(Bochum, Germany, April 1, 2019) How can companies increase their delivery reliability and reduce logistics costs at the same time? Experts from the Bochum-based software house Setlog will answer this question at the Hannover Messe, which takes place from April 1-5 in the Lower Saxony metropolis. At the International Data Space booth (IDS, Hall 8 / C25), the SCM and IT experts from the Ruhr region will be explaining the application example “Logistics cost reduction based on predicted lead times” from Setlog and Deutsche Telekom to visitors of the trade fair.
Background: It is difficult for companies to accurately predict when their goods will actually arrive at their destination, especially in international goods traffic. A container from Asia, for example, can be several days longer at sea than planned due to bad weather conditions. Exact scheduling of storage and picking processes is therefore often not possible for companies. Shippers are dependent on the forecasted lead times of their forwarders.
In the use case “Logistics cost reduction based on predicted lead times”, companies can obtain transport offers from forwarders and compare the various prices immediately. Once they have decided on a transport with the freight rates offered, the OSCA Setlog system uses Data Intelligence Hub technology to predict a more accurate Estimated Time of Arrival (ETA). For this purpose, transport data from the past is combined with planning data from the MMS, actual data from OSCA and publicly accessible data (e.g. from the areas of traffic or weather), so that the user receives a more precise statement about transport and delivery time. If it turns out, for example, that a low-cost transport will arrive at its destination later than announced, the user can decide on an alternative offer before placing the order. Risk management therefore takes place at the time of booking. During the transport period, the tool offers an ETA alarm in the event of unplanned delays. Further advantages of the system:
“A delivery time as accurate as possible saves companies expensive buffers in the supply chain. Complex supply chains can be planned more securely for all partners using our tool,” emphasizes Ralf Düster, Managing Director of Setlog GmbH.
The platform for the consolidation and analysis of the data is provided by the Telekom Data Intelligence Hub (DIH) already presented at the Hannover Messe 2018. It is based on the International Data Space (IDS) standard developed under the leadership of the Fraunhofer-Gesellschaft. Setlogs OSCA serves as an IDS connector. OSCA now has more than 40,000 users in 92 countries. Data traffic based on the IDS standard is handled exclusively between a company that provides data and its partners, external or central data storage is no longer necessary. Companies who supply data also retain control over their bits and bytes and can determine to whom which information is passed on and to what extent.
In 2019, the Hannover Messe will be held under the motto Industrial Intelligence – The Networking of Man and Machine in the AI Age. More than 6,500 exhibitors from 75 countries will be presenting their innovations at Deutsche Messe AG from April 1-5.
Nora Breuker, Digital Marketing Strategist
Setlog GmbH, Alleestraße 80, 44793 Bochum, Germany Phone +49 234 720 285 78, email@example.com, setlog.com
Setlog Holding is a provider of tailor-made Supply Chain Management (SCM) software solutions. The central product is the cloud-based SCM software OSCA®, which is used by over 150 brands in the apparel, electronics, food, consumer goods and hardware sectors. With the help of OSCA®, companies network with their customers, suppliers and service providers to optimally coordinate their supply chain, accelerate processes and manage supply chains efficiently.
Setlog GmbH is a wholly owned subsidiary of Setlog Holding AG. Founded in 2001, the company is now a leading provider of SCM software with over 40,000 users in 92 countries. The software company employs 60 people between Bochum (headquarters), Cologne and New York. www.setlog.com