Real-time logistics projects meet profitability and open the door for a new and deep perspective of the material flow. Matthias Hülsmann explains, how full transparency of current and historic data combined with real-time steering of the material flow are becoming the guiding principle of digital logistics.
Industrial revolutions don’t happen overnight. Everyone who has been active in logistics knows that innovations take especially long in the supply chain ecosystem. When we speak about digitization, we automatically picture a fully connected supply chain. Logistics objects, assets, humans – they are all connected with each other. The complete supply chain is transparent and agile. Constantly increasing customer expectations and short product lifecycles set the pace.
Let’s make logistics easier
Ok, it will take some time until we reach the truly digital supply chain. Actually, there is quite some room – and need – for improvement, above all regarding idle resources. From customer projects and practical experience we know that:
- logistics assets like forklifts can show an amazing 60-80% of non-productive time;
- up to 50% of cyclic transport runs of milk runs are empty;
- returnable stock is oversized by 20-40%;
- logistics planners spend approx. 20-30% of their time gathering status information and coordinating non-transparent material flow processes.
But most importantly, we also know from practical experience that logistics is a stressful business, especially for the staff involved. Powerful tools, IoT technology and real-time information are available. Let’s use them in a pragmatic way to make life easier for logistics people!
Time for the next logistics revolution
With the advent of affordable digitization technology, it is time for a paradigm shift in logistics – from ERP-based document flow management to real-time IoT-based steering of the material flow. Obviously, the document flow in the ERP system remains important for what it was designed for: managing the business process, such as orders, confirmations, invoices. This remains the so called digital core. However, the time lag of document flow data compared to real-time material flow was and still is the main root cause for many logistic pain points.
This is exactly where pragmatic real-time logistics comes into play. Easy-to-implement IoT-based solutions that focus on added value and savings in the user story empower logistics staff to manage assets and objects in real time without system delays. This makes their work a whole lot easier and provides value-adding benefits. Apart from reducing wrong deliveries, logistics errors and costly countermeasures (e.g. express costs), current projects show that real-time logistics can:
- reduce search and inventory efforts by 75 to 100%;
- cut down movement bookings and barcode scanning efforts by up to 100%;
- improve uptime or availability of returnables by up to 30%;
- optimize resources by 30% with visualization, dynamic routings and “next best order” algorithms.
Historic real-time data unleashes the true data power
Evidently, reacting to real-time deviations is already an important step. But avoiding deviations in the first place is even better. Historic real-time data and algorithms based on machine learning make a proactive supply chain management possible and unleash the true data power.
Take the tracking history of logistics assets: track records of transport boxes show that they often move as little as 8% of their available time. So-called hidden pockets (when assets are stored somewhere without being used or when they are being used for other than logistic tasks) are easily identified. This makes it possible to eliminate or reduce regular reinvestments in these moving assets for many years.
Up to 30% uptime improvements
In daily work, uptime improvements of up to 30% do not come as a surprise: significantly fewer assets are needed for the same amount of transports. This, in turn, leads to a cutback of often oversized moving asset stock. Moreover, heatmaps can display hotspots and bottlenecks in the transportation flow. As soon as they are known, they can be counteracted, and targeted infrastructural improvements can be implemented.
Digging deep down into the available data helps to understand regularly occurring patterns. Hence data mining provides valuable information about the why, where and when of events and anomalies, which leads to more informed decisions and planning. Last but not least, the smart data history of assets can be used as a basis for proof of liability in case of damage. It also enables a precise rental accounting, which enforces the cost-by-cause principle.
New guiding principle of logistics
With a mass-scale adoption, pragmatic real-time logistics overcomes the shortfalls of document-flow logistics between ERP systems with many media disruptions and different interfaces. Pragmatic real-time logistics is based on easy-to-use and affordable IoT technology which delivers the data from the supply chain processes – and enables an important change of perspective: by focusing on the pain points in the user story, pragmatic real-time logistics is all about making the material flow visible to logistics staff and empowering employees to actively steer it with real-time tools and services.
In doing so, pragmatic real-time logistics becomes the “guiding principle” of logistics and, in a nutshell, shows the fascinating future of real-time supply chain management.