Why IoT Is Not the Answer When It Comes to Supply Chain

Global supply chain disruption costs the average large business $182 million a year – despite the deployment of more than 10 billion Internet of Things (IoT) devices worldwide, which are constantly adding data to already overflowing data stores. The problem is not a lack of data, which is why IoT is not the solution.

At the heart of the problem is the fact that a supply chain has numerous stakeholders operating in different jurisdictions, across multiple enterprise platforms and often in several languages. Creating effective connections between them is the real challenge.

With goods moving between different physical locations and a variety of independent stakeholders, achieving visibility of every part of the supply chain is difficult. It is comparatively simple to digitize a factory – everything is under one roof and controlled by one organization. However, an entire global supply chain is a very different matter.

Mobile devices are often seen as a potential solution when fixed infrastructure is too expensive and impractical outside of a stakeholder’s internal network. They are not only expensive but costly to maintain. Although mobile devices could offer truly remote monitoring, they would have to be retrieved after use, which significantly limits their operational use in a complex supply chain involving multiple different organizations.

The data to achieve the granular visibility required is present across the supply chain today. However, data is fragmented across many siloed systems, each owned, operated and controlled by many independent organizations. The real challenge is twofold: How can businesses access the data they need when much of the data is fragmented across myriad systems being used within a supply chain – and how can that data be used to drive action?

Data Mesh Technology

New “data mesh” technology is now providing a breakthrough, making it possible to harness data across the supply chain for true cross-stakeholder visibility to unlock valuable benefits.

Data mesh is based on distributed architecture for analytical data management and enables end users to easily access and query data where it lives – without first transporting it to a data lake or warehouse. Data ownership is distributed to domain-specific teams that manage, own and serve the data as a product.

The aim of data mesh is to eliminate the challenges of data availability and accessibility at scale. It allows business users and data scientists to access, analyze and use business insights from virtually any data source, in any location. Data becomes accessible, available, discoverable, secure and interoperable.

Using the distributed architecture approach of data mesh, data from multiple supply chain systems can be captured and combined to create a “digital twin” of a consignment, providing a single data product from which all stakeholders can get the visibility they need.

Intelligent data orchestration is then the secret to success for the supply chain. Just like in a traditional orchestra, a “conductor” takes center stage and synchronizes all various data inputs, applying analytics to enable end-to-end visibility and automation as goods move between stakeholders.

Each separate system communicates directly and only to the conductor platform, removing the need for numerous discrete connections and maintaining data integrity. The conductor ensures only relevant data is captured from connected domains, which maintains privacy across the various organizations. The platform can handle inputs from multiple sources and is scalable, secure and robust.

Digital twins within the platform combine data from systems such as order management, warehouse management, transport management and telematics systems to deliver rich data products that include consignment data, inventory, value, documentation, allocated transport and even the scheduled route.

Data from GPS trackers in delivery vehicles is then dynamically added to provide real-time location updates for each consignment. These updates can be distributed to key stakeholders across the network and, when recorded, build a life-cycle record for each consignment, paving the way to process automation. Over time, these records also highlight any bottlenecks in the system so that remedial action can be taken.

With the movement of goods from a supplier to a customer via a third-party logistics supplier, typically involving at least three warehouses and two transportation legs, it is no surprise that communication is often poor, and time is wasted on administration and chasing up consignments. Yet businesses often rely on partners to handle their logistics. This means they are leaving the face-to-face relationship with their customer – including communication of critical events – to a dispassionate third party.

Connecting all stakeholders and their systems improves communication, thus reducing disputes and saving time. It also enables businesses to control their own communications with their customers, which allows for branding and customization.

A New Route for Data

Intelligent data orchestration with digital twin technology is key to ensuring businesses can actually use the data they can access. It deals with the challenges regarding different data types, structured and unstructured data, and differing latencies and methods of communication, all of which are inherent in using data across many systems.

Using digital twin technology as a framework to capture, collect and use data helps businesses create a foundation of new data products to build on. Given that 50% of a typical data project is absorbed by time spent cleansing and structuring data, this new approach to creating firm data foundations will unlock speed and agility and, critically, pave the way for future data-driven applications.

Adding IoT into a system or operation will provide new data. However, given the challenges businesses face harnessing the huge volumes of data they already have, this approach without a core underlying data strategy is likely to simply perpetuate the problems businesses already face.

The increasing complexity of supply chains is making optimization more challenging than ever, and the cost of inefficiencies is growing. Research suggests that businesses with optimal supply chains can halve their inventory holdings, reduce their supply chain costs by 15% and triple the speed of their cash-to-cash cycle. Data mesh and intelligent data orchestration are now providing a new route to unlock supply chain value and deliver competitive advantage.