Our Approach

IoT enables you to realise efficient, intelligent and highly automated end-to-end processes even beyond the boundaries of your ERP.

End-to-end processes

End-to-end processes put the customer at the centre of corporate action: starting from a customer need, "something" runs into corporate systems and then back to the customer at the end. All activities that support and flank this process should be coordinated as seamlessly as possible - even across system boundaries - so that the customer gets his need met as quickly as possible. The more efficiently these processes run, the more profitably a company can fulfil customer needs. Against this background, the following applies: the smaller the number of systems a process goes through, the easier it is to handle and the easier it is to incorporate automation.

On the one hand, process automation is based on the linking of sub-processes; on the other hand, it requires (real-time) data-supported intelligence: logics stored in the system and machine-learning-based knowledge provide the basis for autonomous decisions and the triggering of follow-up processes. Ideally, the employee only has to intervene in exceptional cases or in the case of unexpected events (exception-based action). This enables the cost-efficient realization of individual customer requirements up to lot size 1 production orders.

All of this can be mapped within modern, intelligent ERP systems such as SAP S/4HANA. However, a complete end-to-end process goes beyond the boundaries of the ERP: areas in manufacturing, logistics or products in customer use (whose constant availability is part of the customer's need) often remain outside - IoT technology can help to close this gap.

End-to-end up to the "Thing”

Real-time data from machines and sensors, but also information about manual work progress, which is recorded via AutoID or feedback terminals, can be combined with process data and used for the intelligent automation of processes:

  • For example, machines can deliver status data to a cloud environment (big data), where it is analysed and examined for patterns or correlations with malfunctions and failures. The (condensed) findings - such as forecasts of impending failures - can proactively trigger the deployment of service technicians or spare parts orders.
  • Another example is the continuous recording of order progress in the company's own production. These can be integrated into the ERP in real time so that, for example, detailed planning can be continuously optimized and the plant manager can implement an optimal utilisation of all available resources.

In principle, it makes sense to distinguish between concepts for (I)IoT scenarios for in-house production (internal perspective - "IIoT") and for products used by customers (external perspective - "IoT"), as different processes and company areas are affected in each case.

As a digitisation partner for SMEs, our vested interest lies in transferring such sometimes technologically demanding scenarios into solutions that are as easy to implement and operate as possible, reducing complexity wherever possible. Against this background, we work close to or integrated with SAP and try to avoid complex third-party systems, such as an MES, with additional interfaces. We base our solutions on clearly tangible use cases and, whenever possible, build them up modularly with proven modules such as the All for One IIoT Connector. In this way, we ensure that our customers achieve their goals with investments that are appropriate for medium-sized businesses and benefit from easy scalability.



We're looking forward to receiving your message!