Automation of Financial Planning: Excel-Based Systems
Financial planning automation enables companies to streamline and optimize their financial management processes.
However, despite implementing specialized financial planning and budgeting systems, companies often find the functionality lacking, and finance professionals return to their preferred Excel files because of its simplicity, flexibility, and broad functionality. While IT experts may strive to replace Excel’s financial modeling capabilities entirely, finance professionals are reluctant to let go of this familiar tool for several reasons.
Advantages of Using Excel in Financial Planning
Accessibility and Ease of Use: Excel is widely accessible, with an intuitive interface and straightforward functionality that is easy for most users to understand. Additionally, numerous reference materials and forums exist where advanced Excel users share tips and modeling techniques.
Flexibility and Customization: In Excel, companies can build financial models, forecasts, and reports tailored to specific business needs. Any methodology, model, or table can be implemented and adjusted as needed.
Analytics and Visualization: Excel offers both basic and advanced analytics and visualization tools—charts, graphs, conditional formatting—that allow effective data processing and representation.
Rapid Calculations and Modeling: Excel supports complex financial calculations, scenario testing (e.g., scenario analysis or sensitivity analysis), quick data adjustments, and modeling of forecasts. Financial planners appreciate the ability to connect data sets and create any calculation dependencies needed for their models.
Compatibility and Integration with Other Systems: Excel integrates well with other solutions, making it easy to export and import data. Most systems support data exports to Excel.
When Excel May Fall Short
Despite its strengths, Excel does have limitations:
Scalability: Excel works well for small to medium-sized businesses or for targeted tasks in large companies. However, for large-scale data, multidimensional reports, or complex calculations, it may not be powerful enough.
Errors and Risks: Since most data is entered manually, there is a high risk of errors and inaccurate calculations, with the likelihood increasing as models become more complex.
Limited Collaboration: Real-time collaboration is challenging in Excel, so users must input data sequentially, increasing the risk of data loss.
Lack of Process Automation: Excel lacks built-in functions for process automation, such as treasury, accounting, or budgeting. This makes financial control tasks more challenging and slows down financial planning.
Insufficient Analytics and BI Integration: For advanced analytics and data visualization, Excel may not be ideal, as it lacks features like forecasting and enhanced visualization often found in BI systems.
Optimal Solution - Excel-Based Financial Planning Systems
Several systems extend Excel’s capabilities for financial planning, budgeting, data analysis, and reporting. These solutions enhance efficiency and accuracy within Excel by leveraging built-in tools and integration with other systems.
For example, they help reduce implementation costs. Excel-based systems are often cheaper and quicker to implement than full ERP or EPM systems. They generally do not require specialized coding skills; understanding the system’s logic and having a vision of the desired result are often sufficient.
Excel-based financial planning systems are also user-friendly. While they may have their own operational logic, they work through Excel’s familiar interface, significantly reducing adaptation time.
These systems, like Excel itself, provide maximum customization for model development while overcoming the limitations of traditional spreadsheets.
An example of such a system on the market is Spreadym — a platform for business planning and budgeting. Spreadym is fully integrated with Excel’s interface, offering an advanced computational engine that significantly reduces processing time, supports large data sets, controls data input and display, and allows the creation of financial models of any complexity.