At a glance
By Abigail Murison
Like AI (artificial intelligence), machine learning and automation, data visualisation is another concept that’s supposed to help transform business – and the finance function.
However, while AI may still be out of reach for many businesses, especially SMEs, data visualisation is something accountants can harness right now – in fact, you’ve probably been using it for some time.
What’s changing is the data visualisation tools that make the process faster and easier and communicate financial stories more effectively.
“All financial professionals are analysts, in that it’s their job to turn financial data into finance and board reports,” says Brett Thebault, director at Aginic, a company specialising in data analytics and business intelligence.
“You may not have ‘analyst’ in your job title, but you are doing the job of an analyst. Data visualisation tools take raw data and help analysts turn it into information, intelligence or insight. They also speed up the analysis process.
“The other thing these tools do is… help communicate this insight really well to others. The tools are a mechanism to provide insight to the masses.”
Know the data visualisation tools
Examples like this data visualisation of global commodities or this one of plastic bottle waste are stand-out examples of how data visualisation can tell a story, but bar charts, line graphs, scatter plots, pie charts, heat maps and even timelines are all simple, familiar and highly useful forms of data visualisation.
Modern data visualisation tools simply help you create these elements without having to manually enter and manipulate the data, or move it from Excel into other programs, line by line.
“So-called ‘traditional’ data visualisation tools have been in the market [for] around four or five years,” says Marty Conneely, director at Aginic. “They include Power BI (from Microsoft), Tableau (from Salesforce) and Qlik.
“More recently, other tools have entered the market that have different capabilities. For example, ThoughtSpot allows you to use natural language to create data visualisation.
You might ask the tool ‘what were my sales last month?’ and the tool will suss out what data is most relevant and how to display it most effectively.”
“Looker is another new data visualisation tool that was recently purchased by Google, and is showing promise,” adds Thebault.
Telling financial tales with data
Conneely says there are two reasons to look at financial data. The first is for investigative or exploratory analysis (such as audit). The second is for reporting or providing insight via hypothesis-driven analysis (for regular reporting, board papers and management accounting).
“For instance, if you are looking at expenses, you might have a rule that no credit card expense should be greater than A$500, so you create a data visualisation of all the transactions that were greater than A$500 in the last year,” he says.
“That’s your hypothesis-driven analysis. It might show that one employee had two expenses greater than A$500 in the last year.
“You can then move to exploratory analysis, comparing all employee expenses: patterns of spend according to merchant, day of the week, and so on. That way, you may discover that another employee has never spent over A$500, but they have a pattern of spending at the casino, late at night. That’s your audit perspective.”
When it comes to data sources for visualisation, Thebault says the more the merrier: the more data you combine, the more insights you’ll find.
“A CFO might combine expenditure data and sales data, but if they complement that with external market data, they are likely to find new insights,” Thebault says.
“For instance, if they add in weather data, they may discover the company makes more sales on sunny days. These patterns will exist because businesses operate within the market.”
Scale and share
Aginic is working on two finance-related data visualisation projects that demonstrate how data visualisation tools can scale and help share financial stories across a business.
In the first project, Aginic is working with a state audit office: helping them set up a platform for audit-type analysis, so the finance team no longer has to manually extract data from Excel. The data visualisation tool accesses the data automatically and creates the visualisation.
The second project involves helping a superannuation company set up a business intelligence portfolio of data visualisations. In this case, certain departments or stakeholders may only need access to parts of the data and the portfolio, while the CFO will need access to everything.
Start small, start now
If you would like to try out a data visualisation tool, Conneely’s first piece of advice is to find, organise and centralise your data.
“Think about storing all your data in a data lake: a place where raw data can reside. Storage is cheap and all your data will be in a single place, and not in sources owned by other people.”
There can be complications integrating data visualisation tools with older products, like older versions of SAP or old ERP systems, for example. A whole new market has formed to solve this problem. Data integration tools such as Stitch Data and Fivetran can extract and move data into a data lake for you.
If your data is already centralised or stored in modern accounting software, there is no reason why you can’t get started straight away.
“Data visualisation tools have built up a library of connectors, so you can plug-and-play. With software like Xero, current tools can all plug into the data,” Conneely says.
Thebault’s advice is to start small and work in an agile way; don’t be afraid to fail. “Choose a small question – like a credit-card analysis – and try it out,” he says. “Engage the whole finance team immediately. Within weeks you can get genuine benefits if you have a business goal front of mind, and work in bite-sized chunks.”
With most data visualisation tools now charging a low per-user subscription fee, even SMEs can afford to try it out. Says Thebault: “The worst thing you can do, is to do nothing.”