Spreadsheet good practice guidelines
Why good practice matters
Spreadsheets are important. Essential, even.
Far ahead of any other software, spreadsheets are the most widely used tools for analysis, reporting, and presentation. In 2016, Microsoft CEO Satya Nadella said that 1.2 billion people use Microsoft Office, of which Excel is a key part. The number of users has only grown since then. And that isn't counting other spreadsheet software, such as Google Sheets – which is reported to have another almost 1 billion users (in 2023). Many organizations simply couldn't operate without spreadsheets. They use spreadsheets for critical tasks in finance and many other fields.
With such wide use, often for critical tasks, yet with extraordinarily high error rates, it is clearly essential that we need to do better. That is, concisely, why good practice matters.
In this section, we delve into some aspects of why we need to take spreadsheet good practice seriously.
These guidelines have been developed based on:
- Extensive practical knowledge from building, testing, and using spreadsheets.
- Decades of consulting experience offering modelling and analysis services globally.
- A review of the academic research about spreadsheet practices, especially spreadsheet risks.
We know that spreadsheets are important for many applications, including informing decision making. We also know that spreadsheets have real and substantial risks.
Therefore, an obvious question is: Why is spreadsheet practice generally so poor?
Spreadsheet errors are ubiquitous. But, relative to their occurrence frequency, few spreadsheet errors become public. When an organization's spreadsheet errors are publicized, the revelation is seldom made by choice.
Nonetheless, there are many examples of spreadsheet errors being public. Some errors have been widely reported in the media, due to their substantial impacts.
We trust spreadsheets more than we should. Because the computer says so, and computers don't make mistakes, we think that the result must be right.
That is, a spreadsheet becomes "truth", losing any uncertainty that it may have had while being developed.
The phenomenon of abstract results gaining a sense of concreteness and reliability, beyond what is reasonable, is called reification.
Really, that statistic needs to be repeated: 95% of spreadsheets have errors.
This is not just a random, made-up statistic. Extensive research into spreadsheets has consistently found that almost all spreadsheets have errors.
Large spreadsheets are more likely to have errors, meaning that they're almost certainly wrong.
When looking to understand how to make better spreadsheets, we need to be clear that spreadsheet formulae are a programming language.
Professional software developers learnt long ago that they need to apply good practices to their work. Spreadsheet developers need to learn the same lessons.
