SAP is designing processing and research automation solutions for all kinds of work sectors. Its solutions are suitable for the organizations of all sizes as well. Those organizations looking for cost-effective automation solutions depend a lot on SAP modules to realize their innovation purposes.
Right from healthcare to the logistics sector, from IT to supply chain, there is no field where SAP solutions have not turned the operational scene for the better. The recent product, SAP Analytics Cloud, has been designed for financial planning and has several promises to make for the users. Let’s take a look at the present values offered and future possibilities of Cloud-based SAP Analytics in financial planning.
Wholesome Tool for Planning
SAP Analytics Clouds have all that it takes to make the financial planning an easy affair. The cloud is designed to ensure that planners do not need to run from solution to solution to handle various planning processes. It has arrangements or features for both the analytics, reporting and forecast based on data analysis.
SAP Analytics uses the strengths of data science, predictive analysis, and machine learning to make more sense from database analytics and leverage its results to have a fair idea of what to expect in the coming times. It is a singular decision-making platform that weaves business intelligence and predictive modeling in a cohesive frame to offer support for making future strategies.
New Features Supporting Data Storage in a Comprehensive Manner
The SAP Analytics Cloud planning tool is enriched with features that talk cohesively about the decision-making, futuristic planning, and ways to research better for more accurate predictions. Some of the interesting features of this analytics tool are:
- Waves 8-11: This feature adds to the convenience of predictive analysis by combining the data more extensively or deeply. It utilizes the core competencies of business intelligence modules.
It combines it with more refined data presentation techniques to predict future trends more likely to be closer to the upcoming realities. Thus, it proves its utility as a dependable decision-making tool.
- New columns in table component: The new column is designed to integrate more information into the grid. Shortcuts, similar to those available in MS Excel, help improve the utility and effectiveness of this table for decision-making purposes.
Ease of use of customized formulas, custom cells, and compliance with International Business Communications Standard to store and present financial data gives users a handy analytics tool to use for research-backed planning.
- Integration with MS Office: Financial planning and calculation experts are quite conversant with the MS Excel. They can add and manage macros swiftly. A more accurate approach to adding the Excel data with SAP Analytics makes the reporting worksheets more robust and accurate in giving results.
- Data Actions and Formulas: Apart from doing normal functions of storing, sorting, and performing calculations on the table components, the SAP Analytics clouds come with Data Actions functions.
The actions possible to do with Data Actions are – create and populate new planning information, including forecasts, copy data between various model sections, and ultimately, decode and use any complex information.
Other Important Features That Contribute to Better Financial Planning
The users involved in financial planning do not remain the same set of people always. The change in technologies also needs to be addressed. Some of the innovative features included in the SAP Analytics Clouds planning module that help manage these situations easily are:
- Member on the Fly: The system is scalable enough to incorporate new members as the planning team grows or the members’ roles change. It becomes easily and instantly available for data input and analysis as soon as the member with a new entity or changed entity logs on to the planning module.
- Data Locking and Access Rights: Financial planning is all about handling money and ensuring its availability for future projects. Thus, the users having ample rights only are to be given access.
The safety of data becomes easy to achieve with such security-focused features. Data leakages and misuse are the most significant threats that can hamper the sanctity of any tool. The analytics cloud makes it possible to have a cover of safety and let interactions happen in a safe and well-coordinated environment.
The data locking means setting the granular limits at which the access to data has to be restricted. It is coupled by defining the roles and operational authorities, which can be done in a documented manner with a process controller. Modifying cells with multiple lock stages is a smarter approach that imparts the cloud more user-specific intelligence.
- 3. Calendar and process integration: Some financial planning actions need to keep an eye on date-wise development. The ease of adding notes on that date, like conditions that prevailed on that day, rise, or fall of price data accordingly, and others can help the planners to predict better in terms of clarity and accuracy.
- SAP S4/HANA Cloud integration: SAP S4/HANA cloud integration with the analytics cloud by SAP does the job of bringing intelligence in the working of all aspects of organizational management.
Thus, the costs under all heads or revenues from all sources when providing input to analytics give the data intelligence a touch of sophistication and added practicality.
SAP S4/HANA Cloud has encompassed all the departments like logistics, HR, supply chain, goal planning, and several others on a single interface. Thus, integrating all these functional departments with the analytics cloud can be an innovative addition that may help users extract the best benefits from it.
A lot has been done in the Analytics Cloud of SAP that supports financial planning activities and related decisions. The road ahead comprises more introspection and realizing of the inclusion of intelligent features in the current model.
Developers from SAP are working towards bringing live integration and connectivity of business intelligence modules and people. Secondly, the research is on to know how to enable embedding and more optimization in the tool. This approach aims to enable getting the results that are more unbiased and telling of the organization’s real situation.