Introduction to @RISK. Monte Carlo Simulation addin on Excel

Through a simple profit and loss forecast, the new user is introduced to @RISK, Excel's Monte Carlo simulation add-in.

What you'll learn
By the end of this course, you should be able to understand how @RISK works as a Monte Carlo simulation engine on top of Exceland set up a model on your own by inserting some basic distributions, running a simulation and interpreting basic graphs and information generated by it.

Requirements
Intermediate level of Excel.

Description
This is an introductory course to @RISK (Palisade's Monte Carlo simulation software on top of Excel). You will learn how to set up, run a simulation and interpret results for any type of model.We use an example of a simple business example: Joe runs a small contracting business repairing residential exteriors. We introduce the decisions he has to make. Step by step we explain how, by using @RISK, he is able to make sound and consistent decisions around his business.Joe runs a small contracting business repairing residential exteriors. He and his two cousins working for him mainly contract on painting jobs, roofs repairs and landscaping. On average, he is able to service 8 monthly contracts during non-winter months and 4 monthly contracts during winter months, December to January. If there is an increase in demand, he can contract additional manpower at a higher, yet variable, hourly rate.Preparing next year’s plan, he is considering the possibility of hiring a third fixed employee on payroll. This would allow him to increase his offer and eventually be able to service an average of 10 contracts during non-winter months. By doing this, he would be able to increase his total annual revenue by servicing more customers and decrease the expensive variable cost when he needs to subcontract additional manpower. However, during winter, he would be tolled by a higher fixed cost, probably making him run on losses during three consecutive months.On the other hand, he is also considering downsizing his operations by excluding one of his cousins out of his payroll. With a downsized operation, he could only be able to handle an average of 7 service contracts per month on non-winter months. This would lighten up his fixed cost burden during the low activity winter months. He would be able to hire any required flexible manpower at a per hour basis. Evidently, this option could be less profitable but more secure and flexible.

Who this course is for
Quantitative students and professionals interested on running Monte Carlo simulation on top of Excel.