At a glance
By Adam Turner
Electronic spreadsheets helped to drive the business PC revolution in the early 1980s. Ever since, Microsoft Excel has been an essential tool for accountants.
Far more than a digital general ledger, Excel has evolved to offer a range of advanced features for data manipulation.
Excel cannot perform every task, however, so it is a good idea to have some alternatives, because it can save time and improve productivity in the long run.
This especially important as many accountants transition from number-crunching to more advanced work in pursuing valuable business insights.
This guide can help accountants decide when an Excel alternative could be a better choice for them.
1. Large volumes of data
Microsoft bumped up Excel’s maximum number of rows from 65,000 to one million back with Office 2007. This upgrade allows the software to handle vast amounts of data, but there is still a limit.
This is particularly the case when it comes to merging datasets.
“The more data that you put into Excel and the more you ask it to do, the slower it’s going to become,” says Andrew B. Jackson, associate professor with UNSW Business School.
“A database tool like SQL can be much more efficient at bringing disparate datasets together, after which Excel may or may not be the right tool for manipulating that data.
“If you are running something like a Monte Carlo analysis to predict the possible outcomes of an event, you can do it in Excel, but it will soon get very slow,” Jackson explains.
Excel can be less efficient at processing large volumes of data and creating relationships between disparate datasets, says Slav Tabachnik, analytic solutions partner at Deloitte Australia.
“In Excel, you can use VLOOKUP as a workaround, but this is slow and error prone,” Tabachnik says.
“In later versions of Excel, you can use Power Query, but SQL still offers advantages.
2. Recurring processes
Many tasks that accountants perform in Excel are recurring, such as month-end close.
Repeating the same tasks in Excel each month presents a range of challenges. For instance, having multiple people working on the same spreadsheet can increase the risk of accidental introduction of errors.
“If you’re looking to create processes that are repeatable and scalable, it’s much easier to turn to something like SQL,” says Tabachnik.
“It can ingest the information into a relational database, put governance around the data access and then automate the execution of the analysis.”
3. Data visualisations
“The modern-day accountant is essentially a trusted business adviser. This means data visualisation becomes a really important tool for turning all your data into actionable insight,” Jackson says.
“Tools such as Tableau help accountants take that next level when it comes to visualising data and conveying meaning to stakeholders.”
4. Deeper insights
Working with more than 10 variables to predict their impact on an outcome is another example of where Excel is no longer the best tool for the job, says Dr Kellie Nuttall, analytics and AI partner at Deloitte Australia.
“If you’re working in Excel, you need to make a lot of assumptions when it comes to the behaviour of the different levers that impact that prediction. This means the ability to gain foresight is fairly limited,” Nuttall says.
“This is a perfect scenario to consider how machine learning tools can take your analysis to the next level.
“By studying all the permutations, machine learning can discover patterns and uncover unknown relationships between the variables. This provides you with a much richer and more accurate view of the big picture.”