Posts by Daniel Adelhardt:
The current coronavirus pandemic poses enormous, unprecedented challenges for companies. Efficient risk management plays a central role in meeting these challenges. It is not so much a question of whether the current situation could have been anticipated and planned for. Rather, the focus is on how companies can now best protect their core processes and increase the resilience of their operations. Read more
Transport damages to goods, delays in delivery, poor delivery reliability: These are three typical use cases in which Smart Logistics Data helps to identify and counter risks well in advance. Read more
Missing supplies, i.e. delayed, deficient, and completely absent deliveries, are a serious and recurring problem for companies. But what can you do? And how can you ensure that ordered goods actually arrive on time?
Smart Logistics Data – that is, the intelligent collection, enrichment, and usage of data relevant to the logistics process – promises relief.
Nowadays, everyone is preaching that data is the new oil. But unlike oil, it’s not (just) the sheer output volume that matters here. What really counts is the efficient use of this data so as to draw the right conclusions in terms of the supply chain reliability. Read more
A supply chain has to be agile, robust and resilient. Capable of anticipating potential risks and responding in advance, detecting problems early on and flexibly circumventing them.
All this requires the intelligent use of data. But how can we really make data “smart”? Read more