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Trends and Outliers

TIBCO Spotfire's Business Intelligence Blog

03/14
2013

CFOs + Big Data Analytics = One Version of the Truth

Increasingly CFOs and other organizational leaders are relying on data-led decision making rather than gut instinct. And that means they need access to data from multiple sources outside the general ledger, such as sales, marketing, and supply chain information.

truth CFOs + Big Data Analytics = One Version of the TruthOperational and monetary information that contribute to a company’s overall financial health is derived from a variety of different business, functional, and geographic inputs.

So it’s critical for CFOs to be able to assess all the financial information that’s available to help them arrive at a “single version of the truth” regarding the overall financial performance of a company, says IDC Vice President and IT Executive Advisor Joe Pucciarelli in a recent interview.

“When we start using predictive analytics and big data, you’ll have people outside of finance contributing data to the decision making process,” says Pucciarelli. As a result, finance chiefs will be called upon in the future to vet data from marketing, supply chain, sales, and other groups to better verify the accuracy of financial forecasting and performance, he adds.

For CFOs the beauty of using predictive analytics and big data is the opportunity to make use of a much broader data set to understand the performances of product-focused and geographical business units. Predictive analytics and big data can also offer deeper insights about customer, market, and supply-chain trends that are impacting business performance.

Meanwhile, visualization tools can help CFOs reduce their companies’ exposure to risk by identifying customers, employees, and even operational processes that pose higher levels of risk to the organization.

For instance, retail CFOs can use big data and analytics to spot and evaluate possible cases of fraud being committed by cashiers. CFOs and their finance teams can analyze POS and transactional data and then monitor specific registers and cashiers to determine whether fraud is being committed.

The speed in which financial data is flowing through the enterprise is staggering. Yet the data on its own doesn’t provide CFOs and their teams any value without the analytical tools to help them make sense of it.

As CFOs and their organizations gain additional experience using big data and analytics, they can apply predictive analytics to perform business modeling and simulations to try to predict what will happen in terms of financial outcomes, according to a report on big data by A.T. Kearney.

Because CFOs are meticulous about capital spending and investments – and because they’re often reticent about investing in IT and data without clear ROI or business benefits, they can also use big data and analytics to evaluate the cost of collecting, storing, analyzing, and acting on big data.

The use of predictive analytics can enable CFOs and other CXOs to determine which data sets are delivering the greatest amount of business value to the organization along with those that are offering the least value.

This type of analysis can help CFOs and other executives determine which data sources are worth investing in – or which they should increase investments in – depending on the level of returns being generated through the use of the data.

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