Common FP&A Problems With Excel & How to Fix Them
Updated: Jul 28
Decades after the creation of Microsoft Excel, many FP&A professionals today continue to use this 34 year old application. Excel has remained relevant for good reasons. Finance teams can apply Excel to a multitude of tasks, including financial modeling, visualization, data analysis, data storage, textual and quantitative data, and regression/statistical analysis. The primary reason for these specific uses of Excel is its flexibility: Excel allows practitioners to tackle a throng of different responsibilities in a relatively inexpensive, intuitive platform.
Despite these positive aspects of the application, Excel users do consistently encounter multiple specific problems, such as:
A small margin for critical error
A lack of efficiency and control
Lost time to data collection
Therefore, it is critical for FP&A professionals to understand these specific drawbacks, and when Excel use is or isn’t appropriate. To address its shortcomings, finance teams need to use resources in addition to Excel, and should be aware of the best solutions to different challenges in FP&A.
Small Margin for Critical Error
The margin for error is tiny in Excel. Finance spreadsheets are heavily dependent upon small bits of underlying data. If users make even the slightest mistake, that single slip up can result in a ruined data set. Trudging through the manual tasks required to make accurate spreadsheets is too prone to human error, and too often has disastrous consequences.
For example: In October 2003, a single Excel mistake required The Federal National Mortgage Association (Fannie Mae) to restate its unrealized gains by an amazing $1.2 billion—shortly after it had announced third-quarter earnings. In another case, a simple spreadsheet error caused a company’s stock price to tumble so dramatically that trading was halted. Unfortunately, errors like this exist in a high percentage of business critical spreadsheets.
Lack of Efficiency & Control
Excel use in the wrong circumstances can lead to wasted time and wholly inaccurate data sets. The following 3 cases illustrate why:
When a data file is too large, it can make the Excel program run very slowly, especially if all the data is in one file. Trying to break the data down into smaller files can lead to some of it being lost or misplaced. Excel is not user-friendly and the application rounds off very large numbers using imprecise calculations, which compromises accuracy.
Excel is also a standalone application, and is typically not fully integrated with other business systems (though there are ones which can be integrated with Excel). It does not provide sufficient control because sales managers don’t have easy and consistent visibility of the quotes sent by their reps, or the history of those quotes.
Excel systems cost time because most users invent a unique solution to a common problem. Such solutions are often unseen because they get erased in the merger of data into a single format. Merging data this way wastes time, and checking the data set plus correcting errors wastes even more.
Wasted Time on Data Collection
To caveat on the previous subject, one of the biggest losses from excessive time wasted on the extraction and manipulation of spreadsheet data, is that this leaves little room for the drawing and analysis of insights from the data collected. Back in 2017, Mark Garrett, the CEO of Adobe Inc, stated that he was moving towards cutting Excel out of parts of his finance department. Garrett said, “I don’t want financial planning people spending their time importing and exporting and manipulating data, I want them to focus on what the data is telling us.”
Low Grade Security
Fraudulent manipulations in company Excel files have already resulted in some million dollar losses. The main underlying reason behind this spreadsheet vulnerability is the inherent lack of controls which makes it so easy to alter formulas, values, or dependencies without being detected.
The adoption of an FP&A software has proved to be a great way for a number of organizations to address the potential drawbacks of Excel use. Financial software systems provide automation, different analyses of collected data, and higher grade security, hence solving issues of potential fraud, human error, and data accuracy.
However, it should be noted that the aforementioned issues with Excel do not mean that finance teams should bag Excel altogether. Excel’s versatility, universality, and updates make it relevant in a variety of FP&A tasks. The conclusion from considering Excel’s potential drawbacks should be that finance teams can continue to use Excel; they just need to use other resources in addition to it (namely, a software). Ideally, the other tool used should be aimed at complementing spreadsheet usage.