Supply chain visibility is a key focus area for many organizations. Therefore, it’s no wonder that visibility, monitoring, analytics, and forecasting tools continue to be at the top of the list when it comes to supply chain technology investments.
Despite companies understanding the importance of visibility and investing in tools to improve it, the results have not been great. According to one study by PwC, 69% of operations and supply chain officers say that their supply chain technology investments have not delivered the expected results. Other studies have pointed to similar findings about the gap between expected and realized ROI for supply chain tech.
On top of this, another study found that only 12% of supply chain leaders believe that their investment strategy fully meets the needs of their supply chain. So, what gives? Why are most organizations failing to reach their goals, and what can be done to change course?
Varying definitions of supply chain visibility can distort expectations
It is good to recognize that the term supply chain visibility can mean different things to different people. Definitions vary from being specific to, for example, shipment tracking to covering ambiguous monitoring of all supply chain processes across multi-tier networks. To some, it means visibility into supplier inventory for planning purposes. Others may use the term when discussing the availability of supplier sustainability information.
Each organization has their own challenges and priorities that focus the conversation around visibility on specific areas. Yet, if you ask two people in distinct roles even in the same organization, they will likely give you different definitions of what supply chain visibility means for them.
When discussing ROI of supply chain visibility solutions, this diversity of definitions can lead to misalignment between expectations and what is realistically achievable in each situation. However, despite the diversity, we can identify some familiar challenges across the distinct types of supply chain visibility use cases.
Three key challenges around supply chain visibility
The first challenge is availability of data. Digitization has come a long way. However, there are still substantial gaps in capturing structured data on different supply chain processes. This means the available data only partially covers the real-world supply chain activities.
The second challenge faced by most companies is access to data. Even when processes are digitized and data is available for analytics, it may only be accessible for a specific function. For example, if the data from a logistics control tower is only available to the logistics team and not to procurement, sourcing, planning or customer fulfillment, these other teams may have gaps in their understanding of what is really going on in the business.
Finally, even when data is both available and accessible, companies often have challenges around the quality of data. Doing traditional analytics based on incorrect data is counterproductive. However, proliferating the use of incorrect data through AI algorithms can be downright catastrophic to the business. Therefore, the more advanced capabilities an organization is looking for, the more important data management, quality control and governance capabilities become.
Addressing these challenges requires an innovative approach to supply chain visibility
It’s great that companies understand the value of visibility and are investing in tools to improve it. However, addressing the challenges around availability, accessibility and quality of data will be the key to achieving their goals.
Digitize supply chain processes to make supply chain data available
Availability of data is intricately linked to digitization of supply chain processes. This often requires capabilities such as a modern integration solution. It means that an essential part of improving supply chain visibility in each area is reviewing existing processes and tools around capturing and exchanging data and addressing any gaps that limit visibility. Depending on the desired scope, this can also mean examining the order-to-cash or purchase-to-pay processes, logistics, data flows, or other areas in the supply chain.
Leverage data-centric solutions to make supply chain data accessible
Addressing challenges around data access requires an original approach to analytics. Organizations associate traditional visibility with siloed, application-centric thinking where business applications—such as TMS, WMS, ERP, CRM, and e-procurement platforms—are the main source of data. They tend to limit access to separate analytics tools aggregating data from multiple systems to the team they were built for.
In contrast, companies should leverage a data-centric approach, where the supply chain analytics data is stored in a shared data hub, and function or role specific views are created on top of this central data repository. Supply chain command centers are an emerging approach typically leveraging this approach.
Deploy comprehensive strategy to ensure the quality of your supply chain data
Finally, issues with data quality are perhaps the most challenging to tackle and require a multifaceted approach combining robust data management and governance practices and tooling. Depending on the desired scope, organizations may need different forms of data validations, process controls, master data management, and other capabilities to ensure that the insights delivered are accurate and reliable.
And as with any investments, clear definitions of scope and quantifying the impacts on supply chain operations will help guide the path forward. Without clear focus, supply chain visibility projects can turn into an attempt at “boiling the ocean” where confusion reigns between stakeholders and expectations fall far short of what was expected.
Find out how OpenText can help digitize your supply chain processes and improve visibility.
