Burlington Northern (A)

Janice H. Hammond

Case | HBS Case Collection | April 1989 (Revised August 1989)

Burlington Northern (A)

Abstract

Describes the forces that led to the development of a logistics analysis program by the Burlington Northern Railroad. The first half of the case describes changes in industrial structure, technology, demographics, shipper practices, and government regulation that led to the general decline of the railroad industry following World War II. The remainder contains the Burlington Northern's competitive response to its changing environment, including the company's decision to develop a logistics analysis program to improve their employees' and their customers' understanding of logistics. Also contains an example of logistics cost tradeoffs.

Keywords: Change Management; Rail Transportation; Logistics; Rail Industry; United States;

Format: Print

15 pages

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Citation:

Hammond, Janice H. "Burlington Northern (A)." Harvard Business School Case 689-081, April 1989. (Revised August 1989.)

Case | HBS Case Collection | October 2014 (Revised August 2018)

Caesars Entertainment

Janice H. Hammond and Aldo Sesia

This case describes the introduction of a regression analysis model for forecasting guest arrivals to Caesars Palace hotel in Las Vegas, Nevada. The company will use the forecast to staff the front desk in the hotel. The staff is unionized and the company has little flexibility to change staffing levels on a short-term basis. The case is set in the context of industry overcapacity and lower customer demand.

The case describes several models that could be used to forecast guest arrivals, including a moving average technique and a multiple regression model. The multiple regression model includes over 40 independent variables, including dummy variables (e.g., to represent day of week, month, year, holidays, paydays) as well as continuous variables to represent customer segment and average daily room rate. The case contains tables showing the output of the regression model, and compares the fit of the moving average and regression models. The case allows students to understand how such a model is developed within an organization and to evaluate the models presented. Students may work with a data file with several years of historical data or they may work with the model description and output results in the case.

Keywords: Forecasting; staffing; gaming; gaming industry; hotel industry; Decision Making; Forecasting and Prediction; Human Resources; Selection and Staffing; Entertainment; Games, Gaming, and Gambling; Operations; Service Delivery; Service Operations; Accommodations Industry; Travel Industry; Tourism Industry; Food and Beverage Industry; Las Vegas;

Citation:

Hammond, Janice H., and Aldo Sesia. "Caesars Entertainment." Harvard Business School Case 615-031, October 2014. (Revised August 2018.) View Details

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This case describes a medium-sized business that manufactures animal feed for commercial and companion animals. The company has been growing rapidly and is considering whether or not to implement an enterprise resource planning (ERP) system. Ozark currently uses an IT system built and refined in house and, though less flexible than desired, allowed for some specific functionality the company used, such as a pricing system tied to the company’s commodity hedging positions on a real-time, as well as off-the-shelf systems, for recording financial transactions and reporting, purchasing, warehouse management, and manufacturing execution. The case provides an overview of ERP systems and implementation. Ozark is deciding among three ERP options; different senior executives support different options.

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Burlington Northern (A)

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Burlington Northern (A)

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