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The Interplay of Three Technologies is Transforming Logistics - Kearney

13/09/21, 14:34
The Interplay of Three Technologies is Transforming Logistics - Kearney
The interplay of three technologies is
transforming logistics
The mutual fertilization of artificial intelligence, mathematical optimization, and blockchain
will revolutionize supply chain management.
Three hot topics are on the boardroom table of every logistics company around the world. In
the race to implement solutions based on artificial intelligence (AI), mathematical
optimization, and blockchain, well-established companies are forming special units and
project teams and are scrambling for scarce resources in the form of specialists and
specialized consultants. Meanwhile, start-ups are proliferating with innovative solutions and,
as an example, are expected to create around 50 percent of the new jobs in logistics and
supply chain management in Germany. Capabilities in these fields now have a relevant
influence on the valuation of logistics companies.
Logistics leaders understand the profound potential and impact of these advanced
technologies, recognizing that the industry is at a tipping point. “The traditional model is
facing unprecedented levels of disruption from new hardware technologies combined with
information and analytics solutions,” says DHL Supply Chain’s Chief Development Officer José
F. Nava. For example, smart sensors and machine-learning algorithms are capturing and
processing information about aircrafts, ships, trucks, and rail rolling stock to optimize
operations and maintenance into one integrated process.
Although the potential of each of these advanced technologies is now widely discussed,
what has so far been lower on the radar is the power of these technologies to work together
to create new applications and achieve even greater productivity gains. As forward-thinking
companies capitalize on this synergy, logistics and supply chain management will see a
transformation in several dimensions: value chain configuration, sourcing and interaction
between players, routing and scheduling, and allocation of capacity and the workforce.
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In this paper, we first discuss what these three technologies are before turning our attention
to how they can reinforce one other to create powerful benefits for the logistics industry.
Three innovative tools
Despite their ubiquitous presence on management agendas, AI, mathematical optimization,
and blockchain are not well-understood, which is not surprising considering their complex
nature. It is important to note that the three technologies are in very different stages of
development. AI is at the forefront with high global investments driven by e-commerce,
mobility, and defense. Meanwhile, mathematical optimization, which as a discipline of
operations research has been around even longer, will be a fast follower in terms of the rollout
of use cases. Blockchains and the implementation of the principles behind them in various
formats still face several hurdles, which will put this technology in third position in making a
large impact on logistics and supply chain management. We begin by briefly describing
applications and characteristics of these technologies in supply chain management and
logistics and how they might develop in the future (see figure 1).
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A powerful convergence
These three tools have the power to reinforce and cross-fertilize each other with an impact
that is not additive but rather multiplies (see figure 2).
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The effect of this interplay between the three technologies can be observed not only in terms
of productivity gains such as reducing processing time, optimizing the use of resources, and
moving tasks from humans to machines but also in terms of the speed of their adoption and
the penetration into supply chain management (see figure 3).
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Many applications are already taking advantage of this technology cross-fertilization. For
example, global transport and logistics company Kuehne + Nagel’s comprehensive digital
supply chain management platform KN ESP offers a modular architecture to connect all
stakeholders in the company’s international supply chain—from sourcing, quality control,
purchase order negotiation, and management to commercial invoice release, buyer’s
consolidation, transportation, and delivery. KN ESP uses predictive analytics and AI to
optimize orders and prioritize transportation decisions based on the customer’s defined
business rules, costs, and service options.1 DHL is using machine learning for transport
pricing by its in-house start-up Saloodo! The company is also using chatbots for customer
service and deep learning-based computer vision to detect fraud and optimize air cargo
loading.2 Forwarding and logistics services provider Panalpina is pursuing ways to integrate
blockchain technology in core systems and is planning to run pilots and trials using
blockchain together with start-ups for certain markets and specific customer needs.3
“Blockchain is one of the most promising technologies in logistics,” said Martin Kolbe, chief
information officer of Kuehne + Nagel. In the rail industry, Deutsche Bahn is using
mathematical optimization for predictive maintenance and to help dispatchers reallocate
passenger trains during network disruptions, such as those caused by accidents or
unplanned maintenance events.
For blockchain technology, where benefits so often depend on cross-value chain or even
cross-industry adoption, we are starting to see new partnerships that could profoundly
change the logistics landscape by jointly establishing unified standards, achieving gravity,
and overcoming first-mover disadvantages. For example, shippers such as Henkel, Beiersdorf,
and Oetker are collaborating in blockchain-based track and trace and accounting of pallets.4
Microsoft and Ardents are developing a blockchain-based platform called Novatrack for
tracking products end-to-end. Maersk and IBM are developing a platform based on
blockchain and artificial intelligence, creating transparency into the supply chain and
digitizing the import and export paper flow. The platform, which is open to forwarders,
shipping lines, terminal operators, ports, and customs authorities, aims for the participation of
several—if not all—players in the global shipping-related supply chain.5 “The potential from
offering a neutral, open digital platform for safe and easy ways of exchanging information is
huge, and all players across the supply chain stand to benefit,” says Maersk’s Chief
Commercial Officer Vincent Clerc.6
Other examples of blockchain projects in the container shipping industry include the planned
platform of MOL Logistics, NYK Line, and K Line, the TBSx3’s pilot with Hamburg Süd, DP
World Australia, and DB Schenker as well as the feasibility study of Pacific International Lines,
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IBM, and PSA.7 Hong Kong-based start-up 300cubits promotes a blockchain solution called
TEU tokens. To succeed, the industry will need a joint adaptation.
The future of logistics
The implications for all stakeholders are both multidimensional and disruptive. With the
convergence of artificial intelligence, mathematical optimization, and blockchain, logistics
could look very different in the not-too-distant future. Following is our vision for what a future
driven by these three technologies might look like for six categories of service providers and
the challenges each is likely to face.
Transport organizer
For forwarding and broker firms along with courier, express, and parcel companies, almost all
events in the supply chain are handled by algorithms with event management capabilities
based on machine learning. They have much more flexibility to change routes, ports, and
carriers. Routing is automated based on customer requirements and the optimal cost path.
Algorithms optimize the mix of suppliers as well as the mix of spot buying versus wider
commitments at any given moment. Paper documentation has been eliminated, and firstlevel customer service handling human requests is based on natural language processing. In
the past, the most important suppliers were those physically handling the shipment during
the transport process; today, the most important business partners perform different tasks of
data management. Digital partner management is now a core competence.
Transformational challenges:
• Tap into the power of smart management, integration, and replacement of diverse legacy
IT systems when competing against greenfield digital competitors.
• Establish a digital platform model with enough gravity.
• Manage the workforce transition. More than 50 percent of today’s office workforce will be
reduced, and another 20 percent of the workforce will migrate to improving AI-,
mathematical optimization-, and blockchain-related tools and processes.
• Balance the hiring of costly talent in AI, mathematical optimization, and blockchain versus
procuring specialized services.
• Decide whether to invest in or buy new digital and analytics players at the right time.
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• Choose whether to depend on local fixed assets or digital innovation for small players to
differentiate in the market and survive.
Carrier
Owners and operators of mobile assets in road, sea, air, and rail are conducting their business
in a much different landscape. Ships, trucks, locomotives, and inner-city delivery vans are
autonomous. Fleet operators are not small subcontractors any more but large asset
operators, including digital natives and original equipment manufacturers. Drivers and
captains who support difficult operations are managed by specialized intelligent platforms
automatically identifying the next available resource. Stowage planning, global container
repositioning, and fuel-optimized speed for sea and air freight are fully automated. The
combination of automation and meta platforms managing neutral fleet of containers allows
for handling of more diverse sizes of sea containers. The share of the total fleet capacity
available on demand is much higher and not locked up by a specific transport organizer or
shipper in long-term contracts, for example, with rail car on demand. Predictive maintenance
is fully integrated with operational optimization of resource allocation to make last-minute
adjustments when things do not go as planned. All levels from strategic capacity planning to
tactical operations and revenue management are fully integrated to optimize capacity
utilization.
Transformational challenges:
• Set the right priorities and budgets on AI, mathematical optimization, and blockchain as
leading competitors or start-ups may shake up the industry cost structure and customer
experience. Some players will be too late to follow.
• Manage the transition from dispatchers being the most valued people taking operational
decisions to dispatchers being the most valuable people to improve algorithms.
• Make sure the people who automate the processes, make decisions, and implement
machine learning and robots know the physical reality (based on the Internet of Things,
cameras, and site visits).
• Establish an omnichannel business model with control over capacity allocation and pricing:
direct to shippers, forwarders, platforms, container providers, and all parties acting as
resellers.
• Have the courage to compete with digital platform business models and on-demand
capacity, including from smaller players cannibalizing comfortable long-term contracts and
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stable revenues.
• Manage the job shift from driving to maintenance and add-on services.
Infrastructure operator
For air and sea ports, rail tracks and terminals, roads, warehouses and depots, and sorting
plants, the allocation of scare capacity to customers is based on auctioning algorithms for the
long, medium, and short term. Long-term capacity allocations and commitments have shifted
to more on-demand schemes and high-priced securing of specific AI-predicted bottleneck
capacities. Optimization of utilization, maintenance, and event management is based on data
from the Internet of Things from all equipment and pre-configurated and simulated events of
all kinds. The 24/7 management of operations is highly automated, including for all
foreseeable events, second-level support, and maintenance.
Transformational challenges:
• Integrate the data exchange between all stakeholders—possibly checking, cleaning, and
enriching data in the process.
• Maintain the cybersecurity of IT-systems of infrastructure.
• Become the local digital platforms for all services connected to the infrastructure.
• Connect or join standards with similar infrastructure globally to achieve scale for
operations and for customers.
• Become masters in reaping the extra profits for scarce capacity in peak periods, for
example via auctioning, processing micropayments, and preferred service in real time
against add-on fees.
• Build new business models around separated infrastructure for service provision to
transport organizers (for example, groupage courier, express, and parcel services or airlines
offering cross-continental e-commerce parcels).
Value-added service provider
For fulfillment, confectioning, customs, document handling, payment-related activities, and
data-driven services, all document-processing related activities have been significantly
reduced and automated, including the clarification process for missing or wrong data.
Confectioning and fulfillment are using more robots and android technology. Customs
processes are fully automated with physical control by robots. Data-driven meta service
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providers have achieved economies of scale across industries and regions in a logistics
industry segment where scale used to be of minor importance. Micropayments for individual
process steps are based on smart contracts, and crypto currencies are triggered by the
Internet of Things devices connected to containers or cargo. Information, financial, and
physical flows are fully synchronized.
Transformational challenges:
• Sell data against subscriptions and micropayments. In the past, customers and business
partners were unwilling to pay for data. Now, they are willing.
• Be mindful about small trackers and loggers. In the future, they may be at the heart of
blockchain, micropayments, and automated event management and may reap a
significant part of the profit pool, just as Google does in retail.
• Expand fourth-party logistics and control tower services as they are flourishing, absorbing
some of the workforce of forwarding customer service and dispatching.
• Provide third-level support for supply chains based on robots and AI with new business
models.
• See compliance and process auditing become a major task for humans, assisted by AI.
Digital platform
For meta forwarders, meta brokers, and demand aggregators, almost every successful
business is also a platform, allowing third parties to thrive on their physical or virtual
infrastructure in competition and symbiosis with their business. The boundaries of a classical
forwarder and a digital platform are now blurred, just as it happened for e-commerce versus
stationary retail. New companies with a globally integrated IT architecture have outgrown and
replaced established companies that failed to unify their fragmented systems fast enough.
Successful platform providers are focusing on data-driven value-added combining services
driven by AI, blockchain, or mathematical modeling space.
Transformational challenges:
• Be a scale and cost leader as high transparency drives out margins. Expect gravity to lead
to selected digital platforms grabbing more than 50 percent of some logistics markets
(such as INTTRA in ocean booking) but not for very long.
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• Consolidate as players from different continents, especially China, India, and the United
States, will go global and buy up other local and regional firms.
• Understand that some platform business models with limited added value will disappear as
large, integrated, and fully automated platforms operating at a minimal cost and low
margins call for other pure digital players to clearly differentiate and innovate their services
based on AI, mathematical optimization, and blockchain.
• Build niche online services to seamlessly integrate and operate background logistics
platforms, for example, around blockchain, event management, trade flow analytics (just as
in online advertising and consumer analytics).
Supply chain planner, procurer, and manager
The supply chain departments of all major shippers, be it manufacturers or retailers, have
used digital to integrate all tools and processes across geographies, subsidiaries, and,
perhaps most importantly, across planning horizons. For network planning, network and
transport sourcing, routing and allocation management, and event management, planning
tools are fully integrated—from the strategic (manufacturing and inventory footprint) and the
tactical (inventory rules and preferred ports) down to the operational (production plan and
last-mile) level. Planners have shifted their time from adapting calculations to new
requirements to improving modeling quality and devising conclusions from model results.
Modeling results either support final human decision-making or automatically lead to
changes in processes and supplier selection and procurement transactions within defined
rules with no human interaction. Planning and sourcing tools are integrated. All transactions
are transparent and documented using variations of blockchain technology with auditors and
government agencies checking for compliance via constant data connections and AI-based
methods.
Transformational challenges:
• Shift staff from supply chain administration and bottom-up planning to improving the
planning and execution algorithms and surveilling and supervising the results.
• Invest in automated execution and event handling.
• Expand your supply chain partner ecosystem from forwarders to more companies and
integrators.
• Improve real-time supply chain key performance indicators to track results of automated
decision-making on out-of-stock performance, quality, supply chain-related customer
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satisfaction, and supply chain costs.
• Rid yourself of fixed assets and capacities wherever possible, but build safety into
contracts to secure peak capacity.
• Leverage platforms to remarket your fixed supply chain capacity.
Riding the wave of disruption
AI, mathematical optimization, and blockchain are reshaping supply chains and the logistics
industry—reinforcing each other in the possibilities they create, in their impact, and in their
potential speed of adoption across supply chains and all related services.
The speed of adoption may primarily be determined by the lack of specialists and project
leaders, be it as employees, consultants, or service providers, and by the capacity for
managing change by top and middle management, trainers, and every employee in supply
chain management, transportation, and logistics.
Data is the oil of the 21st century, and AI, mathematical optimization, and blockchain are the
engines to burn it. Together, they will create an industry that is capable of fully integrating
services around the physical movement of goods, the flow of payments, and the movement
of information, which had been in the hands of various industries, such as financial services.
The impact will reshuffle the industry and create a competitive race between large
incumbents in infrastructure management, mobile asset management (carriers), and
forwarding against new entrants with pure platform models, which may start with a
specialization of services in one domain of AI, mathematical optimization, and blockchain but
may converge in the future.
At the same time, well-managed shippers will benefit from investments—whether in their own
internal resources or with a unique combination of external services to achieve a competitive
advantage—from greater market transparency, better service offerings, and more competitive
pricing. As seen in numerous Kearney projects, prototypes for high value-creating AI or
mathematical optimization applications can be built in two to four months, and solutions that
are fully integrated into the IT environment can be implemented within six to 18 months
depending on the complexity at hand. Typically, the payback for implementation of any one
of these tools—or a combination of them—materializes in less than a year—often less than six
months after project completion.
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Although exponential growth can never be sustained, the speed of technological change will
continue to pick up pace, creating a wealth of new possibilities. Forward-thinking logistics
companies will master the transition of both their operating model and their workforce—from
top management to dispatchers and front-line employees—by weaving together artificial
intelligence, mathematical optimization, and blockchain in a step-by-step agile approach
supported by intensive change management communication to create cutting-edge supply
chain management.
1
Kuehne + Nagel
2
Saloodo!, EnterpriseTech
3
Panalpina in Air Cargo News
4
Wirtschaftswoche,base58.de
5
ShippingWatch
6
Forbes
7
Deutsche Verkehrs-Zeitung (DVZ)
8
300cubits, New Jersey Institute of Technology
Authors
Sumit Mitra
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Partner
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