Stress testing and Sensitivity analysis: This way, the model can be tested with sensitivity analysis in order to be assured of accuracy for all the different scenarios. The main use of sensitivity analysis is to judge how the model reacts when assumptions and key variables are changed. For example, what happens if the revenue growth rates are ±5%? This changes profitability and cash flows, and testing different scenarios gives you an understanding of the strengths and weaknesses of the model so that strategies may be created based on the possible outcomes. Validation of Model: Once this is complete, ask someone else to review the model. Smaller mistakes in formulas or assumptions can be significant when calculating projections. You may use Excel's error-checking tools, and also verify outputs where possible with the historical data. It's also worth validation with the colleagues or experts in terms of the assumptions and calculation used for the model. Documentation of assumptions, methodology, and sources will come in handy in subsequent reviews as well.