At the same time, the research also makes clear that ambition and vision are not enough.

The orchestration gap

Nearly half of the executives surveyed by IDC recognize the substantial benefits of end-to-end orchestration鈥攂ut many have yet to take decisive action. The true challenge lies not in understanding its value, but in bridging the gap between strategic intent and effective execution.

IDC surveyed C-level leaders across industries and regions. The message was consistent. Leaders understand the destination, but they want clearer guidance on the blueprint to execution. As the IDC white paper said, 鈥淎 majority of executives see value in an orchestrated supply chain and believe they must move in that direction, yet the precise steps are unclear, and they are not sure where best to start鈥攖hey need help.鈥�

That tension is familiar. Many organizations have made progress in operational silos, but far fewer have connected design, planning, procurement, manufacturing, logistics, and service into a truly coordinated operating model.

What orchestration really means

An orchestrated supply chain connects people, processes, and technology to provide agility and deliver continuous improvement, despite persistent disruption. Agentic AI is fundamentally reshaping orchestration, enabling systems to analyze, decide, and coordinate across functions in real time. From sourcing and procurement to planning, manufacturing, logistics, and delivery, the focus shifts from optimizing individual functions to achieving enterprise-wide alignment.

Traditional linear supply chain models were built for a more predictable world. Today鈥檚 reality is different. Geopolitical uncertainty, AI-driven disruption, climate pressures, regulatory complexity, and rising customer expectations are constant. Decisions made in one area now ripple quickly across the rest of the supply chain.

Orchestration addresses this reality by establishing a shared foundation of contextually relevant information, designing processes to operate together, and enabling systems that support end-to-end decision-making and execution. Technology plays a critical role, but orchestration ultimately depends on organizational alignment: clear roles, shared metrics, and coordinated processes. Instead of optimizing planning or execution in isolation, orchestration evaluates trade-offs based on their impact on the entire supply chain and the broader business.

Different leaders, shared outcomes

The IDC research also highlights how perspectives on orchestration vary by role. COOs focus on enterprise performance, CSCOs balance transformation with operational demands, and CPOs emphasize cost and risk exposure in direct materials, including mitigation strategies. Orchestration must deliver value across these perspectives while maintaining a unified, end-to-end view.

This diversity of perspective reinforces why orchestration matters. Success comes from respecting functional priorities without allowing silos to drive disconnected decisions, enabling coordinated decision-making that optimizes the whole, not just the parts.

Efficiency and agility, not trade-offs

Many executives perceive a trade-off between efficiency and preparedness, but orchestration changes the equation. With integrated data, shared context, and agile tools, companies can respond faster, reduce disruption response times, and make informed trade-offs鈥攄emonstrating that agility and efficiency can reinforce each other rather than compete.

As one procurement leader told in the IDC white paper, 鈥淲e have to be able to be both resilient and efficient, or at least be able to make informed trade-offs quickly. Right now, we have neither the necessary supply chain integration nor agile enough tools to be able to do that.鈥� Without integrated supply chains and shared context, that balance is difficult to achieve. When companies can identify issues earlier and respond faster, recovery times shrink, translating into lower costs, less expediting, and more reliable customer service.

The role of agentic AI

Agentic AI is emerging as a practical, transformational path to supply chain orchestration. AI-driven agents can monitor signals, evaluate scenarios, and recommend or initiate actions within defined guardrails. Across 麻豆原创 customer environments, AI delivers value in supplier onboarding, predictive maintenance, and rapid rebalancing of inventory or capacity. Leaders generally prefer AI as an advisor rather than a fully autonomous decision-maker, reflecting the continued importance of human judgment, accountability, and experience. Orchestration works best when AI strengthens decision-making while keeping people firmly in the loop.

Data, platforms, and the role of 麻豆原创 Supply Chain Management

Effective orchestration requires more than connectivity, it depends on harmonized data, coordinated processes, and contextual intelligence embedded where work happens. As supply chains extend across multi-tier supplier networks, logistics partners, and service providers, the challenge is no longer access to data, but making data usable, contextual, and actionable at scale.

The IDC research underscores that true end-to-end orchestration must span both internal operations and external ecosystems. Much of the most critical information鈥攔isk signals, capacity constraints, execution status鈥攍ives outside the enterprise. Without a common data foundation, organizations struggle to move from insight to action.

This is where plays a distinct role. 麻豆原创 brings together an end-to-end portfolio of supply chain applications, deeply integrated with ERP and line-of-business systems, and connected externally through . Planning, sourcing and procurement, manufacturing, logistics, and service operate as a coordinated system rather than isolated domains.

At the data layer, provides a normalized foundation that can harmonize operational, transactional, and network data. This shared context provides visibility, analytics, and AI. On top of it, embedded and extensible AI鈥攊ncluding agentic AI and Joule鈥攕upports orchestrated decision-making, helping to accelerate time to decision and time to recovery while keeping people engaged and in control.

Turning priority into practice

The move toward orchestrated supply chains is well underway, but progress remains uneven. Only a minority of organizations consider themselves close to full, end-to-end orchestration. Technology alone is not the constraint. Data readiness, clarity of outcomes, organizational alignment, and change management matter just as much.

Leading organizations start with clear objectives, invest in people alongside platforms, and build pragmatic road maps that prioritize time to value. Orchestration is not a single project. It is a progression that evolves as capabilities mature.

At 麻豆原创, our focus is on making orchestration practical and accessible. Through 麻豆原创 Supply Chain Management solutions and 麻豆原创 Business Network, we help organizations align teams, connect processes, integrate partners, and embed AI into core supply chain activities鈥攅nabling better decisions, faster execution, and sustained enterprise impact in a constantly changing world.

Hagen Heubach is chief marketing officer for Supply Chain Management at 麻豆原创.

IDC White Paper, sponsored by 麻豆原创, Orchestrating the End-to-End Supply Chain: Strategic Priority, Practical Reality, #US54385326-WP, April 2026

As discussed in a new whitepaper, , this perspective is grounded in interviews with supply chain leaders across six industries: automotive electronics and software, agricultural equipment, chemicals, global technology, automotive supply, and home appliances.

Their experiences reveal where companies are investing, where adoption challenges remain, and where the next wave of value is likely to emerge.

Supply chains are entering an era of permanent disruption

Four structural forces are reshaping global supply chains simultaneously: geopolitical instability, economic pressure, demographic shifts, and accelerated digital transformation.

Since 2017, relative to trade among closer partners, signaling growing fragmentation in global commerce. , while labor shortages and digital skill gaps continue to constrain operations.

Europe alone could face by 2028, and 63% of companies cite .

Together, these pressures are pushing supply chains beyond the limits of the traditional 鈥減lan-source-make-deliver鈥� model.

Companies are shifting from optimization to AI-enabled orchestration

Supply chains are increasingly viewed as strategic levers for resilience, service differentiation, and competitive advantage.

Across all six companies interviewed, each is investing in at least three forward-looking AI use cases in planning alone.

• A leading agricultural equipment company has deployed more than 1,000 AI agents to support orchestration, scenario planning, and value chain visibility. A global chemicals company is embedding AI across planning and scenario management while emphasizing explainability and trust.
• A home appliance company is applying AI selectively to improve forecasting, transport optimization, warehouse safety, and logistics costs.

The common theme: organizations are redesigning how the enterprise senses, decides, and acts.

Resilience is now defined by decision velocity

In today鈥檚 fragmented environment, resilience is no longer about static buffers. It is about how quickly companies can convert disruption signals into coordinated action across sourcing, production, planning, and logistics.

• An automotive electronics and software company centralized electronics ordering across roughly 30 plants and redesigned crisis-management processes, reducing disruption response times by approximately 95%.
• A global technology company adopted a regional 鈥渢wo-leg鈥� supply chain model, using inventory strategically to respond faster to disruptions.

The emerging differentiator is not forecast accuracy alone, but the speed from disruption detection to execution. Visibility remains important, but visibility without coordinated action is no longer enough.

Trust and governance are the biggest barriers to scaling AI

Despite rapid interest, . The challenge is not model accuracy alone; it is trust, explainability, fragmented systems, and manual overrides.

• One global chemicals company found that scaling AI depended less on technical performance and more on whether users could understand and trust the outputs. This led to stronger human-in-the-loop governance and progressive autonomy thresholds.
• A major automotive electronics company requires transparent, traceable AI reasoning before planners rely on AI-generated recommendations.

The path to autonomy will be incremental: companies will first augment human decision-making, then automate routine and semi-structured decisions as governance, trust, and data maturity improve.

The next frontier is the Autonomous Enterprise

The Autonomous Enterprise is an operating model where AI workflows, contextual business data, and embedded governance work together to anticipate disruption, coordinate action, and continuously improve performance.

The shift is moving from isolated copilots to coordinated agent-to-agent workflows spanning the supply chain.

In autonomous production environments, supplier reliability agents can monitor vendor risk while workforce orchestration agents align labor capacity with demand. Procurement agents execute sourcing decisions, and production planning agents dynamically rebalance schedules in response to changing conditions.

A similar pattern is emerging in asset management, where alert-processing, maintenance, warehouse replenishment, and goods-movement agents collaborate to resolve operational issues with minimal human intervention.

The business impact is significant. Agentic AI has by 20 to 30%, , and helped .

Collectively, these improvements mark the transition from reactive supply chains to systems that can increasingly anticipate, decide, and execute autonomously.

Building the autonomous supply chain

Capturing this opportunity requires three capabilities that remain fragmented in many organizations today:

• Organizational intelligence: The ability to detect patterns, anticipate risks, and reason across constraints
• Contextual data: Trusted operational data, business rules, workflows, and policies that ground AI decisions in enterprise reality
• Embedded execution: Integrating intelligence directly into workflows so actions can move from recommendation to execution without manual intervention

This creates a virtuous cycle: better data improves decisions, better decisions improve processes, and improved processes generate richer operational data over time.

Importantly, companies do not need to rebuild the enterprise from scratch. Deterministic systems of record remain essential for control, compliance, and auditability. The real transformation lies in rewiring how decisions are made and governed.

Organizations moving fastest are focusing first on high-value, high-frequency decisions such as forecasting, inventory optimization, disruption sensing, transport planning, procurement workflows, maintenance, and customer-service resolution.

The bottom line

The future of supply chain management will not be defined by more digital tools alone. It will be defined by the ability to operate the supply chain as a connected, adaptive, and increasingly autonomous system.

For leaders who move first, supply chain will evolve from a cost-management function into a competitive differentiator, enabling faster time to market, stronger service levels, and greater resilience. The organizations that lead will not be those running the most AI pilots. They will be the ones using AI to redesign how the enterprise senses, decides, and acts across the end-to-end supply chain.

For more information about Autonomous Supply Chain Management, download the white paper, .

Hagen Heubach is chief marketing officer for Supply Chain Management at 麻豆原创.

Imagine streets populated with electric vehicles (EV) and gas stations replaced by EV charging stations at shopping centers and grocery stores. Mobility-as-a-service (MaaS) dominates the transportation landscape, offering鈥痷sers the most affordable, sustainable, and efficient way to get around. Some cars are self-driving and interconnected, talking to each other and sharing their location and next moves.鈥疻hat鈥檚 more, many cars are connected with the ability to send and receive all types of users鈥� data.

To realize this new reality, change will happen quickly, and regulations will only accelerate this transition. In Europe, a package of legislative proposals, 鈥�,鈥� aims to reduce greenhouse gas emissions by 55% by 2030. It includes a policy that requires a 55% reduction of average emissions in new cars by 2030 and a 100% reduction by 2035. In the United States, President Biden set a bold goal that EVs make up at least 50% of all vehicles sold by 2030. Since he took office, automakers announced investments of more than in EV manufacturing and $48 billion in battery production in the U.S. alone.

Add consumer sentiment to the equation 鈥� of global car buyers are looking for an EV 鈥� and it鈥檚 no surprise that carmakers, suppliers, and dealerships recognize the need for dynamic and continuous innovation to be profitable and sustainable.

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In a world of disrupted supply chains, new market participants, digitized factories, and a growing demand from regulators and consumers for sustainable vehicles, automotive businesses are embracing the following five trends to stay competitive.

1. Shifting Gears to Electric

A massive shift to vehicle electrification will require efficient and scalable EV charging infrastructure, ideally on one platform with seamless integration into existing business systems used by automakers, suppliers, and dealerships. It will also change supply chains and the role of parts suppliers as they shift from providing components needed for internal combustion engines to those needed for EVs. To prepare for vehicle electrification, automakers and suppliers can leverage the power of technology to manage charge point infrastructure and interact along the mobility value chain in the cloud to support collaborative, end-to-end business models and processes.

麻豆原创 customer provided the first intelligent, multi-socket charging solution for EVs. It allows multiple electric cars to charge simultaneously. The solution helped ChargeX lower time spent on daily charge-point operations and improve customer satisfaction with intuitive user interface and straightforward, automated processes.

2. Making Cars Smarter

Cars are the next smartphones. As consumers increasingly expect more from their vehicles, automobile manufacturers must find ways to continually enhance vehicle intelligence and connectivity.

Even in the 2020s, software reshapes how drivers interact with their cars. Automation has taken over braking, climate control, cruise control, entertainment, and more. Routine software updates bring drivers continuous improvements,鈥痑dding safety features, better performance, and greater efficiency.

Fully autonomous driving, currently in its infancy, continues to learn and will soon鈥痓ecome a common feature. Like vehicle electrification, regulatory requirements and consumer behavior inspire companies to develop innovative solutions that push the boundaries of automotive capabilities.

One company, , uses flexible and scalable manufacturing solutions from 麻豆原创 to build its fully autonomous, purpose-built vehicle fleet.

3. Considering Mobility-as-a-Service

An uptick in technology-powered smart cities 鈥� spurred by our response to the effects of climate change 鈥� will force auto manufacturers and suppliers to rethink their business models. Communities will reimagine fundamental public services, including transportation, encouraging citizens to swap their vehicles for public and shared transportation services.鈥疘n fact, by 2030, the shared mobility market is expected to exceed .

Mobility-as-a-service platforms offer users an integrated package of transportation options accessible through a single payment channel. These implementations will play a fundamental role in solving urban challenges, reducing congestion, greenhouse gas emissions, and accessibility constraints. Car manufacturers and suppliers can rethink and innovate their product offerings through this modality.

Take the robotaxi by . Passengers request a ride from this driverless taxicab via their smartphones. Zoox robotaxis go up to 75 miles per hour, revolutionizing ridesharing. The application provides the backbone for the robotaxi production.

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4. Prioritizing Operational Resilience聽

Amid the evolving automotive landscape, automakers and suppliers must ensure resilient supply chains are in place to meet changing demand, including increasing requests for EV components, while combating battery and chip shortages. The disruption caused by COVID-19 and the war in Ukraine highlighted the threat external events can have on automotive industry operations. Technology will play an even more critical role in enabling businesses to respond to potential supply chain disruptions.

Real-time tracking and analysis can better forecast supply and demand, fostering a more agile and resilient supply chain. As a result, carmakers, suppliers, and dealerships can respond to the unexpected as soon as it happens, make better inventory management decisions, and reduce waste.

Electric motorcycle company and German multinational manufacturer of EVs and motorcycles BMW teamed up with 麻豆原创 to succeed in the new world of mobility. With real-time information, detailed insights on performance, and analytics to improve decision-making across the manufacturing value chain, Zero Motorcycles and BMW can achieve operational resilience while pushing the boundaries of innovation.

5. Embracing Digital Retail

Due to consumer behavior change accelerated by the pandemic, the automobile industry recognizes the urgent need to adopt a digital-first, omnichannel sales strategy. Car buyers and sellers have started turning to contactless car buying and online dealerships. And even as the world recovers from COVID-19, vehicle retailers see automotive e-commerce searches reaching an as many customers now prefer digital retail experiences for sales, trade-ins, and services.

麻豆原创 partner makes it easier for importers, dealerships, and service locations to adopt digital retail options, optimizing end-to-end sales and service processes. With innovative products for 麻豆原创 S/4HANA, dealerships and service locations can continue to drive sales, deliver services, and meet shifting customer expectations.

Above All: Collaboration Is Key for Future Success

The automotive industry faces enormous challenges. Despite competition in the automotive industry, automakers and suppliers gain critical value through collaboration, particularly in such a dynamic environment for innovation. Catena-X 鈥� as front-runner for the automotive industry 鈥� aims to bring all business partners, including multi-tier suppliers, original equipment manufacturers (OEMs), or recycling service providers, into one network to help ensure an open, secure, and interoperable data exchange along the value chain. The transparency of data helps participants gain visibility into the complete material flow of a product life cycle, from 鈥渃radle to grave.鈥� Utilizing information available in shared digital twins improves decision making for end-of-life vehicles, thus useful parts can be circulated back for refurbishment or reuse and valuable raw materials can be recycled in a more effective way. With , 麻豆原创 can provide software and network services to Catena-X and the automotive industry at large.

Learn how you can 听飞丑颈濒别 that are ready to meet the road ahead with industry cloud solutions from 麻豆原创.

Hagen Heubach is global vice president of Automotive Industry Business Unit at 麻豆原创.
Kelly Cannon is head of Industry Thought Leadership at 麻豆原创.

packages help enterprises gain insights into their product carbon footprint data and identify further potentials in reducing greenhouse gas (GHG) emissions.

Scope 3 Emissions: The Biggest Challenge to Achieve Net Zero

Despite the massive disruptions that businesses are currently facing, climate change remains the most critical challenge that industries must jointly tackle. To achieve the goal of the Paris Agreement of limiting global warming to 1.5掳C — which would reduce the possibility of initiating the most dangerous and irreversible disasters of climate change — net zero CO2 emissions need to be secured globally around mid-century. The European Union (EU) set an even more ambitious target to reach climate neutrality by 2050.

This means, in short term, that GHG emissions need to be reduced by more than 50% by 2030 in order to set a responsible pathway to meet the net zero target.

Although the largest companies have specifically articulated sustainability or carbon neutrality as their strategic goal, few have painted a clear and comprehensive action plan for the transition. Regulations such as the Corporate Sustainability Reporting Directive (CSRD) or new rules proposed by the United States Securities and Exchange Commission (U.S. SEC) on disclosing corporate carbon data leave businesses no time for empty green statements. The time to act is now!

Why is it so difficult to report on carbon emissions? emissions has already been well established in many companies throughout the world, visibility into the GHG emitted through the supply chain (scope 3), which constitute the significant share of the overall emission, is often not sufficient.

In the automotive industry for instance, . That is why it is even more crucial to identify carbon footprint reduction opportunities along the supply chain. Lack of trust, lack of access to high-quality data, inconsistent methodology or standards of data accounting, and lack of interoperable technology solutions across the highly complex automotive supply chain are the main obstacles to overcome.

Unleash the Network Power for Decarbonization

To meet sustainability and regulatory requirements, companies need to work together with partners, suppliers, and customers and establish transparent processes and common data standards 鈥� from material acquisition to manufacturing to distribution.

As the first open and collaborative data ecosystem, is targeting a more sustainable industry value chain by incorporating all participants involved and enabling the data transparency. Tracking the product carbon footprint is one of the first use cases that Catena-X is now addressing. This is the starting point for a better understanding of the scope 3 GHG emissions, which sets the foundation of enforceable decarbonization opportunities.

On one hand, a common accounting and reporting methodology on product carbon footprint data is required to support the consistency, comparability, and verifiability of the data sourced from the network partners. By partnering with the World Business Council for Sustainable Development (WBCSD), Catena-X adopts the framework of CO₂ calculation scheme and data model.

Earlier this year, 麻豆原创 was the first organization in the world to achieve a standardized carbon footprint value in a WBCSD proof of concept. Importantly, the standardized approach also encourages network partners to move away from unspecific industry average measurements and toward using accurate primary emission data.

On the other hand, technology is key to operationalizing emission accounting and sharing. With its longstanding industry process know-how as well as solution best practices, 麻豆原创 acts strongly as a key enabler in product carbon footprint data tracking within the automotive network.

Industry Network Solutions Empower Automotive Value Chain in Chasing Zero

With , companies can share their product carbon footprint with their business partners in an easy, efficient, and secure way.

GreenToken is a Web-based, subscription SaaS solution striving to create accountability and transparency across the material supply chain. Being compliant with the standardized data model defined with WBCSD helps ensure data consistency across the network.

The product carbon footprint data can be managed and transferred easily on material level between direct business partners.

It leverages to notarize and transfer carbon emissions via tokens from one supply chain member鈥檚 wallet to the next, without disclosing private or confidential data. As these tokens travel along the supply chain downstream, the collected information gets shared, creating a reliable, immutable, and auditable chain of custody. In addition, not only CO₂ data but also other information such as the origin of parts and certifications can be shared via this trustful and verifiable approach.

The solution provides a secured open API, accessible to other carbon emission calculation tools or back end solutions for transactions. A direct integration with 麻豆原创 ERP Central Component 6.0 and 麻豆原创 S/4HANA software is in place.

Transactions can also be driven by import of CSV files or manually, which means that small and midsize enterprises (SMEs) without back end enterprise resource planning (ERP) solutions can also leverage GreenToken for carbon data sharing within the network.

鈥淕reenToken鈥檚 novel approach has the potential to create an accountable and auditable network to scope 3 reporting that is lacking today,鈥� said James Veale, co-founder of GreenToken by 麻豆原创. 鈥淲hat is more, we have already proved GreenToken at scale in other supply chains, and the solution is now ready for Catena-X.鈥�

Hagen Heubach is global vice president and head of Industry Business Unit Automotive at 麻豆原创, and a Board Member of the Catena-X Automotive Network.
Heiko Flohr is senior vice president and head of Product Management for 麻豆原创 for Discrete Industries, and a member of Guidance Board for Catena-X Automotive Network.
Leyi Liu is part of Solution Management for 麻豆原创 Industry Network for Automotive and Catena-X Automotive Network.