Data-Driven Finance to Enhance Business Performance

Leadership and Strategy to Change the Culture

Companies with data-driven finance do more than just crunch numbers. They take the guesswork out of decision making, driving results through predictive analytics to seize opportunities and reduce risks. Learn how finance leaders in your organization can start leveraging big data and analytics.

Data-Driven Culture

Enhancing Performance Through Cost Optimization and Fact-based Decision Making

Data-driven finance is not just about running the numbers more efficiently through standardization, simplification and rationalization. It’s about optimizing business performance through broader and deeper visibility into operations, more insightful analysis and more rigorous, fact-based decision making.

So What Does It Take to Achieve a Data-driven Finance Culture?

What’s more, research from the Hackett Group, a leading finance benchmarking firm, and other analysts demonstrates the benefits for companies with data-driven finance organizations:

  • Lean cost structures, with more resources committed to value-adding services
  • Fewer metrics overall and more effective prioritization based on what really matters to the business
  • More time and resources focused on analysis and commentary – and less time and fewer resources working to gather data
  • Stronger predictive and early-warning capabilities
  • Higher rates of automation and use of advanced technology to improve efficiency and flexibility and generate insights

In summary, data-driven finance is not a single tool or technology or a commitment to gathering every piece of available data. Think of it as a way of life and an evidence-based approach to setting priorities, evaluating performance and making decisions. And it’s a means for CFOs to expand their strategic and advisory roles with CEOs and other business leaders.

CFO 2.0 – Analytics Champion, Business Advisor, C-Suite Whisperer

Data-driven finance and Big Data are transforming the role of the CFO – not just what they do, but why and how they do it as well. Consider how they change the game in these strategic and tactical ways:

A Principled Approach to Big Data Analytics

Data-driven finance organizations can become analytics champions by embracing five key principles – agility, sustainability, extensibility, predictability and accountability.

Playing “Moneyball" to Uncover Cost Savings Opportunities

World-class CFOs manage data as an asset and use analytics to generate value from company resources and uncover “hidden gem” opportunities for cost savings and operational improvements.

A More Strategic Role for CFOs

It’s practically a new job description for CFOs – delivering more detailed analysis and more actionable insights, more predictive forecasts and enhanced information on customers, products and suppliers.

How to Make Data-Driven Finance a Reality

So where do finance leaders start to leverage the transformative potential of Big Data and Big Data analytics? Much depends on how quickly their organizations set themselves up with data management systems that foster financial transparency, as well as related organizational structures and decision-making practices. It will be a multi-dimensional journey for most organizations. That means CFOs and other leaders seeking to make Data-Driven Finance a reality must ask the right questions to:

Data-Driven Finance: Above and Beyond the Bottom Line

Doing more with less and lowering the cost of the finance function are the eternal imperatives for CFOs. Data-driven finance certainly pays dividends in these areas. But it’s also about CFOs seizing the opportunity to engage the business as a strategic advisor providing insights that promote operational excellence and foster innovation, while eliminating waste and reducing risk.

Data-Driven Companies

Beyond running the numbers, the CFO organization at the world’s largest aerospace company engages the business with action-oriented data to achieve the strategic vision and change the decision-making culture.

More granular financial and operational data and advanced modeling led to more detailed, accurate and consistent measures of profitability – by product, customer or channel – at Fortune 500 industrial supply company.