If you want to standardize your spreadsheets, automate repetitive tasks, and implement validation rules to prevent unauthorized changes, this article is for you! Learn how to ensure data accuracy and boost your productivity in Excel.
Imagine the following situation: you receive a file from a colleague to continue an urgent task, but when you open it, you realize that the data is scattered and disorganized. The formats are inconsistent, the formulas are broken, and there is no clarity about what each spreadsheet represents. The result? Hours wasted trying to understand and fix errors, an increased risk of mistakes, and the possible loss of important information.
I’ve been through this before, and the feeling is sheer fear—fear of entering any data because a simple mistake could compromise the entire work (or even my job).
The lack of standardization not only makes collaboration difficult but can also lead to poor decisions based on incorrect information. Disorganized spreadsheets can be costly for companies and professionals, resulting in calculation errors, misguided decisions, and unnecessary rework.
This is where standardization comes in—a set of best practices that ensures consistency, reliability, and efficiency in spreadsheet use.
If the lack of spreadsheet standardization is affecting you or your company,
get in touch and find out how I can help you.
Why Standardize Spreadsheets?
Standardizing spreadsheets is not just about aesthetics—it’s about security and productivity. Here are some key benefits:
✅ Error reduction: Consistent formats prevent confusion and broken formulas.
✅ Ease of reading and interpretation: A clear structure helps different users quickly understand the data.
✅ Efficient automation: Well-structured spreadsheets make it easier to create macros and integrate with other tools.
✅ Better traceability and auditing: Following standards makes it easier to track changes and validate information.
✅ Increased productivity: Less time spent fixing errors means more time for analysis and decision-making.
How to Ensure Spreadsheet Quality?
Throughout my experience, I’ve developed numerous spreadsheets for use by others. Anticipating all the possible "bad practices" that might be applied within the spreadsheet is a big challenge. However, over time, I’ve mapped out, studied, and developed a set of best practices to avoid the most common mistakes.
The best way to avoid errors is to apply best practices right from the creation of the spreadsheet. Among the ones I use, here are ten essential treatments and validations that you can implement to ensure data quality:
1) Organize the different stages of the process in separate spreadsheets.
Have you noticed that, in summary, most systems can be divided into three essential parts?
1️⃣ Registration: Includes basic information, such as customers, suppliers, salespeople, and products/services.
2️⃣ Transactions: Connects the registrations to daily operations, such as sales orders, quotes, and invoices.
3️⃣ Reports: Provide analysis and insights based on the registrations and transactions.
This structure ensures organization, integration, and efficiency in data management and can be applied to your file:
Spreadsheet 1: Create a spreadsheet solely for registration data and parameters. It will centralize,
in one place, the changes that the user can make to the file. Arrange the parameters either horizontally or vertically (do not mix both). This way, the user will have a sequence, a pre-defined path for the parameters they need to fill out.
Horizontal:
Vertical:
Avoid scattered parameters:
Spreadsheet 2: In another spreadsheet, establish the connection between the data and the parameters provided by the user. Here, for example, you can have a table consolidating the results obtained through formulas, VBA, and Power Query.
Spreadsheet 3: In a third spreadsheet, create the charts, indicators, and insights obtained.
This way, the file will contain the spreadsheets for parameters, consolidations, and charts. The naming of the spreadsheets can vary, but the concept remains the same:
2) Review the file organization
File organization is such an important aspect that it deserves a dedicated topic.
Depending on the purpose of the work, the file format may vary in terms of parameters, consolidations, and the presentation of charts. For example, you may need a greater number of spreadsheets to better separate information or include a sheet with a specific function, such as structuring data to be populated into the system.
The problem typically arises when there is an improper mix of these elements. Imagine inserting charts in the parameters sheet or spreading parameters across multiple sheets. Disorganization can confuse the user and make it harder to navigate the file. Even if calculations, validations, and other items are technically correct, usability is key to ensuring that the file is intuitive and efficient.
If necessary, create an additional sheet to include supplementary information, such as data entry instructions, file objectives, and usage frequency. This practice improves understanding and minimizes errors.
In more complex cases, it might be helpful to create a dedicated sheet for checks. For instance, if we’re developing automation to import a sales report extracted from the system, we could validate whether the sum of the sales lines matches the report's totalizer. This simple check ensures both the correct data import and the integrity of the totalizer. As obvious as it may seem that the totalizer should be the sum of the records, I’ve observed reports with errors in this calculation, which were identified through this check.
Finally, name each sheet clearly and objectively, ensuring that the name accurately reflects its content and function within the file.
If we compare this process to building a house, it’s like we’re creating the blueprint: we define the support structure, organize the spaces, and establish the connections between rooms to ensure a logical and functional flow. Now, we move on to the foundation stage, or better yet, the structure that will house the data in the file.
3)Format cells appropriately
Use correct formats for each type of data: Numbers should be in numeric format, dates in date format, and text as text. This prevents issues such as values that cannot be summed or dates being interpreted incorrectly.
When using Power Query, it’s important to pay attention to the automatic data typing. In some cases, dates may be converted to formats from different locales, which can affect chronological consistency. Additionally, Power Query may base the data typing on only a sample of the data, leading to incorrect classifications.
Here’s an example where I created a table with two columns – the first one filled with zeros up to row 202, where I inserted the decimal value '0.1', and the second with the decimal value '1.1' in all records. Power Query correctly identified the second column as decimal type. However, the first column was classified as an integer because it used only the first few rows to determine the data type.
4) Use data validation
Set rules to restrict input values. For example, prevent the entry of text in numeric columns or limit dates to a specific range.
By preventing incorrect data entry at the source, we prevent the propagation of inconsistencies throughout the process.
In this example, the user tried to enter a date in a format different from 'day/month/year'. Since there was a data validation rule in place, the incorrect input was blocked, and the user received an alert informing them of the correct format to enter.
If the lack of spreadsheet standardization is affecting you or your company,
contact me and find out how I can help you.
5) Use conditional formatting
Conditional formatting is a powerful tool for controlling duplicate records, making it easier to identify data inconsistencies. Observe the two tables below: both contain the same data, but in the second table, conditional formatting has been applied. As a result, the duplicate records are highlighted with a different background color, making it evident that the product code "1" is repeating.
This feature is especially useful for preventing errors in databases, ensuring better control and reliability of the information. As soon as the user enters a duplicate code, conditional formatting automatically activates, signaling the duplication and allowing adjustments to be made before it causes future discrepancies.
6) Avoid embedding parameters within formulas
In the example below, we have a sale of R$ 100.00 and a commission of R$ 10.00 in cell "E3". Notice that the formula consists of the sale amount multiplied by the 10% commission rate
By constructing the formula this way, maintenance becomes more laborious. Imagine the scenario where the commission rate is no longer 10%, and you need to change it in several files, with the calculation applied this way multiple times in various cells. You would have to go through the entire file to identify the occurrences or use some VBA code to assist with this task.
Now, observe how maintenance becomes easier when the commission percentage is not embedded in the formula. In the example below, the formula consists of multiplying the sale amount by the commission percentage, which is in cell “E2”, meaning the commission percentage is no longer embedded in the formula. If all formulas involving the commission percentage reference cell “E2”, and we need to make a change to that percentage, we simply need to alter cell “E2”, and the entire file will be updated with the new percentage.
7) Cell locking
Files typically contain an editable section for data entry and another with fixed elements, such as predefined formulas.
To prevent unauthorized changes, these fixed elements should be protected. In the example below, the commission calculation is locked, preventing edits and displaying a warning to the user if they attempt to modify it.
To make it easier for the user to identify, we can use a different background color. In this example, we use green for cells that cannot be edited.
8) Use drop-down lists
One of the most common mistakes in spreadsheets is incorrect typing. And this doesn't only happen with beginners—even experienced users can make mistakes due to tight deadlines, urgencies, or overconfidence in their knowledge of the process.
The drop-down list is a powerful tool within data validation to ensure standardization, as well as to prevent typing errors. In the example below, where the state abbreviation (UF) needs to be entered, the drop-down list limits the available options, allowing only predefined values to be typed. This not only makes the process easier but also increases the accuracy and consistency of the recorded information.
The user is alerted if they try to type a value outside of the predefined options.
9) Handle data in Power Query
Power Query is an incredible tool for data processing. Among the various features I use, I will demonstrate four that help in data standardization. Although these are relatively simple techniques, using them is part of my development checklist. Consistently applying them makes a difference in the quality of the work. To illustrate, I will use the table below:
9.a) Remove spaces
In line number 1, we can observe that there is a space at the end of the text, as highlighted in red.
With the "Trim" option, spaces at the beginning and end of the text are removed.
9.b) In line 2, we have the text broken into two lines:
Using the "Clean" option, the line break is removed:
9.c) In lines 3 and 4, we have duplicate records:
By applying the "Remove Duplicates" option, the duplicate data is removed.
9.d) Now we have a null value in line 4.
For this example, let's apply the "Remove Blank" option. This way, we complete the necessary treatments for the table
10) Observe how the user interacts with the file
Analyzing how the user interacts with the file is a crucial step in identifying areas for improvement and process optimization. Observing how they navigate between spreadsheets, move through rows, and which functionalities they use can reveal opportunities for automation and simplification. Additionally, identifying areas where the user still performs manual checks is key, as these points may be ideal candidates for implementing automatic validations or processes that ensure data accuracy without constant intervention.
This analysis also involves mapping workflows, understanding routines and repetitive tasks, and assessing the file's usability. By doing this, improvements can be identified that not only make the process more efficient but also reduce errors, increase productivity, and provide a more intuitive user experience.
Bonus tip: use comments, cell descriptions, and elements that both facilitate user interaction and make the file easier to maintain by another collaborator. Documenting codes and formulas is essential for good governance.
Start Standardizing Your Spreadsheets Now!
Now that you understand the importance of standardization and are familiar with the key validations to avoid errors, it's time to put this into practice! Review your current spreadsheets, implement these improvements, and see how the quality of your data will improve.
A well-structured spreadsheet is a competitive advantage for any professional. If you work with Excel or other analysis tools, start applying these best practices today!
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