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Handling the disruptions and constraints that impact multi-tier supply chains

O9 blog industrial transportation july28
Published: August 20, 2021Reading time: 5 min
aim10x Digital Transformation Community
aim10xDigital Transformation Community
Published: August 20, 2021

The industrial sector has faced a multitude of uncertainties across the supply chain network—from Covid to commodities shortages—but still faces immense pressure to deliver materials and finished goods despite disruptions seamlessly.

During the Supply Constraints: Manage your Multi-tier Supply Chain Effectively webinar, addressing the issues currently impacting industrial manufacturers sparked a lively discussion from:

  • Knut Alicke, Partner at McKinsey
  • Dr. Frank Stegherr, Senior Vice President Supply Chain Management & Logistics at Schaeffler
  • Stephan de Barse, Executive Vice President at o9 Solutions
  •  Koen Jacobs, VP Industry Solutions at o9 Solutions

The group spoke about the current semiconductor shortage as an example catalyst that outlines the need for greater data-driven transparency across multiple-tier supply chains to address emerging disruptions—even before companies are affected by a shortage or crisis.

“The semiconductor shortage is something that happens every now and then, and there have been monitoring systems around it,” says Knut Alicke. “As things go back to normal when we solve the capacity problem, then we don’t need to have these systems right? Then there’s the next crisis and we’re not fast enough [to respond.] So, in an ideal world, we would have perfect visibility—not only into your suppliers, but also our second-tier, third-tier, and fourth-tier suppliers and their capacity situation, inventory situation, and logistics.”

Leveraging knowledge modeling to gain upstream visibility

Currently, many organizations are using planning models that focus solely on their own organization and their first-tier suppliers. Collaboration with first-tier suppliers is often highly transactional, with limited trust between parties. Additionally, many OEMs' planning and procurement teams manually collect supplier data to assess excess or limitations around capacity. In addition to being time-consuming, this method doesn’t necessarily account for constraints impacting their upstream suppliers, directly affecting the organization’s production capabilities. To gain greater visibility into supply chain constraints, industrial manufacturers must use this aggregate data to find greater insights into emerging multi-tier supply chain issues and respond proactively. In short, they need a knowledge model.

A knowledge model captures all relevant multi-tier demand and supply constraints such as forecasts, orders, (supplier) capacities, (supplier) inventories, etc., and provides relevant―and sometimes hidden―insights into the relationships between each node. A next-generation knowledge model, such as o9’s Enterprise Knowledge Graph, is ideally suited for user-friendly and scalable OEM-supplier collaboration.  Due to its flexibility and extensibility,  the model can be continuously updated with relevant information such as demand signals, supplier capacities, supplier constraints, and external data sources such as market information, commodity prices, etc., while still performing at a high level (e.g., no more three-day batch runs). 

With a knowledge model, industrial manufacturers can sense disruptions and opportunities in real-time, gain immediate insights into the impact and implications of these disruptions, collaborate on multiple resolution scenarios, and enable continuous learning through collaborative post-game analysis. Furthermore, manufacturers can leverage the knowledge model to proactively sense future disruptions, determine the best approach to managing inventory of critical components, and, if needed, find alternate suppliers. 

Building greater trust within a supply chain network

Another theme within the webinar was the need for greater trust and sharing of information amongst all partners in the supply chain. OEMs may be hesitant to divulge specific data with suppliers and vice versa, but sharing aggregated and up-to-date data would provide the visibility needed to address potential supply chain constraints and strengthen the relationship between an OEM and a supplier. 

Dr. Frank Stegherr mentioned that it’s common for automakers to be in regular communication with their parts suppliers to stay updated about potential delivery delays. But this type of communication becomes more challenging with second and third-tier suppliers further down the supply chain. To foster greater trust with upstream suppliers, Knut Alicke suggests manufacturers start by collaborating very closely with first-tier suppliers and, where possible, leverage their relationship with second and third-tier suppliers as a means of building greater trust throughout the entire supply chain. Another idea would be to create an independent platform that collects the needed data to inform all key stakeholders of supply chain issues and mask any sensitive supplier/manufacturer data. This communication and knowledge sharing enables better planning decisions across the industry while creating a supply chain that can respond to disruption more effectively (and, ideally, infrequently).

Overall, the benefits of knowledge models go beyond proactive planning and trust building. It allows for greater visibility into a supply chain network by connecting OEMs and suppliers on one source of truth, leading to better relationships with suppliers and a shared trust that is critical in times of crisis. “Just understanding each other… so, do I really understand how the others [within my supply network] work, how they have to work, and how do I have to deal with their challenges?” says Dr. Stegherr. “So, it’s a question of trust, it’s a question of technology, but it’s also a question of do I understand the [supplier’s] challenges and differences of processes on their end?” 

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