Automation of analysis is the key for finance to become data-driven

Every now and then, we’re introduced to a game changing innovation. Remember the days searching for songs on CDs? Or even the CDs themselves—where did you put them? How did you file them? Then along came Spotify. All your music in one place. All your playlists, all your favorites, and an inbuilt recommendation engine that searches through millions of songs to recommend what you would probably like based on what it learns from you. No need to store, sort through, or search for music on CDs anymore. Now you can spend less time searching for music and more time listening to music.

Now imagine a similar concept in the finance function. Data is the music of finance. Finance needs to become more data-driven and put all available data to work. But this can be quite intimidating because finance teams have only so many people and hours in the day. How can they take on more data and analyze all of it? Automation of data analysis has to be the key here. It will empower finance to deal with more operational data and address business problems with broader scope.

Now imagine: “All relevant insights on your screen.” Imagine being able to see any anomaly, bias, or correlation in your data right away, without spending hours gathering up, preparing, and analyzing your data!

With Oracle’s IPM Insights, we are making this vision a reality. Insights, a key capability of the Intelligent Performance Management (IPM) initiative within Oracle Cloud Enterprise Performance Management, uses data science techniques such as pattern detection to help finance streamline reporting, analysis, and decision making. These insights are automatically generated and delivered in a single dashboard so that finance can focus on taking action in collaboration with operating functions—enabling finance to eliminate grunt work and deliver value through informed decision making.  

Key benefits of automating data analysis

Speed and efficiency

Oracle’s Insights engine scans vast amounts of data and displays all the relevant “hot spots” on a continuous basis, enabling finance to take action effectively instead of spending hours analyzing data. This makes finance responsive and more efficient.

Quality insights

Automated pattern detection helps finance uncover insights that are not previously known or easily discovered. It can easily remove trends and seasonality from data, and detect biases, correlations, and anomalies in data that are often not picked up through manual analysis.

Collaboration

All stakeholders in finance and operating functions can now have a common store of all current and historical insights that they can monitor, analyze, and collaborate on. This will improve cross-functional alignment and ensure that key patterns never get overlooked and issues get resolved.

Insights has a wizard-driven interface allowing business users to easily configure target data, insight variables, and materiality around three main types of insights: 

• Forecast variance and bias insights can highlight gaps between forecasts and actuals, uncovering systematic biases in the forecast. For example, if a certain sales rep is overly optimistic in his forecasts, that pattern can be highlighted so that the territory manager can not only adjust the forecast and improve the overall forecast accuracy, but also coach the rep going forward.
• Prediction insights measure the variance between two projections—such as forecasts from business users and machine-generated predictions—and perform a reality check on forecasts in situations where the predictions track the actuals better.
• Anomaly insights detect outliers in recent actuals. You can quickly see unusual patterns in data by removing trends and seasonality and easily highlight an unusual spike in sales without analyzing multiple reports.

Beyond these, the Insights engine is being continuously enhanced with new types of insights to broaden its applicability across all EPM business processes.

Tested with early adopters

Cormac Steer, a senior finance executive at Oracle who has been an early user of Insights, has described it as truly game changing for finance. Before using Insights, his team was spending hours doing things like gathering data, scouring intersections to find insights, and then raise them either up the chain within finance or to business partners. The use of Insights will allow them to automate data analysis and focus on foresight, writing policies and processes, and operational execution.

Cormac says, “This can change the way we work—not just find insights and act on them, but the way we collaborate across functions. I'm super-excited to use this capability going forward. We can really transform an organization with this.”

Now, don’t lose any time. Take a hard look at how much time and effort your finance department spends today in gathering and analyzing data. With Insights, you can shift the focus to acting on data-driven insights.

Take a look at IPM Insights in action. Watch this video.