Overall Satisfaction with Microsoft Excel
Excel is a critical tool for our organization in most departments and at all levels, but very heavily within our department. From the finance and accounting perspective, it is largely used for modeling. This includes business process models on the accounting side (loading journal entries, uploading calculating and uploading invoices based on data extracts) and predictive modeling on the finance side (modeling forecasts, customer retention, and cash flow analysis). We also produce reports using excel until development can be done to create these reports within business systems.
- Modeling - very versatile in the way data can be summarized, calculated, compared
- Loading data - easy to convert models into CSV files
- Organizing data - able to created mini relational databases using lookup fields
- Retaining formatting - it is challenging to keep the formatting the same when opening files
- Identifying duplicates in a lookup
- Creating warning when referential information is broken
- Positive impact on creating a forecasting process
- Positive impact on creating efficiencies around data loads
- Positive impact on financial analysis
Cognos has many of the same abilities as excel, which allows you to manipulate data in a much more structured way. What is being done in Cognos is being done across the entire dataset without exception. This allows for greater integrity. However, let's say that you want to build some exceptions. In that case, Excel would allow you to have a lot more flexibility (while taking on spreadsheet risk).
Do you think Microsoft Excel delivers good value for the price?
Are you happy with Microsoft Excel's feature set?
Did Microsoft Excel live up to sales and marketing promises?
Did implementation of Microsoft Excel go as expected?
Would you buy Microsoft Excel again?
Overall, the tool is pivotal to our organization. Modeling within excel is very powerful and flexible. Within a few hours, you can pull, summarize, and create a predictive model that can be used to make business decisions quickly. However, you have to know when you have overloaded the program. The system does not warn you well against formula errors or referential integrity which can lead to spreadsheet risk. One bad formula can do some real damage if left unchecked. Consider migrating complex models into more robust forecasting systems.