Embarking on a riveting exploration of the symbiotic relationship between deeptech and logistics, our journey delves into the transformative realms where cutting-edge technologies intersect with the complex networks of supply chains. Within this dynamic landscape, autonomous vehicles and drones emerge as heralds of a new era in transportation, promising to redefine the logistics industry. However, their trajectories are not without turbulence, and as we navigate the twists and turns, the allure of innovation clashes with the pragmatic challenges of implementation.
Written by: Tanay Sonawane, Jonathan Ouyang and Filip Vrábel
Autonomous Vehicles and Drones
Autonomous vehicles could either prove to revolutionise our road traffic systems or just be the latest fad to never materialise into reality. Such vehicles aim to be at least a partial replacement of a human driver in travelling distances while avoiding road hazards and responding to traffic conditions. So far, this has meant testing self-driving cars with oversight provided by at least one human driver and an external monitoring team. In recent history, Waymo, a Google subsidiary specifically created for this aim has engaged in an enormous number of tests - over 20 million miles on public roads and tens of billions of miles in simulation. Tesla’s ‘autopilot mode’ has achieved over 3 billion driven miles and the space is receiving attention even from traditional car companies such as Audi, BMW, GM, Nissan, Ford or the tech giant Nvidia (ibid).
In the start-up arena, the UK-based Wayve is “reimagining self-driving with embodied AI, ushering in a new era of technology”. For both VC funds and founders, it may be interesting to note that the startup received $2.5M in seed funding and then $20M in Series A while opening a new HQ in London just about two years later - by the beginning of last year Wayve achieved a first in AI for mobile robotics by developing a driving model capable of generalising to different cities and different vehicle types, receiving $200M in funding. Consequently they opened a second office in California and teamed up with Microsoft to scale deep learning for AVs (ibid). The commercial progress of the company is remarkable and so is the absolute explosion of financing from one round to another - one could note here a practical 10x of funds received per round. Thus, Wayve as an example illustrates the allure of this sector - why shouldn’t VC firms run to such startups with open hands if the progress they would offer would be just so wonderfully linear, both in company growth terms and filling up the cap table? The answer lies in the title of a 2022 Forbes article: “Self-Driving Startups Have Lost $40 Billion In Stock Market Valuation In 2 Years”. It is not that the technology is not there, but rather that it is getting there too slowly. Promises that never materialised are plaguing the industry to this day, whether that be Musk’s expectations of full level five self driving technology in 2020 or Apple’s 2024 plan to ship a self-driving car by 2024, which seems extremely unlikely at this point (ibid). Autonomous vehicles thus may seem alluring but investors (and potential founders) should think twice before interacting with this peculiar market.
Drones, on the other hand, have been here for quite some time and are used on a daily basis in warzones. The technology is world-famous and fairly well known, so let’s jump into the startup space straight away.
Volocopter is a German startup, with 6 funding rounds behind it €369,200,000 to prove it. It proclaims itself the “pioneer of urban air mobility (UAM), an emerging branch of fully electric aviation” meaning air taxis, cargo drones, and longer-range passenger aircraft. Such solutions may be of interest to green funds and investors as an impact-solution as Volocopter proclaims its products and services “emission-free” (ibid), and whether this is true or not, one could see quite easily why drones would be good reducing carbon emissions in urban tasks regularly delegated to much more CO2-emissions-producing vehicles. Another interesting example is the Dublin-based ‘Manna Drone Delivery’. It asks the simple question of why should we not replace the delivery driving market with delivery drones and answers it with what you would expect from a drone startup with ‘Delivery’ in its name. After 4 funding rounds, it has received $30,200,000 and thus while not yet financially comparable to the German juggernaut above, one could see that it could scale its services from Dublin to Europe and then the US and thus secure quite a juicy market share in deliveries. It is certainly a company one ought to keep an eye out for.
Blockchain for Enhanced Transparency
Telefonica proclaims “Blockchain technology is a shared, decentralised, immutable and transparent database,”. This hardly helps blockchain’s reputation for being a difficult technology to understand but alas, if we simplify further we can say that blockchain is basically just a network of computers with the same transactional history; i.e, data is not stored in one computer (or any other location) but dispersed among these databases so as to prevent modification and ensure reliance. The ‘blockchain’ itself is a general word for a chain of information-containing blocks so that when a transaction occurs, the relevant data is added to a block. The information in any specific block cannot readily be modified once it has been recorded. If one block is modified, all the following blocks must also be changed. Depending on what rules the network is set to use, most of the ‘computers’ (any equivalent databases storage platforms) may need to agree on such a modification.
One may ask how could such a non-transparent concept lead to more transparency? The answer is quite straightforward actually - due to what we have outlined above blockchain technology can enhance transparency by providing digital records that cannot be altered. In the real world, states such as Colombia and Peru have used the technology in fighting corruption. As an illustration, in Colombia a programme has been made to monitor the selection and procurement processes of suppliers for a school food programme, while a public procurement project has been carried out in Peru. In Spain, educational centres such as ISDI and the Carlos III University in Madrid validate their degrees with Blockchain.
For startups, blockchain could represent an opportunity to provide “an auditable and transparent record of their activities, fostering trust and confidence among stakeholders”. Startups often struggle to get money and investors. The usual ways of getting money can be slow and complicated. But thanks to blockchain technology, there are now easier ways to raise money - by using blockchain-based technologies like Initial Coin Offerings (ICOs) and Security Token Offerings (STOs) to issue digital tokens or securities. This makes it possible for more people around the world to invest, and it simplifies the rules that companies have to follow. With blockchain, everything is clear and easy to check, making it simpler for startups to find investors and raise money on decentralized crowdfunding websites. In addition, normally startups depend on middlemen or central authorities to handle transactions and verify information. This centralised setup can cause delays, higher expenses, and risks if one part fails. Blockchain changes this by allowing direct transactions between peers and using decentralised agreement methods. Startups can use smart contracts to automate and simplify their tasks, cutting down on the need for middlemen. This decentralised way not only makes things more efficient but also gives startups more control over their operations and data. In summary, the decentralisation aspect of blockchain allows for financing transparency which could mean the world for the startup industry which is dependent on funds availability. Obviously looking at all of this though, this technology has incredible benefits for the logistics industry in increasing transparency within supply chains.
One firm making an impact here is OpenPort, which utilises blockchain technology to increase transparency in supply chains within emerging markets.
Digital Twins for Supply Chain Optimization
The complexity and expansion of our economic system, along with potential geopolitical issues, have resulted in sophisticated supply chains that are increasingly challenging to manage. However, the emergence of the digital twin technology has the potential to revolutionise supply chain management by resolving some of the challenges we are currently facing. But first, what is digital twin technology?
Put simply, a Supply Chain Digital Twin is a detailed simulation model of an actual supply chain. It is created by combining various enabling technologies, including sensors, cloud computing, AI and advanced analytics, simulation, visualisation, AR, and VR Companies often use a customised mix of the above technologies depending on their own internal requirements. The technology utilises real-time data, obtained through a network of sensors, to support end-to-end visibility and traceability. This will assist supply chain practitioners to recognise the patterns and dynamics of a complex supply chain, thereby allowing them to facilitate appropriate action plans.
In the venture capital space, TwinThread is one of many startups that are leading the way in digital twin technologies for supply chain optimisation. The company specialises in a predictive operation platform using digital twin technology to help optimise industrial operations. The firm has secured a total funding of US$3.08M in August, 2018.
However, although the technology does sound exciting, data does demonstrate a funding drought that could slow the progress in this market. In 2023, the total funding for the digital twins space only reached US$0.3Bn, compared to US$1.4B in 2022, and US$2.7B in 2021 .
Economic instability can perhaps be attributed to this downfall, as the world is still battling with bouts of economic contraction, inflation and increased national debt. The increasing concerns around cybersecurity may have also cautioned investors against funding startups that do not yet have robust security measures in place. Lastly, the complexity of the technology, where one must integrate advanced AI and other tools, may also increase development costs and raise the demand for niche expertise, making it difficult for startups to quickly develop market-ready solutions.
Given everything above, it is evident that while the market does display exciting growth and innovation prospects, recent economic instability, and prolonged diffusion period for the technology may pose a challenge for the market to blossom.
Supply Chain Resilience with AI
Supply chain resilience, in short, is the ability to respond quickly to operational disruptions. The resilience capacity is made up of two parts: resistance, and recovery . It has often been said that by implementing AI into supply chain management, we can observe enhanced capabilities in visibility, risk, sourcing, distribution, and more. This will therefore offer unprecedented levels of resilience, as well as efficiency, enabling companies to adapt to the dynamic global market. Indeed, in the long-run, it is indisputable that AI will help organisations enhance operational efficiency, improving supply chain resilience. However, has AI actually helped us so far?
In truth, the expectations regarding the capabilities of AI to transform the supply chain has largely been unmet. Contrary to what you might think, the issue is not with the shortcomings of AI technology itself, but rather with its implementation in business practices. In addition to a general lack of trust in AI among the workforce, the main issue lies with organisational and technical barriers with its implementation. Namely, the complexity of supply chain management, where multiple different functions have conflicting optimisation goals, makes the implementation of end-to-end AI optimisation difficult. The existing organisational structures, as well as incentive systems, contrasts with holistic supply chain performance objectives. Combined with the lack of proven at-scale AI-driven learning systems, and the lack of quality data for training these systems, companies are presented with considerable technical challenges in implementing said AI system. Furthermore, as the world is still recovering from the COVID-19 pandemic, the focus on addressing immediate pandemic-related issues has diverted funding and resources away from implementing AI learning systems into supply chain management.
Thus, while the revolutionary impacts of AI on supply chain management is already within reach, we still require a paradigm shift in how companies view and implement AI. Overcoming the organisation and technical challenges outlined above will therefore allow our economy to embrace AI as an essential step towards realising the full potential in operational efficiency with regards to supply chain management.
As this industry unfolds and matures, the potential for transformative change becomes even more pronounced. From the promising horizons of autonomous vehicles to the agile flight of drones and the blockchain-led transparency revolution, logistics is undergoing a profound shift. The dynamics of digital twins and AI-driven resilience harmonises with the logistical intricacies of our modern world, offering a glimpse into a future where efficiency, transparency, and adaptability reign supreme. Think about it, soon your online orders might arrive faster than ever before! Yet, amidst the promise, we confront the stark realities—funding droughts, implementation challenges, and the ongoing dance between innovation and market dynamics. We will certainly keep watching where this industry goes, that is for sure!