Supply chain operations can be complex, especially where
multi-modal transport is necessary and where dynamic decision making is
required for the routing of goods in-transit. These supply chain operations are
pursued in an environment that can be characterized as a self-organizing
ecosystem. Connections between various (local) data sharing environments in
networks of networks enable stakeholders in the supply chain to enhance their
information base. The latest internet of things (IoT) technologies can provide
complementary insights as to the whereabouts and status of goods and assets.
Combining all available data improves situational awareness. Data sharing
enables green and humanitarian decision making and facilitates a truly smooth
and seamless movement of goods.
Information and data are the foundation of insight.
Substantial investments today are being made in digital technologies allowing
for more digital data streams in supply chains. Logistic Service Providers
(LSP), carriers, intermodal operators (air, sea, ground etc.), port authorities
and terminal operators, regulatory bodies, and Beneficial Cargo Owners (BCO)
are all working on this topic. The European Commission forecasts exponential
growth of data streams.
Efficient routing and high utilization of logistics assets
and infrastructure lead to cost efficiency benefits. This includes the
efficient use of vessels, planes, trucks, barges and trains, as well as
loading/unloading equipment. Episodically visiting actors are being served
just-in-time with short turn-around times at transhipment hubs, reducing
waiting times to a minimum. All of these require the sharing of information
about goods and transport as the basis for visibility and transparency.
Visibility and transparency are critical for condition and
time sensitive goods, like vaccines and flowers, and for bringing agility,
resilience, and predictability into the supply chain. Such visibility and
transparency require data; about the location of shipments, about the
temperature and shock conditions goods are exposed to, also the situation
merchandise faces along the supply chain, like transit delays or bad weather.
Supply chain visibility is needed to realize improved
outcomes for society and the environment. As a result of Covid-19 restrictions
across the globe the number of people facing starvation due to food insecurity
at the beginning of 2020 has doubled from a projected 135 million to more than
270 million by the end of the year. According to a July 2020 Oxfam Report, this
could result in 6,000-12,000 deaths per day.
Transparency is a must to improve emergency and humanitarian
support, such as with the COVID-19 pandemic. Flagging a container 'COVID prio'
in a truly transparent supply chain would make it visible for all relevant
supply chain participants thereby allowing priority treatment to speed up
movement and delivery, and pre-emptively circumvent disruptions in the system.
With the right infrastructure in place, a carrier could put such a container on
deck, the terminal could off-load it first, customs could fast-track clearance
or clear the container while still at sea, the port could even make sure all
the traffic lights in the port are set to green for the haulier’s truck, etc.
Similarly, the distribution of a COVID-19 vaccine is at
present a logistics challenge that has never been faced before. The
optimization of insufficient and constrained air cargo capacity (due to
COVID-19) as well as the limited cold chain infrastructure, combined with the
short expiration dates of vaccines means that increased visibility and
transparency of vaccine logistics data literally equates to more lives saved.
More visibility and transparency aid `green decision making`
on transport choices and routings. Optimized routes and flows produce less
carbon emissions. Supply chain visibility is an important ingredient for true
planetary and human benefits to be realized. Visibility also allows for post
transport analyses and the verification of fair charges. Price-gouging or
excesses in supply chains could more easily be exposed.
Greater visibility creates new opportunities and innovation
for trade financiers, risk managers and insurance companies. Ports and
hinterland carriers want to know what cargo (and how fast it) is approaching
them, and where it is heading. All share the need for data, and all want to
know more.
Situational awareness can be derived from combining the
small pieces of information that each involved LSP is willing to share. There are
many sources for those pieces of information, such as IoT devices, and systems
of records for engaging LSP’s that provide data on agreements and achievements
within a system of production.[i] There are various means to share, varying
from central databases such as UNCTAD ASYCUDA’s “Digitizing Global Maritime
Trade" (DGMT) project, or ASYCUDA Single Windows or shared blockchain ledgers, and there are
various methods to control the sharing - who can see what.
Cargo being transported can take different routes through
logistics networks, within regions and globally. Therefore, the need for the
many actors to be digitally connected. All parties along the transport chain
need to be well joined up. An important task for all involved is collaborative
alignment. As most transport involves multiple modalities, and as goods being
transported along the supply chain have different characteristics, it is
important to understand the many aspects that can influence a shipment, from
environmental conditions, to security and safety.
Initiatives such as IATA’s ONE Record, building upon the
Internet of Logistics, or the TradeLens data sharing environment, originating
from the collaboration between Maersk and IBM, are two initiatives intending to
create a network of (local) networks. Within the European initiative of the
Digital Transport Logistic Forum (DTLF), concepts for a federated environment
of networks of networks are now emerging and being validated within the
FEDeRATED and FENIX projects.
Multiple entities within the consumer and supply chain and
transport arena are exploring the concept of data aggregation for the common
good. Essentially, bringing the least granular level of anonymized data from
multiple open and closed network sources (and existing aggregator platforms)
together in a non-commercial, open-source global supply system dashboard
(GSSD), providing system wide visibility on the movement of essential goods to
vulnerable communities served by the humanitarian sector. Further, we now see
the introduction of such things as smart containers (IoT), as a source of data
that cuts across the different modes of transport.
When parties decide to collaborate and agree to mutually
share data about a shipment, the benefits are huge: Increased visibility and
transparency, integrated performance (i.e. that actions pursued by all actors
are continually coordinated and synchronized) throughout the supply chain,
latter parts of the transport chain being administratively prepared before the
actual physical operations happen, reduced waiting time, secured fulfilment
levels, minimized administrative burden, collaboration regardless of location,
data point accuracy, cost effectiveness, increased resilience, improved and new
services, innovation potential, capabilities for predictive actions, enabled
post transport analytics, real time decision making, and increased automation.
All these contribute to cost effective, integrated fluid
supply chains, and provide the means for appropriate commercial, societal, and
environmental prioritization throughout the global supply chain.
Imagine a situation where the many actors engaged in the
supply chain, across and among the different modes of transport, provided
minimum levels of data to enable decisions on the prioritization of transport
to be made collaboratively leading to reduced delays and waste, increasing the
number of lives protected. Imagine analyses on areas of extreme poverty and
famine; food, medicines and medical equipment arriving faster to save lives.
The value of these benefits for BCO’s, carriers, LSP’s and
other stakeholders, including the customs authorities offsets the effort
required and data governance frameworks can help to overcome intuitive
reluctance to sharing data.
The transport ecosystem is reliant on many autonomous
actors. Sometimes they are simply competitors chasing the same customers, yet
at other times the same players seek to collaborate to reap the benefits of
co-opetition. This collaboration is usually sub-optimal. To overcome this,
local information sharing communities have emerged to obtain higher
performance. Port Community Systems, Government Single Windows, Trader
Community platforms are all examples of this sort of development.
An issue here is to allow for the co-existence of multiple
platforms, both as local information sharing communities and as horizontal
information sharing communities enabling the end-to-end supply chain.
Inter-operability through standardized messaging and interfacing between
information sharing communities is key for success.
The Data for Common Purpose Initiative (DCPI) at the World
Economic Forum focuses on creating a new flexible data governance model that
allows for the combining of data from personal, commercial, and government
sources. The DCPI is built on a belief that orienting data policy and data
models around common purposes, such as specific use cases, will unlock
opportunities for public good and commercial spheres. The view is that data can
and should be treated differently depending on its actual and anticipated use,
and that Fourth Industrial Revolution technologies can enable differentiated
`permission-ing` of the same data, dependent upon context.
At the local level there are several specific requirements
and challenges to address, including:
Overcoming resistance to new business models
A need to lower the thresholds for any actor to become
digitally included
Establishing agreed way(s) for identifying the cargo being
transported, with different levels of granularity
Addressing the automatic fear of data sharing, even when it
will be protected by robust data sharing rules and governance models
Overcoming the misconception that withholding non-sensitive
data will create a sustainable competitive advantage
Substantiating data sharing trust and security models
between role players