Tornado diagram: Difference between revisions

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{{infobox4
'''Tornado diagram''' '' - it is one of the diagram types, which is used for deterministic [[sensitivity analysis]].
|list1=
<ul>
<li>[[Parametric analysis]]</li>
<li>[[Heavy users]]</li>
<li>[[Book to market ratio]]</li>
<li>[[Information]]</li>
<li>[[Look-Ahead Bias]]</li>
<li>[[Media mix]]</li>
<li>[[Capital market theories]]</li>
<li>[[Property assessment]]</li>
<li>[[Point elasticity]]</li>
</ul>
}}
 
'''''Tornado diagram''' ''it is one of the diagram types, which is used for deterministic [[sensitivity analysis]].


The other well-known titles of this diagram type are tornado charts or tornado plots. The main use of this [[method]] is to show to the analyst which aspects are having more or less of influence on the decision she or she is interested to make (E. Bodmer, 2014, pp. 232-246).
The other well-known titles of this diagram type are tornado charts or tornado plots. The main use of this [[method]] is to show to the analyst which aspects are having more or less of influence on the decision she or she is interested to make (E. Bodmer, 2014, pp. 232-246).


== What is sensitivity analysis? ==
==What is sensitivity analysis?==
'''Sensitivity analysis''' is a category in Math Statistic science concerned with influence which one (or more) various independent variables affect one particular dependent variable in specified [[system]] of assumptions.
'''Sensitivity analysis''' is a category in Math Statistic science concerned with influence which one (or more) various independent variables affect one particular dependent variable in specified [[system]] of assumptions.


In [[economics]] sensitivity analysis is used for simulation analysis. Another title of this category is ''what if''and it is mainly used by analysis to make a foresee result of a making decision including definite diapason of variables. Due to this, analyst can measure how changes in one variable affect the result (P. McNamee, J. Celona, 1987, p. 157).  
In [[economics]] sensitivity analysis is used for simulation analysis. Another title of this category is "''what - if''" and it is mainly used by analysis to make a foresee result of a making decision including definite diapason of variables. Due to this, analyst can measure how changes in one variable affect the result (P. McNamee, J. Celona, 1987, p. 157).  


==Sensitivity Analysis contra Scenario Analysis==
==Sensitivity Analysis contra Scenario Analysis==
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The foundations of '''sensitivity analysis''' are variables which influence estimation. This affect can be demonstrated on a financial model for example with using different prices. The sensitivity analyst separates those variables after what he or she can write down the diapason of probable results.  
The foundations of '''sensitivity analysis''' are variables which influence estimation. This affect can be demonstrated on a financial model for example with using different prices. The sensitivity analyst separates those variables after what he or she can write down the diapason of probable results.  


In opposition to that, '''scenario analysis''' identifies a definite scenario. For example, it might be crash on the stock [[market]] or changes in laws, which regulate [[industry]]. The scenario analyst changes the variables in the models, after what he or she can adjusts the model with that scenario. In the end, analyst knows the all spectrum of results, including all the extremity. Also, he or she is able to understand that the results are in specified system, which is characterized by real life scenarios ( D. Matheson, J. Matheson, J. E. Matheson, 1997, pp. 232-234.).
In opposition to that, '''scenario analysis''' identifies a definite scenario. For example, it might be crash on the stock [[market]] or changes in laws, which regulate [[industry]]. The scenario analyst changes the variables in the models, after what he or she can adjusts the model with that scenario. In the end, analyst knows the all spectrum of results, including all the extremity. Also, he or she is able to understand that the results are in specified system, which is characterized by real life scenarios ( D. Matheson, J. Matheson, J. E. Matheson, 1997, pp. 232-234.).


== How does tornado diagram looks like? ==
==How does tornado diagram looks like?==
[[File:Tornado Diagram for Profitability – example.png|300px|right|thumb|Fig. 1 Title (''[https://books.google.pl/books?id=KUsx-PhOOtoC&pg=PA204&dq=tornado+diagram&hl=uk&sa=X&ved=0ahUKEwi0vJr-gqXhAhVwhosKHZRABUQQ6AEISDAE#v=onepage&q=tornado%20diagram&f=false Decision making in Natural Resource management: A Structured, Adaptive Approach ]'', 2013)]]
[[File:Tornado Diagram for Profitability – example.png|300px|right|thumb|Fig. 1 Title (''[https://books.google.pl/books?id=KUsx-PhOOtoC&pg=PA204&dq=tornado+diagram&hl=uk&sa=X&ved=0ahUKEwi0vJr-gqXhAhVwhosKHZRABUQQ6AEISDAE#v=onepage&q=tornado%20diagram&f=false Decision making in Natural Resource management: A Structured, Adaptive Approach ]'', 2013)]]


== How to build Tornado Diagram? ==  
==How to build Tornado Diagram?==
One of the main advantages of tornado diagram is that it is very easy to create. Moreover, you do not [[need]] any specific programs or computer softvare.  
One of the main advantages of tornado diagram is that it is very easy to create. Moreover, you do not [[need]] any specific programs or computer softvare.  
Here you have 8 steps how to create tornado diagram in one of the general Microsoft programs Excel:
Here you have 8 steps how to create tornado diagram in one of the general Microsoft programs - Excel:  
# Put needed data into Excel table
# Put needed data into Excel table
# Convert the data in one of the columns to negative value (multiply that data with -1)
# Convert the data in one of the columns to negative value (multiply that data with - 1)
# Create a bar chart with data in the table (Insert Tab -> Charts -> Bar Chart)
# Create a bar chart with data in the table (Insert Tab - > Charts - > Bar Chart)
# Open formatting [[options]] and change label position to “low” (Axis Option -> Labels -> Label Position)
# Open formatting [[options]] and change label position to "low" (Axis [[Option]] - > Labels - > Label Position)
# Modificate axis position in the reverse order (Axis Options -> Axis Position)
# Modificate axis position in the reverse order (Axis Options - > Axis Position)
# Modificate series gap and gap width (Series Options -> Change Series Overlap)
# Modificate series gap and gap width (Series Options - > Change Series Overlap)
# Modificate number formatting of the horizontal axis (Axis Option -> Number -> Select Custom and put ##0; ###0)
# Modificate number formatting of the horizontal axis (Axis Option - > Number - > Select Custom and put ##0; ###0)
# Modificate the format of data labels for column with -1 (Label Options -> Number -> Select Custom and put ##0; ###0)
# Modificate the format of data labels for column with - 1 (Label Options - > Number - > Select Custom and put ##0; ###0)


== What does it mean "an appropriate tornado diagram"? ==
==What does it mean "an appropriate tornado diagram"?==
Appropriate tornado diagram is the diagram, which is showing a proper ranking of the value and decision sensitivity of a decision analysis with certain [[risk]] aspects. The proper ranking means that the analyst is not letting peculiarity of the model structure or our own preferences to blur the real important of the aspects.
Appropriate tornado diagram is the diagram, which is showing a proper ranking of the value and decision sensitivity of a decision analysis with certain [[risk]] aspects. The proper ranking means that the analyst is not letting peculiarity of the model structure or our own preferences to blur the real important of the aspects.


== Why it is so important to build an appropriate tornado diagram? ==
==Why it is so important to build an appropriate tornado diagram?==
It is important to remember, that tornado diagram is one of the steps to make an excellence decision. This type of diagram shows the possible model of decisions to an analyst rather than the certain decisions as a topic of the analysis.
It is important to remember, that tornado diagram is one of the steps to make an excellence decision. This type of diagram shows the possible model of decisions to an analyst rather than the certain decisions as a topic of the analysis.


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==Examples of Tornado diagram==
==Examples of Tornado diagram==
* A Tornado diagram is a graphical representation of a range of values for multiple variables that are linked to a single output. It is typically used to visualize the sensitivities of a model or process to changes in its variables. For example, it can be used to examine how a company’s profits might be affected by changes in the price of a raw material, the cost of labor, and other input costs.
* A Tornado diagram is a graphical representation of a range of values for multiple variables that are linked to a single output. It is typically used to visualize the sensitivities of a model or [[process]] to changes in its variables. For example, it can be used to examine how a company’s profits might be affected by changes in the [[price]] of a raw material, the [[cost]] of labor, and other input costs.
* Tornado diagrams are often used to compare two or more scenarios and identify which variables have the most influence over the output. For example, a business might use a Tornado diagram to compare the impact of different marketing campaigns on their sales. By looking at the impact of each variable, the business can determine which marketing tactics will be the most effective for achieving their goals.
* Tornado diagrams are often used to compare two or more scenarios and identify which variables have the most influence over the output. For example, a business might use a Tornado diagram to compare the impact of different [[marketing]] campaigns on their sales. By looking at the impact of each variable, the business can determine which marketing tactics will be the most effective for achieving their goals.
* Tornado diagrams can also be used in the context of financial planning. For example, an investor could use a Tornado diagram to compare the impact of different stock portfolios on their expected return. By looking at the range of returns across the different portfolios, the investor can determine which portfolio will have the best chance of achieving their desired return.
* Tornado diagrams can also be used in the context of financial [[planning]]. For example, an investor could use a Tornado diagram to compare the impact of different stock portfolios on their expected return. By looking at the range of returns across the different portfolios, the investor can determine which portfolio will have the best chance of achieving their desired return.


==Advantages of Tornado diagram==
==Advantages of Tornado diagram==
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==Other approaches related to Tornado diagram==
==Other approaches related to Tornado diagram==
One-sentence introduction: Other approaches related to Tornado diagram include:
Other approaches related to Tornado diagram include:
* Sensitivity Analysis - an analysis of the influence of each uncertain parameter on the overall result of the model.
* Sensitivity Analysis - an analysis of the influence of each uncertain parameter on the overall result of the model.
* Monte Carlo Simulation - a tool used to calculate the probability of a certain outcome based on varying input parameters.
* Monte Carlo Simulation - a tool used to calculate the probability of a certain outcome based on varying input parameters.
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In summary, Tornado diagram is a type of diagram used for deterministic sensitivity analysis, but there are other approaches related to it, such as Sensitivity Analysis, Monte Carlo Simulation, Scenario Analysis, Regression Analysis and Decision Trees.
In summary, Tornado diagram is a type of diagram used for deterministic sensitivity analysis, but there are other approaches related to it, such as Sensitivity Analysis, Monte Carlo Simulation, Scenario Analysis, Regression Analysis and Decision Trees.


== References ==
{{infobox5|list1={{i5link|a=[[Analytic network process]]}} &mdash; {{i5link|a=[[Decision tree]]}} &mdash; {{i5link|a=[[Principal component analysis]]}} &mdash; {{i5link|a=[[Multivariate data analysis]]}} &mdash; {{i5link|a=[[Strategic scenarios method]]}} &mdash; {{i5link|a=[[Attribute control chart]]}} &mdash; {{i5link|a=[[Economic feasibility]]}} &mdash; {{i5link|a=[[Hierarchical regression analysis]]}} &mdash; {{i5link|a=[[Analysis of preferences]]}} }}
* Bodmer E. (2014). ''[https://books.google.pl/books?id=qYHsDQAAQBAJ&pg=PA232&dq=tornado+diagram&hl=uk&sa=X&ved=0ahUKEwi0vJr-gqXhAhVwhosKHZRABUQQ6AEIMDAB#v=onepage&q=tornado%20diagram&f=false   Corporate and project Finance modeling, Theory and Practice ]'' John Wiley & Sons Press, pp. 232-246.
 
==References==
* Bodmer E. (2014). ''[https://books.google.pl/books?id=qYHsDQAAQBAJ&pg=PA232&dq=tornado+diagram&hl=uk&sa=X&ved=0ahUKEwi0vJr-gqXhAhVwhosKHZRABUQQ6AEIMDAB#v=onepage&q=tornado%20diagram&f=false Corporate and project Finance modeling, Theory and Practice ]'' John Wiley & Sons Press, pp. 232-246.
* Matheson D., Matheson J., Matheson J. E., (1997). ''[https://books.google.pl/books/about/The_Smart_Organization.html?id=v3MsPzCzlSsC&redir_esc=y The Smart Organization: Creating Value Through Strategic R&D ]'' , Harvard Business School Press, pp. 232-234.
* Matheson D., Matheson J., Matheson J. E., (1997). ''[https://books.google.pl/books/about/The_Smart_Organization.html?id=v3MsPzCzlSsC&redir_esc=y The Smart Organization: Creating Value Through Strategic R&D ]'' , Harvard Business School Press, pp. 232-234.
* McNamee P., Celona J., (1987). ''[https://books.google.pl/books/about/Decision_Analysis_for_the_Professional_w.html?id=De2WAAAACAAJ&redir_esc=y Decision Analysis for the professional with Supertree ]'' , Scientific Press, p. 157.
* McNamee P., Celona J., (1987). ''[https://books.google.pl/books/about/Decision_Analysis_for_the_Professional_w.html?id=De2WAAAACAAJ&redir_esc=y Decision Analysis for the professional with Supertree ]'' , Scientific Press, p. 157.

Latest revision as of 06:51, 18 November 2023

Tornado diagram - it is one of the diagram types, which is used for deterministic sensitivity analysis.

The other well-known titles of this diagram type are tornado charts or tornado plots. The main use of this method is to show to the analyst which aspects are having more or less of influence on the decision she or she is interested to make (E. Bodmer, 2014, pp. 232-246).

What is sensitivity analysis?

Sensitivity analysis is a category in Math Statistic science concerned with influence which one (or more) various independent variables affect one particular dependent variable in specified system of assumptions.

In economics sensitivity analysis is used for simulation analysis. Another title of this category is "what - if" and it is mainly used by analysis to make a foresee result of a making decision including definite diapason of variables. Due to this, analyst can measure how changes in one variable affect the result (P. McNamee, J. Celona, 1987, p. 157).

Sensitivity Analysis contra Scenario Analysis

It is very important to mention that sensitivity analysis and scenario analysis are not the same methods as some might think. The foundations of sensitivity analysis are variables which influence estimation. This affect can be demonstrated on a financial model for example with using different prices. The sensitivity analyst separates those variables after what he or she can write down the diapason of probable results.

In opposition to that, scenario analysis identifies a definite scenario. For example, it might be crash on the stock market or changes in laws, which regulate industry. The scenario analyst changes the variables in the models, after what he or she can adjusts the model with that scenario. In the end, analyst knows the all spectrum of results, including all the extremity. Also, he or she is able to understand that the results are in specified system, which is characterized by real life scenarios ( D. Matheson, J. Matheson, J. E. Matheson, 1997, pp. 232-234.).

How does tornado diagram looks like?

How to build Tornado Diagram?

One of the main advantages of tornado diagram is that it is very easy to create. Moreover, you do not need any specific programs or computer softvare. Here you have 8 steps how to create tornado diagram in one of the general Microsoft programs - Excel:

  1. Put needed data into Excel table
  2. Convert the data in one of the columns to negative value (multiply that data with - 1)
  3. Create a bar chart with data in the table (Insert Tab - > Charts - > Bar Chart)
  4. Open formatting options and change label position to "low" (Axis Option - > Labels - > Label Position)
  5. Modificate axis position in the reverse order (Axis Options - > Axis Position)
  6. Modificate series gap and gap width (Series Options - > Change Series Overlap)
  7. Modificate number formatting of the horizontal axis (Axis Option - > Number - > Select Custom and put ##0; ###0)
  8. Modificate the format of data labels for column with - 1 (Label Options - > Number - > Select Custom and put ##0; ###0)

What does it mean "an appropriate tornado diagram"?

Appropriate tornado diagram is the diagram, which is showing a proper ranking of the value and decision sensitivity of a decision analysis with certain risk aspects. The proper ranking means that the analyst is not letting peculiarity of the model structure or our own preferences to blur the real important of the aspects.

Why it is so important to build an appropriate tornado diagram?

It is important to remember, that tornado diagram is one of the steps to make an excellence decision. This type of diagram shows the possible model of decisions to an analyst rather than the certain decisions as a topic of the analysis.

In addition to that, tornado diagram is an intuitive diagram, which usually is presented as an element of the final conclusion. However, knowledge about risk aspects, which are having the most influence, may be totally different from what analyst was expecting him or her to do.

For example, in some cases the top bar of the tornado diagram is unimportant to the final decision. it may be when the bar is creating big swings in the value, in spite of having same influence to all of the variants which are presented. Sensitivity analysis is using that sort of information in which companies are always interested the most to be able to make profitable decision. Due to that, decision sensitive aspects should not be ignored.

Examples of Tornado diagram

  • A Tornado diagram is a graphical representation of a range of values for multiple variables that are linked to a single output. It is typically used to visualize the sensitivities of a model or process to changes in its variables. For example, it can be used to examine how a company’s profits might be affected by changes in the price of a raw material, the cost of labor, and other input costs.
  • Tornado diagrams are often used to compare two or more scenarios and identify which variables have the most influence over the output. For example, a business might use a Tornado diagram to compare the impact of different marketing campaigns on their sales. By looking at the impact of each variable, the business can determine which marketing tactics will be the most effective for achieving their goals.
  • Tornado diagrams can also be used in the context of financial planning. For example, an investor could use a Tornado diagram to compare the impact of different stock portfolios on their expected return. By looking at the range of returns across the different portfolios, the investor can determine which portfolio will have the best chance of achieving their desired return.

Advantages of Tornado diagram

Tornado diagrams are a type of graphical representation used in sensitivity analysis to compare the relative importance of variables. It is often useful to identify which parameters have the greatest influence on the outcome of a model. The advantages of Tornado diagrams are:

  • They provide a visual representation of the relative importance of each input parameter, making it easier to compare the relative effects of each parameter on the output.
  • They can be used to identify potential areas of improvement, as parameters with the most impact can be modified to optimize the model.
  • They provide a quick overview of how sensitive the model is to changes in the input parameters.
  • They are relatively easy to create and can be used to show the effects of varying parameters on the output in a single diagram.
  • They can be used to identify relationships between input parameters, which can be used to develop a better understanding of the model.

Limitations of Tornado diagram

Tornado diagrams are useful tools for visualizing and analyzing sensitivity analysis, however they have some limitations. These include:

  • They are only applicable to deterministic sensitivity analysis and cannot be used to model stochastic or probabilistic scenarios.
  • They are limited to only two variables and cannot analyze multiple variables at once.
  • They cannot show the interaction between multiple variables and the effect of their relative values on the output.
  • They do not show any absolute values, so it can be difficult to interpret the results accurately.
  • They often require significant time and resources to create, making them impractical for large-scale analysis.

Other approaches related to Tornado diagram

Other approaches related to Tornado diagram include:

  • Sensitivity Analysis - an analysis of the influence of each uncertain parameter on the overall result of the model.
  • Monte Carlo Simulation - a tool used to calculate the probability of a certain outcome based on varying input parameters.
  • Scenario Analysis - a technique which helps to analyze the possible outcomes of a decision based on different scenarios.
  • Regression Analysis - a statistical technique used to identify relationships between different variables.
  • Decision Trees - a graphical representation of different choices and the corresponding outcomes.

In summary, Tornado diagram is a type of diagram used for deterministic sensitivity analysis, but there are other approaches related to it, such as Sensitivity Analysis, Monte Carlo Simulation, Scenario Analysis, Regression Analysis and Decision Trees.


Tornado diagramrecommended articles
Analytic network processDecision treePrincipal component analysisMultivariate data analysisStrategic scenarios methodAttribute control chartEconomic feasibilityHierarchical regression analysisAnalysis of preferences

References

Author: Olha Slyuzar