Leveraging Big Data to Influence Corporate Strategy

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Rodger Howell Headshot v2In this special guest feature, Rodger Howell, an Advisory principal for PwC’s Strategy&, provides a number of examples of the ways in which organizations that have implemented data analytics practices to increase revenue, boost operating excellence, improve compliance and streamline financial reporting. Rodger  helps companies align costs to their business strategy. He has 24 years of experience in business model and operational model innovation, enterprise profitability and operations, quality systems design, and implementation. His industry experience includes industrial products, aerospace, electronics equipment, networks service providers, managed services companies, and electronic medical devices. Rodger earned a master’s of business administration from the University of Pittsburgh and a bachelor’s of science in electrical engineering from the University of Michigan.

The role of today’s CFO extends beyond financial stewardship and accountability to functions previously assigned to a chief information officer. No longer solely tasked with financial transaction management, the modern CFO can now serve as an even greater asset to the C-suite by becoming a strategic partner responsible for using data-driven insights to influence day-to-day decision making.

While many CFOs recognize the value of big data and its insights, some are overwhelmed by the volume of information available and have yet to fully leverage it. A 2014 study by PwC revealed that 58 percent of executives consider converting data into insights to be a major challenge. Furthermore, 43 percent of North American C-suite executives believe their senior management colleagues lack the skills and expertise needed to successfully use data analytics for smart decision making. Antiquated business analytics programs and acceptance of current financial reporting methods contribute to this skills gap.

CFOs may feel their company already demonstrates satisfactory reporting capabilities. Most traditional reports provide a wide array of detailed information. Yet they often fail to further interpret the data points they contain to provide meaningful strategic insights. By adopting data analytics into the organization’s decision making and protocol, business leaders can disrupt the status quo and usher in a culture of “data relevancy” and sharper analysis to support (and drive) the company’s growth strategy.

Below are examples of the ways in which organizations that have implemented data analytics practices to increase revenue, boost operating excellence, improve compliance and streamline financial reporting:

Increase revenue and drive profitability: Data analysis helped a medical device company prioritize markets by growth and profitability. By developing an interactive application to simulate three different scenarios, the company was able to more adequately allocate resources, execute the most viable strategy and, ultimately, increase profitability.

Boost operating excellence and supply chain management: A global pharmaceutical company employed data analysis to assess the performance of a sample medical device program by comparatively looking at territories and prescribers that overperformed or underperformed. This helped the organization improve targeting based on expected revenue and outcomes.

Improve compliance and avoid risk: A leading cable and entertainment company analyzed consumer billing and pricing data to ensure compliance with FCC regulations. This process also informed the company when creating business-wide guidelines and helped it develop a monitoring platform to observe compliance on a routine basis.

Streamline and modernize financial reporting: The CFO of a major home entertainment company was able to experiment with three data analysis platforms to assess the accuracy, usefulness and robustness of their existing platform. By collecting data from three programs, the group was able to improve forecasting and implement more reliable annual projections and budgets.

Of course, CFOs are not expected to become overnight data and informatics experts. Nor should they become overly analytics-reliant. While today’s analytics programs are both intuitive and customizable, they will not completely replace the human element. Finance leaders should confer with their IT and analytics department to assess the best applications for analytics, as well as to ensure raw data is being collected and translated correctly. This will produce credible business intelligence for the CFO and finance team. The right approach to data analysis can help CFOs elevate their role in the C-suite and ensure their organizations have the correct business models, platforms, talents and tools to succeed.


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