June 17, 2026
By Vanguard with the work of Michael Porter, Marco Iansiti, Karim Lakhani, Hau Lee, and Yossi Sheffi.

The New Boundary of Operations

Operations excellence was once understood largely within the walls of the firm. Leaders improved factories, warehouses, service centers, procurement systems, planning routines, quality processes, and internal workflows. External parties mattered, but they were often treated as suppliers, vendors, distributors, contractors, or customers positioned outside the core operating system.

That boundary is weakening.

Today, many of the capabilities that determine operational performance sit outside the firm. A company’s speed may depend on a logistics partner. Its resilience may depend on a supplier’s supplier. Its innovation may depend on a technology platform, university lab, startup, contract manufacturer, or data partner. Its cost structure may depend on shared infrastructure. Its risk exposure may depend on regulators, utilities, cloud providers, industrial parks, ports, and cross-border compliance regimes.

This is why ecosystem orchestration has become an operations issue, not merely a strategy issue. The strongest firms are not only improving internal processes. They are coordinating external networks so that suppliers, platforms, partners, customers, infrastructure providers, and complementary firms can create value together.

The managerial challenge is substantial. Ecosystems are more powerful than traditional vendor relationships because they combine capabilities no single firm fully controls. But they are also harder to govern. Partners have different incentives, different risk tolerances, different investment horizons, and different definitions of success. The leader’s task is not simply to collaborate. It is to orchestrate.

From Supply Chain Management to Ecosystem Management

Traditional supply chain management focuses on the flow of goods, information, and capital across a network. It emphasizes reliability, cost, quality, service, inventory, lead time, and supplier performance. These remain essential. But modern operations increasingly require a broader lens.

An ecosystem is not just a chain. It is a system of interdependent actors whose combined contributions create an outcome that none could easily produce alone. A logistics provider may contribute reach. A technology partner may contribute data visibility. A supplier may contribute specialized engineering. A platform may provide marketplace access. A utility may provide energy capacity. A regulator may shape what is permissible. A customer may contribute demand signals that improve planning.

The difference is important. In a chain, the firm often tries to optimize sequential handoffs. In an ecosystem, the firm must coordinate interdependencies. The value comes not only from transactions, but from how the actors work together.

HBR’s ecosystem strategy work has emphasized that leaders must decide what role they should play in an ecosystem: orchestrator, partner, participant, or complementor. The issue is not simply whether to join an ecosystem, but how to create value through the right role and governance model.

For operations leaders, the question becomes practical: which external relationships are now essential to performance, and how should they be governed so that the operating system becomes faster, more resilient, and more innovative?

Why Ecosystem Orchestration Matters Now

Several forces are making ecosystem orchestration more important.

The first is supply-chain fragility. Disruptions have shown that firms cannot protect continuity by managing first-tier suppliers alone. Resilience depends on visibility into deeper networks, shared contingency planning, alternate capacity, and better information flow across companies. McKinsey has argued that future-ready supply chains must add resilience and agility to traditional objectives of cost, quality, and service, and that agility must extend across R&D, procurement, planning, manufacturing, and logistics.

The second is technological complexity. AI, cloud systems, automation, cybersecurity, digital twins, robotics, and data platforms create operational power, but also dependency. PwC’s 2026 Digital Trends in Operations Survey found a gap between confidence and execution: 85% of surveyed operations and supply-chain leaders said they were ahead of most competitors in digital transformation, yet 89% said their technology investments had not fully delivered expected results. The problem is often not lack of tools. It is weak integration across systems, partners, and workflows.

The third is innovation speed. New products, services, and operating models increasingly require capabilities distributed across multiple actors. A manufacturer may need software partners. A retailer may need logistics analytics. A healthcare company may need device makers, data platforms, payers, and providers. A mobility firm may need battery suppliers, charging infrastructure, regulators, and energy partners.

The fourth is risk sharing. In uncertain markets, firms are reluctant to carry all investment, capacity, and technology risk alone. Ecosystems allow participants to share risk, but only if incentives and responsibilities are clear.

The fifth is customer expectation. Customers increasingly experience the output of the ecosystem, not the individual firm. A late delivery, failed integration, poor installation, product shortage, or cybersecurity incident may involve several partners, but the customer attributes the failure to the brand that promised the outcome.

Operations excellence now depends on the ability to make external complexity feel internally coordinated.

The Orchestrator’s Dilemma

The orchestrator’s dilemma is that the firm must influence actors it does not fully control.

Inside a company, leaders can set roles, budgets, incentives, reporting lines, and performance standards. Across an ecosystem, control is weaker. Partners retain their own strategies, economics, leadership teams, investors, customers, and risk preferences. The orchestrating firm may have contractual rights, but contracts rarely solve the full operating problem.

This creates a delicate balance. If the orchestrator controls too tightly, strong partners may resist, underinvest, or leave. If the orchestrator controls too loosely, the ecosystem fragments. Standards diverge. Data does not flow. Investments become misaligned. Customers experience inconsistency. Risk accumulates in unseen parts of the network.

The skill is to design enough structure to coordinate performance without suffocating partner initiative.

Industrial research on ecosystem orchestration has identified several interdependent practices that matter for firms managing complex ecosystems, including strategic design, relational practices, resource integration, technological practices, and innovation practices. These categories are useful because they show that orchestration is not one activity. It is a system of managerial practices.

Operations leaders must decide who belongs in the ecosystem, what each participant contributes, how information flows, how decisions are made, how value is shared, how disputes are resolved, and how the ecosystem adapts when conditions change.

Mapping the Ecosystem

The first discipline of ecosystem orchestration is mapping. Leaders must identify the actors that materially influence operational performance. This includes obvious suppliers and partners, but also less visible actors: sub-tier suppliers, logistics nodes, technology providers, data intermediaries, utilities, contract manufacturers, platform owners, certification bodies, regulators, financing partners, and customers whose behavior shapes demand.

An ecosystem map should go beyond organizational names. It should identify roles, dependencies, bottlenecks, incentives, capabilities, risk exposures, and switching constraints. Which partner controls a critical capability? Which actor has the strongest customer relationship? Which supplier has the longest recovery time? Which platform determines data access? Which logistics provider controls regional responsiveness? Which government or utility constraint could limit expansion?

The map should also identify value flows. Who creates value? Who captures value? Who bears risk? Who invests? Who benefits from resilience? Who pays when disruption occurs? Misalignment often begins when these questions are unclear.

A company may discover that its most important operating constraint is not inside its own process, but in a partner’s capacity, a supplier’s technology roadmap, a port’s throughput, or a platform’s data rules. Without a map, leaders may optimize the wrong part of the system.

Governance Beyond Contracts

Contracts are necessary, but insufficient. They define obligations, rights, remedies, service levels, pricing, confidentiality, and liability. But ecosystem performance depends on ongoing coordination. Partners must share information, adjust to changing conditions, resolve trade-offs, and invest in capabilities whose benefits may not be evenly distributed.

This requires governance.

Ecosystem governance should define decision forums, escalation paths, data-sharing protocols, performance dashboards, dispute mechanisms, investment responsibilities, and review cadences. In a supplier ecosystem, this may involve joint business reviews, shared demand forecasts, resilience planning, and supplier-development programs. In a platform ecosystem, it may involve technical standards, API governance, data rights, security reviews, and partner certification. In a cross-industry ecosystem, it may involve steering committees, public-private coordination, shared infrastructure planning, and regulatory engagement.

Governance must also distinguish between routine coordination and strategic decisions. Not every issue should rise to senior leadership. But issues involving capacity allocation, customer-impact risk, data access, intellectual property, strategic investment, or major service failure may require higher-level intervention.

The purpose of governance is not to create meetings. It is to make interdependence manageable.

Incentive Alignment as Operating Design

Many ecosystems fail because incentives are misaligned. Each party behaves rationally within its own economics, yet the ecosystem underperforms.

A supplier may be rewarded for low cost, while the buyer needs resilience. A logistics partner may be measured on shipment cost, while the customer values reliability. A technology platform may prioritize feature expansion, while enterprise users need stability and security. A contract manufacturer may be paid by volume, while the brand needs quality and flexibility. A data partner may benefit from data accumulation, while the customer-facing firm carries privacy and reputational risk.

Incentive alignment is therefore an operating design problem. Leaders must ask whether the economics of the relationship support the behavior the ecosystem requires.

This may involve shared savings, gainsharing, volume commitments, performance bonuses, risk-sharing clauses, joint investment pools, preferred-partner status, long-term contracts, innovation incentives, or penalties for failure. It may also involve non-financial incentives such as access to data, market visibility, technical support, training, or participation in future growth opportunities.

The principle is straightforward: partners will not consistently deliver ecosystem value if their incentives reward local optimization.

Data as the Coordination Layer

Ecosystems require information flow. Without timely data, partners cannot coordinate demand, capacity, quality, inventory, risk, or customer commitments. Yet data sharing is often one of the most difficult parts of ecosystem orchestration.

Companies may hesitate to share data because of confidentiality, competitive sensitivity, cybersecurity, privacy, regulatory constraints, or fear of losing bargaining power. Partners may use different systems, definitions, and data standards. Even when data is shared, it may not be trusted.

The solution is not unlimited transparency. It is purposeful transparency. Ecosystem partners should share the information required to improve performance, reduce risk, and coordinate decisions, while protecting sensitive boundaries.

For example, a manufacturer may share demand signals with suppliers without revealing all customer economics. A supplier may share capacity constraints and risk indicators without exposing its entire cost structure. A logistics partner may share real-time shipment visibility while protecting proprietary routing models. A platform may provide operational data access through governed APIs rather than uncontrolled exports.

Data governance becomes an operational capability. It defines what information is shared, with whom, how often, in what format, under what security conditions, and for what decisions. In digitally enabled ecosystems, the coordination layer is often the difference between collaboration as aspiration and collaboration as performance.

The Platform Partnership Challenge

Platform partnerships are increasingly central to operations. Cloud platforms, AI infrastructure, logistics platforms, procurement networks, industrial software, payments systems, and digital marketplaces can extend capability quickly. They can also create dependency.

A company that builds critical operations on a platform gains speed, scale, and technical power. But it may also become exposed to pricing changes, service interruptions, data-access restrictions, cybersecurity vulnerabilities, roadmap shifts, or changes in platform governance. The platform partner becomes part of the operating system.

This requires a different form of partnership management. Leaders should evaluate not only current functionality, but strategic dependency. What happens if the platform changes terms? Can data be migrated? Are workflows portable? Does the company understand the platform’s own incentives? Does the platform compete with any part of the company’s business? Are there backup options? What service-level guarantees exist? Who owns the customer relationship?

Platform partnerships should be governed with the same seriousness as critical supplier relationships. The fact that a capability is digital does not make it less operationally material.

Cross-Industry Collaboration

Some operational problems cannot be solved within a single industry. Energy resilience, circular economy models, critical-mineral supply, semiconductor capacity, cold-chain infrastructure, cybersecurity standards, healthcare interoperability, and logistics decarbonization often require cross-industry collaboration.

These collaborations are difficult because the participants may not share the same business model. A manufacturer, utility, software firm, government agency, logistics provider, and financial institution may all be necessary to solve the problem, but each has different incentives and timelines.

The orchestrator’s role is to define the shared problem clearly enough that collaboration becomes rational. What is the mutual value? What risk is being reduced? What investment is required? Who benefits first? Who pays? What governance model prevents free riding? What standards are needed? What happens if one participant underperforms?

Cross-industry collaboration often succeeds when the shared constraint is strong enough to overcome institutional separation. A region needs energy infrastructure. A sector needs secure data standards. A supply chain needs traceability. A customer segment needs reliability. The clearer the shared constraint, the easier it becomes to design a coalition.

Case Pattern: The Resilient Supplier Network

Consider a manufacturer dependent on specialized components with long qualification cycles. Historically, the company treated suppliers as cost centers and negotiated aggressively on unit price. That approach delivered savings but left the firm exposed when disruptions appeared. Suppliers had little incentive to invest in redundancy, share early risk signals, or prioritize the manufacturer during constraint.

An ecosystem approach would redefine the supplier relationship. The company would identify critical suppliers, share demand forecasts earlier, establish joint risk reviews, support supplier development, and create incentives for continuity. It might offer longer commitments in exchange for capacity assurance, transparency, and resilience investments. It might work with suppliers on dual sourcing, inventory buffers, or process innovation.

The result is not a softer procurement model. It is a more strategic one. The company still manages cost, but it recognizes that resilience, innovation, and continuity are part of supplier value.

Case Pattern: The Platform-Enabled Logistics Network

Consider a retailer with fragmented logistics providers across regions. Each provider performs adequately in isolation, but the retailer lacks end-to-end visibility. Inventory is difficult to reallocate. Delivery promises vary by region. Disruptions are detected late. Customer experience is inconsistent.

The retailer builds an ecosystem model around a logistics visibility platform. Regional providers remain in place, but they integrate into shared data standards, tracking protocols, exception-management routines, and performance dashboards. The retailer creates governance forums with major logistics partners and uses shared data to improve routing, inventory positioning, and customer communication.

This is not simply a technology implementation. It is ecosystem orchestration. The platform becomes the coordination layer, but the performance improvement depends on partner adoption, common standards, aligned incentives, and operating discipline.

Case Pattern: Cross-Industry Energy Resilience

Consider an industrial park where manufacturers, data centers, utilities, local government, and infrastructure investors all face the same power constraint. No single company can solve the grid problem alone. Each wants reliable energy, but investment timing, cost allocation, and infrastructure governance are difficult.

An ecosystem solution may involve joint planning with the utility, shared investment in substations or storage, demand-response agreements, renewable power purchase arrangements, backup generation protocols, and local government support for permitting. The value is collective: faster capacity expansion, reduced outage exposure, more predictable growth, and stronger regional competitiveness.

The hard part is governance. Who invests first? How is capacity allocated? How are benefits shared? What happens if one participant’s demand grows faster than expected? The orchestrator, whether a lead firm, utility, developer, or public-private body, must create a structure that converts shared constraint into shared commitment.

The Ecosystem Orchestration Framework

Leaders can build ecosystem orchestration capability through a practical framework: map, align, govern, integrate, and learn.

Mapping identifies the actors, dependencies, bottlenecks, incentives, and risks that shape operational performance. The goal is to see the system as it actually functions, not as contracts suggest it should function.

Aligning clarifies the shared value proposition. Partners need to understand why collaboration is worthwhile, what each actor contributes, and how benefits and risks will be distributed.

Governing establishes decision rights, escalation paths, data protocols, performance metrics, investment responsibilities, and dispute mechanisms. Governance turns collaboration into an operating system.

Integrating connects workflows, systems, data, standards, and routines across organizational boundaries. This is where ecosystem strategy becomes operational reality.

Learning reviews performance over time. Which partners created value? Which incentives failed? Which risks were missed? Which coordination mechanisms worked? Which relationships should be deepened, redesigned, or exited?

This framework is simple, but it addresses the main reason ecosystems fail: companies pursue collaboration without designing the management system required to sustain it.

Measuring Ecosystem Performance

Ecosystem performance cannot be measured only through internal metrics. Leaders need measures that capture interdependence.

Useful metrics include supplier recovery time, partner service reliability, shared forecast accuracy, ecosystem response time, joint innovation cycle time, data-quality compliance, partner adoption rates, customer-experience consistency, risk visibility, and value created through joint initiatives. Financial metrics should include cost reduction, revenue enabled, avoided disruption, working-capital improvement, and margin impact from ecosystem performance.

The most important question is whether the ecosystem improves outcomes that matter to customers and strategy. Does it deliver faster? Innovate faster? Recover faster? Share risk better? Improve quality? Reduce exposure? Enable new offerings? Strengthen loyalty?

If ecosystem activity cannot be connected to operational outcomes, it risks becoming partnership theater.

The Leadership Role

Ecosystem orchestration requires a different leadership posture. Leaders must be comfortable influencing without owning, coordinating without commanding, and creating standards across boundaries they do not fully control.

This requires relational credibility. Partners must believe the orchestrator is serious, fair, competent, and capable of sustaining commitments. It also requires strategic clarity. The orchestrator must know which partners are critical, which relationships are transactional, which capabilities must remain internal, and which external dependencies are acceptable.

Leaders must also protect the organization from ecosystem sprawl. Not every partnership deserves deep integration. Some relationships should remain transactional. Others should become strategic. The danger is trying to orchestrate everything. The art is knowing where orchestration creates advantage and where it creates unnecessary complexity.

The executive standard is therefore selective depth. Deep collaboration should be reserved for relationships that materially affect speed, innovation, resilience, customer value, or strategic optionality.

From External Relationships to Internal Strength

The purpose of ecosystem orchestration is not to make the organization dependent. It is to turn external capability into internal strength. A well-orchestrated ecosystem expands what the firm can do while preserving clarity about what the firm must own.

The company may not own every asset, but it should understand every critical dependency. It may not control every partner, but it should govern the relationships that matter. It may not build every capability internally, but it should know which external capabilities are essential to its customer promise.

Operations excellence is therefore becoming more relational, more systemic, and more externally aware. The firm that performs best will not always be the firm with the most assets. It may be the firm that coordinates the best network.

In a fragmented, technology-intensive, resource-constrained economy, no company can build everything alone. But not every company can collaborate well. The advantage belongs to those that can turn collaboration into disciplined execution.

That is the promise of ecosystem orchestration: external relationships converted into operational strength.