Logistics processes

What is the challenge?

Companies strive to optimize their procurement and delivery routes in order to reduce costs and improve delivery and storage times. Route planning involves complex processes of grouping and determining routes in order to optimally combine groups of goods or transport orders and to receive them or bring them to the customer via the transport network structures. A large amount of information flows into the planning processes, which are very time-consuming when performed manually. In the event of short-term fluctuations or change requirements, the processes are also difficult to adjust manually. 

What data can help?

  • Warehouse data (e.g. from scan codes)
  • Movement data
  • Detailed information about the planned tour (opening times at customers, conditions at the unloading point at the customer, orders along a tour, restrictions on vehicle type and size, other restrictions along the routes, prohibitions on combined loading, road works in the road network, driver availability, CO2 minimization targets of the company)
  • Procurement routes are simulated from this data and further used as simulation data
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Use case category: logistics processes

How can companies use their data?

Route planning can be optimized by combining the data. Automatic procedures can also be used to take into account the multitude of relevant information. In this way, users receive individual suggestions for routes. Simulations can be used to make weak points in the transport network visible in advance. Real-time data can also be used to react dynamically to changes “on the road”.

Where is this use of data already being applied?

The company KOCO solutions offers an IoT fleet management solution for waste logistics. Using various software modules for data collection and processing, the routes of sweeper and waste machine fleets can be optimized.

The Walmart retail group can track merchandise routes by using simulation data. This allows intermediate stops to be noted and weak points in supply chains to be found.

Würth, a manufacturer of production and assembly technology, uses data exchange to partially automate the procurement process for goods. For this purpose, all data of the supply process is stored in standardized formats. Communication can take place via the ERP system without manual breaks, even across company boundaries.

How does this use of data contribute to value creation?

The optimization and transparency of tours improves existing value creation by realizing logistics processes more efficiently and accelerating them. Resources can thus be used more economically.

Aim of data use

Sources: Kirchhoff Gruppe (2017), The AnyLogic Company (2020), MM Logistik (2018)