Business modeling is the process of translating a business model into financial results, or other required outputs, using input variables together with logical arguments for how outputs are derived from inputs.
Business modeling forces the business model designer or analyzer to identify key variables, make and verify important assumptions, test for different scenarios and by that understand the complexities of the business model and how different attributes and factors relate to each other. In some cases the business modeling process may not produce an answer to a specific business question, but may be constructed simply to enhance the understanding of the business model and its environment.
24. What will be the major drivers of revenues and costs?
25. What are the trends regarding the identified major drivers?
26. When in time are revenues and costs expected? When all variables that influence the business are identified, it is important to identify relationships between input variables to reduce the data that needs collecting. Variables that can be derived from others should be removed. The Business ModelDatabase| 03
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28. Not all relationships may at first be clear and the business modeling process often clarifies how the business model really "works".
29. To make the model easy to use, further develop, test and debug, it is recommendable to separate formulas into easy to understand modules.
30. Before expanding into full scale model test each module with different trial solutions to check the logic.The Business ModelDatabase| 04
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32. In some cases it will not be possible to find all data that is necessary and assumptions have to be made or additional variables may need to be added that can derive the required variable with missing data.
33. Document all references and assumptions that are made, so it is easy to understand how solid the results are and where input data can be improved
34. Try to verify each assumption in different waysThe Business ModelDatabase| 05
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36. Separate between sheets with "input", "logic" and "output". If you chose to use only one sheet use borders, shading and colors to distinguish between cell types.
37. Starting with the "input" sheets, related data should be grouped together and entered into the spreadsheet with labels that identify the data, and the source of data or assumptions that have been made.
38. To make the code easy to modify it is important to design the model so that each piece of data is entered only once, and if used in additional places the original data cell is referred to.
39. To make the formulas easy to understand name all input fields to reduce the time to interpret and understand formulas.
40. In the "logic" sheets, no new data should be entered and entering any numbers directly into the formulas should be avoided. Separating all data from the formulas makes the model easier to interpret, easier to modify and easier when performing sensitivity analysis to see what the effect would be if some of the estimates were to take other values.
41. Keep all formulas as simple as possible and when complicated formulas are required, break it out into separate calculations with subtotals.
42. Finally the "output" sheets, should answer the fundamental business questions, stated in 1. It is the presentation of the results from the "logic" sheets and can be presented together with key variables and assumptions from the "input" sheets.The Business ModelDatabase| 06
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44. Testing and debugging can be done in numerous ways and some basic things to check for is to use simple test data and perform manual checks, examine logical operations and check for column and row consistency.
45. Range test the model using the extreme edges of expected possible input data
46. Stress test the model using unexpected inputs such as negative values when positive values were expected, very large or very small values or set all inputs to zero.The Business ModelDatabase| 07
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49. Focus should be on realistic alternative scenarios with changes in input variables that have a high level of uncertainty and high impact on the business outcome.
50. Simulation such as the Monte Carlo method can be used to simulate the uncertainty in input variables generating an average output as well as its volatility and other sensitivities to present the probability distribution around the average output.x1 x2 x3 y1 y2 The Business ModelDatabase| 09
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52. What changes can be made on the business model to improve the results?
53. What strategy can be applied to execute the business model differently?
54. How can the ranges of uncertain variables be lowered?
55. Can the same revenues be generated with a lower cost structure or with lower risk?Business modeling is an iterative process and when forced to identify key variables and assumptions, the business model designer may find new ways to innovate and adjust the business model not only to maximize the output of the most realistic scenario, but to create robust business models if some of the assumptions turn out to be false... The Business ModelDatabase| 10
56. Thank you! For more information about Business Models and Business Modeling, visit The Business Model Database www.tbmdb.com The Business ModelDatabase| 11