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DiscoverSim™ Case Studies

Case Study 1 – Basic Profit Simulation: Introduction

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This is an example of DiscoverSim Monte Carlo simulation to determine probability of daily profit using a basic profit model for a small retail business. We will apply distribution fitting to historical data and specify input correlations to define the model in a way that closely matches our real world business.

The profit (Pr) requirement is Pr > 0 dollars (i.e., the lower specification limit LSL = 0)

The profit equation, or “Y = f(X) transfer function”, is calculated as follows:

Total Revenue, TR = Quantity Sold * Price

Total Cost, TC = Quantity Sold * Variable Cost + Fixed Cost

Profit, Pr = TR – TC


In this study we will use DiscoverSim to help us answer the following questions:

  1. What is the predicted probability of daily profit?
  2. What are the key X variables that influence profit Y? Can we reduce the variation in profit by reducing the variation of the important input variables?
Summary of DiscoverSim Features Demonstrated in Case Study 1:

  • Distribution Fitting – Discrete
  • Distribution Fitting – Continuous
  • Create Input Distributions with Stored Distribution Fit
  • Specify Input Correlations
  • Run Simulation and display
    • Histograms, Descriptive Statistics, Process Capability Report
    • Percentile Report
    • Scatter Plot/Correlation Matrix
    • Sensitivity Chart of Correlation Coefficients
    • Sensitivity Chart of Regression Coefficients

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