Glühbirne mit Funken


How BLG LOGISTICS continually digitalizes and improves logistics with innovations

As a logistics company, we are particularly in tune with current developments in the world. From the state of the economy to consumer behavior, we immediately detect change. That includes changed expectations of our customers, business partners and employees. It seems like the world is turning faster all the time and the demands on businesses are increasing. So logistics services must keep pace, becoming faster and more flexible. We don't see this as a problem, because the opportunities for making logistics much more efficient are also growing. The 21st century offers us countless innovative digital possibilities.

Find out here how we can together not only think about innovation and digital transformation, but also actively shape the logistics of the future.

All our innovations have something in common: At their core is creating extra value for employees or customers, plus they are sustainable and scalable.

We see these three factors as essential to good innovations. For us, innovation means achieving genuine novel developments in logistics, not simply improving on existing systems. This is important because the world around us in constantly changing: new goods flows, new challenges, new possibilities. The word "innovation" comes from "nova", which means new. And fresh thinking is part of our mentality. Of course, we will continue to optimize existing processes. But that's not new. For BLG LOGISTICS, innovation in logistics also means embracing new technologies. Technologies that create added value for us and our business partners. BLG LOGISTICS is open to new, sustainable, digital business models that secure the long-term success of the company and our employees.

The "app toolbox" – agile digitalization of small, heterogeneous processes

The challenge

Many of today's business processes are based on data, or a broader database would make them more reliable or capable of optimization. Companies must collect the data as efficiently and reliably as possible. But often, companies still collect a large part of their data in analog form. Above all, this takes up far too much time. What if we could digitalize lots of data-based processes, including smaller processes, in apps? The tricky thing is that the app would have to be accessible to all employees with no significant learning effort.

The many small processes in the company are all very different. It's impossible for a single app to cover all processes and all use cases in which analog data needs to be digitalized. But if would be ridiculously expensive to engage a service provider to develop different apps for all possible work areas within our divisions. For smaller use cases, it is simply not worth developing more and more new apps or adapting core systems. 

Predicting personnel requirements using predictive analytics and machine learning

The challenge

Optimal personnel planning is the basis for the smooth running of all processes in a company. But it is a challenge, especially in operational areas in logistics. We are faced increasingly with fluctuations that we have to manage at short notice. Many internal and external factors impact on the personnel capacities we need. This often makes planning difficult.

Our solution

For a solution based on predictive analytics, we record the relevant internal and external influencing factors. This data forms the essential basis that can enable us to predict personnel needs. We can only do this together with our employees on the ground. Working from historical data, we can compile accurate forecasts – for example about volumes in the various functional departments and the personnel needed. Depending on our requirements, we can plan weekly, daily or shift deployments. By applying the software, we were able to significantly improve personnel requirements forecasting and planning during the test phase. The next step is to further optimize the solution, improve the data and identify new use cases.

R&D projects at BLG LOGISTICS

There are problems in logistics for which we don't yet have any elegant, efficient solutions. But there are lots of ideas. The problem is, until we have a guarantee that they work, we can't use these ideas on a large scale. That's what our research projects are for. As a rule, we do not conduct research projects on our own. Instead, we put together an interdisciplinary team from various companies with different specializations. Often, a university institute is on board to provide scientific backing. BLG is also always keen to give SMEs and startups the chance to take part in these projects.

That's because especially small companies frequently have new, innovative solutions and can quickly try them out in practice. Usually, the projects also receive government funding.

Our R&D projects are often collaboration projects between BLG, various startups and SMEs, a research institute and a supporting government authority.

Here is an example of an R&D project:

Isabella and Isabella 2.0: smart automobile logistics

In the R&D project Isabella and its successor Isabella 2.0, we are working on automobile logistics in sea and inland ports. We wrapped up the first phase in June 2020. In the project, we developed an intelligent planning and control system that supports us with the handling and monitoring of automobile movements in sea and inland ports.

Isabella has two dimensions:

  1. On a multitouch table, we can visualize the current situation of a terminal and realistically map, simulate and evaluate possible planning scenarios. This will make vehicle handling in ports more efficient in the future.
  2. With Isabella, we can see the current position of every vehicle, even if it is on the move. As a result, we can more accurately manage transport orders and communicate more effectively with drivers. This is how we optimize routes even more efficiently.

Now Isabella 2.0 integrates external transport carriers such as trains, ships and trucks, including their loading and unloading. Read more about Isabella 2.0 here.

Here is an example of an R&D project:

KITE – artificial intelligence for more sustainable truck transport

Every time a truck drives without a payload, it causes unnecessary emissions. And because we take sustainability in logistics very seriously, we want to minimize emissions. With our research project KITE, we are taking a further step toward climate neutrality. Using AI-based transport volume prediction, we intend to prevent empty transports and additionally reduce our CO2 footprint. KITE is an acronym for the German project name, which translates as
Artificial Intelligence in Transport for Emissions Reduction.

With KITE, we are developing a system for predicting transport volumes. The process will operate on various levels (customers, companies, branches) and in various time periods (days, weeks, months). Our project goal is to reduce empty travel by 15%.

Thanks to AI predictions of transport volume, we can better time truck transports, pool shipment volumes, optimize networks or set up new interfaces where required.

Our key principle: Innovation is a team sport

Every colleague has different viewpoints, experiences and talent we want to utilize. That's why it's important to us that we work with the people who shape and further develop the business of BLG LOGISTICS every day. Top-down ideas are not enough. That would waste opportunities. Innovations rooted in practice are the way forward. Our innovation principle is: innovation involves everybody and is not a spectator sport! 

[Translate to Englisch:] Gruppe von BLG-Mitarbeitenden in einer Halle

Follow us on social media too!