The future of supply chains will be shaped by cloud-enabled ecosystems

Dr. Adrian Reisch
October 22, 2021
future of supply chains

We live in a changing world, where in the future, supply chains will no longer be managed in a linear fashion, as suggested by the SCOR model of Source-Make-Deliver chains. In this article, we present our vision for the future of supply chains and the topics that will determine their competitiveness. The future of supply chains will be characterized by growing business networks and cloud-enabled ecosystems. Companies will be members in multiple ecosystems and may play multiple roles. For instance, an OEM could act as a supplier, an engineering contractor, and a participant in a marketplace he has created with competitors.

What changes with digital ecosystems?

Digital ecosystems do not work linear; they form flexible networks. They are much more agile than traditional supply chains and form new relationships and structures. Information can be shared flexibly between all members via cloud-based IT systems, enabling seamless collaboration between network members. New hybrid forms of collaboration and competition - coopetition - will emerge from the cloud-enabled network, defining new ways of doing business and delivering value to customers.

Digital ecosystems require new types of management. Conversely, they also enable new management processes and structures through cloud-based infrastructure. End-to-end transparency, product architecture and portfolio management, circular and sustainable supply chains, master data excellence, automation & supply chain as a service and closed-loop performance management are new management paradigms for the future of supply chains to stay competitive in an increasingly VUCA world.


Management of flexible and reactive supply chain ecosystems requires end-to-end transparency.

The future of supply chains will be characterized by growing ecosystems of different players. OEMs, suppliers, contractors (production, logistics, engineering, etc.), competitors, connectors, customers will collaborate, supported by a digital, cloud-based infrastructure. These networks can adapt flexibly to changing conditions, new requirements, and opportunities. Network structures are superior to static structures in terms of agility and resilience.

To manage supply chain ecosystems, end-to-end transparency of master data structures, demand and supply situations, and inventories must be achieved. Optimizing costs, resolving bottlenecks, responding to risks, and establishing compliance in a supply chain ecosystem require data about operational processes, ideally in real-time. A supply chain digital twin connects to the operational and planning systems of the players in a supply chain ecosystem and builds a digital model of the current supply chain situation. A supply chain control tower uses this model to control the supply chain's operational processes, manage the cooperation of the players, and detect deviations, events, and risks at an early stage.

Supply chain analytics is needed to get end-to-end transparency across the ecosystem, enabling all participants to make informed and optimized decisions collaboratively with all other members of the network. Analytics tools like AIOinsights offer you a deep dive into supply chain improvement areas and automated generation of findings, which make issues explicit and help you understand the physics of your supply chain, and create end-to-end transparency.

Product architectures and portfolios need to be adapted to business opportunities in the ecosystem.

A supply chain ecosystem provides new opportunities to optimize product structures and the portfolio. Changing demand structures also impose new requirements. Increasingly individual and volatile demand drives the shift from classical towards an agile product portfolio management that quickly reacts to business cycles in a VUCA world. Supply Chain Segmentation aligns a portfolio of products, customers, and suppliers while harmonizing internal processes or policies. Segmentation enables serving different customer channels through dedicated and tailored supply chains.

Modular product structures lead to a higher degree of reuse and simpler supply structures while at the same time expanding the variety of products and offerings. Ecosystem partners may take over-engineering or production, while assembly and logistics may be outsourced to other partners.

In the supply chain of the future, product portfolio management is shifting towards ecosystem portfolio management based on coopetition, including startups, material, software, and service supplier as well as competitors, aligning their offerings and forming a joint system of product portfolios. This will achieve a broader functional offering, more flexibility and agility, lower costs, and a faster time-to-market.

The cloud-based infrastructure of the supply chain ecosystem provides new ways of collaboration. For instance, product lifecycle management systems and 3D-CAD systems in the cloud support joint product development and product data exchange. Internet-of-things applications connect smart products with systems to analyze how customers use products and provide insights into the optimization potential of complex product architectures and portfolios. AI-based applications like AIOintelligence identify similar products and product structures, indicating opportunities for rationalization.

Supply chains need to become more circular and sustainable, reusing materials and avoiding waste and pollution.

Supply chains are the largest consumers of natural resources and energy. The way supply chains are managed needs to change to reduce pollution and waste and reduce the carbon footprint. Circular supply chain structures will help reuse components and materials from used products instead of making products completely from new components and raw materials. Sustainable processes in the supply chain avoid waste and environmental pollution - e.g., inferior quality, excess inventory, rush shipments - and ensure respect for human rights, good working conditions, and fair payment for suppliers. A regionalization of supply chains additionally improves sustainability but is also inevitable when assessing the risks of globally integrated asset networks.

Cloud-based ecosystems directly support the building of circular and sustainable supply chains. Through the transparent network structure, information can be transferred directly from suppliers to customers, unnecessary production is avoided, an effort is saved on transports, and quality problems are quickly identified and rectified. Through end-to-end transparency, the carbon footprint is continuously monitored, and operational processes are optimized to avoid emissions and save energy and resources.

Supply chain analytics systems like AIOinsights are used to create end-to-end transparency, monitor the supply chain constantly, and identify sources of waste and pollution. AI-based algorithms like those provided by AIOintelligence may be used to optimize operational processes, create better forecasts, and identify patterns where circular supply structures may be established.

Master data from different sources need to be linked consistently, providing a semantic layer for the ecosystem.

Consistent and accurate master data is a prerequisite for any decision support and optimization system in supply chains. Master data describes products, suppliers, bills of materials, routings, customers, supply relationships, inventory and planning policies, delivery times, yields, and many other operational parameters in supply chains. In a cloud-based ecosystem, master data is managed overlappingly in many systems; each company typically has a central system where essential master data is maintained.

At the same time, material numbers and designations are often distinct, so a common semantic layer is needed. This layer is pronounced based on the cloud-based infrastructure of the ecosystem and enables AI algorithms to recognize synonyms and relate different master data related to the same objects in the supply chain. This creates a uniform semantics of master data in a supply chain.

AI-based algorithms, such as those from AIOintelligence, support the identification of synonyms, generation of uniform classification schemes and hierarchies, and correction of inconsistent and erroneous master data in the network. The result is a uniform language for all companies involved in the ecosystem and seamless and lossless communication based on uniform master data semantics.

Cloud-based ecosystems enable the automation of planning and decision-making processes.

The integration of all parties involved in the supply chain ecosystem via the cloud-based infrastructure and the unified semantics layer enables the automation of many planning and decision-making processes in the supply chain. For example, machine learning-based algorithms can largely automate forecasting processes; about 20% of the products still require further planning by humans; the rest is planned automatically.

In supply planning, bottlenecks can be identified automatically by integrating all companies involved in a supply chain, and suggestions for eliminating the bottleneck can be generated. Rule-based systems help prepare the decision for one of the options. The determination of inventory parameters such as safety stocks, minimum order quantities, and reorder points can be determined automatically by optimization methods. Machine learning-based algorithms are used to monitor the quality of the planning results and to learn from deviations.

Future competitiveness will be driven by supply chain as a service from providers with top expertise.

These automated processes require continuous monitoring, parameterization, and adaptation. If an automatism delivers poor results, the causes must be analyzed and appropriate countermeasures initiated. This requires experts who have mastered the underlying algorithms (e.g., machine learning or operations research) to be supply chain experts and be familiar with the data structures used - e.g., time series or order networks.

In industrial companies, such experts are often challenging to recruit and utilize permanently. Furthermore, experts who work on the supply chain of only one company do not have experience from other situations and therefore cannot transfer expertise. For these reasons, we are convinced that complex mathematical methods for optimizing supply chains in conjunction with expertise in cloud technology will increasingly be provided by service providers in the future, especially planning and fact-based decision making such as:

  • Supply chain planning as a Service
  • Product availability & allocation as a Service
  • Sales & operations planning as a Service

Digital execution systems close the loop from decision making and execution to continuous improvement of the supply chain.

All aspects of the future of supply chains discussed so far generate decisions and measures for tactical optimization of supply chain structures and processes. End-to-end transparency identifies supply chain performance gaps and areas for improvement that need to be executed. Optimization of the product architecture and product portfolio also requires tactical decisions and measures. The same applies to the introduction of circular and sustainable supply chain structures and processes. Master data corrections and the introduction of automated optimization algorithms also require tactical decisions. Today, tactical decisions are managed and executed manually after making them - e.g., via Excel and email.

This approach brings two types of problems: First, the employee in charge of the execution is not digitally supported during the execution of the necessary steps. Secondly, it is not possible to receive valuable feedback on the success of the measures, and therefore we cannot learn from the situation. A digital execution system like AIOimpact is required to support the management of tactical decisions in the network and the continuous improvement in the network. The more companies participate and are integrated via the cloud-based infrastructure, the more powerful digital execution management will be.

The future of supply chains will feature the continuous improvement of all operations across all functions and participants in the ecosystem. It will allow for closer integration, better collaboration, as well as avoidance of waste and losses to boost the supply chain performance.

To determine the influence of the VUCA world and the current and target maturity grade of these topics in industrial companies, we are carrying out a survey: The Future of Supply Chains - how to stay competitive in a VUCA world?

Participate in the survey and get a chance to win an inventory analytics on-demand bundle!

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Dr. Adrian Reisch


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