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.

Marex Media