Tools

1. Amirkabir University of TechnologyComputer Engineering & Information Technology Department Tools Dr. Saeed Shiry

2. Spreadsheets • Spreadsheet: most popular end-user modeling tool • Powerful functions • Add-in functions and solvers • Important for analysis, planning, modeling • Programmability (macros)

3. @RISK • @RISK brings advanced modeling and Risk Analysis to Microsoft Excel. You might wonder if what you do qualifies as modeling and/or would be suitable for Risk Analysis. If you use data to solve problems, make forecasts, develop strategies, or make decisions, then you definitely should consider doing Risk Analysis

4. What Is Risk? • Everyone knows that "risk" affects the gambler about to roll the dice, the wildcatter about to drill an oil well, or the tightrope walker taking that first big step. But these simple illustrations aside, the concept of risk comes about due to our recognition of future uncertainty — our inability to know what the future will bring in response to a given action today. Risk implies that a given action has more than one possible outcome.

5. Characteristics of Risk • Risk derives from our inability to see into the future, and indicates a degree of uncertainty that is significant enough to make us notice it. This somewhat vague definition takes more shape by mentioning several important characteristics of risk.

6. The Need for Risk Analysis • Risks for New Product Development and Marketing — Will the R&D department solve the technical problems involved? Will a competitor get to market first, or with a better product? Will government regulations and approvals delay product introduction? • Risks for Securities Analysis and Asset Management — How will a tentative purchase affect portfolio value? Will a new management team affect market price? • Risks for Operations Management and Planning — Will a given inventory level suffice for unpredictable demand levels? Will labor costs rise significantly with upcoming union contract negotiations? • Risks for Design and Construction of a Structure (building, bridge, dam,...)— Will the cost of construction materials and labor be as forecast? Will a labor strike affect the construction schedule? • Risks for Investment in Exploration for Oil and Minerals — Will anything be found? If a deposit is found, will it be uneconomical, or a bonanza? Will the costs of developing the deposit be as forecast? • Risks for Policy Planning— If the policy is subject to legislative approval, will it be approved? Will the level of compliance with any policy directives be complete or partial?

7. Assessing and Quantifying Risk • The first step in Risk Analysis and modeling is recognizing a need for it. Is there significant risk involved in the situation you are interested in? • In most real life situations, you can't perform an "experiment" to calculate your risk the way you can for the flip of a coin. How could you calculate the probable learning curve associated with introducing new equipment?

8. Describing Risk with a Probability Distribution • If you have quantified risk — determined outcomes and probabilities of occurrence — you can summarize this risk using a probability distribution. A probability distribution is a device for presenting the quantified risk for a variable. @RISK uses probability distributions to describe uncertain values in your Excel worksheets and to present results. • Over thirty types of distributions are available to you in @RISK for describing distributions for uncertain values in your Excel worksheets.

9. What Is Risk Analysis? • In a broad sense, Risk Analysis is any method — qualitative and/or quantitative — for assessing the impacts of risk on decision situations.

10. Risk Analysis in @RISK • Risk Analysis in @RISK is a quantitative method that seeks to determine the outcomes of a decision situation as a probability distribution. In general, the techniques in an @RISK Risk Analysis encompass four steps • Developing a Model— by defining your problem or situation in Excel worksheet format • Identifying Uncertainty — in variables in your Excel worksheet and specifying their possible values with probability distributions, and identifying the uncertain worksheet results you want analyzed • Analyzing the Model with Simulation — to determine the range and probabilities of all possible outcomes for the results of your worksheet • Making a Decision — based on the results provided and personal preferences

11. Simulation • @RISK uses simulation, sometimes called Monte Carlo simulation, to do a Risk Analysis. Simulation in this sense refers to a method whereby the distribution of possible outcomes is generated by letting a computer recalculate your worksheet over and over again, each time using different randomly selected sets of values for the probability distributions in your cell values and formulas.

12. Sensitivity Simulation • How Do Changes in Model Variables Affect My Simulation Results? • @RISK lets you see the impact of uncertain model parameters on your results. But what if some of the uncertain model parameters are under your control? In this case the value a variable will take is not random, but can be set by you. For example, you might need to choose between some possible prices you could charge, different possible raw materials you could use or from a set of possible bids or bets.

13. Distributions fitting • @RISK allows you to fit probability distributions to your data (Professional and Industrial versions only). Fitting is done when you have a set of collected data that you want to use as the basis for an input distribution in your spreadsheet. For example, you may have collected historical data on a product price and you might want to create a distribution of possible future prices that is based on this data.