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The results of
our latest research highlight the important role that data
plays in supply chain management and the breadth of related
challenges faced by organizations today.
Based on a global survey of more than 900 respondents from 36
industries (including chemicals, oil and gas, and logistics and
shipping companies),
our report provides valuable insights into the ways
organizations are thinking about all aspects of their supply
chains, from spend and category management through to contract and
supplier performance management. Data is critical at every point in
this lifecycle. However, the findings highlight a number of common
data challenges that are preventing organizations from realizing
potential gains.
When asked what the biggest data-related challenges are for
supply chains, the top results were "timely, easy access to
data" and "integration of data across users,
technologies, and the broader supply chain" (both cited by
18% of respondents). These were followed by
"manual processes and errors in managing data"
(16%) and "checking data quality and
correcting bad data" (15%). The almost
even split between the findings (only "understanding data
lineage" was a cited by less than 10% of
respondents) speaks to the breadth of data challenges faced by
organizations throughout the supply chain today.
These stats add quantifiable detail to anecdotal evidence about
the industry's approach to data and the role data plays in supply
chain ecosystems. As Peter Björkborg (Manager, Sustainability &
Transformation, at Stena Bulk) noted in a recent
Trade Winds white paper: "The industry has access to plenty of
data, but it is often scattered, low quality and underutilized.
Best case, that is a waste. Worst case, it means bad intelligence
and inaccurate insights leading to inefficient operations and bad
decisions."
Port congestion
Access to consistent, accurate and timely data can provide the
visibility organizations need to spot issues in their supply chains
as they emerge (or even before) and adapt accordingly. To take just
one example, we continue to see a record number of vessels sat idle
offshore for weeks due to congested ports (causing delivery delays,
higher freight costs and greater carbon output). However, those
with trusted data and integrated workflows have been able to pivot
efficiently, finding alternative partners, routes, and channels to
deliver product and serve their customers.
Access to reliable data is not only critical for responding to
unforeseen events, but also has an important role to play in
helping organizations better plan to mitigate risk and volatility,
creating greater resilience. It is clear the right data, when used
in the correct way, has the potential to fuel significant supply
chain optimization, from meeting decarbonization goals to improving
vessel ETA scheduling, which helps on-land operations such as
equipment management and personnel allocation.
So, what is preventing more organizations from using their data
assets in this way? And how can they overcome these challenges?
Hampered by legacy technology and entrenched manual processes,
many maritime and shipping organizations lack the ability to
integrate disparate data into a consistent, validated, central
source that can be used to create actionable analytics. The siloed
nature of these processes is an opportunity lost for industry
participants.
Digital transformation
To overcome this challenge, as part of their digital
transformation strategies, organizations need to prioritize best
practice data management, including using a core technology
solution that integrates and quality-checks data before it is used
in decision-making. The solution should empower users by automating
workflows and delivering consistent, validated data to the systems
and users that need it. Further, data governance should be a core
pillar of data strategies to build trust and transparency in
information that is shared across the value chain.
As maritime and shipping companies look to implement and upgrade
to best-of-breed technologies (such as voyage management systems,
enterprise resource planning platforms, and weather routing
solutions), they should first ask questions about their data and
supporting applications such as: "who needs the data, in what
format, at what time, in what system?" Decision-making tools
will only perform reliably when fed with the correct data that has
gone through a governance process. By instilling best practices
from the outset, organizations can avoid the pain of untangling and
re-engineering data manually.
Of course, as new technologies are embraced, data volumes and
types are increasing rapidly. While digitalization across the
ecosystem presents opportunities, it also poses challenges for all
industry participants who must be able to handle flows of data in a
scalable way - only then will we see compounding gains. As supply
chain dynamics continue to evolve and cost pressures mount,
cloud-based solutions offer the ability to scale as data and
technology demands increase. Specialist managed service providers
can also alleviate resource costs and technology debt.
Data management is critical for supply chain optimization. While
many organizations have potentially insightful data, now is the
time to focus on implementing a strategic framework (investing in
projects and solutions that can improve data integration, quality,
and transparency), so you can confidently harness these data assets
and adapt quickly to evolving supply chain environments.
