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Data Silos: Why CFOs Think This Is the Biggest Financial Mistake

Industrial Silos In The Chemical Industry

What are the biggest (or most common) financial mistakes most companies make? After posing this very question to finance chiefs across all industries and varying business sizes in a recent global survey, the leading answer became evident: data silos.

In the latest Adaptive Insights CFO Indicator Report Q3 2015, 69% of CFOs said that keeping information siloed in departments is the biggest or most common financial mistake that companies make today. How far do the silos spread across the organization? Nearly 40% of respondents said they’re currently managing data from three to five sources, while more than 20% said they’re managing anywhere from five to 10 sources.

In today’s business world, executive decision-makers are asking CFOs for a forward-looking view of the organization to help make the most well-informed and strategic decisions. As a result, CFOs are looking for ways to break down these data silos and create a single source of truth through which they can analyze the fast-growing amount of business data and provide a holistic view of cross-functional performance.

Learn How to Find Hidden KPIs You’re Missing.

A single source of truth is a dependable, accurate, and consistently updated source of data from across the business. It’s an inside look at the digital trace left behind by an entire organization’s activity—one that leaders of all business functions can accept as an accurate representation of their department’s performance, according to the most impactful key performance indicators (KPIs). It’s a centralized and easily accessible hub of information that provides a foundation for discussions about the state of the business today, so that executive decision-makers take the best course of action for tomorrow.

Establishing that single source is easier said than done, as just 38% of survey respondents said their organizations have such a go-to source for accurate and widely-accepted performance metrics. Reaching this goal requires finance teams to embark upon a data journey littered with roadblocks, including manual data aggregation processes and a lack of cross-functional collaboration. These and other significant hurdles along the route can prevent CFOs from getting the information needed to become strategic business influencers and close partners to the CEO in defining the direction of the company.

So how can current finance chiefs guide their teams along this journey to establish a single source of truth? How much of a difference does that centralized source of information actually make for a finance team, and for the broader organization?

Answering the first of these questions is becoming increasingly vital. According to, the amount of available business data is doubling roughly every 12 months, and the general consensus among CFOs within the latest CFO indicator Report is that the amount of data finance leaders will be asked to manage will significantly increase over the next several years (Figure 1).


CFO expectations of data increase, according to the Adaptive Insights CFO Indicator Report Q3 2015.

These trends are leading to an increase in financial technology investment (47% of CFOs surveyed in the CFO Indicator Report Q2 2015 said investing in technology is a top priority, second only to process improvements, and only 5% of CFOs foresee a decrease in finance technology investments over the next two years), as businesses look to automate data aggregation and other manual and error-prone processes, and flow cross-functional information into a centralized location that everyone can trust, thus breaking down data silos. The resulting benefits from breaking down those silos can vary by company and industry, ranging from weeks of time-savings annually to uncovering new performance trends that lead executives to make better, more informed decisions.

For Bonneville International CFO Kent Nate, a centralized source of performance metrics has helped him shift the entire company’s approach to evaluating performance toward a smarter, faster, and more efficient use of business data. According to Nate, that new company-wide focus on leveraging performance metrics and analytics has led the television and radio broadcasting company to make several revolutionary moves within the media industry.

“In the case of our Phoenix market, our consolidated view into performance data led us to move our local talk radio programming in the region across the dial from AM to FM,” Nate said. “We’ve opened-up new ways for employees to look at information … it’s a much more precise methodology.”

Then there’s Steve Omli, director of finance and accounting at the University of Central Florida College of Medicine, who spearheaded the college’s switch from an unsustainable spreadsheet-based budgeting and forecasting process to a new streamlined and efficient approach that includes a centralized location of performance data. With this new information resource in place, Omli and his finance team can make changes to budgets and forecasts on the fly and allow the college’s executive team to take swift action according to changes in everything from tuition fluctuation, to enrollment numbers, to unexpected changes in state funding.

After years of looking at big data primarily as a marketing opportunity and a new way to drive revenue, data analytics projects are now steadily moving up the list of priorities for the finance function. According to the Deloitte CFO Signals: 2015 Q3 Survey, an increasing number of CFOs see themselves as being responsible for assessing the risks and rewards of different strategic initiatives, and for helping other business leaders apply financial strategies to their particular projects. That can only happen once finance leaders create a holistic view of organizational performance from which they guide forwarding-looking business decisions.

Download a full version of the latest Adaptive Insights CFO Indicator Report to find out how today’s most strategic CFOs are breaking down data silos to harness the power of data.

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