Threats that lead to interruptions in the supply chain lurk at many points. Many pitfalls will continue to remain unforeseeable in the future, making a delay here or there unavoidable. However, if “Big Data” is also used sensibly in logistics, risks can be better assessed or disruptions to the supply chain can be avoided with alternative solutions. Keeping an overview of the challenge saves time and therefore money.

Just as there aren’t exactly two or four reasons why brands such as Google, facebook, eBay or Amazon have been able to leave behind their competitors, it is not always three or five logistics index numbers that can comprehensively illustrate the success or failure of supply chain management. But in no enumeration of these Key Performance Indicators, in which achievements in the supply chain are made measurable, the aspect of punctuality is missing. Even though the rate of on-time deliveries in individual projects can usually be calculated quite clearly – the number of on-time deliveries divided by the total number of deliveries made times 100 – there are hardly any branch-wide surveys on delays and supply chain interruptions. The logistics market is too large, complex and fragmented to document punctuality in entirety. However the fact, that in a broad-based study – conducted two years ago by a German association for materials management, procurement and logistics (it was the Branchenverband Materialwirtschaft, Einkauf und Logistik | BME) – only eight percent of the purchasing agents could say there was no interruptions in the supply chain in the past twelve months shows just how present the challenge is.

Full of potential traps

Anyone who has been in the logistic business for a long time can tell an anecdote or two about why deliveries were late, goods were going in the wrong direction or roads suddenly ended in nowhere. In everyday life, the “usual suspects” dominate: weather phenomena or short-term driver cancellations can, for example, delay the departure of a transport. Time-consuming traffic jams on the way result from accidents, from heavily frequented bottlenecks or complex customs formalities at border crossings. Closed gates at the entrance to the destination or a lack of powerful cranes or stackers for the unloading process can further negatively impact the time account at the end of the supply chain. Of course, many potential breakdowns can already be avoided by professional supply chain management. But many unforeseen events will still lead to disruptions in the previously announced processes – even in a future of transport logistics that will become more digitized and has grown in terms of expertise.

ETA predictions optimize work processes

Thanks to the historical data that we at Synfioo have processed on many transport routes worldwide, recurring patterns become visible, for example where certain bottlenecks exist, which may even occur only at certain phases of the week, month or year. In the “big data” age, information technology can be used to quickly create alternative options. These routes would normally result in longer transit times. However, due to the high probability of disruptions occurring on the standard way, the replacement solution already shows up in advance as the more efficient approach for carrying out the transports in certain time windows. But once the carrier is on the road, we at Synfioo monitor and analyze the entire transport process in real-time. In this way, the status quo is always visible to all parties involved – to avoid flying blind regarding the current location of the goods. For some years now, navigation devices have been standard in private cars, which allow current traffic jams to be incorporated into the ever updated arrival time prognosis. In the B2B sector, digital companies like us provide reliable ETA predictions as well as a wide range of live information for all parties involved in the transport. Current disturbance and motion data, which include weather information, facts about customs controls or information about the status of the transport infrastructure, allow the visualization of the kilometers already driven and the one which still have to be driven and the time spent on them. The information provided thus gives a data-based summary of traffic on road and rail as well as in water or in the air. With this knowledge, the resources can be used even more effectively in a situation-specific manner, not least at the destination of a transport.