What are the most innovative supply chain coordination strategies?

Blockchain is the ideal technology to implement trace and track-solutions in industries which require full traceability amongst various participants in the supply chain, e.g. Aerospace. It helps to enforce trust between the participants and makes documentation of transactions between those participants not only easier but also helps to do it in a paperless and more sustainable way.

Three points to ponder: Block chain governance is a critical element as firms have to decide on whether to be part of public or private blockchains or hybrid ones. Besides, global businesses require government regulations and interactions with regulators - so how to ensure completeness of the blockchain chain. Thirdly, blockchain technology forms the foundation of Smart Contract- thus, to what extent contract automation would be feasible for supply contracts .

The supply chain innovative approaches include: 1. Internet of Things 2. Blockchain Technology 3. AI and machine learning 4. Autonomous supply chain decision making 5. Autonomous vehicles and Drones These innovative strategies are continually evolving, and their adoption depends on a company’s specific needs, goals, and industry. Implementing the right combination of these approaches can significantly improve supply chain coordination and performance.

Blockchain is an interesting use case for supply chain coordination and traceability..It's immutable property makes sure data is not tampered with about the products and Metadata on routing.

The most innovative supply chain coordination strategies employ intermodal transport for versatile shipping, blockchain for transparent and secure data exchange, AI for predictive analytics and decision-making, IoT for real-time monitoring, autonomous vehicles and drones for efficient last-mile delivery, and robotics for streamlined warehouse operations. These technologies collectively improve efficiency and responsiveness within supply chains

One of the most critical aspect is end to end visibility of supply chain - from supplier's supplier to buyer's buyer. Slow innovation in this space can be attributed to lack of single ownership for end to end demand and supply view, conflict of interest amongst various supplier levels, complex licence mechanism etc. An over-arching control tower giving a view of end to end demand supply encompassing multiple parties of competing priorities is the key here. The benefits can be many e.g. better cost, inventory accuracy, wastage reduction, accuracy of demand forecast, and others. The impact of these benefits will be enjoyed by all parties by simply being part of that ecosystem. With AI this should become a reality soon.

The Aerospace industry for example is moving more and more into ecosystem-based coordination and collaboration between OEM their Tier-suppliers. thyssenkrupp Aerospace is a leader in the development, implementation and management of Global Control Tower solutions. These solutions improve the visibility along the supply chain and therefore increase its resilience. Eco-system based coordination and collaboration help to reduce the negative impact of the ?bullwhip effect“ as participants in the supply chain align their inventory management and production capacities amongst each other.

From my perspective, this strategy provides an adaptable framework beyond mere transactional relationships. It helps cultivate a culture of joint problem-solving and shared opportunity. By engaging in co-creation, co-investment, and co-sharing of risks, companies can unlock synergies. These collaborative endeavors often result in accelerated innovation, as ideas flow more freely within a trusted ecosystem. Furthermore, the shared governance structures and aligned incentives make it easier to adapt to market shifts or disruptions quickly. For example, using shared dashboards can enable real-time decision-making based on collective insights, making the entire supply chain more resilient and agile.

Especially the Aerospace industry is to benefit from data-driven collaboration and increased visibility in the supply chain among the various participants. Global Control Towers, which include Machine Learning components to improve forecasting accuracy and developed by thyssenkrupp Aerospace are being adopted more and more as state-of-art solutions in the industry. The benefits are a better allocation of resources and capital, higher forecast accuracy, better risk mitigation strategies and a shortened reaction time to unforeseen events.

This strategy is a must for any supply chain aiming to thrive in today's brittle, anxious, nonlinear, and incomprehensible (BANI) environment. What sets data-driven coordination apart is its ability to turn large volumes of disparate data into actionable insights. The impact of harnessing advanced analytics, AI, and machine learning can be monumental, not just for operational excellence but also for strategic foresight. Real-time visibility and predictive capabilities allow for agile responses to market dynamics while pinpointing innovation opportunities that might go unnoticed in a traditional setting. The strategy extends beyond mere operational efficiency to identify new market trends, consumer behaviors, and even potential disruptions.

From my perspective Machine learning (ML) based predictive/prescriptive models offer a wide range of use cases for strategizing supply chain coordination. These models can help optimize various aspects of the supply chain, leading to cost savings, improved efficiency, and better decision-making. Few use cases would be; 1. Multi-Echelon Inventory Optimization - Coordinate inventory decisions across multiple echelons in the supply chain, taking into account demand variability & lead times. 2. Network Design and Optimization - Optimize the design of the supply chain network, including the location of warehouses, distribution centers, and manufacturing facilities, to reduce costs & improve efficiency. 3. Risk Management & Resilience Planning

It is absolutely essential to incorporate and harness the power of data-driven decisions, for any manufacturing-based industry. Understanding the patterns in data can help businesses bridge the gap with their customers.