How data science can pay dividends for finance divisions
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If you work in finance, then you know what pressure feels like. Factor in recent events, and you are probably experiencing a level of tension like never before.
That’s no position to be in. Human beings typically don’t operate well under an enormous amount of stress and strain.
The good news is there’s a relief valve, and the key parts to that valve are Domo and data science. In tandem, they can help you gain the leverage you need to unlock opportunities, no matter what comes your way, or how fast the world turns.
Quantifying Uncertainties
If you’ve ever given your company a financial estimate based on a projection or financial model, you’ve probably experienced some level of anxiety. “What if this is wrong?” you might wonder. As you watch the numbers roll in each quarter, you might hope that your projection is close enough to not draw any negative attention from the business.
Data science can help solve this problem for you. Not only can it hep you provide more accurate forecasts, it can quantify your certainty (or uncertainty) in different projections and forecasts.
You can leverage these tools, from math and statistics, to encode your assumptions and get upper and lower bounds for all your estimates. If your bounds are larger, you will have less confidence in your estimate, and vice versa.
Taking it a step further, data science can allow you to run simulations that are incredibly valuable, especially in times like this, when the data we need to run our businesses is changing by the minute, as is the level of importance around that data.
By running simulations, you can evaluate numerous scenarios (or, counterfactuals), including what effect a pay cut, headcount reduction, or even sales drops of any percentage could have on your business.
For CFOs that now have to worry about supply chains costs all the way down to the most detailed levels, data science can enable them to not only get a handle on those costs, but gain a clear picture of how bold or conservative they need to be with any fiscal initiative—and have the simulations to back up what every possible scenario would look like.
Operation Automation
Another pain point that data science helps alleviate for FP&A groups is the amount of time spent on tasks that can be automated.
Take, for instance, the type of CFO I already mentioned—the one that now has to take into account the cost of materials like, say, cardboard boxes. Most finance departments operate in a lean manner to begin with. If they had to determine the cost of cardboard boxes without data science, it would require them to scour Excel files and then copy that information into their finance model.
So much manual activity would be involved in the project that it probably would take weeks—if not months—to produce even a simplistic point estimate, let alone simulations and machine learning models to improve decision making.
The problem with weeks, even? It’s time finance professionals don’t get to spend making guidance more accurate. And it’s time money continues to be spent in an inexact fashion.
Flexing the Mind Muscle
By automating so many processes through data science, CFOs and their teams are able to think on a higher order. They now have time to focus on the financial forecasting process, examine the error profile in the decisions they make, develop new skills and capabilities, and so much more.
Automation not only takes care of the things the department will always be responsible for—such as the annual business plan, the cost basis for expenses, and revenue projections—it frees everyone up to put their minds to work in a way that adds value to the company.
Conclusion
In times of change and uncertainty, people like to seek shelter in the constant. It’s human nature.
For finance professionals, however, their level of responsibility never changes. To furnish what’s expected of them, at all times, they need a solution built to securely aggregate and transform raw data, in real time, so they can make smart decisions and spot-on recommendations, in no time.
With such technology, finance teams are able to spend more time improving the reports and plans they’re constantly asked to deliver, and create more accurate projections and calculations that affect business operations and growth.
To learn how Domo leverages data science techniques to help finance divisions automate laborious processes, become more data science literate, and, in turn, weather any kind of storm, click here.
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