Are you aware of the benefits of machine learning and how it is able to support you within your daily business activities? As a quick recap you might want to have a look at this fun and insightful video about Intelligent Technologies: SAP Leonardo Machine Learning (Video).
The video provides a nice intro to what exactly is machine learning and how machine leaning contributes to becoming an intelligent enterprise. “Are you still following?”
So, let us now focus on how exactly machine learning can help finance professionals already today in the area of financial statements.
Financial statements and in particular the profit-and-loss statement (P&L) are conflating financial data from single departments and legal entities to the (group) enterprise level. As part of financial reporting P&L statements provide valuable insights into the health of business, as well as proof points for enterprise planning and strategic decisions.
So as a controller, how to gain all the insights the profit-and-loss data can provide you? How to easily profit from your data without spending days for manual investigation of every single cost center, profit center or product category? Without still overlooking the relevant?
That is where SAP Financial Statement Insights offers help!
SAP Financial Statement Insights enables finance professionals to easily discover hidden trends and make strategic decisions by performing personalized, real-time analysis of P&L statements. “Smart Alerts” powered by machine learning indicate unusual business exceptions, making it clear where to focus and what to investigate first.
As a cloud solution within the SAP Cloud Platform it is easily consumable and directly connects securely to existing SAP S/4HANA on-premise or cloud instances. This allows controllers to leverage new visualization and analytics capabilities for real-time P&L data.
Which financial insights do you want to gain from your P&L statements?
In a convenient and easy-to-use way SAP Financial Statement Insights visualizes profit-and-loss data: Compare actuals and plan data on a yearly basis (picture 1) or quarterly accumulated (picture 2), apply filters to slice and dice data using account hierarchies down to cost and profit center level. This helps to check for plausibility and quickly understand the root cause of observed unexpected data anomalies.
Picture 1: Comparing profit-and-loss plan and actuals
Picture 2: Comparing profit-and-loss plan and actuals quarterly accumulated
Looking for data anomalies quickly becomes a cumbersome manual task. Sure, some spikes in the overall data are obvious or unexpected discrepancies from plan are good hints where to look for. But what if all your aggregated data looks perfectly fine and your usual detailed looks into specific product categories are good to go, too? Do you continue investigating further without even knowing what exactly to look for?
Data anomalies deep down in individual cost or profit centers are easily overlooked even when spending a lot of time manually slicing and dicing your data.
Smart Alerts using machine learning
Here, machine learning technology is covering your back. With Smart Alerts in SAP Financial Statement Insights machine learning is pointing you to business exceptions. This provides smart guidance on where to focus on and have a deeper look at. On a daily level machine learning is detecting discrepancies between your actual profits and losses and system-calculated expected values. The machine learning model is automatically trained on your historical data. Smart in-app notifications then pointing the finance professional to relevant data points to focus and spend your valuable investigation time on. For each business exception an overview together with a description is given (picture 3). With another single click all related single line items can be displayed to start analyzing the root cause of this anomaly. This helps to quickly find, investigate, understand and act on unexpected data in your profit-and-loss financial statements.
Picture 3: Smart Alerts guided to a business exception in profit-and-loss statement comparing actuals with machine learning expected data
Smart Alerts within SAP Financial Statement Insights help to easily increase the quality of P&L statements to always stay on top of your company’s P&L data. We’re providing a free public trial to get your hands on. Simply give it a try here.
And there is more than that. While deep-diving into the profit-and-loss structure using human learning, you might come up with ideas and thoughts about how to improve your cost and profit structure. For example, moving from a sales channel view to a product category view might be better in your specific case. Within the cloud solution it is possible to quickly simulate these changes by building new hierarchies. These “what-if investigations” are performed on the actual S/4HANA real-time data without any change in the actual ERP system. So, there’s no need to reach out to your ERP master data specialists and having them temporarily build up these new hierarchies in the ERP just for playing around and to understand possible impacts. Needless to say, the approach of SAP Financial Statements Insights is much more insightful than exporting data into spreadsheets and running investigations manually on outdated data.
Interested to see what insights you can gain from your profit-and-loss statements?
Register for our free public trial and immediately try out SAP Financial Statement Insights in the SAP Cloud Platform: Register now!
More details about SAP Financial Statement Insights can be found on the product page, in the product video.
Okumaya devam et...
The video provides a nice intro to what exactly is machine learning and how machine leaning contributes to becoming an intelligent enterprise. “Are you still following?”
So, let us now focus on how exactly machine learning can help finance professionals already today in the area of financial statements.
Financial statements and in particular the profit-and-loss statement (P&L) are conflating financial data from single departments and legal entities to the (group) enterprise level. As part of financial reporting P&L statements provide valuable insights into the health of business, as well as proof points for enterprise planning and strategic decisions.
So as a controller, how to gain all the insights the profit-and-loss data can provide you? How to easily profit from your data without spending days for manual investigation of every single cost center, profit center or product category? Without still overlooking the relevant?
That is where SAP Financial Statement Insights offers help!
SAP Financial Statement Insights enables finance professionals to easily discover hidden trends and make strategic decisions by performing personalized, real-time analysis of P&L statements. “Smart Alerts” powered by machine learning indicate unusual business exceptions, making it clear where to focus and what to investigate first.
As a cloud solution within the SAP Cloud Platform it is easily consumable and directly connects securely to existing SAP S/4HANA on-premise or cloud instances. This allows controllers to leverage new visualization and analytics capabilities for real-time P&L data.
Which financial insights do you want to gain from your P&L statements?
In a convenient and easy-to-use way SAP Financial Statement Insights visualizes profit-and-loss data: Compare actuals and plan data on a yearly basis (picture 1) or quarterly accumulated (picture 2), apply filters to slice and dice data using account hierarchies down to cost and profit center level. This helps to check for plausibility and quickly understand the root cause of observed unexpected data anomalies.
Picture 1: Comparing profit-and-loss plan and actuals
Picture 2: Comparing profit-and-loss plan and actuals quarterly accumulated
Looking for data anomalies quickly becomes a cumbersome manual task. Sure, some spikes in the overall data are obvious or unexpected discrepancies from plan are good hints where to look for. But what if all your aggregated data looks perfectly fine and your usual detailed looks into specific product categories are good to go, too? Do you continue investigating further without even knowing what exactly to look for?
Data anomalies deep down in individual cost or profit centers are easily overlooked even when spending a lot of time manually slicing and dicing your data.
Smart Alerts using machine learning
Here, machine learning technology is covering your back. With Smart Alerts in SAP Financial Statement Insights machine learning is pointing you to business exceptions. This provides smart guidance on where to focus on and have a deeper look at. On a daily level machine learning is detecting discrepancies between your actual profits and losses and system-calculated expected values. The machine learning model is automatically trained on your historical data. Smart in-app notifications then pointing the finance professional to relevant data points to focus and spend your valuable investigation time on. For each business exception an overview together with a description is given (picture 3). With another single click all related single line items can be displayed to start analyzing the root cause of this anomaly. This helps to quickly find, investigate, understand and act on unexpected data in your profit-and-loss financial statements.
Picture 3: Smart Alerts guided to a business exception in profit-and-loss statement comparing actuals with machine learning expected data
Smart Alerts within SAP Financial Statement Insights help to easily increase the quality of P&L statements to always stay on top of your company’s P&L data. We’re providing a free public trial to get your hands on. Simply give it a try here.
And there is more than that. While deep-diving into the profit-and-loss structure using human learning, you might come up with ideas and thoughts about how to improve your cost and profit structure. For example, moving from a sales channel view to a product category view might be better in your specific case. Within the cloud solution it is possible to quickly simulate these changes by building new hierarchies. These “what-if investigations” are performed on the actual S/4HANA real-time data without any change in the actual ERP system. So, there’s no need to reach out to your ERP master data specialists and having them temporarily build up these new hierarchies in the ERP just for playing around and to understand possible impacts. Needless to say, the approach of SAP Financial Statements Insights is much more insightful than exporting data into spreadsheets and running investigations manually on outdated data.
Interested to see what insights you can gain from your profit-and-loss statements?
Register for our free public trial and immediately try out SAP Financial Statement Insights in the SAP Cloud Platform: Register now!
More details about SAP Financial Statement Insights can be found on the product page, in the product video.
Okumaya devam et...