The principles of best practice outlined here are for the purpose of reducing errors and making a model easier to read, audit, update, and use for its intended purpose. This chapter is by no means exhaustive, but outlines the most important principles in using Excel for business analysis and financial modelling. By following these key principles, your model is easier to navigate and check, and much more likely to be robust, accurate, reliable, and error-free.
Good assumptions documentation is one of the most important principles of best practice. It is impossible to check, validate, or use a model if you are unable to verify the integrity of the data sources or methods of calculation in the model. Your model design, layout, and structure can be perfect, but its validity is really reliant on the assumptions that go into it (i.e., garbage in, garbage out). The most beautifully structured model in the world is pretty useless if the assumptions that go into it are garbage!
Documentation of assumptions helps with validation and avoids misinterpretation. If there is any possible misunderstanding about why, how, or what the assumptions are in the model, make sure it’s recorded in black and white on the assumptions page.
List assumptions on a separate page, clearly labelled. For a smaller model, you might decide to mix source data and assumptions together, or they could be separated in a large model.
The more ...