Excel is a familiar and favorite tool for many finance professionals, and is typically embedded in many workflows across a company. Let us preface by stating we’re not here to bury Excel, but to highlight its strengths and weaknesses as a finance tool. It’s an essential analytical tool when used appropriately, with an intuitive interface that lends itself to it being extended beyond its capability.
There are excellent technology solutions; however, that you can leverage with an Excel interface, while avoiding the pitfalls of over-reliance on Excel. In this post, we spotlight seven common Excel problems and some of the solutions successful finance teams deploy to overcome them.
The problem with Excel is that it’s not meant to efficiently store and organize data, tasks better left to databases and data warehouses. Where Excel begins to breakdown is when finance teams start to rely on it as a database and reporting system — instead of adopting a financial planning and analysis (FP&A) platform.
Finance must aggregate all necessary facts (data) and maintain control over the sources of truth to develop reports and create forecasts that inform strategic conversations. Solely relying on Excel to manage dispersed data sets requires database management and technical skills that are difficult to develop and a challenge when operating with headcount restrictions or capacity limitations.
For finance to analyze data and facilitate a company’s decision-making process, it needs an informative framework that doesn’t require time-consuming data manipulation. Data aggregation can seem endless, and without dedicated data warehouses and automation to support Excel, its problems for financial analysis compound.
There comes a time when every company and finance function will outgrow Excel, some sooner than others. We’ve all exported data from a source of truth and imported it into Excel. In fact, many finance functions begin with this process. Unfortunately, data imported into Excel isn’t necessarily structured in a fashion that lends itself to deep analysis. Due to Excel’s limited capacity to store data, more issues arise as more rows of data are added.
According to Microsoft, the maximum data Excel can handle is capped at 1,048,576 rows and 16,384 columns. A million rows might seem like an unthinkable amount for some, but for high-transactional industries like retail and eCommerce or mid to large-sized enterprises, reaching the cap can happen quickly.
Manipulating hundreds of thousands of rows of data becomes an improbable task for a finance team. To avoid this limitation, successful finance teams utilize more robust software to streamline financial planning and analysis (FP&A) workflows and get the most of their data. Some FP&A platforms offer configurable options, including an Excel-native interface, to mimic the look and feel of a spreadsheet, while providing far greater functionality to easily analyze your data.
Although second on this list, “running slow” is reportedly the most common problem for Excel users. It’s no surprise, since Excel was first launched in 1985, and additional functionality hasn’t kept pace with other financial software. As you add more data to an Excel spreadsheet, the more performance and refresh speed issues arise.
It’s a painful process to wait for calculations and updates to load with no end in sight. It’s a limitation that not only hinders productivity but also adds frustration for end-users. Isn’t technology supposed to eliminate those issues? The short answer is yes. However, Excel was never intended to be a workhorse to store large subsets of data for finance to conduct analysis.
This goes back to the lack of Excel’s scalability and the need for finance teams to seek more capable software that centralizes data from sources of truth and automates manual tasks to make data not only accessible, but also useful for analysis.
Maintaining version control is crucial to ensure the accuracy of financial reporting and forecasting. It’s not uncommon for companies to share Excel files with budget owners and others in accounting and finance to input data like monthly expenses and metric results. Although you can edit and share new versions of a spreadsheet, real-time collaboration isn’t feasible.
Since anyone with access to the Excel file can alter the data in spreadsheets, models, and calculations relying on that data changes in each instance. This can be problematic for scenario planning and forecasting relying on data sets that might be outdated. The last thing you want is to have stakeholders viewing the same report with different data.
Data warehouses paired with FP&A platforms leverage direct integrations to manage your data sources of truth within a centralized software, so finance doesn't have to worry about untracked updates made by other stakeholders.
Most companies rely on a variety of systems to help manage and streamline specific department processes. For example, Netsuite is a useful ERP System for transactions and accounting data; Salesforce is a popular CRM tool to manage customer data, pipeline and bookings; Insperity is an HRIS software to manage headcount, benefits and employee records. These systems hold the detailed items for each of the data sets. There’s an inherent manual export/import function that is required and prone to error.
Integrations are a powerful automation tool for data management and don’t require any complex technical acumen to execute. A centralized FP&A platform integrates directly with your sources of truth, so data from each of your systems is aggregated and organized in real time for ease of use.
Excel’s mass application of usage also plays into its problems and limitations. There isn’t any categorization aligned with your data sets, and adding any formatting parameters is a time-consuming manual process. As mentioned in the problem above, integrations are a powerful tool for finance to control data sources, which is an essential function to facilitate analysis.
However, Excel doesn’t offer dedicated integrations to your sources of truth, which frame how your company categorizes, segments and formats its data. Exporting and importing data is also susceptible to errors and omissions that could lead to additional issues as you begin to model out scenarios and forecasts. It’s a vicious cycle that will hinder your ability to draw impactful conclusions and provide actionable insights for decision-makers.
The majority of people are visual learners, and even if you’re not, it’s still far more efficient to study and analyze a detailed chart or graph than rows and columns of data. There are some options to create charts and graphs using pivot tables in Excel, but you must manually update data to reflect in the visual elements.
On the other hand, data visualization tools bring metrics to life and provide real-time updates with an interactive component. For example, let's say you had an additional source of revenue from won opportunities last month. Through direct integration with the revenue source of truth (Salesforce), that information updates automatically in the report. While it’s possible to produce graphical reports in Excel, not only are the capabilities limited, but you’re still subject to all of the problems listed in this blog post.
Without a data warehouse and data visualization tool, you can’t automatically update in a visualized chart or graph. You’ll need additional technical acumen and refresh the data manually to update your charts and graphs. With a data visualization tool, visualized reports are available for stakeholders like executives, board members and investors with automatic live updates for them to reference at any time, knowing it’s the most current state of the company’s affairs.
Unfortunately for humans, and yes, that includes finance professionals, we’re prone to error. If a data set has a calculation error, typo, or other notable mistakes, the entire model can be flawed. Though Excel triggers a few error codes, like the dreaded #Value error or formula #Error!, it assumes you’ve imputed all of your data correctly, so there is no identification of manual errors in your spreadsheets.
These erroneous errors can easily go unnoticed, yet have the most profound impact on your forecasts and analysis. It’s a common but avoidable mistake that the addition pf financial analysis software can resolve. Some FP&A platforms automate calculations and have pre-loaded equations, so you can produce forecasts and scenarios with little effort compared to an Excel spreadsheet.
You don’t need to be a data scientist to control your company’s data and stage it for analysis. If you want to experience a far superior solution to solve your Excel problems, FutureView’s FP&A Platform might be a fit for your finance function. We offer direct and rapid integrations with your ERP and other sources of truth and automatically stage your data for consumption and analysis. Our dedicated finance experts will have you up and running in weeks, not months, so you can make a substantial impact before every completing the onboarding process with competing software solutions.
If you wish to spend less time aggregating and more time analyzing, contact us or schedule a free demo of our Platform to learn how you can leverage automations and our methodologies to enhance your finance function.
Let us know what interests you most, and your availability. We look forward to introducing you to the FutureView Systems Platform, and demonstrating how it can transform your finance processes.