores are located in u
an areas and the average rent on a 2,100 square foot store is $49,000, how might this analysis influence how the company negotiates with landlords, and how changing geographic store locations could enhance performance?
Due Date: