Forecasting ManagerImprov, Inc.
ManagerImprov Inc. (MI Inc.) is a small company that conducts seminars on productivity issues for corporate executives. MI Inc. focuses on improving the quality of work and the attitude of workers in service organizations. The company tries to provide seminar participants with the tools essential for dealing with hard-to-measure issues. Originally, its seminars were geared toward hospital administration-specifically, topics included how to motivate nursing staffs and how to provide quality care for patients. Over the years, the demand for seminars has grown, as has the company's client base. Clients now include insurance executives who want to improve the quality and productivity of their claims recorders, travel agency directors who want to improve the service of their agencies, and managers of secretarial pools who wish to improve the attitudes in their offices. MI Inc. has offered one seminar each season for the past nine years. Each seminar lasts for one week and is typically held at a resort or spa. The location has varied over the years, but the winter seminars have tended to be in Florida, the spring seminars in Chicago, the summer seminars in the Carolinas, and the fall seminars in the northeast corridor (between Washington and Boston).
The following table shows the number of persons attending seminars since MI Inc. began.
Participants per Year/Quarter
Year -Qtr 1 2 3 4 5 6 7 8 9
Winter 35 68 70 64 73 89 96 93 95
Spring 44 61 62 72 62 66 78 80 82
Summer 54 61 70 76 85 82 95 88 89
Fall 49 75 74 72 72 92 94 101 87
MI Inc. is considering a major expansion program. Before committing to it, however, the company would like to be able to forecast the size of its seminars. MI Inc. is wondering if it should expand in all four seasons or if it should concentrate on one. The company would like to know if the growth has been even in all four regions or not. Find a forecasting model that best answers MI Inc.'s questions. What is the forecast for each quarter in the next two years?
Please see the attached Excel sheet for results and calculations.
Although there are many other methods for forecasting, regression analysis has been considered to be the most widely used. In my solution, I use such method to find the equation that will best fit the operational data up to date. After that, I simply plug the value for the next two periods (10 and 11 respectively) into the regression equation to obtain the forecasting.
Once you open up the Excel sheet, you should notice that I separated the data according to different season into four different worksheet, labeled "Winter", "Spring" etc. After I input the data into different sheet, I graphed the series using a 2-D line graph. Here is there the regression comes in. Once you are done, right click on the plotted line and select "Add Trendline" (see attachment labeled "Step 1"). In ...
The solution examines product management for forecasting ManagerImprov, Inc.