Revolutionizes Endress+Hauser’s Data Processing

As a manufacturer of more than two million sensors and systems annually, Endress+Hauser is a global market leader in measurement instrumentation and automation technology for process and laboratory applications. Devices, solutions, and services of the Swiss company are used in many industries to gain valuable knowledge from applications. This enables customers to improve their products, work economically, and, at the same time, protect people and the environment.

Almost every instrument delivered is unique and adapted to the customer’s individual requirements. Analyzing and entering the customer’s configuration requirements for the instruments into the respective systems was a time-consuming manual task. However, this changed during a project with SAP AppHaus Network member sovanta. With the help of SAP Business Technology Platform (SAP BTP), sovanta’s assistant now automates the time-consuming and error-prone task powered by artificial intelligence (AI).

Before: Error-Prone and Manual Paperwork

Endress+Hauser’s core competency is to provide customers with devices of the highest quality, taking into account their individual requirements. However, necessary preparatory work prevents employees from fully concentrating on this.

Before the instruments can be configured based on the specification data, the requirements must be processed manually. For one project, between 100 and 10,000 data sheets are provided by the customer. The format, layout, and description of the attributes vary between customers and projects. The challenge of the time-consuming and error-prone import of the specification data had to be solved, and it was an ideal use case for sovanta’s new assistant powered by machine learning. in a Nutshell is a factory for digital assistants based on artificial intelligence. Endress+Hauser’s assistant automatically transfers requests and information to the right place within the SAP system with the help of AI. Data that comes in via e-mails, PDFs, or images is classified, contextually understood, transferred to the SAP system, and finally filed. Manual clicks become obsolete. Using a dashboard, the activities of can be monitored and corrected, so that it quickly learns and improves.

The resulting process optimization can be achieved in order entry, cost classification, ticket assignment, invoice approval, master data maintenance, and other repetitive and time-consuming business processes. Adaptable to any use case, can be ready for individual use cases within a time frame of six weeks.

After: Automated Data Processing

In light of Endress+Hauser’s initial business challenge, the answer is obvious. Communicating with SAP Business Technology Platform, takes over the processing of customers’ configuration requirements for the instruments. For this purpose, is provided with the customer’s specification data as a trigger to proceed further. With the help of a machine learning algorithm, it decides how to process the data so that it can be transformed into the right output format. Customer attributes, such as units used, are automatically identified. Ultimately, the specification data is imported in a fully automated fashion into Endress+Hauser’s platform. Employees can monitor and correct the processing in the project dashboard at any time.

“Our customers send us specifications with measurement requirements every day, and we have to transfer these from PDFs, images, or text files into our project format. This process is very time consuming and error prone,” David Haener, program manager, engineering, Endress+Hauser Group Services, explained. “With we can automate 60% completely! But we have set ourselves much higher goals, which we are getting closer to every week together with the team from sovanta.”

High Optimization Level with a Steep Learning Curve

Endress+Hauser doesn’t supply mass products. The business segment of the Swiss company is characterized by customer orientation and consideration of their requirements – a special challenge for that it solved with excellence. The recognition rate is currently at 60% and benefits from continuous improvement, as the assistant learns with each new import. Additionally, as specification data sheets are standardized in the future in terms of format, layout, and description of attributes, the automation rate will continue to climb. Since its introduction, allows the sales and project teams to focus on their value-adding core competencies, thus further ensuring the success of the company.