Data “Do’s And Don’ts” For CFOs

Henner Schliebs

Part 3 in a 3-part series. Read Part 1 and Part 2.

In the new world of data-driven business, a key challenge for CFOs is to determine what data to focus on and what to ignore. Where can you discover insights, and which information is just background noise?

These tips from four finance experts can help you maximize the usefulness of your data and make more effective use of your time.

Don’t boil the ocean

Consumer behavior, commercial factors, market changes – the potential data sources in the digital landscape are endless. But that doesn’t mean it’s all useful. In fact, too much data can lead to ill-informed conclusions. According to Marc Havercroft, COO & vice president, digital strategy & transformation, SAP SuccessFactors, many CFOs get lost in the sea of data, thinking they need to use every data point.

“Sometimes, we have customers who say, ‘Okay, but we’ve got all this data since we started in 1945, so we need to use all of that, right?’” Havercroft says. “The trouble is that people think however much data we create, all of it is valuable, and therefore we must capture it all. Then we’ll think about what we do with it. It’s just the wrong way to think about it. From a CFO’s perspective, start to think about what questions are important to you, and that will align you with what data is important.” Havercroft advises.

Do use predictive data

Narrow your focus to the data that directly informs crucial business decisions. That might mean typical finance data, but it’s important to also look at relevant data from human resources, customer service, and other departments throughout the organization. The right data can help you pinpoint risks and opportunities outside of the traditional finance role, but that fit squarely in your expanded role as trusted adviser.

For example, Havercroft says, “With the right data answering the right questions, you can predict what type of business structure works in one particular country. You can predict retention rates, customer acquisition rates, or when a customer might be at risk of leaving. You can predict whether a manufacturing plant in Southeast Asia is going to continue to be productive for you or become a risk, whether that be as a people risk or a productivity risk.”

The good news is that predictive technologies are more accessible and sophisticated than ever. Through tools like predictive analytics software, you can more accurately anticipate business outcomes before they happen, allowing you to proactively respond to problems or opportunities.

Don’t ignore data bias

Data bias can quickly ruin an analysis, leading to misinformed business decisions that could negatively impact the bottom line. While it may be impossible to eliminate human bias, it can be measured, monitored, and corrected for, says Dr. Aswath Damodaran, professor of finance at NYU’s Stern School of Business.

“Data is contaminated along the way because people have agendas,” he says. “Data analysis should keep track of the different biases that happen at each stage of the process because everybody has an agenda.”

One way businesses can fight bias is through artificial intelligence (Read: How AI Can End Bias). With an algorithm trained to flag potentially biased data, CFOs and business leaders can become more aware of data bias, where it comes from, and how it could skew their data.

Do analyze potential data stakeholders

Your business intelligence tools or data management systems need to include the whole business, from sales and marketing to HR and beyond, in order to make more precise decisions.

Amy Wu, SVP of finance for the global digital division of Discovery Inc., says, “All of my decisions are driven by data, and that’s everywhere from finance data to sales data to marketing data.”

To make well-rounded business decisions, you need to gather insights from these disparate sources, adds Christopher Argent, business intelligence and analytics program lead for Vodafone.

“You have this world of internal data that you can use for performance monitoring. You’re not just focusing on finance data; you’re looking at HR, workforce planning, and retention rates,” Argent says.

Finding those potential data sources takes a creative mind, however.

“If you’re trying to drive down recruitment costs by retaining employees, then maybe there’s behavior analytics that you bring in from your HR team,” Argent continues. “That’s the sort of out-of-the-box thinking that we need in finance right now.”

Simply put, to make business decisions that drive long-term results, CFOs will need to get out of their comfort zone and look beyond the numbers.

It’s only by surfacing the most relevant data and subjecting it to analysis that we can arrive at useful insights. With tools like predictive data, artificial intelligence, and data management solutions, you can optimize the process of turning data into informed decision-making, increasing the speed of insight.

For more tips on how to manage your organization’s financial data and maximize its potential, visit The CFO’s Guide to the New Era of Intelligent Finance.

Why have AI, machine learning, predictive insights, and digital assistants become the must-have new tools of forward-thinking CFOs to drive business performance? Watch the webcast Tuesday, Nov. 6.

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About Henner Schliebs

Henner Schliebs is global vice president Audience Marketing for SAP S/4HANA and Finance at SAP. He is a progressive sales/marketing executive with 15+ years of experience in business software solutions focused on corporate functions. He has strong marketing and go-to-market skills and a proven track record in enterprise software solutions, along with significant experience in solution management and customer engagement.