CLOUD computing has spurred a revolution in private and business applications over the past decade. Today, data and software programs can be saved or run in any data processing center in the world. Everything is operated via the internet, completely independent of the location or device. Cloud computing has made installation, administration, and updates significantly easier and has thereby laid the foundation for Software as a Service (SaaS). This business model provides many advantages:
- Processing big data efficiently
- Rapid integration
- All-round care package with clear cost structure
- Access to latest features
- Pay as you grow
How cloud computing is used in logistics
Also for logistics, cloud computing and artificial intelligence is opening up fantastic new opportunities. Using these technologies increases transparency in logistics networks and allows them to become more intelligent. How so? By combining the vertical integration across several system levels of a single location with the horizontal integration across a logistics network.
Cloud computing bundles all the data and services in one single infrastructure. The benefits speak for themselves:
- The operating data of one or more systems is centrally and readily available for further processing, regardless of whether it is for the logistical or the technical operation of the system.
- Data can be easily used for various applications such as detailed monitoring and analysis of operations, planning, optimizing stocks and use of resources or preparing recorded master data for other locations. A popular application in logistics is data analytics: By continuously merging data from a wide range of systems – from machine control units, other IoT devices, WCS and WMS to TMS and ERP – the cloud service provides a clear overview of the complex processes in the systems as well as in the entire supply chain. Data can be monitored over the long term, and important trends and forecasts can then be derived. It is a great resource for making the right decisions in logistics.
- Various AI applications can be easily supported because cloud computing provides the infrastructure needed to support various, data-intensive AI methods such as machine learning and deep learning. It helps provide data and images, train neural networks, as well as validate, manage, and roll out generated models to the customers’ systems. Open interfaces and IT and data security allow working together with partners.
- Hardware and software support, IT security, data security and interfaces between applications are ensured out of the box, regardless of the software or automation supplier.
To meet all logistical requirements cloud computing still needs on-premises systems
Looking at the many benefits cloud computing delivers one may ask: Do we still need on-premises systems for software applications in logistics? While in some countries, autonomous cars are already driving on public roads. The question is: can we also operate a warehouse fully autonomously?
Cloud computing is already very widely used in the logistics world, full stop. However, there are technological limitations to it. In logistics, it is just like with cars: much of the data is located and managed in the cloud, with system updates often being installed over the air. But decisions that have to be made in real time within milliseconds or those critical to safety can only be made directly at the vehicle.
It can be concluded from this that the potential of cloud computing can also be used to great effect in logistics applications, provided that the response times and security requirements permit this.
Therefore, a hybrid IT infrastructure – also known as edge computing – is the solution for future-oriented value chains: System-critical software programs with high real-time requirements run on-premises. Data storage and supply chain tools for analysis and optimization tasks are all managed in the cloud. To best exploit the potential of both IT worlds, the two systems should be closely interconnected.
In practice, it also means that, typically, transport management systems (TMS) or warehouse management systems (WMS) without automation can be operated entirely in the cloud. Whereas with automated installations, machine controls still need to run locally due to machine security and highest real-time requirements.
For typical business models with very short order lead times and the ability to change orders until they are shipped at its core, having a highly integrated WMS and warehouse control system (WCS) or warehouse execution system (WES) with high real-time capabilities is a real differentiator. However, cloud infrastructure cannot cater to that. Therefore, also in this case on-premises infrastructure, that is essential for automation anyway, is necessary. By installing these systems in the same on-premises environment allows to raise the full potential of the overall solution.
The bottom line is that cloud computing forms the ideal addition to on premises applications to further optimize value chains. This hybrid approach is the real deal by combining advantages of both worlds. Cloud services offer many opportunities to customers to choose between the various SaaS or subscription business models. Standard services to optimize in-house logistics can be rapidly activated with almost no initial costs. The pay-as-you-grow principle allow companies to easily expand their use of services as they grow.
Bernd Stöger, Executive Product Manager at KNAPP, is responsible for Software and Value Chain Solutions. During his 17 years at KNAPP, Bernd has worked in different roles both at the headquarters in Austria and at the company’s Brazilian subsidiary. Earlier in his career, he gained valuable experience in the automotive industry at BMW. He holds a university degree in industrial management from the University of Applied Sciences FH Joanneum in Austria and from the OAMK in Finland. He is a European Certified Logistician with senior management level.
