Five Ways CFOs Can Implement Advanced Analytics


As the amount of data available grows exponentially, businesses increasingly recognize data and analytics (D&A) as valuable assets. Meanwhile, institutional investors and equity analysts are now evaluating companies’ D&A strategies as part of their valuations, according to a 2015 report by KPMG.

In this context, the use of advanced analytics has the potential to transform the role of the CFO.

Advanced analytics (machine learning, natural language processing, optimization, predictive and prescriptive analytics) can extract patterns hidden behind big and unstructured data, model hundreds of possible scenarios and optimize the best courses of action among all alternatives.

The result? Improved human decision-making capabilities to drive improved customer experience, higher growth and efficiency, and a culture of innovation within their respective companies.

CFOs can implement advanced analytics to optimize their business decisions in a number of ways:

Early detection of activity changes. Most CFOs use historical measures and ratios in financial analysis to understand and forecast the financial condition of their organizations. In today’s disruptive business environment, it’s critical that CFOs detect and understand early signals of change and position their organizations to adapt.

Advanced analytics can help extract internal and external data to get a holistic view of customers, competitors, suppliers, partners, and employees, helping to manage business performance at granular levels. Multiple models with hundreds or thousands of variables can be considered, and those with the best results can be selected to generate optimized results.

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Consider a traditional business with a proven rival. For years, the company focused on its competitor. For this company, news of a startup with a similar product that just received a major funding stream would be a new story. In today’s environment, learning this news too late can spell trouble.

Predictive analytics tools that can detect and interpret these market signals on a global scale and continuously provide CFOs with valuable insights that will enable them to not only adapt successfully, but also thrive in the current market.

Fixed assets management. An organization’s capital assets (for example, facilities, infrastructure, equipment, and networks) are often its most significant resource investment.

Data collected from sensors, performance reports, maintenance history, inspections and a range of other sources can be leveraged to predict and even make decisions about when to repair or replace aging assets. With this information, CFOs can better manage asset value, customer satisfaction, and overall performance.

Optimization of budget planning. When preparing a budget, complex business rules and constraints are usually involved. The planning process can become very complex due to a large number of decision points that need to be assessed simultaneously, including demand and availability of funds.

D&A optimization techniques effectively translate business rules into mathematical formulas that can be used to create dynamic budgeting and forecasting scenarios. Algorithms solve these equations and provide the best budget allocation options among all possible alternatives and sets of criteria, such as managing cash flow and ROI, maximizing reliability, and minimizing risk.

Predict internal disturbances. Internal risks and uncertainties can disrupt business. Managing supply chain risk, for example, is a key strategic responsibility for the finance office. The finance organization has access to data such as accounts payable, accounts receivable, manufacturing, and shipments. By using advanced analytics, finance has a great opportunity to turn data into insights to help proactively manage risk.

Predictive analytics — the CFO’s periscope. Every industry faces fierce competition, from traditional rivals to unidentified new entrants to the market. Traditionally, CFOs could only consider a few scenarios to manage the changes facing their business. But in today’s disruptive environment, CFOs need the help of “broad intelligence” – tools that will help them see emerging trends and potential threats around the corner.

With advanced analytics, including predictive analytics and machine learning, CFOs have tools that broaden their view and present a wider range of scenarios that could disrupt their business.

It’s up to CFOs to embrace predictive technologies and use the insights derived from them to help make their businesses relevant and successful.

Viral Chawda is managing director of data and analytics at KPMG.


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