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Still using spreadsheets for your business intelligence?

Written by David Burnham | September 05, 2024

What’s wrong with using spreadsheets for driving insights from your data?

Spreadsheets, whether MS Excel, Google Sheets, Apple Numbers, etc, are now a ubiquitous tool for business, and for that reason, are usually the first step a company takes in their data driven journey. They are great for many purposes, including ad-hoc analysis, and most employees can use them effectively. However, that ease of use inherently helps to create several limitations when it comes to their broader use for data analytics and business intelligence.

How much data, and how often it can be updated matters.

Spreadsheet providers have continually improved their limits on data storage with new features and ways of handling data. However, as data accumulates, spreadsheets can become slow and harder to manage. The data might need manual updating, time consuming manual uploads, or appending new data to an existing spreadsheet. Automation is possible, but even that can ‘drop’ records coming from the database and result in data gaps. More robust data connections are not always simple to set up (even for some advanced users). Any of these issues can compromise the reliability of any insights drawn from the data, which make spreadsheets a less-than-ideal option when dealing with bigger data scenarios.

Security Features

Spreadsheets can lack the robust data governance and security features that your organization requires. This makes them more vulnerable to data breaches, potentially posing significant risks to the integrity and confidentiality of the data. In addition, deployment across your organization may be complicated if you have sensitive data that needs to be confined to a subset of employees, but you still want insights and interactive reports published more broadly.

Multiple Key Data Sources

If you are trying to aggregate multiple data sources and manipulating that data manually, the chance of misinterpreting the incoming data, making an erroneous shortcut assumption, like omitting a complicated data source or making join errors, can lead to difficulty in diagnosing issues that can even go unnoticed. If you are using the output for "informed" strategic decisions, how confident are you that you got it right?

Spreadsheets are not inherently designed for complex data analysis and visualization.

Spreadsheet providers are making improvements, but these products still lack advanced data visualization tools needed for extracting meaningful insights from complex and large-scale data sets. Pivot tables and simple charts are helpful, but they aren’t sufficient, or can slow down performance, particularly on older computers. And, as noted above, they lack the secure interactivity desired in today’s workplace.

The big issue is the susceptibility of spreadsheets to human error.

The use of spreadsheets can require a significant amount of manual work. Often data needs to be entered, and updated manually, making it susceptible to accidental changes or deletions. The most sophisticated analysis often requires the creation of complex, custom-made formulas. This not only consumes valuable time but also requires a certain level of expertise, which may not be available in all teams or organizations. A small, easily made mistake in data entry or a formula can have significant consequences on the outcome of the analysis, and be difficult to find and fix.

While spreadsheets can be a valuable tool for ad-hoc analysis and storing of small datasets, like some infrequently updated metadata, they are not equipped to handle the complex and dynamic needs of data analytics and business intelligence. Organizations looking to leverage data for strategic decision-making may need to consider more advanced, dedicated tools and solutions. These tools can offer more powerful analytics, real-time updates, improved data security, and automation capabilities, all of which are critical in modern data-driven business environments.

Please reach out to discuss your current and future data analytics and business intelligence needs and how you can migrate away from spreadsheets on your data driven journey.