Spreadsheets are arguably the best thing to come out of the computer age. Spreadsheets were the first killer app for computers (source). Good spreadsheets are powerful, well organized and, most importantly, useful. Decorative spreadsheets, on the other hand, give the appearance of being useful but in reality resist any kind of deeper analysis or utilization. I hope to clarify what separates the two and help you avoid creating the latter.
We all know that spreadsheets are tools that were created to tame huge sets of numbers. But not everyone realizes that the spreadsheet unlocks amazing capabilities. A good spreadsheet gives users the power to filter, sort, query, pivot, aggregate, project and chart data. It allows people to gain deeper insights into data. It allows sharing data with others and allowing them to remix it for their own needs. The best part is that you don’t have to build any of these features, they are inherent in the spreadsheet app so long as your data is well organized. A good spreadsheet can be used by novice as well as power users.
The problem is that some spreadsheets are being created which, probably unintentionally, are impossible to use as real spreadsheets and rebuff the power user. They give the appearance of being a nice spreadsheet, but are only useful to display what the creator intended and resist any further analysis. That’s why I call them “decorative”. They look good but are not useful beyond their surface appearance.
Here’s why this is important: Spreadsheets are not meant to be pretty; that’s what slide presentations are for. Spreadsheets are meant to make data available for computation and analysis. Decorative spreadsheets break the intended purpose of spreadsheets.
Early in my career, one of my clients asked for help with her spreadsheet. When I fixed her issue, she gave me some of the greatest advice I’ve ever gotten: “If you get good at spreadsheets, people will think you are a genius”. I’m obviously no genius, but I have found that my ability to wield spreadsheets is something I get the most comments about.
I now realize that the advice I got as a young professional actually hinted at something deeper: spreadsheet skills are impressive because most people are NOT good at spreadsheets, and see them as some kind of opaque, technical tool to be feared or dumbed down into a glorified slide presentation. But I’m here to tell you that you don’t need to become a spreadsheet master. You can ignore all the fancy spreadsheet features. All you need to do is follow some basic rules to make your spreadsheets accessible to those who want to dig deeper.
Below I have attempted to define the basic rules for accessible spreadsheets. Please send this to people when you find them creating decorative spreadsheets.
Rules for a well organized, useful spreadsheet
The key is to think of your spreadsheet as a big table ▦ of data and keep these rules in mind:
1. Each row of data represents a unique and non-overlapping item of data
This doesn’t mean that some data can’t be repeated across rows. It means that the complete data record represented by the row should be unique. It can be completely distinct, like Product A vs Product B. Or it can represent adjacent slices of data, such as Product A Sales in March vs Product A Sales in April.
2. Each column represents a unique and non-overlapping dimension or metadata about the data
Think of columns as describing the data. If your rows represent Products, then the columns may include price, color, size, manufacturer, etc. If the rows represent Sales, then the columns may include date, amount, unit price, customer, etc. They key is that columns generally apply to all the rows (with a few exceptions).
3. Use column values, not separate columns, to represent dimensions
If you have a dimension of the data, say the region in which sales took place, it’s better to make that its own single column rather than create separate columns for each dimension value.
In other words, don’t create separate columns for “East Region Sales”, “West Region Sales”, “South Region Sales”, etc. Instead, create a “Region” column (where you can put in the values East, West, South, etc) and a “Sales” column where you put the sales for that region. This allows for aggregation, filtering, etc.
5. Blank cells are OK, but not ideal
If you have a column that doesn’t apply to a specific row of data, and it’s not because you violated any of the rules above, then it’s OK to leave it blank. However, it’s better to put 0 or N/A to make it clear the column does not apply to that row and not that the data is missing
5. No blank rows
Ideally you shouldn’t need any blank rows in your data, as a blank row has no meaning and implies you are trying to “separate” data which will only break aggregations and filters.
Example
Here’s an example of a Decorative vs Useful Spreadsheet
The first sheet shows a decorative layout. This may look nice, but the problem is that it violates rules 1, 2, and 3
- rows are not unique items of data - the teams are repeated across “2026 H1” and “2026 H2”
- the columns do not represent unique metadata - instead we see repeated columns for group, team, capacity, % allocation, and net allocation
As a result, it’s impossible to do any kind of analysis on this data. You cannot filter it, sort it, aggregate it, etc.
The second sheet shows a much better layout of data. There is a separate row for each unique combination of domain, inititiave, period, group, and team.
The meain reason why this is better is that it allows you to analyze the data in ways not possible with the first sheet. Since the data is recorded as a big table, you can easily create filter views, pivot tables and tcharts to analyze the data. For example, all of this analysis was able to be created very quickly because the data was laid out in a table.
Bonus
If you’d like to get even better at spreadsheets, read my Google Sheets Power User Tips!