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More Time and Better Results with Siemens Gas and Power Thanks to Alteryx
Technology Category
- Analytics & Modeling - Data-as-a-Service
- Analytics & Modeling - Real Time Analytics
Applicable Functions
- Business Operation
Use Cases
- Predictive Maintenance
- Process Control & Optimization
Services
- Data Science Services
The Challenge
The Siemens Gas and Power Division launched a productivity offensive for power plant service in 2016. The objective was to analyze areas where unnecessary costs, such as excessively high material expenses, could be prevented. With several thousand various measures, more than 5,000 different data sets, and over 8,000 employees in the business unit, the investigations were complex and time-consuming. The analyses were nearly obsolete by the time the results were available. The first step was to switch to Tableau to improve the visualization. However, the actual problem with the time-consuming and complicated provision of data was still not solved.
About The Customer
Siemens is one of the most important companies in Germany, established in October 1847. Today, the technology corporation is active in 190 countries, with 125 locations just in Germany. This company, which is traded on the DAX 30 exchange, has about 379,000 employees worldwide. The Siemens Gas and Power Division is one wheel in this huge drive. To ensure that all of the processes interact efficiently here, in 2016 Siemens launched a productivity offensive for power plant service.
The Solution
The big change came about with Alteryx. Alteryx provided automation, so repetitive tasks, such as manually updating the data, are no longer necessary, and the employees can focus more on the analysis. In addition to the time saved, Alteryx also improved the quality of the analysis. Because the dashboards are automatically updated in three-hour cycles, the data is never outdated. Alteryx is user-friendly and easy to learn, these are two pivotal reasons that the employees like Alteryx so much. With Alteryx, employees in a wide variety of departments can be trained as citizen data scientists. In the case of the Siemens Gas and Power Unit, the software is mainly used in middle management for specific process optimization.
Operational Impact
Quantitative Benefit
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