Latent potential

Mr. Köhler, as processes become more digitized and automated, planners are increasingly focusing on data. How will that benefit day-to-day logistics operations?

A functioning exchange of data is fundamental to the flow of goods and one of the basic necessities of today’s logistics. However, data quality has often been neglected in everyday logistics activities. In some cases, the experience and knowledge of standard routines that scheduling staff and drivers have is enough to deal with ambiguities in data—when it comes to actual parking space requirements or delivery addresses and the associated delivery times, for example. But against the backdrop of increasingly complex processes and extremely stringent transport efficiency requirements, in the future this will no longer suffice. The planning algorithm takes all the data provided at face value and makes logical decisions based on this input—improvisation will no longer be a viable solution.

Think, for example, of the dangerous goods division. In this area of the business, for a long time we’ve needed to know exactly which substances we’re handling, which goods can be transported together, and—just as importantly—which cannot. The applicable regulations and laws together with safety requirements and the shortage of loading space form a tight framework for such transports. As it’s been this way for many years, everyone involved in the associated chain of duties has become aware of the importance of correct data.

To schedule our operations appropriately and responsibly, we therefore need transparent data that leaves no room for interpretation.

How will you achieve this?

First, we have to ask the right questions. This starts with the master data. What do we know about the customer and how they’re set up? What are their delivery and collection times, and do they have any access restrictions, for example. And does the customer actually know what exactly they are sending where and what’s connected with the address data?

International addresses are particularly susceptible to errors, as spellings within Europe sometimes differ considerably from country to country. First and foremost, we depend on the integrity of the data from our customers’ upstream systems, which we mainly receive via EDI or eLogistics.

We aggregate all the relevant master data into a single, central data set that our applications can access. Through the ongoing and increasingly automated measures we’re implementing to validate our existing data, we’re gradually increasing the quality of the master data.

In many cases, we can cross-reference transaction data with our master data to iron out any inconsistencies, which ultimately gives us data records with no room for misinterpretation.

Where do you see the long-term advantages of early, complete, and correct planning data?

The earlier we receive shipment data and the better its quality, the greater the benefit for senders and logistics providers in terms of securing capacity and flexibility. At the same time, we increase their ability to respond to challenging market situations.

Logistics providers cannot single-handedly compensate for volatility in the market and the associated risks. So the logical solution is for the sender to supply the delivery data on the day before—something that is set to become increasingly standard practice in the future.

Complete and correct data enables us to schedule the trucks and plan their routes at a high level and with as much automation as possible, as well as optimize loading bay capacities—if we can ensure the right vehicle is at the right bay at the right time. Last but not least, it helps us optimize use of loading space, so we can avoid unnecessary transports. And that remains the most effective way of cutting CO2 emissions in logistics.