The Future of Logistics: Data-Driven Transformations in 2023 and Beyond
Technological advances have allowed
organisations to accumulate data at a rapid pace. Data is now the lifeblood of
our digital world and when used effectively can optimise every aspect of
business operations. Organisations can use data analytics to make informed
decisions, such as understanding customer preferences, through to identifying
operational inefficiencies. Data-driven decisions often result in better
outcomes and competitive advantages.
However, to harness the value of
data, organisations must find a way to collect, analyse, and use the vast
amounts of data they generate to inform decision-making and gain valuable insights.
The process of transforming real-world interactions, workflows, and processes
into digital data that can be stored, analysed, and monetised is known as
datafication.
The Evolution of Data Use in Logistics
Printed forms, manifests, and
paper-based tracking systems dominated logistics management for many decades.
It was arduous and manually intensive to maintain accurate record keeping. As
technology moved on, organisations embraced systems that could manage
inventory, track shipments in real-time with GPS technology, providing precise
locations of shipments and revolutionising the way goods were monitored in
transit.
Today, with the explosion of
available data, analytics tools can optimise routes, predict demand, and reduce
costs. Technology has allowed organisations to shift from basic data collection
to advanced analytics and prediction. In the current business landscape, datafication
has emerged as a critical trend that profoundly impacts the way supply chain
organisation’s function. It has already begun transforming the transport and
logistics sector and is poised to drive even more change in the future.
Predictive Analytics & Machine Learning
Datafication is helping the
logistics sector to predict demand patterns more accurately. By analysing
historical data and patterns, organisations can anticipate demand fluctuations,
enabling better inventory management and the planning of more efficient
transportation routes. With predictive analytics, routes can be optimised in
real-time based on traffic data, weather conditions, and other variables,
ensuring timely deliveries and reduced fuel consumption. These more efficient
transportation routes enhance supply chain performance, reduce delivery times,
and decrease carbon emissions.
Predictive analytics is also facilitating
logistics organisations to predict when maintenance is needed for their
vehicles and equipment. By analysing maintenance history and performance
metrics data gathered from sensors on vehicles and infrastructure,
organisations can schedule maintenance tasks proactively, reducing downtime and
increasing the lifespan of assets. This reduces operational costs by preventing
expensive and unexpected breakdowns.
Real-Time Supply Chain Visibility in the Logistics Sector
Within the logistics sector,
datafication has ushered in advancements in real-time supply chain visibility,
enabling logistics companies to identify bottlenecks, optimise inventory
levels, and enhance overall supply chain resilience. By analysing data on
transportation, warehousing, and inventory management, businesses can
streamline processes, reduce lead times, and minimise waste.
This provides stakeholders with a comprehensive
view of the entire supply chain, including monitoring shipments, vehicles, and
inventory in real-time. With this insight, organisations can pinpoint a
shipment's exact location and monitor specific conditions, such as the
temperature for perishable goods, ensuring the integrity of sensitive items
during transit.
This level of transparency is
revolutionising inventory management practices. By having precise and timely
data, businesses can anticipate potential delays and optimise routes, ensuring
smoother operations. This significantly reduces costs associated with non-deliveries
and improves customer satisfaction.
Enhanced Clarity and Insight
Extracting, combining, and
analysing data from multiple systems to uncover actionable insights can be
challenging. For many companies this remains a manual process, and the
complexity of managing information from so many data feeds is often inefficient
and prone to human error.
EVOLink from Touchstar is a
cutting-edge software middleware tool that seamlessly tackles the challenges of
data integration. Confronted with an array of data sources and formats,
businesses often grapple with the herculean task of consolidating information.
EVOLink simplifies the process of amalgamating data from multiple systems,
whether it’s from the sales order processing system, warehouse management
system, or EPOD system. EVOLink centralises data from multiple sources, streamlining and accelerating data analysis. Customers are
empowered to derive new insights, craft key performance indicators, and achieve
a level of business clarity previously out of reach, all thanks to the
transformative capabilities of EVOLink.
One customer, The Bread Factory,
uses EvoLink to automatically consolidate information from various data feeds,
even when they occur at different times. After extracting and reformatting the
data, EvoLink uploads the information into their proof of delivery system as
individual tasks. This gives drivers a comprehensive view of the transport
plan, including route details, drop sequences, box counts, and special delivery
instructions.
Using this data, TouchStar’s EPOD
system provides route optimisation, estimated arrival times, and an auto-send
feature for proof of delivery. As a result of implementing EvoLink with
TouchStar’s EPOD solution, The Bread Factory has seen a sharp decrease in customer
delivery inquiries, notably faster issue resolution time, and reduced operational
costs.
Autonomous Logistics
In the logistics sector, the rise
of autonomous vehicles and drones is revolutionising the landscape of
deliveries. Companies, such as Co-op stores in Greater Manchester, are offering
autonomous delivery services in efforts to reduce traffic congestion. Customers
can choose from a wide range of grocery items, schedule their delivery, then
drop a pin where they want their delivery to be sent with the ability to watch
the robot travel in real-time via an interactive map.
Prime Air, Amazon’s much
anticipated drone delivery service has begun durability and reliability testing
which is required for permission to fly safely over urban areas. Their next
generation delivery drone will have increased range, expanded temperature
tolerance, and the capability to fly in light rain, bringing the vision of
urban drone delivery a step closer.
As this innovative technology
matures, we may see fleets of self-driving trucks and agile delivery drones become
more commonplace as logistics companies look toward
the horizon and explore the many possibilities that autonomous vehicles can
offer.
Central to the safety and
efficiency of these autonomous systems is data. Harnessing vast amounts of
information, advanced AI algorithms evaluate, plan,
and adapt, ensuring that these vehicles navigate safely. They can intuitively
optimise delivery routes and make real-time adjustments in response to
variables like unpredictable traffic or sudden weather changes, underscoring
the indispensable role of data in the next chapter of logistics.
Enhanced Customer Experience through Data
Datafication has emerged as a
critical tool for elevating customer service and delivering an overall enhanced
customer experience. By harnessing the power of data, logistics
companies are becoming adept at gathering key customer feedback and perceiving
their preferences. This invaluable insight allows for tailored services that align
with individual customer needs, fostering enhanced satisfaction and bolstering
loyalty.
With a cost-of-living crisis and
high inflation, retaining customers is vital for any business. The era of
data-driven customer service has dawned. By leveraging data analytics, logistics companies can provide updates on shipment
statuses, integrate real-time tracking, and engage in proactive communication. This
approach not only streamlines operations but is pivotal in cultivating customer
trust and loyalty.
Sustainability through Data-driven Decisions
In today's business environment, an
emphasis on sustainability is paramount, and the logistics
sector is no exception. Through the lens of data-driven decision-making, organisations
are making strides in minimising their carbon footprints. By leveraging data
analytics, they can optimise routes and ensure vehicle operations are at peak
efficiency, thereby reducing emissions and environmental impact.
Data plays a transformative role in
underpinning environmental, social and governance (ESG) within logistics. Ultimately, the combination of data and
sustainability initiatives is facilitating a new era of green logistics. Armed with accurate and real-time
analytics, logistics organisations can measure and
assess their environmental impact and uncover actionable insights to drive
eco-friendly and sustainable improvements.
Conclusion
The horizon of 2023 and beyond
paints a vivid picture of the logistics landscape, fundamentally reimagined by
the transformative power of datafication. As logistics organisations advance, they
will be able to harness the full potential of their data. The intricacies of business
operations will be further unravelled, streamlined, and enhanced through the
use of advanced data. This will enable forward looking companies to chart a
trajectory of innovation, efficiency, and customer-centricity.
The combination of real-time
analytics, predictive modelling, and deep learning is set to redefine the
benchmarks of operational excellence in these sectors. For logistics companies that
are pondering the future, the message is crystal clear: investing in and
prioritising data-driven strategies isn't just an option—it's an imperative.
Those ready to harness the full spectrum of datafication's potential will
undoubtedly be the pioneers, leading the industry into a brighter, more
sustainable, and interconnected future.