Logistics meets Innovation

Logistics meets Innovation - Supply Chain conference

May 28th, 2019

Vlerick Business School, Brussels, Belgium

About the conference 2019

Artificial intelligence already powers many real-world applications, from facial recognition and fraud detection to language translators and smartphone and home assistants like Siri and Alexa — and now, the powerful software is also being applied to core logistics operations. This should be a golden era of practical AI, when algorithms give way to implementation.

For decision-makers in the logistics industry, it is worth understanding some of the basics behind those algorithms to help ensure that first experiences with AI in your workplace are successful. During the 4th edition of our Logistics meets Innovation conference, we have covered the basics of AI, machine learning, and data science as well as practical applications of this technology in the logistics operations: from data cleansing to spot truck pricing to ETA calculation.  

About the Presentations

“Precision Pricing with AI”

Jonah McIntire
Founder and CEO
TNX Logistics
TNX Logistics
During the presentation, Jonah McIntire, Founder and Managing Director of TNX Logistics, shared that there is a real lack of understanding of how to transfer AI from a lab setting to the practical logistics in a successful way. Mr. McIntire presented a framework on how non-technical business leaders can evaluate proposals about potential AI-based projects, consisting of 5 criteria: Is this a high-frequency decision? How data-driven is this decision? Do we have the data quality? How important is Explainability? Can we tolerate some mistakes? The keynote concluded with an interesting view on AI entering the workforce and the way some people can benefit from the technology that eliminates the worst/repetitive part of their jobs. However, at the same time AI also poses a risk because it may eliminate some jobs entirely. That is why logistics companies need to pay attention to the organizational transformation in order to help their staff accept the new AI software and take adequate measures to keep employees motivated.

“Enhanced Dispatching via Augmented Intelligence”

Nicholas Minde
Senior Vice President Overland Germany
Kuehne + Nagel
Kuehne + Nagel
In the second presentation, Nicholas Minde, Senior Vice President Overland Germany at Kuehne + Nagel, discussed what makes road forwarder successful and how an old-fashioned road forwarding industry can benefit from AI technologies. He shared that road forwarding companies are typically good in understanding what went right or wrong yesterday, but they don't know whether this would matter on the next day. Also, on average this part of the industry is quite old-fashioned and no-tech often beats high-tech in it. In Mr. Minde’s opinion, road forwarding can benefit from “selective revolution” – using “augmented intelligence”, which combines the knowledge of the logistics experts with powerful computer algorithms. To make AI projects successful, Mr. Minde advised the audience to be highly selective from the beginning, to focus only on the parts that logistics companies can’t do well themselves, to find a solution that fits the existing business model, and to not aim for perfect results – they just need to be accurate enough to achieve real business benefits.

“Augmented Intelligence for Logistics: Behind the Scenes”

Asparuh Koev
Co-Founder and CEO
Transmetrics
Transmetrics
Asparuh Koev, Co-Founder and CEO of Transmetrics, started his keynote from pointing out the fact that the current hype around AI in logistics is mostly connected to exciting technologies like automated warehouses, self-driving trucks, drones, delivery robots, and more. Those are technologies that can replace some manual jobs that don’t require complex skills. For high-skilled positions like logistics planners, Mr. Koev suggested that AI technologies should empower employees instead of replacing them. To improve logistics planning, companies should use AI, though not in the sense of “Artificial Intelligence”, but “Augmented Intelligence”. At the current state of the art, AI helps planners in real logistics operations by using intelligent predictive alerts. The next step for AI in logistics planning is the so-called “Human-in-the-loop AI” approach which works by training AI algorithms that offer suggestions to the planners who then make a choice whether to accept them or to change them. Mr. Koev concluded the presentation with the ultimate goal for AI in planning, the so-called “Pilot in the plane cockpit”. This is the concept where AI automatically does all the calculations and suggestions and planners interfere when needed to account for unforeseen factors.

“Machine Learning vs. Rule-Based Approaches to ETA Calculation”

Vincent Beaufils
Director/CDO
LKW WALTER
LKW WALTER
In the last presentation, Vincent Beaufils, Director/CDO at LKW WALTER, talked about the importance of AI-powered calculations for Estimated Time of Arrival (ETA) based on the example of LKW Walter. The main goals for the company were not only to improve customer service and transport monitoring but also to increase automation and to drive internal optimization since ETA is key to generating triggers in the supply chain. Mr. Beaufils then demonstrated how LKW Walter used the Internet of Things, Big Data, and Artificial Intelligence in this project. ETA calculation is structured as a pipeline, where different models are used for calculating each step of the pipeline. For loading/unloading/POI waiting time profiles, LKW Walter predicts drivers’ behavior by using classical statistical models. Mr. Beaufils concluded the presentation with an argument that if you compare rule-based vs Machine Learning approaches, no model is better than the other and logistics companies need to balance between the two of them. Nevertheless, even though Artificial Intelligence and machine learning models are very resource-intensive to set up and train, once it’s done, the models mostly produce the results without the need to work on them further.

Panel Discussion and Conclusions

The keynotes were followed by an interactive panel discussion, which provided both speakers and the audience with an opportunity to explore additional aspects of Artificial Intelligence in logistics. In particular, conversations were around the topics of data quality issues in logistics, challenges of selling such technologies into companies, costs and ROI of such projects, and more. The panelists shared an opinion that it’s not that expensive to trial these technologies. The founders of both TNX Logistics and Transmetrics confirmed this argument by the facts that TNX uses the approach “pay if it works” with their customers saving about 4% on average on their transport, while Transmetrics offers their software on a monthly subscription basis with their customers saving on average 8-10% of the transport costs. The panelists representing large logistics service providers raised another argument related to the project cost consideration – what will happen in the near future if your business doesn’t invest in these technologies now? Overall, the event provided further insight into the practical issues of Artificial Intelligence in logistics both on the technological and business sides.

The conference concluded with a dinner reception during which the participants had a chance to network with other logistics and supply chain executives as well as to discuss the topic in the informal atmosphere of Vlerick Business School.

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