Financial reports are the backbone of data-driven business models
Across the board, industry leadership is increasingly tied to process rather than product. The Information Age has made data-driven business models imperative for all industries. Financial analytics is the foundation that orients business intelligence and advanced analytics. This shift is mirrored in the rapid evolution of the roles of the CFO and the finance department.
“The financial health of the enterprise becomes more closely connected to technologies such as Big Data, analytics, mobile and cloud-based solutions,” according to CIO.com
Dataviz-enhanced reports and dashboards pay analytics forward
Brilliant insights are useless if they can’t be understood. For BI initiatives and advanced analytics to yield, their core metrics, financial data, must be understood by all users. Financial data visualisations use visual elements to tell stories that translate universally, regardless of technical expertise.
Vizlib Finance is the most powerful financial reporting product for Qlik Sense.
Data visualisations educate and engage a rapidly growing non-finance user base
Spreadsheet assaults and data dumps won’t cut it. It’s up to finance teams to cultivate the financial literacy and engagement among a rapidly growing report user base.
Even so, according to the Corporate Data Literacy Index, Finance and Insurance are one of the most data-literate industries.
Image is a universal language that leapfrogs words and fast-tracks to cognition
The art and science of visual storytelling with data as a function:
If: picture = 1000 words
Then: data visualisation ≥ 1000 data points
When it comes to telling stories in a business environment, understanding what levers to pull and which hormones to induce (as well as how to do it) can be the difference between a relaxed, engaged audience and a room of blank stares.
Use all the data. Really, all of it.
A 2016 big data study by Forrester found that BI and analytics don’t use the majority, 60% to 73%, of their enterprise data. Using data visualisations for exploration makes it possible and practical to examine all enterprise data. Dive into those data lakes.
Dataviz transforms financial analysts into citizen data scientists
Wading through enormous spreadsheets and hopping back and forth between tables searching for patterns and irregularities is time-intensive. Until recently, leaving data, a lot of data, on the cutting room floor was tacitly accepted as impossible to avoid. No more! Using data visualisations, financial analysts are now free to about the data. All. The. Data.
Data visualisations provide adaptable views that help business users to literally see meaningful relationships and anomalies, and pluck stories and patterns from noise. More comprehensive analysis. Faster turnaround time. Deeper insights. More useful results. Self-service and simple setup. No IT chaperone needed. Let’s do this!
The applications of data visualisation in financial analysis
Discovery
Expanded Coverage + Intuitive Tools = Enhanced Analytics
Data visualisations streamline processes that were literally impossible not too long ago. Finance teams used to burn countless hours short-circuiting their brains on cocktails of high risk and tedium. Is it even possible to avoid confirmation bias using an abridged dataset?
Data visualisations are game-changers for data discovery. Not only can analysts easily review enormous datasets, dataviz tools enable them to reconfigure those datasets and swap out analytical methodology at will and instantly. No developer required.
Form and function, part 1: Artful reports
How simple dataviz augmentations cut through info-clutter
There’s more than one reason why P&L, balance sheet, etc. are presented as tables. You don’t need to fix things that aren’t broken. Data visualisations can’t and won’t replace balance sheets and P&Ls. That said, augmenting those reports with simple, in-table data visualisations can help audiences parse the information quickly yet accurately.
For example, colour-coded bars make it easy to lead people through the story of the past three years’ cash flow reports. Instead of dizzying arrays of numbers, people can hopscotch through the report. Simple but effective visual cues ensure that they intuitively follow the storyline. All of this happens in a fraction of the time needed to communicate the same information verbally.
Form and function, part 2: Beautiful and interactive financial reports
How data visualisations educate and engage
Just as engaging with data enhanced the discovery process, giving report users similar abilities on now-curated datasets fosters financial literacy. Financial knowledge develops organically as users are able to ‘touch’ the data, learning visually through experimentation.
Sometimes the form is the key to function
It’s OK. We can say it. Part of what makes data visualisations effective is that they’re beautiful. This is a statement of evolution and neuroscience. Every species attaches appreciation [acknowledgement] to visual cues associated with ‘things’ that improve their quality of life. The visual space and mental energy necessary to understand this Sankey chart are not even a fraction of those required to parse the tables of data that inform it. Classifying this dataviz as aesthetically appealing is our brain’s shorthand for ‘easy to use’.
Less is more in financial reporting: best practices for dataviz in finance
Just because you can, doesn’t mean you should
During discovery, data visualisations provide bird’s eye views that enable analysts to spot relationships and anomalies story amid the noise. But once the story has been plucked from the noise, the role of dataviz shifts gears and flips approach from all-inclusive to ‘needs-must’.
Elegance is simplicity
The art of explanatory dataviz is telling the story with the fewest elements possible. Like reports on steroids, data visualisations distil stories down to their essence. The crucial points that shape and move the story. Stick to the old programmer’s motto and ‘do the needful’.
Storytelling starts by considering the audience
As data visualisation expert Scott Berinato observes, effective dataviz relies on understanding your audience in terms of the Law of Prägnanz: ‘pithiness. We find the easiest meaning we can in the chart itself.’ Try to step outside of yourself and your knowledge of the backstory.
First impressions don’t count; they define
Several studies have demonstrated that false first impressions often resist correction. First impressions, your gut reaction, persist even when corrected. Data visualisation taps visceral experience in its first impression. What is the initial 3-second statement of a dataviz? While it doesn’t need to tell the whole story, the initial sentiment must resonate with the greater message.
Meet your audience where they are by learning about human perception
That first impression speaks a primal human language. In that first instant, a visualisation is reduced to colour and shape. Do you see a blue blob, or the undulating patina of a heatmap that uses contrasting colours? What if the viewer is colour-blind? A little armchair neuroscience and design theory can catapult your dataviz into the communication stratosphere. Like false impressions, instant recognition and visceral responses are cognitive duct tape.
You can make your P&Ls easier to understand at-a-glance by incorporating colour-coded indicators and other visual elements.
More than a single source of truth: Consistent calculation and display
Visual finance can be the jumping-off point for financial literacy and analytics engagement across an organisation. But, to pay it forward as the backbone of effective BI, consistency is key. Beyond telling stories about data drawn from a single source of truth (SSoT), dataviz must apply consistent calculation methodologies and display standards.
Collaboration and interaction require granular access privileges
Access to dataviz tools must be granted on a granular level to distinguish between data consumers and collaborative creators. The CEO should be able to see and comment on everything. Regional managers only need read-only access to very specific datasets. Various finance teams need read, write and comment privileges for their individual coverage areas.
Wrapping up
Corporate finance has always been the core of organisation operations and success. It’s in the job description. The dawn of big data and the Information Age have pushed financial analytics out from behind the curtain. Financial metrics are not front and centre as the core logic for data-driven strategies implemented as business intelligence and advanced analytics. Data visualisations help finance teams to tell compelling stories that educate and engage a rapidly growing and diverse userbase.
Financial analytics draw meaning from their context and earn value from their strategic application. Data visualisations ensure responsible, efficient and effective leverage of financial data by connecting with users through the primal human languages of the image and story.
[…] 3. Why finance teams need data visualisation to tell better stories? […]