Performing Sensitivity Analysis Using Toprank Product

1968 words - 8 pages

The increase in recent years in the sophistication, power, and user-friendliness of spreadsheets such as Microsoft Excel has meant that more decision makers are building their own spreadsheet models to help them in their decision making. These models however are only as good as two things. Firstly, the data that goes into the model, and secondly, the logic of the relationships built into the model. Inaccurate input data values or faulty logic can only produce bad results, especially if the inaccurate data values are the key or critical variables (Beaman, Ratnatunga, Krueger, and Mudalige, 2002). Obviously, more care should be taken when estimating an input variable to which the output is ...view middle of the document...

The decision maker may then decide whether it is appropriate to concentrate on those variables. As well as allowing the decision maker to determine the key variables in a decision, sensitivity analysis can be used to determine the margin of error in decisions involving those variables (Beaman et al., 2002). In addition, it could also possibly help to highlight faulty logic in that any results of a sensitivity analysis must "make sense". In other words, the model builder should look closely at the logic of any model if a sensitivity analysis highlights a particular input variable as key given that all other indications such as previous company knowledge, "gut feel", etc are that it is not (Beaman et al., 2002).Sensitivity analysis can be performed using either a spreadsheet package, a financial modeling language, a "decision support", or an "add-in" to spreadsheet package. The least efficient, but probably most common approach, is to use a spreadsheet package to repeat the scenario (what-if) analysis process over and over again. For each repetition of this process, the value of one input variable is changed and the results recorded. This process is repeated for a range of values for that input variable, and then the whole process is repeated for any other input variable that the decision maker wishes to vary. By comparing the relative differences in the results as each of these input variables are varied, the decision maker is able to identify those input variables that cause the largest change in the output result; that is, the high sensitivity or critical variables in that decision situation (Beaman et al., 2002).There is also one other way to do sensitivity analysis within standard Microsoft Excel, which is the semi-automatic process of varying the values assigned to input variables. The command to do this is Data Table. Microsoft Excel's Data Table command allows the decision maker to vary one (or two) input variable/s to identify the effect that this change has on one (or more) formulas (ie. output results) of interest. The "table" output from this command shows the decision maker the sensitivity of the results to one (or two) input variable/s (Beaman et al., 2002). The dialogue box for Excel's Data Table command is shown in Figure 1.Figure 1. Microsoft Excel's Data Table Dialogue BoxAnd, as a result from the use of this Data Table command, Microsoft Excel will (semi) automatically produce a what-if table. From this table, the decision maker could analyze which variable, between the two variables, that is more sensitive to the result. The sample result of the Data Table command is shown in Figure 2.Figure 2. Sample Result of the Data Table CommandBut, unfortunately, performing sensitivity analysis using this standard Microsoft Excel's command is very inefficient. The first reason is because it is a table, it is not as easy to read as the graphical outputs produced by another methods. And, the second reason is because that the Data Table...

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