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Evaluate company data to plan or even predict the future

Most companies collect data to control key figures. A smart analysis tool makes it much easier to collect, evaluate and visualise data. In addition, it is possible today to draw conclusions regarding future events with so-called predictive analytics.

The demands of the management level

Reporting should provide managers with all the information they need about the company. Compressed and up-to-date financial key figures from the individual departments are used to prepare, plan and control decisions. Ideally, employees with the appropriate authorization can simply pull the reports they need from the system. At the very least, however, it should be easy to distribute the reports to those responsible. It should be possible to create the required reports as efficiently as possible, the collected data should be selectable according to various criteria, and the results should be clearly presentable. Today, automated processes and algorithms can also be used to create future forecasts or run through various scenarios on the basis of the analyses created.
Most companies compile data to monitor key performance indicators. A smart analysis tool massively facilitates the collection, evaluation and visualization of data. In addition, it is possible today to draw conclusions regarding future events with so-called predictive analytics.

Our proposed solution

SAP Analytics Cloud With SAP Analytics Cloud, users can create analyses and evaluations themselves. The visualisation is based on dashboards. The evaluations can be displayed from a wide variety of angles, and charts with filters and deviations can be inserted and edited. SAC contains a comment function and collaboration elements. This turns the dashboard into a team analytics tool and is the basis for discussions in the specialist departments. Thanks to an interface between the reporting and source systems, the data from a wide variety of sources can be merged and condensed in a semantically correct way. The use of so-called in-memory technology enables real-time data collection and a computing power that classic relational database systems cannot provide.

Reporting solution with the SAP Analytics Cloud

THE REQUIREMENTS

  • Targeted merging of data from different sources
  • Mobile solutions for reporting
  • Reports and BI for specialist departments
  • Factors influencing data points - Smart Insights e.g. identify data-specific success factors of successful branches
  • Factors influencing KPIs - Smart Discovery e.g. which raw materials have to be purchased when
  • Key figures at a glance
  • Visualisation of the standards - Management Information Design

THE POSSIBILITIES

 

  • Creating visualisations
  • Performing ad hoc analyses
  • Rapid recognition and evaluation of important key figures
  • Simple integration and use of further data
  • Create profit centre / cost centre levels
  • Drill-down / drill-up by cost centre and cost type
  • Self-service BI for responsible persons
  • Visualisation suitable for the target group
  • Role concept, access of the responsible persons
  • Selection of evaluations depending on authorisation
  • Plan / actual data comparisons, selectable by plan version
  • Notation concept IBCS®
  • Access to tables always possible even with visualisation
  • Access to on-premise and cloud data
  • Highlights of the most important information Smart Insight - influencing factors on your data points
  • Smart Discovery - Forecast function

Advantages of a reporting tool from the cloud

Authorised persons can access the data at any time from anywhere. Data availability and flexibility increase, the effort of the IT department decreases - this benefits SMEs in particular. Outsourcing the applications to the cloud also eliminates the costs for investments in local hardware and software and for ongoing operations. Of course, a hybrid solution is also conceivable. If an SME wants to keep sensitive data in-house, SAC from the cloud can easily be combined with it.

Published by:

Dr. Stefan Lieder

Former Head of Data Science Workshop

AUTHOR:IN

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