CFOs: Embrace Machine Learning to Move Beyond the Spreadsheet

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In today’s digital economy, success hinges on a company’s ability to adapt to dynamic business opportunities quickly. To meet the industry demand of a real-time business model, enterprises are moving away from manual processes and looking towards advanced technologies. Machine learning is one such technology that is ushering in this digital revolution by allowing companies to extract insights, streamline reporting and fuel forecasting without having to program computer systems and set manual parameters. Furthermore, machine learning allows organizations to access, analyze and find patterns in Big Data in a way that is beyond human abilities. While the algorithms that enable machine learning have been around for decades, cloud technology has increased today’s computing power – propelling machine learning to the forefront and making this advanced technology a reality.

One business function already seeing the benefits of machine learning is the finance department. The technology is empowering corporate finance executives to generate business results, model forecasts and run predictive analyses on the spot – for fast, informed decision making. With machine learning capabilities, finance teams can swiftly interpret and act on sophisticated financial analyses, minimizing time spent on data entry and maximizing operational efficiencies.

Machine learning is empowering CFOs and other corporate finance executives to think outside the traditional paradigm of the finance function and become a strategic business partner. There are three main areas where machine learning is playing a significant role in increasing operational efficiencies for corporate finance – allowing finance teams to move beyond pre-defined budget cycles, creating a unified view of the enterprise and ushering in a new generation of finance talent.

Saying goodbye to the annual budget cycle

A decade ago, IT systems were constructed to oversee a company’s finances. While they could balance the books and provide valuable information over time, the manual process of reviewing Excel spreadsheets wasn’t timely, left room for error and could take months to review and develop projections. With the role of finance shifting to encompass business strategy and leadership, machine learning’s value lies in a CFO’s ability to gain control and use analytics to support efforts to transform the business. In today’s unprecedented era of economic and regulatory volatility, CFOs need access to real-time financial information to ensure they are making informed decisions to strategically manage an organization’s day-to-day operations. Automating financial processes brings the flexibility needed to move beyond the annual budget cycle to deliver insights and inform decision-making on demand. In this, the CFO role has shifted from providing long term projections, to in-the-moment strategic counsel on financial solutions.

Removing business silos to increase operational efficiency

Machine learning is dependent upon live, integrated business data. Therefore, to fully embrace machine learning technology, businesses need to embrace digital transformation across the board. A digital business at the core is connected, intelligent, responsive and predictive and breaks the silos between finance, marketing, human resources and IT. This connected infrastructure brings together live data, software solutions and business processes, while machine learning leverages the internal, external, structured and unstructured data.

According to a recent study, finance professionals are unable to streamline their work and achieve success as a result of tools failing at their disposal. With a live connection to the marketing department, CFOs can monitor how consumers are responding to new products and continuously update projections. Furthermore, a connection with HR can result in compensation strategies that retain employees and reduce turnover. With a live view of the entire company, each financial decision a CFO makes is fully informed.

Transforming the workforce

Millennials are quickly becoming the majority in the workforce and have high expectations for their workplace environment. They grew up in a world where speed, automation, and accessibility were conveniences, therefore their priorities differ than those of the generation before them.

While corporate finance was once seen as an Excel driven job, the combination of a tech-savvy generation and the digital economy requires finance to move faster and provide real-time data. To cater to this modern employee, finance departments can automate some transactional tasks through machine learning technology. Instead of manually reviewing months of spreadsheets, self-learning algorithms can find patterns and solutions in data to make decisions easily, and with confidence. By taking the work out of the matching and reconciliation of heterogeneous data in back-office processes like procure-to-pay, order-to-cash and record-to-report, employees will have time for more rewarding and higher-value work allowing them to innovate and grow within the company. The benefits of machine learning go beyond operational efficiency and can ultimately attract and retain talent.

Today’s CFO understands that machine learning is a key component of an effective digital business. With technology that enables end-to-end process coverage in real-time and a workforce that understands it, CFOs can properly steer their enterprise toward success.

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