Term Paper BFIN 305 – 800: Summer 2019 Submit through D2L. Use only Word and Excel. 25% of your total grade. Due date: 4th July 2019 at 11:59 pm. Show detailed calculations and works. State all your assumptions clearly. Make observations and comment on your findings. In this term paper, you will find the value of your undergraduate degree. Step 1: Calculate the cost of the program First fill up the following table to list down the term wise tuitions. Some terms are in the past and some will be in the future (until graduation). This is a term-wise exercise. Use the start of each term as the time/date (column 1 of the table): 15th January for spring, 15th May for first summer, 1st July for second summer, and 1st September for fall terms. Consider all the expenses related to school such as books, fees, etc. as part of Tuition (column 2). Assuming today to be 1st July 2019, find the time difference (column 3) between today and the date for each term. Time from today (years) = Time from today (in days)/365 Now find the value of the tuition as on today (column 4). If the term was in the past, you need to find today’s value in order to find value as on today. If the term is in the future you need to find the PV (present value) in order to find value as on today. You may use the latest 10 years Treasury bond rate (https://ycharts.com/indicators/10_year_treasury_rate) as the discount rate. You just need the latest rate. For past terms: Value as on today = Tuition * (1 + discount rate) time from today in years For future terms: Value as on today = Tuition / (1 + discount rate) time from today in years Finally, add up the last column to find out the PV of the cost of the undergraduate program. Time/Date Tuition ($) Time from today (days) Time from today (years) Value as on today ($) Step 2: Estimate the opportunity cost Since you are a full time or part time student, you might have (and may be in future) foregone earnings that you could have earned had you not enrolled in the program. You may be working for fewer hours a week, or not working at all, or working in a place with lower wage. Find the difference between what you could have earned and what you have actually earned. Estimate similar difference for the future months as well, as you continue until graduation. This will be a monthly exercise (unlike in step 1 which was a term wise exercise). Rest of the directions and assumptions are similar to as mentioned in Step 1. Time/Date Earnings ($) Could have earned ($) Difference ($) Time from today (days) Time from today (years) Value as on today ($) Finally, add up the last column to find out the present value of the earnings foregone. This is your opportunity cost. Step 3: Find out the benefits of the undergraduate degree In this step we will calculate the monitory value of your degree. This is valued as the difference in earnings that the degree makes. This is also a monthly exercise. Start this exercise from the month of graduation and assume that you will be working till 70; you are expected to get a modest pay rise every year that matches the rate of inflation in the recent months. In every 5 years, you may expect to receive a moderate/decent pay rise due to promotion or changing jobs. Your earnings without the degree in the initial months should be in line with the “could have earned” in Step 2. Rest of the directions remain same as in Step 1. However, now you change your discount rate to 11% (we are assuming that this rate is commensurate with the risk of your earnings being different than what you are projecting). Time/Date Earnings with the degree($) Earnings without the degree($) Difference ($) Time from today (years) Value as on today ($) Finally, add up the last column to find out the present value of the benefits of having the degree. Step 4: Calculate the value of your degree The Present Value of your degree = Benefits of the undergraduate degree – Cost of the program – Opportunity Cost Step 5: Analysis A) This exercise requires a number of assumptions to be made by you. Please state all those assumptions clearly and state your basis for such assumptions. B) Make observation on your findings. Comment on how your case may be special or different from other students. C) State what else could have been included in this exercise Special instructions: 1. Start early and submit by deadline. 2. Read this instruction very thoroughly. Ask questions only after you have carefully gone through the instructions. 3. This is a financial exercise. Therefore, ensure that your work makes sense financially. 4. Use MS Excel for all the tables and calculations. 5. Use word document to state assumptions, make comments and observations. 6. Ensure that you show all the calculations and state all the assumptions clearly. 7. After submission, ensure that correct version of all the files have been uploaded. Today Discount rate This is just an example Time/date Tuition/earnings ($) Time from today (days) For a term/month in the past 1-Sep-18 100 303 For a term/month in the future 1-Sep-19 100 62 1-Jul-19 6.00%

NAME Period Full Year Revenue Region UK France Iberia Italy GSA MENA TIG EM Nordic Benelux EMEARCIS RCIS ANZ GC SEA India Korea Japan LATAM July Fcst UK and Ireland…_Revenue 75.8 France.._Revenue 91.7 Iberia.._Revenue 70.3 Italy.._Revenue 80.0 Germany, Switzerland & Austria_Revenue 84.5 MENA.._Revenue 21.4 TIG.._Revenue 22.4 Emerging Markets_Revenue 0.0 Nordics & Baltics_Revenue 36.5 Benelux.._Revenue 23.6 EMEA (ex Russia-CIS)_Revenue 578.7 Russia-CIS.._Revenue 0.0 Australia & New Zealand…_Revenue 32.6 Greater China_Revenue 11.0 South East Asia_Revenue 49.4 India_Revenue 75.9 Korea…._Revenue 14.4 Japan_Revenue 124.1 Latin America._Revenue 235.2 May UK and Ireland…_Subscription UK and Ireland…_Advertising UK and Ireland…_Other Revenue UK and Ireland…_Revenue UK and Ireland…_Programming UK and Ireland…_Marketing UK and Ireland…_Technical UK and Ireland…_Labour UK and Ireland…_Other Overhead UK and Ireland…_Depreciation UK and Ireland…_Allocations UK and Ireland…_Bad Debt UK and Ireland…_Expense France.._Subscription France.._Advertising France.._Other Revenue France.._Revenue France.._Programming France.._Marketing France.._Technical France.._Labour France.._Other Overhead France.._Depreciation France.._Allocations France.._Bad Debt France.._Expense Iberia.._Subscription Iberia.._Advertising Iberia.._Other Revenue Iberia.._Revenue Iberia.._Programming Iberia.._Marketing Iberia.._Technical Iberia.._Labour Iberia.._Other Overhead Iberia.._Depreciation Iberia.._Allocations Iberia.._Bad Debt Iberia.._Expense Italy.._Subscription Italy.._Advertising Italy.._Other Revenue Italy.._Revenue UK and Ireland… UK and Ireland… UK and Ireland… UK and Ireland… UK and Ireland… UK and Ireland… UK and Ireland… UK and Ireland… UK and Ireland… UK and Ireland… UK and Ireland… UK and Ireland… UK and Ireland… France.. 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Italy.._Programming Italy.._Marketing TIG.._Expense Emerging Markets_Subscription Emerging Markets_Advertising Emerging Markets_Other Revenue Emerging Markets_Revenue Emerging Markets_Programming Emerging Markets_Marketing Emerging Markets_Technical Emerging Markets_Labour Emerging Markets_Other Overhead Emerging Markets_Depreciation Emerging Markets_Allocations Emerging Markets_Bad Debt Emerging Markets_Expense Nordics & Baltics_Subscription Nordics & Baltics_Advertising Nordics & Baltics_Other Revenue Nordics & Baltics_Revenue Nordics & Baltics_Programming Nordics & Baltics_Marketing Nordics & Baltics_Technical Nordics & Baltics_Labour Nordics & Baltics_Other Overhead Nordics & Baltics_Depreciation Nordics & Baltics_Allocations Nordics & Baltics_Bad Debt Nordics & Baltics_Expense Benelux.._Subscription Benelux.._Advertising Benelux.._Other Revenue Benelux.._Revenue Benelux.._Programming Benelux.._Marketing Benelux.._Technical Benelux.._Labour Benelux.._Other Overhead Benelux.._Depreciation Benelux.._Allocations Benelux.._Bad Debt Benelux.._Expense EMEA (ex Russia-CIS)_Subscription EMEA (ex Russia-CIS)_Advertising EMEA (ex Russia-CIS)_Other Revenue EMEA (ex Russia-CIS)_Revenue EMEA (ex Russia-CIS)_Programming EMEA (ex Russia-CIS)_Marketing EMEA (ex Russia-CIS)_Technical TIG.. 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Korea…. Korea…. Korea…. Korea…. Korea…. Korea…. Korea…. Korea…. Korea…. Korea…. Korea…. Korea…. Japan Japan Japan Japan Japan Japan Japan Japan Japan Japan Japan_Allocations Japan_Bad Debt Japan_Expense Latin America._Subscription Latin America._Advertising Latin America._Other Revenue Latin America._Revenue Latin America._Programming Latin America._Marketing Latin America._Technical Latin America._Labour Latin America._Other Overhead Latin America._Depreciation Latin America._Allocations Latin America._Bad Debt Latin America._Expense _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ Japan Japan Japan Latin America. Latin America. Latin America. Latin America. Latin America. Latin America. Latin America. Latin America. Latin America. Latin America. Latin America. Latin America. Latin America. _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 2018 FY18 July Forecast Subscription Advertising Other Revenue Revenue Programming Marketing Technical Labour Other Overhead Depreciation Allocations Bad Debt Expense Subscription Advertising Other Revenue Revenue Programming Marketing Technical Labour Other Overhead Depreciation Allocations Bad Debt Expense Subscription Advertising Other Revenue Revenue Programming Marketing Technical Labour Other Overhead Depreciation Allocations Bad Debt Expense Subscription Advertising Other Revenue Revenue 2018 FY18 July Forecast Q1 15,959,922 8,768,195 (1,432,415) 23,295,703 3,021,568 3,140,766 1,222,167 487,140 23,853 72,241 967 77,139 8,045,841 19,474,578 7,432,076 62,195 26,968,849 9,300,709 2,002,002 1,283,742 848,133 41,986 91,126 4,632 (315,687) 13,256,643 9,499,212 17,355,929 38,848 26,893,988 3,584,774 1,148,221 3,708,404 562,439 183,510 23,272 1,309 0 9,211,930 20,167,019 1,188,858 58,878 21,414,756 Programming Marketing Technical Labour Other Overhead Depreciation Allocations Bad Debt Expense Subscription Advertising Other Revenue Revenue Programming Marketing Technical Labour Other Overhead Depreciation Allocations Bad Debt Expense Subscription Advertising Other Revenue Revenue Programming Marketing Technical Labour Other Overhead Depreciation Allocations Bad Debt Expense Subscription Advertising Other Revenue Revenue Programming Marketing Technical Labour Other Overhead Depreciation Allocations Bad Debt 4,818,857 1,464,262 364,060 522,900 209,583 247 192 (46,119) 7,333,983 8,816,680 20,453,834 1,523,394 30,793,909 13,877,025 3,650,665 2,728,576 1,069,148 129,336 345,449 4,151 (104,254) 21,700,094 4,696,172 918 8,933 4,706,022 776,170 196,791 233,382 0 94,825 60,555 0 2,573 1,364,297 5,353,730 341,489 8,227 5,703,447 1,203,797 301,688 534,180 293,863 143,783 89,121 0 (49,220) Expense Subscription Advertising Other Revenue Revenue Programming Marketing Technical Labour Other Overhead Depreciation Allocations Bad Debt Expense Subscription Advertising Other Revenue Revenue Programming Marketing Technical Labour Other Overhead Depreciation Allocations Bad Debt Expense Subscription Advertising Other Revenue Revenue Programming Marketing Technical Labour Other Overhead Depreciation Allocations Bad Debt Expense Subscription Advertising Other Revenue Revenue Programming Marketing Technical 2,517,212 0 0 0 0 (18,591) (0) (0) 295,739 (295,739) 0 0 0 (18,591) 8,333,277 2,417,683 23,231 10,774,191 2,559,458 916,380 865,340 333,321 13,692 102,590 0 7,126 4,797,907 5,082,991 1,870,046 41,198 6,994,235 1,662,478 757,140 260,282 223,798 153,627 50,635 0 (6,504) 3,101,456 113,038,940 64,958,831 365,625 178,363,396 45,104,001 17,298,031 11,024,860 Labour Other Overhead Depreciation Allocations Bad Debt Expense Subscription Advertising Other Revenue Revenue Programming Marketing Technical Labour Other Overhead Depreciation Allocations Bad Debt Expense Subscription Advertising Other Revenue Revenue Programming Marketing Technical Labour Other Overhead Depreciation Allocations Bad Debt Expense Subscription Advertising Other Revenue Revenue Programming Marketing Technical Labour Other Overhead Depreciation Allocations Bad Debt Expense Subscription Advertising 7,684,544 2,235,444 1,911,634 24,576,353 (317,985) 109,516,881 0 0 0 0 (115,879) 325,747 0 6,331 39,875 1,425,000 879,732 0 2,560,805 7,839,165 697,007 48,863 8,585,036 1,141,951 646,789 78,063 525,911 608,358 30,076 1,003,855 (24,220) 4,010,783 2,388,545 0 35,433 2,423,979 461,721 68,880 50,515 418,123 294,172 13,580 141,686 (100,260) 1,348,417 11,879,328 433,541 Other Revenue Revenue Programming Marketing Technical Labour Other Overhead Depreciation Allocations Bad Debt Expense Subscription Advertising Other Revenue Revenue Programming Marketing Technical Labour Other Overhead Depreciation Allocations Bad Debt Expense Subscription Advertising Other Revenue Revenue Programming Marketing Technical Labour Other Overhead Depreciation Allocations Bad Debt Expense Subscription Advertising Other Revenue Revenue Programming Marketing Technical Labour Other Overhead Depreciation 8,521 12,321,390 1,812,713 693,952 829,159 3,057,237 (1,025,856) 542,524 1,153,436 2,304,416 9,367,579 6,761,952 12,106,811 61,332 18,930,095 5,669,331 1,565,295 423,579 1,896,035 682,681 878,818 2,243,923 257,788 13,617,450 2,727,752 873,869 218,028 3,819,649 1,126,221 229,465 348,696 269,263 321,222 17,646 357,198 1,168 2,670,879 20,262,077 8,621,226 2,480,116 31,363,419 9,272,251 2,051,450 5,100,926 2,755,244 1,231,058 371,995 Allocations Bad Debt Expense Subscription Advertising Other Revenue Revenue Programming Marketing Technical Labour Other Overhead Depreciation Allocations Bad Debt Expense 2,949,831 (1,016) 23,731,739 42,518,755 19,555,254 1,454,507 63,528,515 17,096,334 4,704,520 2,784,179 1,904,689 1,801,098 155,261 7,221,992 994,293 36,662,366 _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 2018 FY18 July Forecast Q2 2018 FY18 July Forecast Q3 2018 FY18 July Forecast Q4 2018 FY18 July Forecast Full Year 15,700,989 15,486,356 14,801,063 61,948,330 3,129,396 3,174,378 4,790,170 19,862,139 (1,385,855) (1,318,113) (1,869,558) (6,005,941) 17,444,530 17,342,621 17,721,675 75,804,529 3,310,412 3,564,038 4,002,675 13,898,693 3,235,606 1,552,140 2,843,967 10,772,478 1,248,169 1,231,536 1,273,035 4,974,906 527,897 257,308 287,300 1,559,645 65,071 186,659 (65,066) 210,517 72,461 42,933 40,464 228,098 19,373 (7,885) 7,885 20,339 636 9,144 (9,144) 77,775 8,479,624 6,835,872 8,381,114 31,742,452 19,498,555 19,977,783 18,959,470 77,910,388 2,151,083 1,942,598 2,016,334 13,542,090 80,872 93,472 (1,361) 235,178 21,730,510 22,013,854 20,974,443 91,687,655 8,702,483 8,120,106 8,618,660 34,741,958 2,348,307 1,353,673 1,864,721 7,568,703 1,200,643 1,272,179 1,452,637 5,209,201 822,266 778,958 949,955 3,399,313 59,857 70,550 200,471 372,865 74,259 98,396 222,355 486,137 5,984 2,685 (13,301) 0 147,961 288,739 (212,178) (91,165) 13,361,761 11,985,286 13,083,321 51,687,011 9,535,446 9,610,063 10,089,015 38,733,736 3,746,378 5,770,764 4,396,630 31,269,700 96,412 111,176 34,112 280,548 13,378,236 15,492,003 14,519,757 70,283,984 2,821,908 3,025,179 2,997,827 12,429,688 559,712 855,767 1,702,637 4,266,337 3,261,436 3,156,559 3,191,728 13,318,128 550,822 489,241 469,332 2,071,835 148,335 189,016 211,252 732,113 23,271 23,272 23,271 93,086 7,451 20,447 0 29,207 14,614 (10,847) 0 3,767 7,387,550 7,748,634 8,596,048 32,944,161 20,252,322 20,193,894 16,522,239 77,135,473 453,119 421,504 381,508 2,444,990 152,759 175,656 17,357 404,649 20,858,200 20,791,054 16,921,104 79,985,113 4,573,711 4,826,945 5,911,945 20,131,458 1,120,360 1,646,201 1,663,103 5,893,926 388,232 371,528 590,689 1,714,509 505,670 428,454 374,507 1,831,531 474,820 202,536 302,010 1,188,949 248 247 60,893 61,635 1,105 3,579 (3,361) 1,515 0 0 0 (46,119) 7,064,146 7,479,491 8,899,786 30,777,405 8,915,661 8,881,655 8,683,113 35,297,109 7,790,139 5,485,345 8,591,215 42,320,534 1,455,095 1,826,626 2,062,168 6,867,283 18,160,895 16,193,627 19,336,496 84,484,926 13,250,863 12,058,914 11,984,882 51,171,683 2,597,021 2,218,933 2,739,451 11,206,071 2,662,397 3,292,365 2,478,161 11,161,500 1,029,709 1,021,125 1,074,493 4,194,476 181,893 166,292 370,437 847,958 345,061 365,054 367,169 1,422,733 14,311 (9,792) 9,792 18,462 (15,611) 39,579 80,286 (1) 20,065,645 19,152,471 19,104,671 80,022,881 5,734,232 5,559,215 5,344,645 21,334,265 1,095 1,725 (1,725) 2,013 25,073 28,930 (3,688) 59,248 5,760,401 5,589,869 5,339,233 21,395,525 748,669 1,073,816 1,833,785 4,432,440 148,485 219,644 462,529 1,027,449 240,155 235,430 422,355 1,131,322 0 0 0 0 106,329 166,371 60,248 427,774 60,476 40,720 37,698 199,450 13,146 2,845 (2,845) 13,146 352,714 36,059 (336,059) 55,288 1,669,975 1,774,885 2,477,712 7,286,868 4,529,920 4,731,837 4,075,234 18,690,721 372,513 335,841 376,791 1,426,634 23,094 26,601 2,237,545 2,295,468 4,925,526 5,094,280 6,689,570 22,412,823 1,011,041 1,446,399 3,884,727 7,545,964 416,577 385,654 1,083,099 2,187,018 594,376 473,979 862,975 2,465,510 308,927 289,079 503,599 1,395,468 187,320 34,423 145,462 510,989 89,460 78,496 90,384 347,460 442 0 0 442 (19,701) (36,395) 118,073 12,757 2,588,442 2,671,636 6,688,319 14,465,609 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 (140) 0 (0) (18,731) 0 1 (1) (0) 0 0 0 (0) 313,609 177,235 376,988 1,163,571 (313,491) (177,235) (376,988) (1,163,453) 0 0 0 0 0 0 0 0 0 0 0 0 (23) 1 (0) (18,613) 8,045,261 8,540,102 7,221,823 32,140,463 637,622 714,290 403,526 4,173,122 68,554 78,267 3,813 173,865 8,751,438 9,332,660 7,629,161 36,487,450 3,165,178 2,242,649 2,418,567 10,385,852 818,437 586,654 1,310,036 3,631,507 762,674 736,153 798,825 3,162,992 366,727 178,578 412,507 1,291,132 19,835 113,957 (26,464) 121,020 101,986 77,438 74,969 356,983 2,030 (1,421) 1,421 2,030 3,095 92,124 (92,124) 10,221 5,239,962 4,026,130 4,897,738 18,961,737 5,245,467 4,595,556 4,615,103 19,539,117 374,797 909,407 747,636 3,901,886 52,047 49,170 831 143,246 5,672,312 5,554,132 5,363,570 23,584,249 1,474,591 1,973,517 2,303,648 7,414,234 623,602 1,076,197 1,509,622 3,966,561 382,342 188,215 512,662 1,343,500 223,937 194,687 130,931 773,353 176,383 201,464 156,480 687,955 35,797 29,857 39,391 155,680 0 0 0 0 5,130 6,689 (6,689) (1,374) 2,921,781 3,670,626 4,646,046 14,339,908 112,934,516 112,489,865 104,969,203 443,432,523 20,461,365 21,142,012 23,408,478 129,970,687 723,829 1,267,884 2,978,127 5,335,465 134,119,710 134,899,761 131,355,808 578,738,675 42,888,277 43,955,329 52,136,701 184,084,309 14,995,516 13,077,141 22,318,137 67,688,825 12,571,143 12,080,363 12,054,214 47,730,580 7,904,473 6,889,414 7,314,233 29,792,664 2,990,844 2,466,975 2,804,365 10,497,628 1,882,810 1,805,034 2,201,082 7,800,559 23,119,508 24,130,363 29,044,177 100,870,399 368,522 396,052 (333,400) 113,188 106,721,092 104,800,671 127,539,507 448,578,152 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 (2,313) (34,898) (67,596) (220,686) 23,666 15,954 63,720 429,086 0 0 0 0 16,213 5,364 0 27,907 120,553 43,110 63,428 266,967 1,425,000 1,425,000 1,425,000 5,700,000 909,197 857,211 1,050,780 3,696,919 0 0 0 0 2,492,316 2,311,740 2,535,332 9,900,194 7,696,293 7,618,320 7,334,954 30,488,732 357,856 418,029 472,454 1,945,345 27,434 84,281 0 160,578 8,081,583 8,120,629 7,807,408 32,594,656 1,006,995 1,255,272 2,282,968 5,687,185 775,665 668,407 1,968,277 4,059,138 80,791 81,383 139,442 379,680 592,016 564,074 615,861 2,297,863 594,879 681,096 1,139,099 3,023,432 30,076 21,474 2,847 84,474 1,104,967 1,029,336 1,219,887 4,358,046 32,500 0 24,220 32,500 4,217,890 4,301,042 7,392,602 19,922,318 2,472,922 2,824,600 2,907,550 10,593,618 0 0 312,633 312,633 35,500 35,500 0 106,433 2,508,422 2,860,100 3,220,183 11,012,684 632,230 488,739 1,059,100 2,641,790 135,806 223,252 490,963 918,901 52,334 52,729 66,016 221,595 421,564 417,293 466,777 1,723,757 217,409 325,582 789,836 1,626,999 13,580 15,407 22,305 64,872 532,976 166,067 929,267 1,769,996 0 0 0 (100,260) 2,005,899 1,689,069 3,824,265 8,867,650 11,934,083 12,927,399 8,026,552 44,767,362 310,423 390,660 383,236 1,517,859 1,657,218 601,485 894,396 3,161,620 13,901,724 13,919,544 9,304,184 49,446,841 1,903,877 1,988,353 2,533,833 8,238,775 549,491 763,868 1,747,679 3,754,989 658,651 551,999 923,153 2,962,962 3,063,362 3,078,312 3,352,894 12,551,805 (1,227,382) (1,324,886) (1,131,300) (4,709,424) 473,310 456,180 636,859 2,108,873 1,194,645 1,299,708 1,624,521 5,272,309 (1,186,294) (524,894) (48,313) 544,915 5,429,660 6,288,639 9,639,326 30,725,204 5,965,044 6,006,233 5,979,874 24,713,102 11,714,197 13,783,659 13,244,092 50,848,759 181,410 105,252 37,328 385,322 17,860,651 19,895,144 19,261,294 75,947,184 5,976,903 7,178,637 10,534,618 29,359,489 1,503,271 71,959 5,179,641 8,320,166 589,945 596,536 625,416 2,235,476 2,199,114 2,168,723 2,237,874 8,501,746 774,586 659,904 1,072,615 3,189,787 990,155 948,410 972,752 3,790,134 3,132,275 2,640,720 3,630,027 11,646,944 (197,227) 1,384,444 (1,464,289) (19,283) 14,969,023 15,649,333 22,788,653 67,024,458 2,795,648 2,811,902 2,324,633 10,659,934 558,383 1,237,780 663,491 3,333,524 73,552 29,275 48,000 368,854 3,427,583 4,078,957 3,036,124 14,362,312 1,203,921 1,098,066 1,935,623 5,363,831 444,443 399,032 975,340 2,048,280 402,414 513,315 431,905 1,696,331 370,602 310,823 364,035 1,314,723 269,202 299,446 424,555 1,314,425 18,342 18,690 22,235 76,913 430,631 414,129 381,253 1,583,210 33,591 39,681 8,706 83,146 3,173,146 3,093,184 4,543,650 13,480,859 20,320,359 20,292,451 20,657,581 81,532,467 6,884,251 6,082,866 9,018,347 30,606,689 4,048,558 2,836,607 2,592,845 11,958,126 31,253,167 29,211,924 32,268,772 124,097,282 8,417,745 9,459,488 10,623,394 37,772,878 2,257,281 2,054,356 3,588,760 9,951,846 5,024,938 4,700,122 5,086,368 19,912,354 2,897,002 3,026,509 3,411,580 12,090,335 1,137,331 1,463,552 1,708,370 5,540,310 374,692 471,302 632,420 1,850,410 4,001,665 4,387,997 4,540,103 15,879,596 6,244 6,868 (12,096) (0) 24,116,898 25,570,193 29,578,899 102,997,729 42,561,091 47,620,344 46,319,483 179,019,673 5,443,833 6,757,527 15,181,644 46,938,258 1,139,558 730,594 5,902,588 9,227,247 49,144,483 55,108,465 67,403,715 235,185,178 17,852,881 19,206,786 16,860,362 71,016,363 3,693,402 4,180,993 14,386,039 26,964,954 4,047,617 2,888,679 7,016,693 16,737,169 1,911,062 2,219,961 1,826,196 7,861,908 2,098,830 2,353,300 2,343,909 8,597,137 155,261 155,261 99,510 565,293 7,359,239 8,437,336 8,681,410 31,699,978 (288,110) (265,114) 484,127 925,197 36,830,183 39,177,203 51,698,247 164,367,999 2018 FY18 May Forecast 2018 FY18 May Forecast Q1 2018 FY18 May Forecast Q2 2018 FY18 May Forecast Q3 15,959,922 15,700,989 15,321,979 8,768,195 3,129,396 3,362,129 (1,432,415) (1,385,855) (1,541,134) 23,295,703 17,444,530 17,142,975 3,021,568 3,310,412 3,542,793 3,140,766 3,235,606 1,475,767 1,222,167 1,248,169 1,216,090 487,140 527,897 483,113 23,853 65,071 56,615 72,241 72,461 42,932 967 19,373 0 77,139 636 0 8,045,841 8,479,624 6,817,311 19,474,578 19,498,555 19,699,359 7,432,076 2,151,083 2,253,212 62,195 80,872 63,789 26,968,849 21,730,510 22,016,360 9,300,709 8,702,483 8,169,355 2,002,002 2,348,307 1,347,610 1,283,742 1,200,643 1,332,270 848,133 822,266 857,223 41,986 59,857 111,898 91,126 74,259 153,402 4,632 5,984 0 (315,687) 147,961 (50,439) 13,256,643 13,361,761 11,921,319 9,499,212 9,535,446 9,492,856 17,355,929 3,746,378 5,286,321 38,848 96,412 76,829 26,893,988 13,378,236 14,856,006 3,584,774 2,821,908 3,233,381 1,148,221 559,712 845,196 3,708,404 3,261,436 3,350,358 562,439 550,822 596,779 183,510 148,335 230,895 23,272 23,271 23,271 1,309 7,451 0 0 14,614 (11,708) 9,211,930 7,387,550 8,268,172 20,167,019 20,252,322 20,105,338 1,188,858 453,119 293,433 58,878 152,759 133,665 21,414,756 20,858,200 20,532,436 4,818,857 4,573,711 4,560,381 1,464,262 1,120,360 1,745,418 364,060 388,232 370,052 522,900 505,670 409,016 209,583 474,820 248,060 247 248 0 192 1,105 0 (46,119) 0 0 7,333,983 7,064,146 7,332,926 8,816,680 8,915,661 8,751,342 20,453,834 7,790,139 6,714,178 1,523,394 1,455,095 1,909,411 30,793,909 18,160,895 17,374,932 13,877,025 13,250,863 12,248,608 3,650,665 2,597,021 3,144,533 2,728,576 2,662,397 2,951,659 1,069,148 1,029,709 1,006,969 129,336 181,893 272,369 345,449 345,061 366,111 4,151 14,311 0 (104,254) (15,611) 59,932 21,700,094 20,065,645 20,050,181 4,696,172 5,734,232 5,509,911 918 1,095 0 8,933 25,073 17,481 4,706,022 5,760,401 5,527,392 776,170 748,669 1,163,365 196,791 148,485 298,517 233,382 240,155 237,393 0 0 0 94,825 106,329 117,516 60,555 60,476 40,719 0 13,146 0 2,573 352,714 (300,000) 1,364,297 1,669,975 1,557,510 5,353,730 4,529,920 4,378,791 341,489 372,513 395,816 8,227 23,094 16,101 5,703,447 4,925,526 4,790,708 1,203,797 1,011,041 1,339,874 301,688 416,577 582,350 534,180 594,376 495,644 293,863 308,927 370,400 143,783 187,320 74,694 89,121 89,460 83,297 0 442 0 (49,220) (19,701) 0 2,517,212 2,588,442 2,946,260 0 0 0 0 0 0 0 0 0 0 0 0 (18,591) (140) 0 (0) 0 0 (0) 0 0 295,739 313,609 325,114 (295,739) (313,491) (325,112) 0 0 0 0 0 0 0 0 0 (18,591) (23) 2 8,333,277 8,045,261 7,664,581 2,417,683 637,622 559,388 23,231 68,554 56,842 10,774,191 8,751,438 8,280,811 2,559,458 3,165,178 2,377,191 916,380 818,437 843,228 865,340 762,674 754,715 333,321 366,727 345,542 13,692 19,835 51,351 102,590 101,986 77,438 0 2,030 0 7,126 3,095 0 4,797,907 5,239,962 4,449,465 5,082,991 5,245,467 4,587,076 1,870,046 374,797 848,996 41,198 52,047 25,000 6,994,235 5,672,312 5,461,072 1,662,478 1,474,591 2,180,261 757,140 623,602 1,291,612 260,282 382,342 321,966 223,798 223,937 169,447 153,627 176,383 214,626 50,635 35,797 30,999 0 0 0 (6,504) 5,130 0 3,101,456 2,921,781 4,208,911 113,038,940 112,934,516 110,496,399 64,958,831 20,461,365 22,391,945 365,625 723,829 919,012 178,363,396 134,119,710 133,807,355 45,104,001 42,888,277 43,662,806 17,298,031 14,995,516 15,359,894 11,024,860 12,571,143 11,980,221 7,684,544 7,904,473 7,597,033 2,235,444 2,990,844 2,829,627 1,911,634 1,882,810 1,941,389 24,576,353 23,119,508 26,160,728 (317,985) 368,522 (302,215) 109,516,881 106,721,092 109,229,483 0 0 0 0 0 0 0 0 0 0 0 0 (115,879) (2,313) (37,283) 325,747 23,666 21,421 0 0 0 6,331 16,213 0 39,875 120,553 68,822 1,425,000 1,425,000 1,425,000 879,732 909,197 963,676 0 0 0 2,560,805 2,492,316 2,441,636 7,839,165 7,696,293 7,576,008 697,007 357,856 239,660 48,863 27,434 0 8,585,036 8,081,583 7,815,668 1,141,951 1,006,995 1,201,769 646,789 775,665 1,105,808 78,063 80,791 98,151 525,911 592,016 580,044 608,358 594,879 751,810 30,076 30,076 30,076 1,003,855 1,104,967 1,028,620 (24,220) 32,500 0 4,010,783 4,217,890 4,796,278 2,388,545 2,472,922 2,615,163 0 0 169,994 35,433 35,500 0 2,423,979 2,508,422 2,785,157 461,721 632,230 686,472 68,880 135,806 252,716 50,515 52,334 59,031 418,123 421,564 426,896 294,172 217,409 436,041 13,580 13,580 17,972 141,686 532,976 479,115 (100,260) 0 0 1,348,417 2,005,899 2,358,243 11,879,328 11,934,083 11,964,879 433,541 310,423 383,235 8,521 1,657,218 298,132 12,321,390 13,901,724 12,646,246 1,812,713 1,903,877 2,135,964 693,952 549,491 1,158,531 829,159 658,651 574,900 3,057,237 3,063,362 3,007,960 (1,025,856) (1,227,382) (1,063,667) 542,524 473,310 463,940 1,153,436 1,194,645 1,544,620 2,304,416 (1,186,294) (367,311) 9,367,579 5,429,660 7,454,938 6,761,952 5,965,044 6,608,122 12,106,811 11,714,197 13,524,766 61,332 181,410 37,328 18,930,095 17,860,651 20,170,216 5,669,331 5,976,903 7,770,218 1,565,295 1,503,271 1,462,276 423,579 589,945 746,678 1,896,035 2,199,114 2,102,107 682,681 774,586 824,141 878,818 990,155 1,012,703 2,243,923 3,132,275 2,984,991 257,788 (197,227) 189,740 13,617,450 14,969,023 17,092,853 2,727,752 2,795,648 2,799,369 873,869 558,383 1,079,380 218,028 73,552 50,155 3,819,649 3,427,583 3,928,904 1,126,221 1,203,921 1,285,144 229,465 444,443 422,758 348,696 402,414 386,179 269,263 370,602 338,000 321,222 269,202 313,556 17,646 18,342 17,648 357,198 430,631 360,500 1,168 33,591 0 2,670,879 3,173,146 3,123,785 20,262,077 20,320,359 20,406,605 8,621,226 6,884,251 7,809,869 2,480,116 4,048,558 2,617,214 31,363,419 31,253,167 30,833,688 9,272,251 8,417,745 9,419,010 2,051,450 2,257,281 2,638,341 5,100,926 5,024,938 4,595,106 2,755,244 2,897,002 3,605,951 1,231,058 1,137,331 1,623,552 371,995 374,692 451,861 2,949,831 4,001,665 5,100,067 (1,016) 6,244 0 23,731,739 24,116,898 27,433,888 42,518,755 42,561,091 46,757,633 19,555,254 5,443,833 7,206,220 1,454,507 1,139,558 1,443,182 63,528,515 49,144,483 55,407,035 17,096,334 17,852,881 19,353,390 4,704,520 3,693,402 5,504,498 2,784,179 4,047,617 3,410,909 1,904,689 1,911,062 2,023,078 1,801,098 2,098,830 2,346,913 155,261 155,261 188,651 7,221,992 7,359,239 7,708,501 994,293 (288,110) (238,410) 36,662,366 36,830,183 40,297,531 2018 FY18 May Forecast Q4 2018 FY18 May Forecast Full Year 14,965,440 61,948,330 4,602,419 19,862,139 (1,646,537) (6,005,941) 17,921,321 75,804,529 4,023,920 13,898,693 2,820,858 10,672,997 1,288,480 4,974,906 161,494 1,659,645 64,978 210,517 40,464 228,098 0 20,339 0 77,775 8,400,194 31,742,970 19,237,895 77,910,388 1,705,719 13,542,090 28,322 235,178 20,971,937 91,687,655 8,569,411 34,741,958 1,870,784 7,568,703 1,392,545 5,209,201 871,690 3,399,313 159,123 372,865 167,349 486,137 (10,616) 0 127,000 (91,165) 13,147,288 51,687,011 9,889,015 38,416,529 4,396,630 30,785,257 34,112 246,201 14,319,757 69,447,986 2,997,827 12,637,890 1,702,637 4,255,766 3,391,728 13,711,926 569,332 2,279,373 211,252 773,992 23,271 93,085 0 8,760 0 2,907 8,896,048 33,763,699 15,944,128 76,468,807 509,580 2,444,990 59,347 404,649 16,513,055 79,318,447 6,178,509 20,131,458 1,563,886 5,893,926 592,165 1,714,509 393,945 1,831,531 256,486 1,188,949 61,140 61,635 0 1,297 0 (46,119) 9,046,132 30,777,187 8,813,425 35,297,109 7,362,382 42,320,534 1,979,383 6,867,283 18,155,191 84,484,926 11,795,188 51,171,683 1,813,852 11,206,071 2,818,867 11,161,500 1,088,650 4,194,476 264,360 847,958 366,111 1,422,732 0 18,462 59,932 (1) 18,206,960 80,022,880 5,393,949 21,334,265 0 2,013 7,761 59,248 5,401,710 21,395,525 1,744,235 4,432,440 383,656 1,027,449 420,393 1,131,322 0 0 109,103 427,774 37,699 199,450 0 13,146 0 55,288 2,695,087 7,286,868 4,428,280 18,690,721 316,816 1,426,634 2,248,046 2,295,468 6,993,141 22,412,823 3,991,252 7,545,964 886,403 2,187,018 841,309 2,465,510 422,278 1,395,468 105,191 510,989 85,583 347,460 0 442 81,678 12,757 6,413,695 14,465,609 0 0 0 0 0 0 0 0 0 (18,731) 0 (0) 0 (0) 229,110 1,163,571 (229,111) (1,163,453) 0 0 0 0 0 0 (1) (18,613) 7,597,343 31,640,463 558,428 4,173,122 25,238 173,865 8,181,010 35,987,450 2,284,025 10,385,852 1,053,462 3,631,507 780,264 3,162,992 345,542 1,391,132 36,141 121,020 74,969 356,983 0 2,030 0 10,221 4,574,403 19,061,737 4,623,583 19,539,117 808,047 3,901,886 25,000 143,246 5,456,631 23,584,249 2,096,904 7,414,234 1,294,207 3,966,561 378,911 1,343,500 156,171 773,353 143,319 687,955 38,249 155,680 0 0 0 (1,374) 4,107,760 14,339,908 105,778,520 442,248,374 21,774,397 129,586,538 2,792,653 4,801,118 130,345,569 576,636,030 54,637,427 186,292,511 20,024,812 67,678,253 12,548,155 48,124,379 7,582,152 30,768,202 2,936,303 10,992,218 2,064,726 7,800,558 28,599,673 102,456,261 364,006 112,328 128,757,254 454,224,710 0 0 0 0 0 0 0 0 (67,596) (223,071) 182,235 553,069 0 0 0 22,544 70,093 299,343 1,425,000 5,700,000 1,031,942 3,784,547 0 0 2,641,673 10,136,431 7,377,266 30,488,732 735,103 2,029,626 0 76,297 8,112,368 32,594,655 2,311,090 5,661,804 1,536,796 4,065,058 84,937 341,942 599,892 2,297,863 1,050,585 3,005,633 2,847 93,076 1,083,486 4,220,929 24,220 32,500 6,693,855 19,718,806 3,419,986 10,896,617 178,139 348,133 0 70,933 3,598,125 11,315,683 874,170 2,654,593 452,121 909,523 61,116 222,996 457,192 1,723,775 677,669 1,625,292 19,805 64,937 808,417 1,962,195 0 (100,260) 3,350,491 9,063,051 8,026,556 43,804,845 383,235 1,510,434 894,396 2,858,267 9,304,187 48,173,546 2,382,330 8,234,884 1,353,015 3,754,989 898,680 2,961,391 3,422,658 12,551,217 (1,398,085) (4,714,989) 629,099 2,108,873 1,379,608 5,272,309 (205,896) 544,915 8,461,411 30,713,588 5,505,063 24,840,180 13,796,014 51,141,788 37,328 317,399 19,338,405 76,299,367 10,248,203 29,664,655 3,054,484 7,585,325 836,492 2,596,694 2,146,312 8,343,568 912,241 3,193,649 1,012,332 3,894,008 2,810,680 11,171,868 339,632 589,933 21,360,375 67,039,700 2,604,632 10,927,400 820,620 3,332,253 26,845 368,580 3,452,097 14,628,232 1,636,691 5,251,977 927,955 2,024,622 551,424 1,688,713 338,000 1,315,865 624,888 1,528,868 17,648 71,284 417,500 1,565,829 0 34,759 4,514,107 13,481,917 20,587,944 81,576,985 9,307,165 32,622,510 2,751,897 11,897,785 32,647,006 126,097,280 10,663,872 37,772,878 3,004,774 9,951,846 5,191,383 19,912,353 3,032,138 12,290,335 1,573,393 5,565,333 451,861 1,650,410 3,837,348 15,888,911 (5,228) (0) 27,749,541 103,032,066 45,782,184 177,619,663 16,232,950 48,438,257 5,190,000 9,227,247 67,205,134 235,285,167 16,713,758 71,016,363 13,312,534 27,214,954 3,597,055 13,839,761 2,023,078 7,861,908 2,484,628 8,731,469 66,120 565,293 8,361,833 30,651,566 457,423 925,197 47,016,430 160,806,510 _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \ UK France Iberia Italy GSA MENA TIG EM Nordic Benelux EMEARCIS RCIS ANZ GC SEA India Korea Japan LATAM System UK and 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Iberia.. Italy.. Germany, Switzerland & Austria MENA.. TIG.. Emerging Markets Nordics & Baltics Benelux.. EMEA (ex Russia-CIS) Russia-CIS.. Australia & New Zealand… Greater China South East Asia India Korea…. Japan Latin America. 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India_Depreciation India_Allocations India_Bad Debt India_Expense Korea…._Subscription Korea…._Advertising Korea…._Other Revenue Korea…._Revenue Korea…._Programming Korea…._Marketing Korea…._Technical Korea…._Labour Korea…._Other Overhead Korea…._Depreciation Korea…._Allocations Korea…._Bad Debt Korea…._Expense Japan_Subscription Japan_Advertising Japan_Other Revenue Japan_Revenue Japan_Programming Japan_Marketing Japan_Technical Japan_Labour Japan_Other Overhead Japan_Depreciation Japan_Allocations Japan_Bad Debt Japan_Expense Latin America._Subscription Latin America._Advertising Latin America._Other Revenue Latin America._Revenue Latin America._Programming Latin America._Marketing Latin America._Technical Latin America._Labour Latin America._Other Overhead Latin America._Depreciation Latin America._Allocations Latin America._Bad Debt Latin America._Expense _ UK and Ireland…_Revenue France.._Revenue Iberia.._Revenue Italy.._Revenue Germany, Switzerland & Austria_Revenue 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MENA.._Programming MENA.._Marketing MENA.._Technical MENA.._Labour MENA.._Other Overhead MENA.._Depreciation MENA.._Allocations MENA.._Bad Debt MENA.._Expense TIG.._Subscription TIG.._Advertising TIG.._Other Revenue TIG.._Revenue TIG.._Programming TIG.._Marketing TIG.._Technical TIG.._Labour TIG.._Other Overhead TIG.._Depreciation TIG.._Allocations TIG.._Bad Debt TIG.._Expense Emerging Markets_Subscription Emerging Markets_Advertising Emerging Markets_Other Revenue Emerging Markets_Revenue Emerging Markets_Programming Emerging Markets_Marketing Emerging Markets_Technical Emerging Markets_Labour Emerging Markets_Other Overhead Emerging Markets_Depreciation Emerging Markets_Allocations Emerging Markets_Bad Debt Emerging Markets_Expense Nordics & Baltics_Subscription Nordics & Baltics_Advertising Nordics & Baltics_Other Revenue Nordics & Baltics_Revenue Nordics & Baltics_Programming Nordics & Baltics_Marketing Nordics & Baltics_Technical Nordics & Baltics_Labour Nordics & Baltics_Other Overhead Nordics & Baltics_Depreciation Nordics & Baltics_Allocations Nordics & Baltics_Bad Debt Nordics & Baltics_Expense Benelux.._Subscription Benelux.._Advertising Benelux.._Other Revenue Benelux.._Revenue Benelux.._Programming Benelux.._Marketing Benelux.._Technical Benelux.._Labour Benelux.._Other Overhead Benelux.._Depreciation Benelux.._Allocations Benelux.._Bad Debt Benelux.._Expense EMEA (ex Russia-CIS)_Subscription EMEA (ex Russia-CIS)_Advertising EMEA (ex Russia-CIS)_Other Revenue EMEA (ex Russia-CIS)_Revenue EMEA (ex Russia-CIS)_Programming EMEA (ex Russia-CIS)_Marketing EMEA (ex Russia-CIS)_Technical EMEA (ex Russia-CIS)_Labour EMEA (ex Russia-CIS)_Other Overhead EMEA (ex Russia-CIS)_Depreciation EMEA (ex Russia-CIS)_Allocations EMEA (ex Russia-CIS)_Bad Debt EMEA (ex Russia-CIS)_Expense Russia-CIS.._Subscription Russia-CIS.._Advertising Russia-CIS.._Other Revenue Russia-CIS.._Revenue Russia-CIS.._Programming Russia-CIS.._Marketing Russia-CIS.._Technical Russia-CIS.._Labour Russia-CIS.._Other Overhead Russia-CIS.._Depreciation Russia-CIS.._Allocations Russia-CIS.._Bad Debt Russia-CIS.._Expense Australia & New Zealand…_Subscription Australia & New Zealand…_Advertising Australia & New Zealand…_Other Revenue Australia & New Zealand…_Revenue Australia & New Zealand…_Programming Australia & New Zealand…_Marketing Australia & New Zealand…_Technical Australia & New Zealand…_Labour Australia & New Zealand…_Other Overhead Australia & New Zealand…_Depreciation Australia & New Zealand…_Allocations Australia & New Zealand…_Bad Debt Australia & New Zealand…_Expense Greater China_Subscription Greater China_Advertising Greater China_Other Revenue Greater China_Revenue Greater China_Programming Greater China_Marketing Greater China_Technical Greater China_Labour Greater China_Other Overhead Greater China_Depreciation Greater China_Allocations Greater China_Bad Debt Greater China_Expense South East Asia_Subscription South East Asia_Advertising South East Asia_Other Revenue South East Asia_Revenue South East Asia_Programming South East Asia_Marketing South East Asia_Technical South East Asia_Labour South East Asia_Other Overhead South East Asia_Depreciation South East Asia_Allocations South East Asia_Bad Debt South East Asia_Expense India_Subscription India_Advertising India_Other Revenue India_Revenue India_Programming India_Marketing India_Technical India_Labour India_Other Overhead India_Depreciation India_Allocations India_Bad Debt India_Expense Korea…._Subscription Korea…._Advertising Korea…._Other Revenue Korea…._Revenue Korea…._Programming Korea…._Marketing Korea…._Technical Korea…._Labour Korea…._Other Overhead Korea…._Depreciation Korea…._Allocations Korea…._Bad Debt Korea…._Expense Japan_Subscription Japan_Advertising Japan_Other Revenue Japan_Revenue Japan_Programming Japan_Marketing Japan_Technical Japan_Labour Japan_Other Overhead Japan_Depreciation Japan_Allocations Japan_Bad Debt Japan_Expense Latin America._Subscription Latin America._Advertising Latin America._Other Revenue Latin America._Revenue Latin America._Programming Latin America._Marketing Latin America._Technical Latin America._Labour Latin America._Other Overhead Latin America._Depreciation Latin America._Allocations Latin America._Bad Debt Latin America._Expense _

Question 1 Input: Input your age: Input your younger sibling’s age: Question Can you vote for president? For how many years have you been eligible to vote? Are both me and my younger sibling eligible to vote? 25.0 17.0 Answer IF Formula Input: Input expected company revenue: Input actual company revenue: 300.0 400.0 Input expected company EBITDA: Input actual company EBITDA: 50.0 60.0 Question Did the company exceed revenue expectations? Did the company exceed both revenue and EBITDA expectations? IFERROR – is “NM” Net earnings Shares outstanding Earnings per share (EPS) Answer 2014 2015 $1,500.0 $1,850.0 0.0 50.0 Combine IF and AND functions to answer this question: Criteria: If on the job 5 years or more AND received an 8 or higher for a performance rating, output a salary reflecting a 5% raise, otherwise, output “No raise” Employee Age Salary Years at Company Performance New Rating salary A 25.0 $53,140.0 0.0 10.0 B 48.0 $110,662.0 11.0 2.0 C 48.0 $117,294.0 17.0 8.0 D 34.0 $114,373.0 19.0 10.0 Combine IF and OR functions to answer this question: Criteria: If on the job 5 years or more OR received an 8 or higher for a performance rating, output a salary reflecting a 5% raise, otherwise, output “No raise” Employee Age Salary Years at Company Performance New Rating salary A 25.0 $53,140.0 0.0 10.0 B 48.0 $110,662.0 11.0 2.0 C 48.0 $117,294.0 17.0 8.0 D 34.0 $114,373.0 19.0 10.0 Input Company Name: Tax rate Income Statement for Lemonade Co. Revenues Cost of Goods Sold Gross Profit Operating costs Pretax Profit Taxes Net Profit Basic Shares Outstanding Basic EPS Exit year Select a metric: Lemonade Co. 35.0% 12/31/14 12/31/15 12/31/16 12/31/17 12/31/18 800.0 1,000.0 1,500.0 2,500.0 4,500.0 300.0 500.0 1,200.0 3,400.0 4,000.0 500.0 500.0 300.0 (900.0) 500.0 35.0 45.0 55.0 65.0 78.0 465.0 455.0 245.0 (965.0) 422.0 0.0 0.0 0.0 0.0 0.0 465.0 455.0 245.0 (965.0) 422.0 100.0 110.0 115.0 120.0 125.0 $4.65 $4.14 $2.13 ($8.04) $3.38 12/31/2016 Gross Profit Solution: Combining formulas to make more durable formulas without hardcoding Combination formulas: Accomplish using: HLOOKUP w/ MATCH VLOOKUP w/MATCH OFFSET w/ MATCH INDEX w/ MATCH CHOOSE w/ MATCH MATCH – the third argument – match type 0 = Exact match. You’ll almost always input 0 for an exact match. 1 or omitted = Excel will find the largest value that is less than or equal to the lookup value, as long as data is in ascending order -1 = Excel will find the smallest value that is greater than or equal to the lookup value as long as data is in descending order HLOOKUP / VLOOKUP – the fourth argument – range lookup TRUE (1 or omitted): If an exact match is not found, the next largest value that is less than lookup_value is returned. FALSE (0): Only an exact match will be returned. If no exact match, will return #N/A Important: For text lookups, an exact match (0) is required 2014 2015 Output: 2016 #REF! 2017 2018

Search Engine Enter Unit # to see rent Rental Price Unit # 101 102 103 104 105 106 107 108 109 110 201 202 203 204 205 206 207 208 209 210 301 302 303 304 305 306 307 Exploring Constants for Formulas 101 Apartment Complex Rolling Meadows Rolling Meadows Rolling Meadows Rolling Meadows Rolling Meadows Rolling Meadows Rolling Meadows Rolling Meadows Rolling Meadows Rolling Meadows Rolling Meadows Rolling Meadows Rolling Meadows Rolling Meadows Rolling Meadows Rolling Meadows Rolling Meadows Rolling Meadows Rolling Meadows Rolling Meadows Lakeview Apartments Lakeview Apartments Lakeview Apartments Lakeview Apartments Lakeview Apartments Lakeview Apartments Lakeview Apartments Comparison Date No. of Years Since Remodel Pet Deposit 2 bedroom newer Pet Deposit other # Bed 1 1 2 2 3 3 2 2 3 3 1 1 2 2 3 3 2 2 3 3 1 1 1 1 2 2 2 Rental Price $ 950 $ 950 $ 1.100 $ 1.100 $ 1.500 $ 1.500 $ 1.100 $ 1.100 $ 1.500 $ 1.500 $ 875 $ 875 $ 995 $ 995 $ 1.050 $ 1.050 $ 995 $ 995 $ 1.050 $ 1.050 $ 875 $ 875 $ 900 $ 900 $ 1.200 $ 1.200 $ 1.200 Occupied Yes Yes No Yes No Yes No Yes No Yes Yes Yes Yes No Yes No Yes Yes No Yes No No No Yes No Yes Yes Summary Last Remodel 4/1/2004 3/1/2013 11/15/2005 10/1/2015 10/1/2015 6/15/2004 11/1/2015 8/15/2009 8/15/2009 10/4/2006 4/13/2016 3/1/2013 4/1/2004 4/1/2010 8/15/2011 7/1/2005 8/1/2015 8/1/2015 8/1/2015 11/4/2006 4/15/2008 5/1/2015 5/5/2010 5/5/2010 10/4/2006 6/15/2018 6/30/2008 Years Since Remodel 1/1/2018 10 $275 $200 Pet Deposit Recommendation 20190712180738exploring_e07_grader_h1_apartment 308 401 402 403 404 405 406 407 408 501 502 503 504 505 506 507 601 602 603 604 605 606 607 Exploring Lakeview Apartments Mountaintop View Mountaintop View Mountaintop View Mountaintop View Mountaintop View Mountaintop View Mountaintop View Mountaintop View Sunset Valley Sunset Valley Sunset Valley Sunset Valley Sunset Valley Sunset Valley Sunset Valley Oak Tree Living Oak Tree Living Oak Tree Living Oak Tree Living Oak Tree Living Oak Tree Living Oak Tree Living 2 1 2 3 1 2 3 2 2 1 1 1 1 2 2 2 1 1 2 2 3 3 3 $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ 1.200 875 950 1.200 875 950 1.200 975 975 875 875 875 875 1.100 1.100 1.100 1.500 1.500 1.200 1.200 2.000 2.000 2.000 No No No Yes No Yes No Yes Yes Yes No No Yes No Yes No Yes Yes No Yes No Yes No Summary 9/30/2007 7/1/2005 8/1/2015 5/5/2010 10/4/2006 6/15/2018 4/1/2004 3/1/2013 11/15/2005 10/1/2015 8/1/2015 8/1/2015 7/2/2003 7/2/2003 10/10/2010 10/10/2010 8/15/2004 11/1/2000 8/15/2004 12/1/2003 11/30/2000 3/30/2002 3/30/2002 20190712180738exploring_e07_grader_h1_apartment Criteria Range Unit # Apartment Complex # Bed Rental Price Occupied Last Remodel Years Since Remodel Recommendation Last Remodel 4/1/2004 3/1/2013 11/15/2005 10/1/2015 10/1/2015 6/15/2004 11/1/2015 8/15/2009 8/15/2009 10/4/2006 4/13/2016 3/1/2013 4/1/2004 4/1/2010 8/15/2011 7/1/2005 Years Since Remodel 13,75 4,83 12,13 2,25 2,25 13,54 2,17 8,38 8,38 11,24 1,72 4,83 13,75 7,75 6,38 12,50 Recommendation No Change No Change Need to Remodel No Change No Change No Change No Change No Change No Change No Change No Change No Change No Change No Change No Change Need to Remodel Database Statistics No. of Apts. to Remodel Value of Lost Rent Year of Oldest Remodel List of Rental Property Unit # 101 102 103 104 105 106 107 108 109 110 201 202 203 204 205 206 Exploring Apartment Complex Rolling Meadows Rolling Meadows Rolling Meadows Rolling Meadows Rolling Meadows Rolling Meadows Rolling Meadows Rolling Meadows Rolling Meadows Rolling Meadows Rolling Meadows Rolling Meadows Rolling Meadows Rolling Meadows Rolling Meadows Rolling Meadows # Bed 1 1 2 2 3 3 2 2 3 3 1 1 2 2 3 3 Rental Price 950 950 1.100 1.100 1.500 1.500 1.100 1.100 1.500 1.500 875 875 995 995 1.050 1.050 Occupied Yes Yes No Yes No Yes No Yes No Yes Yes Yes Yes No Yes No Database 20190712180738exploring_e07_grader_h1_apartment 207 208 209 210 301 302 303 304 305 306 307 308 401 402 403 404 405 406 407 408 501 502 503 504 505 506 507 601 602 603 604 605 606 607 Exploring Rolling Meadows Rolling Meadows Rolling Meadows Rolling Meadows Lakeview Apartments Lakeview Apartments Lakeview Apartments Lakeview Apartments Lakeview Apartments Lakeview Apartments Lakeview Apartments Lakeview Apartments Mountaintop View Mountaintop View Mountaintop View Mountaintop View Mountaintop View Mountaintop View Mountaintop View Mountaintop View Sunset Valley Sunset Valley Sunset Valley Sunset Valley Sunset Valley Sunset Valley Sunset Valley Oak Tree Living Oak Tree Living Oak Tree Living Oak Tree Living Oak Tree Living Oak Tree Living Oak Tree Living 2 2 3 3 1 1 1 1 2 2 2 2 1 2 3 1 2 3 2 2 1 1 1 1 2 2 2 1 1 2 2 3 3 3 995 995 1.050 1.050 875 875 900 900 1.200 1.200 1.200 1.200 875 950 1.200 875 950 1.200 975 975 875 875 875 875 1.100 1.100 1.100 1.500 1.500 1.200 1.200 2.000 2.000 2.000 Database Yes Yes No Yes No No No Yes No Yes Yes No No No Yes No Yes No Yes Yes Yes No No Yes No Yes No Yes Yes No Yes No Yes No 8/1/2015 8/1/2015 8/1/2015 11/4/2006 4/15/2008 5/1/2015 5/5/2010 5/5/2010 10/4/2006 6/15/2018 6/30/2008 9/30/2007 7/1/2005 8/1/2015 5/5/2010 10/4/2006 6/15/2018 4/1/2004 3/1/2013 11/15/2005 10/1/2015 8/1/2015 8/1/2015 7/2/2003 7/2/2003 10/10/2010 10/10/2010 8/15/2004 11/1/2000 8/15/2004 12/1/2003 11/30/2000 3/30/2002 3/30/2002 2,42 2,42 2,42 11,16 9,71 2,67 7,66 7,66 11,24 0,46 9,50 10,25 12,50 2,42 7,66 11,24 0,46 13,75 4,83 12,13 2,25 2,42 2,42 14,50 14,50 7,23 7,23 13,38 17,17 13,38 14,08 17,09 15,75 15,75 No Change No Change No Change No Change No Change No Change No Change No Change Need to Remodel No Change No Change Need to Remodel Need to Remodel No Change No Change Need to Remodel No Change Need to Remodel No Change No Change No Change No Change No Change No Change Need to Remodel No Change No Change No Change No Change Need to Remodel No Change Need to Remodel No Change Need to Remodel 20190712180738exploring_e07_grader_h1_apartment Input Area Complex Cost Down Payment # of Pmts per Year Years APR 1st Payment Date $ 1.850.000,00 $ 750.000,00 12 30 4,75% 3/1/2018 Payment # 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 Exploring Summary Calculations Loan Amount No. Periods Monthly Rate Monthly Payment Total Interest Paid Payment Date Beginning Balance What If Collect Monthly Rent # of Units in Complex PV of Future Rent Interest Paid Loan Principal Payment $2.000 8 Ending Balance 20190712180738exploring_e07_grader_h1_apartment 24 Exploring Loan 20190712180738exploring_e07_grader_h1_apartment Grader – Instructions Excel 2016 Project EX16_XL_CH07_GRADER_CAP_HW – Apartment Complex 1.9 Project Description: You own five apartment complexes. You created a dataset listing the apartment numbers, apartment complex names, number of bedrooms, rental price, whether the apartment is occupied or not, and the date the apartment was last remodeled. You want to insert some functions to perform calculations to help you decide which apartments need to be remodeled. To focus on the apartments that need to be remodeled, you will use advanced filtering and database functions for your analysis. Finally, you are considering purchasing a sixth apartment complex. You will perform some financial calculations and analysis to help you decide if you will purchase the complex. Steps to Perform: Step Points Possible Instructions 1 Open exploring_e07_grader_h1_Apartment.xlsx and save it as exploring_e07_grader_h1_Apartment_LastFirst. 0 2 In cell G8 in the Summary worksheet, insert a date function to calculate the number of years between 1/1/2018 in cell H2 and the last remodel date in the Last Remodel column (cell F8). Use relative and mixed references correctly. Copy the function to the range G9:G57. Unit 101 was last remodeled 13.75 years ago. Ensure that the function you use displays that result. 6 3 In cell H8, insert a nested logical function to display the required pet deposit for each unit. If the unit has two or more bedrooms (C8) AND was remodeled less than 10 years ago (cell H3), the deposit is $275 (cell H4); if not, the deposit is $200 (cell H5). Use relative and mixed references correctly. The pet deposit for Unit 101 is $200. 5 4 In cell I8, enter a nested logical function to display Need to Remodel if the apartment is unoccupied (No) AND was last remodeled more than 10 years ago (H3). For all other apartments, display No Change. Although Unit 101 was last remodeled over 10 years ago, the recommendation is No Change because the unit is occupied. 5 5 Copy the functions in the range H8:I8 to the range H9:I57. 2 6 In cell B3 insert a nested MATCH function within an INDEX function that will look up the rental price in column D using the apartment number referenced in cell B2. With 101 entered in cell B2, the lookup function displays $950.00. 5 7 In the Database sheet, enter conditions in the criteria range for unoccupied two- and threebedroom apartments that need to be remodeled. Enter criteria as text only, without use of quotation marks. Be sure to enter the criteria separately in rows 3 and 4. 6 8 Apply an advanced filter based on the criteria range (A2:H4). Filter the existing database (range A15:H65) in place. Nine apartments meet the advanced filter conditions. 5 9 In cell C8, use the DCOUNTA database function to calculate the number of apartments that need to be remodeled based on the advanced filter you created. 5 Created On: 07/05/2019 1 EX16_XL_CH07_GRADER_CAP_HW – Apartment Complex 1.9 Grader – Instructions Step Excel 2016 Project Points Possible Instructions 10 In cell C9, enter a database function to calculate the total value of monthly rent lost for the apartments that need to be remodeled based on the advanced filter you created. 5 11 In cell C10, enter a database function to display the date of the apartment that had the oldest remodel date based on the filtered data. Format the result with Short Date format. 5 12 In the Loan sheet, insert formulas in the range E2:E4 to calculate the loan amount, the number of payment periods, and the monthly interest rate, respectively. Use cell references in all formulas. 6 13 In cell E5, enter a financial function to calculate the monthly payment. In cell E6, insert a financial function to calculate the cumulative total interest paid throughout the loan. Make sure the results display as positive numbers. 8 14 In cell C11, enter a formula to reference the date stored in cell B7. Insert a nested function in cell C12 to calculate the date for the next payment. Nest the YEAR, MONTH, and DAY functions within the DATE function. Add 1 to the month result. Copy the function to the range C13:C34. 6 15 In cell D11, enter a formula to reference the value stored in cell E2. Insert a formula in cell D12 that references the ending balance for the previous payment row (G11). Copy the formula in D12 to the range D13:D34. 5 16 In cell E11, enter a financial function to calculate the interest paid. Copy the formula to the range E12:E34. The result should be a positive value. 6 17 In cell F11, enter a financial function to calculate the principal payment. Copy the function to the range F12:F34. The result should be a positive value. 6 18 In cell G11, enter a formula to calculate the ending balance. Copy the formula to the range G12:G34. Adjust the width of column G, if needed, to display the values. Select the range D11:G34 and apply Accounting Number Format. 6 19 In cell I4 insert a financial function to calculate the present value of the total monthly rent you will collect for the 8 units for 30 years. Use the number of periods and monthly rate in the Summary Calculations section and the cell references in the What If section. The result should be a positive value. 5 20 In the Loan sheet, set 0.5″ left and right margins and repeat row 10 on all pages. 3 21 Save and close the workbook, and submit the file as directed. 0 Total Points Created On: 07/05/2019 2 100 EX16_XL_CH07_GRADER_CAP_HW – Apartment Complex 1.9

Conduct a simulated “Training Video Conference Call”. The intent of this presentation is to conduct a 5 min training session on a piece of software of the student’s choice. However the software does not have to be engineering related but must be class room appropriate. Finally the training presentation will be accompanied by a supplementary instructional document. The intent of this document is to simulate a hand out supplied to a work group audience for reference BOTH during the training and after as reference material that a co-worker could go back to when they try to use the software that they were training on. There is no page requirement for the instructions but they are expected to be thorough and have the appropriate visual aids to be used as a stand alone set of instructions.