Digital Transformation of Supply Chain through IoT, Analytics and Automation
The increasingly fast paced and competitive landscape of products and services have necessitated innovative approaches for managing logistics and supply chain. Logistics pertains to distribution and organization of products within an organization. It includes warehousing and transportation and is considered part of the overall Supply Chain. Visibility and robust tracking of raw materials, components, and manufactured goods to distribution warehouses is a great use case for business value from IoT/IIoT – especially with analytics and automation of end-to-end supply chain value streams. In the top use cases of IoT/IIoT application areas Supply Chain DX is perhaps second only to Digital Prescriptive Maintenance. In fact these two use cases are interrelated, as replacement parts for maintenance typically involve supply chain processes.
How important is Supply Chain? Consider this. About 30% of the world’s food production is wasted in the supply chain! That is just the food industry. All industries and large discrete or process manufacturing organizations rely on efficiencies in their supply chain.
The combination of connectivity (Internet of Things or more specifically Industrial Internet of Things) together with analytics for predictions as well as automation of the end-to-end value streams is poised to improve and disrupt Supply Chain.
First and foremost supply chain is a value stream that starts with a supply chain strategy all the way to the ultimate retirement or recycling of the product. There are many stages in between. There are risks in supply chain, as we have described in the Adaptive Digital Factory.
One needs to look no further than the evolution of supply chain capabilities to see how manufacturing is becoming digitally connected. Digitization of the supply chain through monitoring, connectivity, and end-to-end automated dynamic cases has provided many new opportunities to optimize the supply chain processes.
With the emergence of additive 3D printing for “social” manufacturing, optimization within supply chain management is critical. Companies rely on the timely supply of material or 3D components in order to produce at increasingly demanding service levels. Any disruption to the supply chain has a negative impact.
From a financial perspective, costly disruptions may result in overstocking, underproduction, waste, and, ultimately, the visibility into the supply chain from end-to-end. For that reason, disruptions in the supply chain represent a significant risk for the company. Even in steady or “happy” transactions there are enormous opportunities to optimize the efficiency of processes in transportation and movement of goods and services through digitized dynamic cases and processes. Transportation and asset movement transactions tend to be paper intensive and manual.
In order to minimize that risk, companies must identify the sources of the disruptions – especially the catastrophic ones.
Disruptions in Supply Chain
As indicated in the Adaptive Digital Factory, some of the critical sources of supply chain disruptions include:
- Weather (unforeseen weather impacts, e.g., hurricanes)
- Civil unrest (e.g., protests)
- Labor union challenges (e.g., ports labor disputes)
- Fuel prices (e.g., unwarranted hikes in the rates)
- Vendor market status (e.g., hostile takeovers of suppliers)
In order to minimize disruption risks, data is mined and transformed into information used to take mitigating actions. These “mined” actions are automated and executed through end-to-end dynamic cases spanning the entire supply chain. This data can be gathered from a plethora of sources, including online through social media and other sources. More importantly, the insights gathered from this data need to be operationalized and acted upon.
The predictive models, sensor (IoT) events, and business rules for optimized supply chain execution are all automated and operationalized through dynamic case management. Digitization spans the extended manufacturing digital enterprise, including OEMs, parts suppliers, logistics, and transportation, to name a few.
- Supplier Analysis and Management: optimizing the end-to-end supply chain through analytics
- Inventory Management: measuring depleted inventories, predicting inventory needs and automated counting
- Movement of the goods: location (using GPS of the truck, train, ship, plane, container or the individual good itself), status of the connected goods (such as temperature for goods that could potentially spoil)
Supply Chain DX with IoT/IIoT + Analytics + Automation
Internet of Things (IoT) connectivity of products, logistics, and transportation, especially within the context of digitized value streams, generates concrete business benefits through supply chain optimization. As we have discussed in the Supply Chain post of the Adaptive Digital Factory series, these benefits include:
- Just-In-Time (JIT) Inventory Management: By leveraging digital transformation platform capabilities with IoT connected devices, manufacturers are finding new ways to optimize inventory levels and improve efficiencies and quality. From consumer purchases in retail stores or wholesalers, all the way to parts suppliers, JIT management of inventories is becoming a reality. The digitally extended enterprise can function as an efficient and optimized pipeline of connected parts and supplies.
- Just-Needed Visibility: IoT connectivity spans manufactured devices and inventories of these devices, as well as the logistics and transportation of these devices: connected transportation vehicles as well as connected transportation. What this means is that supply chain inventory management has complete visibility on the entire chain of parts, from source to production. The very nature of work and automation is being transformed with increased visibility.
- Just-Desired Innovation: Innovative technologies such as additive 3D printing for “social” manufacturing, is transforming manufacturing and impacting traditional part sourcing and provisioning models. As discussed in depth in the Adaptive Digital Factory eBook, innovations in robotics and automation on the shop floor are also having a transformative impact on manufacturing.
- Just-Required Collaboration: Supply chain requires collaboration between different parties in the entire ecosystem of manufacturers. From suppliers, to manufacturers, to distributors, to customers, digital technologies such as the cloud, social interactions, and Dynamic Case Management are allowing all these parties in the value stream to collaborate in end-to-end digitized value streams.
- Just-Predicted Mitigation of Risk: In order to minimize the risk of disruption, data is mined and transformed into information used to take mitigating actions. These mined actions are automated and executed through end-to-end dynamic cases spanning the entire supply chain. Supply chain leaders need algorithms that learn, adapt, and become more accurate at predicting with more information.
One interesting emerging technology that might provide promising infrastructure for Supply Chain is Blockchain. I alluded to this in a recent post. As organizations in the end-to-end value stream for supply chain cooperate and collaborate Blockchain can be a promising backbone for three essential categories of exchanges or flows: contractual flow, logistics (movement of goods and material) flow and of course being the foundation of cryptocurrency, the financial transaction flow.
So in conclusion, digitizing the supply chain is both innovative and inevitable. The predictive models, business rules, machine learning from sensor (IoT) events, emerging backbones such as Blockchain, and automation through Dynamic Cases and Processes are the core enablers of digital transformation in supply chain execution. Digitization spans the extended manufacturing digital enterprise, including OEMs, parts suppliers, logistics and transportation. Most importantly, it optimizes the customer experience with timely and high quality innovative products.