Make better business decisions with financial analytics
Find out why finance is beginning to shift its emphasis on advanced and predictive analytics and the capability to use big data to support future business decisions.
While driving down the highway, no one focuses exclusively on the rear-view mirror. Sure, drivers have to check what's coming from behind every so often, but driving safely and effectively requires keeping their eyes on the road ahead. They also monitor the dashboard to make sure they're moving at the proper speed.
As logical as this is, business has tended to work the opposite way: Those doing the driving have relied heavily on the rear-view mirror while using past results and trends as a dashboard indicating what might come next. This has shifted in recent years, as many parts of organizations have moved to more proactive approaches powered by advanced and predictive analytics tools. Finance departments have started using financial analytics to shed their dependence on what happened in the past and instead focus on what's happening in the business now -- and what that's likely to mean going forward.
Using advanced analytics to drive the business forward
Marketing and sales have made a similar move to better understand what customers might do next. Manufacturing has used it to optimize operations based on anticipated fluctuations in demand. Even HR has tapped into analytics to improve the employee recruitment process.
However, finance remained woefully behind, wallowing in continued dependence on history. Most CFOs and their employees still rely upon historical snapshots.
No more. Advanced financial analytics and its ability to use big data to essentially "see the future" has come to finance departments. In fact, recent research from the American Productivity and Quality Center (APQC), which provides business benchmarking and best practices, indicates that 51% of respondents are using predictive analytics in finance.
The combination of a tight process that draws upon a single authoritative source of data and predictive financial analytics that generate forward-looking insights represents a game changer for finance departments.
"It's about fundamentally rethinking our approach to solving problems and supporting business decisions," said Steve Player, senior financial management research fellow at APQC.
That can mean using financial analytics to better predict the immediate future and say goodbye to time-consuming and often frustrating annual budgeting processes. Or it may mean better electronic linkage of records across the supply chain, thus requiring data to only be entered once and, in the process, freeing up finance to more easily validate that data.
Even better, the continuous visibility into financial and operational health doesn't just help with decision-making; it removes the cloak of mystery around the processes that support those decisions. For instance, instead of simply getting data on employee turnover rates and the associated costs after the fact, financial analysts and HR leaders will be able to see what employees are struggling with and intervene not only to improve performance, but also to prevent costly turnover from occurring.
"Most modern businesses measure everything," said Sam Lessin, co-founder and co-CEO of Fin Analytics, a cloud-based platform that uses advanced analytics to measure operations, and former vice president of product management at Facebook. "The big problem historically has been that they might understand their output metrics, but the actual processes have always been a black box."
Bringing processes into the light is a big part of making the most of financial analytics. A lot of finance data coursing through organizations today isn't in sync with actual data. The processes behind the systems that spit out financial insights based on historical data are often disconnected and result in glaring data gaps. For this reason, Chandana Gopal, research director for analytics and information management at IDC, recommends that finance work closely with IT to bring discipline to those processes and ensure that data sources are in sync before going too far down a financial analytics path.
"You don't want to automate a bad process," Gopal said. "If you build those models wrong, you may as well do it manually."
Conversely, the combination of a tight process that draws upon a single authoritative source of data and predictive financial analytics that generate forward-looking insights represents a game changer for finance departments. Instead of spitting out budgets at certain times of year and constantly referring back to them, it becomes possible to do continuous rolling budgeting, thus keeping financial decision-making in sync with what's happening in the business now, not what was happening weeks or even months before.
"We are talking about a much more efficient approach to finance where you're not dependent on snapshots of data and you're not working on intuition," Gopal said. "If you're able to predict where your books are going to close before the end of the period, you can change course before that happens. You're not just looking at data retroactively. You're able to look forward."
Think about that driver whose eyes tend to settle on the rear-view mirror. Businesses still doing things that way are a lot more likely to hit avoidable bumps in the road, or worse, find themselves derailed by crippling accidents they might have avoided.
By shifting their emphasis to predicting the future, finance departments can help to guide their organizations along a much smoother path.
