Consider some of the examples you have brought up in earlier topics. Describe the key differences between simulation models and the models covered earlier in the course. Outline how the approach to solving this problem would differ in terms of applying and computing/solving the models.
Respond to this thread: When selecting the best model, one must consider (1) the context of the forecast, (2) the relevance and availability of historical data, (3) the degree of accuracy desirable, (4) the time period to be forecast, (5) the cost and benefit (value) of the forecast to the company, and (6) the time available for making the analysis (Chamber, Mullick, & Smith, 1971). As I reflect on my examples in previous topics, my thought process to differentiate all modes is a bit of a struggle but key differences set them apart. First, a decision tree analysis allows a visual representation of all possible outcomes, rewards and follow-up decisions in one document (Sullivan, 2018). Second, multiple regression analysis has two main benefits, (1) the ability to determine the relative influence of one or more predictor variables to the criterion value and (2) identify outliers, or anomalies (Weedmark, 2018). Third, simulation model is very diverse in how it can be applied in many industries and disciplines. Not to mention it provides analysis that is easily verified, communicated, and understood. It is important to note, simulation is a (1) risk-free environment, (2) save money and time, (3) visualization, (4) insight into dynamics, (5) increased accuracy, and (6) handle uncertainty (Anylogic, 2018).
The problem I selected was the last post regarding simulation within my department and how “training” was most important when the department direct left (quit and/or fired). I took this situation extremely serious because this week, it affected me, again. My director decided to go on vacation and my president took it upon himself to “run” our department, as they want to keep the rules and responsibilities of the department director a “secret.” I took it upon my self to test all methods to this situation (aka problem) I am facing. Off all methods, simulation seems to be most useful; of course it all depends on the situation. The simulation allowed me to create detailed scenarios to show my director and corporate how important training us employees is vital to running the department responsibilities. In an attempt to apply and compute/solving the methods, there was insufficient data that would show error within my equations. Therefore the simulation method is most affective. However, after training has been established, I do plan on running the performance numbers into a simple linear regression to test performance output. Then, if it shows no relation, it is time to change up the roles, responsibilities, and most of all leadership to execute a more productive department. After all, our department is overseen by the executive staff (e.g., CEO, CFO, corporate elects, etc.) to ensure we meet our “numbers” and is highly competitive, as we are competing with 9 other branches. We are all trying to be the number one department in the company, improve the company, develop better strategies and techniques, but corporate is limiting us in how we can improve the department. It is a challenge, but I do plan on sharing my knowledge with these new methods to impress my executives and incorporate change. Slowly but surely I will make a positive difference.
Anylogic. (2018). Why use simulation modeling?. Retrieved from https://www.anylogic.com/use-of-simulation/
Chamber, J., Mullick, S., & Smith, D. (1971). How to choose the right forecasting technique. Harvard Business Review. Retrieved from https://hbr.org/1971/07/how-to-choose-the-right-fo…
Sullivan, D. (2018). What are the advantages of decision trees?. Chron. Retrieved from http://smallbusiness.chron.com/advantages-decision…
Weedmark, D. (2018). The advantages and disadvantages of a multiple regression model. Retrieved from https://sciencing.com/advantages-disadvantages-mul…
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