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Operational Data Analytics Extends Finance’s Value

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Read more about author Bill Koefoed.

Futuristic films, such as the new “Doctor Strange in the Multiverse of Madness,” are a fun look into what the future might hold. But outside the cinema, we’re seeing shifts in what’s possible right now. By leveraging operational data that’s collected throughout their very own organization, finance leaders are transforming the finance function and extending the value they offer far beyond reporting and compliance.

With the sheer volume of operational data available and the recent advancements in corporate performance management (CPM) software, finance teams finally have the capabilities to deliver on the promise of advanced analytics.

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What Is Operational Data?

In a nutshell, operational data, also known as organizational data, is simply data that is collected through the day-to-day operations of an organization. Things like sales orders, shipments, inventory, supplier performance, customer renewals, and more fall under this data set. 

How Do You Leverage It, and Where?

Despite access to vast amounts of operational data, access to raw data is ultimately meaningless without the capability to interpret that data and understand the impact on financial results.

Finance departments are notoriously slow on adopting new technology, but as advanced analytics are woven into modern CPM software, the technology required to analyze large volumes of operational data and make predictions is becoming more common. In fact, a spring 2022 survey of finance leaders found that only 13% of finance teams are not currently leveraging a predictive analytics tool that uses historic data to help with financial planning, forecasting, and analysis. Additionally, 50% of finance leaders plan to invest more in predictive analytics tools this year than in 2021. 

Leveraging operational data to identify key trends and signals is critical to driving more informed decisions across the enterprise. But, if finance teams are spending too much time collecting and reconciling the data and compiling reports, little time is left to actually analyze the data and drive more informed business decisions. Built-in, advanced analytics allow finance teams to shift their time to value-driven activities, such as forecasting revenue or evaluating key capital investment decisions.

What Are the Business Benefits?

The digital era is carving out an evolving role for finance executives as they’re required to be more agile in their decision-making and strategy. Simultaneously, they need to focus on the longer lead view of their organization while providing line managers with a more immediate view into the pulse of the business.

When integrated into existing financial reporting, planning systems, and processes, advanced analytics (including machine learning and AutoAI) can leverage operational data to arm finance teams with better forecasts, improved decision-making, and increased collaboration with other teams.

It’s inevitable that CFOs and finance teams are facing a growing need to assess, model, and predict future scenarios to support critical decision-making for business continuity. Tapping into the large volumes of data available in the enterprise and implementing advanced analytics creates an opportunity for finance teams to make a strategic impact and become better business partners.

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