How to Be a Data-Driven CFO

Two key tips: Start small, and make sure to gather lots of input from company employees.
Rodger HowellMay 27, 2016
How to Be a Data-Driven CFO

Today’s technology, cloud, and IoT-driven world is continually generating a wealth of data, creating both opportunity and challenge for those tasked with deciphering and analyzing it. CFOs in particular are now facing increased pressure to connect the dots between multiple data streams to identify patterns that will optimize a company’s growth and align its costs with its strategy.

Rodger Howell

Rodger Howell

Although not all CFOs currently rely on data analysis in their decision-making, they are increasingly aware of its necessity. In 2014, nearly 70% of CFOs reported that digital developments are changing their profession and how their companies do business. CFOs are expected to be strategic partners in the C-suite responsible using data-driven insights to enhance profitability, efficiency, and operational success. This new kind of CFO is unlocking the power of big data in order to support his or her company’s long-term strategy and vision.

Understandably, the sheer abundance of information generated by even a moderate-sized operation can be overwhelming to CFOs who have not yet begun to extract and analyze the data available to them. Data sources can be internal or external, structured or unstructured, and useful or useless. Finance professionals are likely to wonder where to begin.

Drive Business Strategy and Growth

Drive Business Strategy and Growth

Learn how NetSuite Financial Management allows you to quickly and easily model what-if scenarios and generate reports.

There is no one-size-fits-all approach to becoming a data-driven CFO. But finance leaders can bring data analytics and integrated thinking into their organization’s day-to-day decision making by exploring the following steps:

Setting Goals and Objectives: CFOs should first identify the organization’s short and long-term objectives, developing key performance indicators to track progress. Consider this step the impetus that will motivate business leaders to introduce data analytics to their day-to-day operations and to assess their impact on business goals. By developing target metrics, a CFO will unconsciously commit the organization to routinely collecting and analyzing data.

Engaging with the Rest of the Organization: After setting an organization’s strategic objectives, it is crucial that CFOs and finance leaders engage with the rest of the organization to ensure data analytics become engrained in routine decision-making. Alternatively, a CFO may find that data analysis is already a well-entrenched part of the machine in other business units, which could create an opportunity to learn from established processes.

A vital aspect of this stage is collecting feedback from those who interact with the data analysis platforms firsthand. Engaging within the organization will not only help finance leaders understand the capabilities and weakness of the existing platforms, it will also safeguard against any inconsistent analytics methods across the company.

Proposing Pilot Projects: Once CFOs have buy-in from key players within the organization, they should use this support to introduce pilot projects rooted in data analytics. CFOs can start small by proposing new operations and always being sure to encourage participation from other members of the organization. As these pilot programs progress, the goal is to illustrate the CFO’s data literacy and knowledge of on-the-ground perspectives to other business leaders.

Collaborating with IT and Data Experts: While data analytics platforms are able to organize large amounts of information into digestible portions, CFOs should remember that their IT departments and data experts are an invaluable resource able to better parse through the results generated. Partnering in this way will inform the decision-making process and also uncover additional points of view which may not have been previously considered. Collaboration with IT and data specialists could also lend additional credibility to analytics-driven initiatives.

Ensuring Accuracy: With deeper use of analytics comes great responsibility. CFOs must remember to work diligently towards strong data governance. This means ensuring that consistent and strict guidelines for analytics are implemented and enforced across the organization. These principles should outline protocols for data ownership, quality, security, and accuracy. Good insights and strategies are born only from reliable and credible data analysis.

Seeking Feedback: There is an adage that says, “If you want to walk fast, go alone; if you want to walk far, go together.” CFOs must realize that ongoing feedback from other members of the organization, including its leadership, is necessary after introducing new data analytics platforms and processes. Seeking out and listening to the input of others will allow finance leaders to adjust course as needed and perfect the system in place.

Undoubtedly, embracing a truly integrated approach to data analytics is a significant undertaking that requires equally significant levels of time, learning, and patience. However, CFOs that actively take steps toward becoming data-enabled can increase their effectiveness and create meaningful change in their organizations.

Finance leaders should start small by educating themselves on data analytics platforms and technology, or by examining existing data to gain greater insights on the business. By taking a prudent yet proactive approach to establishing analytics platforms and processes, CFOs will elevate their role in the C-suite and ensure their organization has the correct business models, platforms, talents, and tools to succeed.

Rodger Howell is a principal at Strategy&, a unit of PricewaterhouseCoopers.

4 Powerful Communication Strategies for Your Next Board Meeting