5 Ways Data Analytics Can Help Retail CFOs Navigate Headwinds

Faced with the highest inflation rates in more than 40 years and macroeconomic uncertainty, retailers urgently need a comprehensive and always up-to-date view of their business. To achieve this, they need in-depth, real-time insights to effectively guide and predict financial performance — and to remain competitive.

For chief financial officers, one of the most powerful tools against uncertainty is data analytics. Here are five ways data analytics can help CFOs seize opportunity and drive value amid the current retail tumult:

Maximize Staff Effectiveness

The battle for talent is not new for retail, but the global pandemic only exacerbated the problem — and the back office hasn’t been immune. More than half (54 percent) of CFOs across all industries say hiring and retaining staff will be their most difficult task in 2023, Gartner finds. Further challenging the finance function, in a separate survey of CFOs: 41 percent indicated they're prioritizing analytics and data storytelling skills of new hires — skill sets and competencies that weren't common prerequisites for most finance roles five years ago.

With the right skill sets, finance teams can consolidate, manage and analyze data across the entire operation, helping to deliver actionable insights to the business. Expanded skill sets, combined with automated reporting processes, will enable teams to spend less time on data entry and more time on value-driven tasks, such as identifying outliers and course corrections.

Go Deep on Strategy

Putting out today’s fires can’t get in the way of building tomorrow’s future. CFOs continue to ask important strategic questions, such as do we have a reasonable profitability goal per store. What store footprints should we have? What are the true labor and fixed costs required to execute and deliver a buy online, pick up in-store business model?

Yet answering such questions in today’s dynamic environment is difficult (if not impossible) without analytics, which offer greater operational dimensionality and can give finance leaders a full picture of their retail transactions by blending data from diverse sources, such as store square footage, CRM, social media, and point of sale. As important, the ability to combine historical and real-time data can provide a competitive advantage as retailers adapt to this ever-changing environment.

Engage Business Leaders With Decision-Ready Insights

Too often, financial, human resources, and operational information sits in data silos. Analytics solutions make it easier to combine and transform these disparate numbers into understandable data stories that can spark collaboration and spur action — whether that’s guiding the CEO through the company’s real estate portfolio or talking through opportunities and risks with the head of merchandising. According to Gartner, the increased use of dynamic, in-context data stories will reduce the amount of time financial planning and analysis (FP&A) teams spend manually populating pre-defined dashboards.

Drive Greater Employee Productivity and Organizational Agility

As CFOs look for ways to fight inflation’s impact on margins, self-service data analytics will be a critical capability for driving employee productivity, according to a Gartner survey. When considering tools to enhance both store manager and employee productivity, nearly half (49 percent) of CFOs put self-service data and analytics at the top. What’s more, at least one in four respondents also view it as a driver of increased organizational speed and agility, a necessity for weathering ongoing market disruptions.

Turbocharge Your Forecasting Capabilities

Supply chain volatility, including ongoing shipping delays and a pullback in consumer demand, have left many retailers with both overstocks and stockouts — and many CFOs with the challenging task of accurately forecasting quarterly sales. A recent Gartner survey found that 36 percent of CFOs rank forecasting as a top challenge in the near future, driven by “persistent inflation and unusually high macroeconomic uncertainty.”

But as McKinsey notes, advanced analytics is allowing retailers to generate better, more accurate forecasts, particularly for demand planning and sales and revenue forecasts. Armed with dynamic forecasts that extrapolate data in real time and allow for a more frequent reporting cadence, retail leaders can more quickly react to shifting changes in the marketplace and recalibrate accordingly.

As we look ahead, artificial intelligence and machine learning (AI/ML) will only add to the value finance teams can deliver through data analytics, helping with the volume and analysis of data. Retail CFOs that expand and hone their organization's data analytics capabilities will be better able to adapt to changing consumer trends, supply chain disruptions, labor fluctuations, and more — now and in the future.

Terrance Wampler is the group general manager for the office of the CFO products at Workday, responsible for leading the strategy and development for the Workday Financial Management suite of products.