These days, LogTech is growing in importance and its potential should not be neglected. Since more consumers become increasingly aware of the logistics industry’s impact on society and nature, expectations of sustainability and efficiency are rising in the logistics market. Simultaneously, it has become more and more visible that logistics are lagging behind other service industries, such as FinTech, HealthTech and FoodTech, in terms of digitalization. But there are promising developments taking place: With the help of digital technologies and disruptive innovations, the logistics field has been subject to dynamic developments in recent years. This is exactly where the term LogTech comes into play. 

In this article, we will provide an overview of what is understood as LogTech, and an outlook into thriving, high potential technologies.



1. LogTech – Thinking of logistics of the future

To put it simply, the term LogTech combines the words Logistics and Technology. But it is more than the mere combination of these two industries suggests.

LogTech stands for an emerging industry sector that strives to improve and disrupt traditional logistics services through the use of technology. The emergence of new technologies such as Artificial Intelligence, Digital Twins and Robotics Process Automation has dramatically expanded the possibilities for logistical innovations that allow for leaner and more transparent processes. Most importantly, these technologies open up new possibilities for profitable ventures driven by out-of-the-box business models or vast cost-saving potential.

While other traditional service industries, such as finance and healthcare, already have well-developed Tech sectors, logistics are somewhat lagging behind. Yet, given the highly manual processes, asset-heavy traditional business models, and fragmented value chains with numerous stakeholders, the potential for disruption through technology is enormous.

Due to the disruptive nature of this emerging sector, LogTech companies can be found primarily in the startup sector. A recent study by McKinsey [1] finds that most successful LogTech startups can be found primarily in two verticals: last mile logistics and the freight forwarding market. This illustrates how difficult it is for outsiders to observe deep-rooted logistical issues. To obtain a sound understanding of the opportunities for digital disruption along the entire supply chain, it is necessary to gain profound insight into processes that take place inside of warehouses and on the road. Therefore, the LogTech sector is prone to cooperation between startups and established logistical players.

LogTech touches upon all logistics verticals: from planning to forwarding, customs, warehousing, fulfillment, distribution and beyond.

LogTech touches upon all logistics verticals: from planning to forwarding, customs, warehousing, fulfillment, distribution and beyond (Source: XPRESS Ventures).

Here, company builders such as XPRESS Ventures come into effect. As the interface between established logistics providers and startups, company builders enable founders to access the critical infrastructure, know-how and networks jointly with the operational support needed to take their idea to the next level [2].

All in all, this is only the start: As new use cases for emerging technologies become feasible, industry verticals along the entire supply chain will become subject to digital disruption. However, to unlock the full potential of LogTech, incumbent-startup partnerships must grow in importance.

2. Logistics technology landscape

The landscape of technologies is broad and intertwined in its development and application. The following provides examples of LogTech enabling us to solve new challenges along the supply chain as well as a brief overview of companies already exploiting their advantage. Sources differ when these technologies will be fully introduced to the market given also the development of infrastructural technologies such as 5G or cloud communication. However, their potential is seen to flourish within the next 1-5 years given the recent exponential developments.

Big Data Analytics

Big data analytics are the first step to overcome data silos across the logistics ecosystem. Hereafter it aims to make this multi-faceted data available for predictive and advanced analytics.
The startupDatumize, for example, uses Big Data Analytics to generate and integrate data in warehouse operations.

Augmented & Virtual Reality

Augmented Reality (AR) and Virtual Reality (VR) make it possible to experiment and work in digital environments to enhance logistic material flows and processes and have all information at the right time in the right place (i.e. Google Glass AR).  
Picavi applies this technology for pick by vision in warehouses.

Digital Twins

The use of Digital Twins describes the creation of accurate digital 3D models of a physical object, i.e. for scenario planning in logistics hubs, creation of virtual delivery networks as well as collection and visualization of product and packaging data of shipments.
Cognition Factory uses the technology for predictive material handling and warehouse automation.

Supply Chain Visibility (SCV)

Supply chain visibility is a solution to track and monitor demand and supply along the supply chain by leveraging data about external conditions (weather, road or traffic) or internal operations (inventory, vehicle capacity, etc.) enabled by IoT sensor technology.
The startupEtheclo uses this technology for cold chain monitoring.

Artificial Intelligence (AI)

Artificial Intelligence is an umbrella term for giving machines and systems the ability to learn and act through data-driven insights.
You can find cases of AI in the following functions: predictive capabilities (demand planning, capacity forecasting), route planning optimization, also software for robotics and autonomous transportation.
Westphalia Datalabs applies AI to, for example, match warehouse utilization and delivery fluctuations, while the startup Smartlane applies it for AI-powered route optimization.

Robotics Process Automation (RPA)

In Robotics Process Automation software robots perform manual-intensive and repetitive tasks for improved cost efficiency, error rate or redundancies.
Use cases for RPA are inventory management, purchase order management, return and refunds.
The startupsShipamax andMagazino use RPA for automatic order processing and intralogistics robotics.

3. Conclusion

Logistics and technology are overcoming what might seem to be a complicated relationship in the past. LogTech will play an increasing role with the evolvement and practical application of technologies along the supply chain verticals. As a consequence of this potential, the term LogTech might sooner or later be as prominent as its “Tech” relatives in other industries.

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