1) Consistency:
Check that the balance sheet's total assets equal the total liabilities and equity.
Verify that the cash flow statement's ending cash balance matches the balance sheet's cash balance.
Check that the income statement's net income matches the change in the equity section of the balance sheet.
2) Accuracy:
Use the latest financial statements and market data to ensure that the model's inputs are accurate and up-to-date.
Check the source of data and calculations to ensure that they are accurate.
Verify the accuracy of the model's outputs by comparing them with actual results.
3) Sensitivity analysis:
Perform sensitivity analysis to determine how changes in key assumptions, such as revenue growth or expense levels, impact the model's output.
Evaluate how the model's output changes when key inputs are varied.
Determine the range of outcomes under different scenarios.
4) Error checking:
Check all formulas to ensure that they are correct and accurately reflect the model's assumptions.
Review all inputs to ensure that they are accurate and correctly entered.
Verify that the model produces results that are consistent with expectations.
5) Reasonableness:
Compare assumptions and inputs with industry benchmarks, historical data, and market trends.
Evaluate the model's output against industry averages to determine if it is reasonable.
Consider any deviations from historical trends and investigate the reasonableness of the assumptions used.
6) Completeness:
Ensure that the model includes all the necessary financial statements, including the balance sheet, income statement, and cash flow statement.
Verify that all assumptions and inputs are included in the model.
Ensure that the model covers all aspects of the business's financial performance and position.
7) Model simplicity:
Use clear and concise formulas and labels to avoid confusion.
Avoid using complex formulas or methods unless necessary.
Ensure that the model is easy to navigate and use.
8) Documentation:
Document all assumptions, inputs, and calculations used in the model.
Include clear and concise explanations of formulas and calculations.
Ensure that the documentation is organized and easy to follow.
9) Model validation:
Verify that the model produces outputs consistent with expectations and actual results.
Compare the model's output to external benchmarks and data sources.
Perform sensitivity analysis to evaluate the model's performance under different scenarios.
10) Future-proofing:
Consider the impact of potential changes in the business environment and adjust assumptions accordingly.
Evaluate the model's output under different scenarios and update the assumptions as needed.
Continuously review and update the model to reflect changes in the business environment.
11) Scenario-driven features using macros:
Use macros to create scenario-driven features that allow users to adjust assumptions and inputs quickly and easily.
For example, create a macro that allows users to adjust revenue growth rates or expense levels based on different scenarios, such as best-case, worst-case, or base-case scenarios.
Macros can help to automate repetitive tasks and streamline the model's usage, making it more efficient and user-friendly.
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