Spreadsheets help individuals and business organizations record financial data efficiently. Excel is probably the most common spreadsheet application used by businesses today. Users program formulas and macros to automate calculation of financial data as well. The seemingly simple financial logic inside spreadsheets can also cause embarrassing errors.
Just back from Hong Kong, Financial Technology Consultant Portia d’Alcantara told AccountingWEB.com that answering the question, “What does the client want to see?” is the main problem she encounters in her financial consulting journeys. After all, satisfying client needs is what spreadsheets do, whether the clients are internal or external. She added that spreadsheets should be designed with the end presentation and use in mind.
d’Alcantara told AccountingWEB.com that most users make spreadsheets more difficult to use than they have to be. They put too much information into a single spreadsheet, instead of limiting columns to six or eight columns. This should also make spreadsheets easier to update. She added that some users “don’t know when to stop using Excel and start using Access.” Access is a Microsoft database application.
d’Alcantara also recommends that users take advantage of the basic features available in the Excel application, as well as validation tools and filters, according to AccountingWEB.com. She said that, “Using the power of Excel can go a long way.” Pivot tables should be used sparingly, while “navigational” information, such as colored or formatted text, helps users and end users get around a spreadsheet easier. Providing summary information also helps users and end users.
A recommended title published on this subject is Spreadsheet Check and Control: 47 key practices to detect and prevent errors, according to Micromail. Written by Patrick O'Beirne, it was published September 2005 to help spreadsheet users avoid rework, help them discover powerful formula auditing techniques, reduce compliance costs for businesses in regulated sectors and ensure data quality and accuracy.