what type of decision-support system analysis uses a backward solution approach that attempts to calculate the value of the inputs necessary to achieve a desired level of output?
The type of decision-support system (DSS) analysis that uses a backward solution approach to calculate the value of inputs necessary to achieve a desired level of output is commonly referred to as "Goal Seek" or "What-If Analysis." This approach is often employed in spreadsheet software like Microsoft Excel and is used to determine the required input values to reach a specific target or goal.
Here's how Goal Seek or What-If Analysis works:
Target or Goal: The first step is to define a specific target or goal for the output variable. This could be a particular value that you want to achieve, such as a sales revenue target, a profit margin, or a desired project completion date.
Initial Assumption: You start with an initial assumption or estimate of the input variables that will produce the desired output.
These input variables could be various factors, such as product price, quantity sold, production costs, or project duration.
Backward Calculation: Using the goal-seeking feature in software like Excel, you specify the desired output value and identify which cell or formula represents the output in your model. The software then performs backward calculations to determine the values of the input variables that would lead to the specified output.
Iteration: The software iteratively adjusts the input variables within specified limits to find a combination that gets as close as possible to the desired output. It repeats this process until the goal is met, or it reaches a defined limit of iterations.
Solution: Once the software finds a set of input values that result in the desired output or come as close as possible to it, it provides these values as the solution. These input values can then be used to make informed decisions or to set specific targets for business or project planning.
Goal Seek and What-If Analysis are valuable tools for decision-makers because they allow for scenario analysis and sensitivity testing. Decision-makers can explore how changes in input variables impact their desired outcomes, enabling them to make more informed decisions, set realistic targets, or identify potential issues and constraints in their plans.
This approach is particularly useful when dealing with complex financial models, project planning, resource allocation, pricing strategies, and other situations where there are multiple interconnected variables, and decision-makers need to determine the necessary inputs to achieve specific objectives.