These days, CFOs are challenged with producing more accurate forecasts of their business, complying with ever-changing regulations and reporting more frequently based on newer streams of data. The business environment today is inordinately more influenced by the events outside the control of businesses than those within the control of organizations. In this hyper-connected world bridged by mobile, social and other real-time technologies, the consumer is truly the king and wields the potential to dramatically impact the “firm value” of even the most respected brands in the world.

But the most important task asked of a CFO is to predict, optimize and grow the firm value of a company. How, then, can a CFO accomplish this objective when a significant number of influencers are outside of his control? This is where the world of Big Data analytics comes to intersect with the challenges of today’s CFO.

While it is important for the CFO to understand the historical performance and benchmarking of a company, which has long been their comfort zone, it is imperative for today’s CFO to be aware, gain insight into, and understand the true impact and the potential influence of all the key external variables – macroeconomic, customer behavioral, demographic and geo-political – on his organization. Big data analytics enables them to do so.

But many analytics initiatives are over before they even begin. A number of organizations, in the rush to understand  and derive value from Big Data streams, are deploying expensive data infrastructure, complex technologies and arcane tools and investing in significant human capital. These siloed initiatives and “boil-the-ocean” kinds of approaches lead to analysis for the sake of analysis, or worse yet, paralysis through analysis. An organization may end up with a handful of new metrics and dashboards from such investments, but are they meaningful? And more importantly, are they adaptable and actionable in dynamic environments?

From the very beginning—before the data collection process even starts—a company must understand that it is more than its processes, information and products. Every company has its very own Higgs boson, if you will—the corporate God particle, which, once captured and defined, provides the deepest level of insight possible into the company’s most important goals and strategies. Management must use laser-like focus to derive actionable results based on continuously changing data. An ideal Big Data environment solves specific problems, answers specific questions, provides predictable guidance and allows for insights to adapt to real world changes as they occur. From an operational standpoint, it needs to deliver faster, more accurate and more focused results than any previous strategy. And from the CFO’s standpoint, the Big Data initiative needs to avoid long implementation times, as well as the unbelievably high costs often associated with Big Data projects. 

There are many ways CFOs can take advantage of Big Data analytics momentum to drive firm value and gain a seat at the strategy table. Here are some examples:

1. Customer Risk
One of the biggest risk areas CFOs need to understand, quantify and predict is customer risk. Big Data analytics solutions can uncover deeper insights into shifting customer behaviors, loyalties, and their sensitivities towards an organization’s products and services. Drawing correlations of these behaviors to sales, cash flows and profits could provide significant ammunition for CFOs to make sound strategic planning decisions.

2. Growth & Innovation
Today’s CFOs are challenged to help their organizations drive growth and innovation beyond pure cost cutting. Big Data analytics can precisely spot incremental growth opportunities from adjacent and newer markets that help organizations achieve scale and efficiency. Deeper and broader insights through data analytics into potential collaboration can help CFOs be more successful in engineering transformational acquisitions.

3. Customer Equity & Valuation
CFOs are frequently asked to forecast firm value based on discounted projection of free cash flows. Big Data analytics enables a CFO to deliver a better prediction into these future cash flows by quantifying customer lifetime values (LTVs). With a better grip on customer behaviors, their purchasing predictions and wallet share, CFOs can accurately estimate the LTV of an organization’s current and future customers, and then an estimate of customer equity, which is the sum of all customer LTVs. Customer equity gives CFOs a very valuable and customer-centric view into “firm value.”

4. Execution Efficiency
Today’s CFOs are challenged to guide their organizations in executing the right strategies when the external environment is rapidly changing. The right Big Data analytics solutions can empower CFOs with continually recalibrated predictions in tune with the fluidity of the external factors.

5. Compliance & Regulation
Compliance and regulatory issues represent a time-consuming resource drain, and a heavy risk if all the information required is not in place. A large organization may face several unforeseen compliance and regulatory issues, especially if they are engaged in new business development, mergers or acquisitions. Gaining a sharply focused view into what is required now, and what is likely to be required in the future, is an essential component of successful growth.

Big Data by itself is an incomplete solution. Big Data analytics with a defined and focused objective is the next step. Identifying problems– and how best to solve those problems using actionable analytics —enables CFOs to find the answers they need to specific problems, and to play a strategic and influential role in steering the direction of their companies.

Phani Nagarjuna is Founder & CEO of Nuevora, a Big Data Analytics firm. His operating experience of over 15 years includes C-level positions across Product Management, Sales & Marketing, and Corporate Strategy and Turnaround.

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