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The purpose of this note is to illustrate the use of Microsoft Excel functions for generating descriptive statistics for continuous data. These functions are common when analyzing data to provide insights for decision making. The note includes practice exercises and their solutions, and a supporting Excel workbook for students.

Student spreadsheet for case W16411.

Student spreadsheet for case W16413.

Student spreadsheet for case W16415.

Student spreadsheet for case W16417.

Student spreadsheet for case W16419.

For several years, a credit card holder had been using a cash-back rewards credit card issued by a major credit card company. He received an email from his mobile phone provider, letting him know that the company was introducing a new rewards card with lower rewards but also a lower annual fee than his current card. The credit card user suspected there might be a level of spending at which one card was preferable to the other, but he thought it might be difficult to find that level because of the structure of the reward tiers offered by his existing card. He also wondered whether the new card would have the same convenience and protections as his old one. How could he evaluate these other factors?

The purpose of this note is to give a brief introduction to dynamic programming. The note introduces dynamic programming terminology and notation and provides motivation for why these problems are difficult to solve. Five examples illustrate how dynamic programming can be applied in a variety of settings.

The purpose of this note is to give a brief introduction to dynamic programming. The note introduces dynamic programming terminology and notation and provides motivation for why these problems are difficult to solve. Five examples illustrate how dynamic programming can be applied in a variety of settings.

A planning analyst at Cancer Care Ontario has been tasked to recommend a strategy for allocating new linear accelerator capacity to the province’s cancer treatment centres over a five-year period. Because the introduction of additional capacity requires the investment of capital resources and long implementation timelines, accurate and timely predictions are critical to the treatment of cancer patients. The planning analyst needs to devise an allocation strategy that will ensure quality radiation treatment across the province.

A planning analyst at Cancer Care Ontario has been tasked to recommend a strategy for allocating new linear accelerator capacity to the province's cancer treatment centres over a five-year period. Because the introduction of additional capacity requires the investment of capital resources and long implementation timelines, accurate and timely predictions are critical to the treatment of cancer patients. The planning analyst needs to devise an allocation strategy that will ensure quality radiation treatment across the province.

Spreadsheet supplement for case W15491.

The purpose of this note is to illustrate the use of Microsoft Excel's Goal Seek feature. The technical note includes practice exercises and their solutions, and a supporting Excel workbook for students.

The newly appointed director of Surgical Business Analytics has been charged with the task of improving predictions of surgical case volume at Vanderbilt University Medical Center in Nashville, Tennessee. He is provided with 48 weeks of elective surgery schedule data that give the number of surgeries booked on specific dates prior to the surgery day and the actual number performed. Variation in daily operating room volumes is a major problem because of the mismatch in timing between when the staff schedules are made and when the final demand is known (usually the day before). This uncertainty creates staffing challenges for all support and ancillary services, including nurses, orderlies, anesthesiologists, the recovery room, pathology, radiology and the sterile cart centre. Can he develop a method to improve surgical case volume prediction that is actionable in a managerially useful time frame? How can he engage and approach stakeholders who may often consider "analytics," "data analysis" and "computations" as a black hole?

The newly appointed director of Surgical Business Analytics has been charged with the task of improving predictions of surgical case volume at Vanderbilt University Medical Center in Nashville, Tennessee. He is provided with 48 weeks of elective surgery schedule data that give the number of surgeries booked on specific dates prior to the surgery day and the actual number performed. Variation in daily operating room volumes is a major problem because of the mismatch in timing between when the staff schedules are made and when the final demand is known (usually the day before). This uncertainty creates staffing challenges for all support and ancillary services, including nurses, orderlies, anesthesiologists, the recovery room, pathology, radiology and the sterile cart centre. Can he develop a method to improve surgical case volume prediction that is actionable in a managerially useful time frame? How can he engage and approach stakeholders who may often consider "analytics," "data analysis" and "computations" as a black hole?

The C&D Hotel, the first five-star deluxe hotel in Xiamen, a coastal city in China, needs to improve its service delivery process. In particular, the hotel’s customer service manager needs to present her plans for handling some recent customer complaints and decide how to compensate hotel guests for errors that have occurred during service delivery.

The C&D Hotel, the first five-star deluxe hotel in Xiamen, a coastal city in China, needs to improve its service delivery process. In particular, the hotel's customer service manager needs to present her plans for handling some recent customer complaints and decide how to compensate hotel guests for errors that have occurred during service delivery.

In late October 2009, the U.S. Preventive Services Task Force (USPSTF), an independent panel of primary care experts, was preparing to release their updated guidelines for the use of screening mammograms, which were given to women in an attempt to detect evidence of breast cancer at a treatable stage. The new guidelines, based on rigorous scientific research and tests, now recommended routine screening starting at age 50 rather than at age 40. The challenge the USPSTF faced was that this shift in the recommended starting age was likely to spark significant debate among medical professionals and in the press. Also available is the supplement 9B14M021.

In late October 2009, the U.S. Preventive Services Task Force (USPSTF), an independent panel of primary care experts, was preparing to release their updated guidelines for the use of screening mammograms, which were given to women in an attempt to detect evidence of breast cancer at a treatable stage. The new guidelines, based on rigorous scientific research and tests, now recommended routine screening starting at age 50 rather than at age 40. The challenge the USPSTF faced was that this shift in the recommended starting age was likely to spark significant debate among medical professionals and in the press. Use with 9B14M020.

In late October 2009, the U.S. Preventive Services Task Force (USPSTF), an independent panel of primary care experts, was preparing to release their updated guidelines for the use of screening mammograms, which were given to women in an attempt to detect evidence of breast cancer at a treatable stage. The new guidelines, based on rigorous scientific research and tests, now recommended routine screening starting at age 50 rather than at age 40. The challenge the USPSTF faced was that this shift in the recommended starting age was likely to spark significant debate among medical professionals and in the press.