People Don't Follow Strategy—They Follow Structure: Why Organizational Design Drives Adaptation More Than Culture or Incentives
- Jonathan H. Westover, PhD
- 3 hours ago
- 24 min read
Listen to this article:
Abstract: Organizations frequently attribute implementation failures and adaptation challenges to cultural misalignment or inadequate incentives. However, mounting evidence from organizational behavior, network science, and comparative institutional research suggests that formal structure—specifically hierarchical configuration and decision-making architecture—exerts greater influence on employee behavior than culture change initiatives or compensation redesign. This article synthesizes research on organizational modularity, structural determinants of behavior, and ecosystem emergence to argue that flattening hierarchies and redistributing authority to operational edges fundamentally rewires information flow, decision velocity, and collaborative patterns. Drawing on empirical cases from manufacturing, technology platforms, and healthcare delivery across North America, Europe, and East Asia, we demonstrate that structural reconfiguration enables adaptive behaviors that resist cultivation under traditional pyramid architectures, regardless of cultural interventions. The analysis concludes with evidence-based frameworks for structural redesign that prioritize network density, decision proximity to information sources, and cross-boundary coordination mechanisms as foundational prerequisites for organizational agility.
Every year, organizations invest billions in culture transformation programs, leadership development, and incentive realignment—initiatives designed to make employees more innovative, customer-focused, and adaptive. Yet organizational change efforts frequently fail to achieve intended outcomes, with research suggesting success rates remain disappointingly low (Kotter, 1995). When post-mortems are conducted, leaders typically diagnose cultural resistance, inadequate leadership commitment, or misaligned rewards as root causes. These explanations feel intuitive: if people aren't behaving differently, surely the problem lies in their mindsets, motivations, or the signals sent by compensation structures.
But this diagnostic framework may fundamentally misidentify the constraint. A growing body of evidence from organizational network analysis, institutional economics, and comparative management research points to a different culprit: formal organizational structure. Specifically, the hierarchical architecture—who reports to whom, where decision rights reside, how information flows between levels—appears to exert stronger influence on employee behavior than cultural narratives or incentive schemes (Puranam et al., 2014). This insight carries profound implications for how we approach organizational adaptation, particularly in environments demanding speed, customer responsiveness, and ecosystem collaboration.
The stakes are especially high in an era where competitive advantage increasingly depends on coordinating across organizational boundaries. Platform businesses, supply chain networks, innovation ecosystems, and multi-stakeholder service delivery models all require organizations to transcend traditional firm boundaries. Yet most companies attempting this transition retain hierarchical structures designed for vertical integration and centralized control—creating fundamental mismatches between strategic intent and operational reality (Jacobides et al., 2018).
This article examines why structure trumps strategy in shaping organizational behavior, how hierarchical flattening rewires work patterns rather than merely "empowering" people, and how structural modularity creates conditions for ecosystem emergence. We synthesize evidence from organizational design research, network science, and field observations across industries to argue that adaptability requires architectural change—not just cultural aspiration.
The Organizational Structure Landscape
Defining Structure Beyond the Organizational Chart
Organizational structure encompasses far more than reporting relationships depicted in hierarchy diagrams. Structure represents the formal architecture governing three critical dimensions: authority distribution (where decision rights reside), information architecture (how signals flow between roles and units), and coordination mechanisms (how interdependent work gets synchronized) (Galbraith, 2014). These elements collectively determine what organizational theorists call the "space of possible behaviors"—the range of actions employees can realistically take given their position in the formal system.
Traditional pyramid structures concentrate authority at upper levels, channel information through vertical reporting lines, and rely on hierarchical supervision as the primary coordination mechanism. This architecture emerged during industrial-era contexts prioritizing standardization, scale economies, and predictable environments (Chandler, 1962). The design optimized for efficiency in stable conditions where senior leaders possessed superior information and expertise relative to frontline employees.
Contemporary organizational challenges present fundamentally different conditions. Customer preferences shift rapidly; competitive threats emerge from non-traditional sources; innovation requires synthesizing distributed knowledge; value creation depends on coordinating across firm boundaries. Under these conditions, traditional hierarchical structures create systematic disadvantages: information bottlenecks at approval layers, decision delays while issues escalate upward, coordination failures when dependencies span organizational silos (Puranam et al., 2014).
State of Practice: The Persistence of Pyramid Structures
Despite widespread recognition that organizational agility matters, most companies retain fundamentally hierarchical architectures. Research examining large organizations has found that structural characteristics like span of control and hierarchical depth have remained relatively stable over recent decades despite dramatic technology advances that theoretically enable broader coordination (Guadalupe et al., 2014). This structural stability persists even as rhetoric around empowerment, agility, and flat organizations intensifies.
Several factors explain this persistence. Hierarchical structures provide clear career progression paths, simplify accountability assignment, and align with deeply embedded management assumptions about control and coordination. Moreover, hierarchy solves genuine coordination problems when tasks are highly interdependent and information asymmetries favor centralized decision-making. The challenge arises when environmental conditions shift but structural inertia prevents architectural adaptation.
Recent decades have witnessed experimentation with alternative structures—matrix organizations, network designs, holacracy, agile team configurations—with mixed results. Organizations that attempted structural delayering have found that benefits in decision speed and employee autonomy materialize only when authority redistribution accompanies hierarchy reduction; simply removing management layers without redistributing decision rights can produce confusion rather than empowerment. This finding highlights a crucial distinction: structural change means redesigning authority, information flow, and coordination mechanisms, not merely redrawing organizational charts.
The emergence of modular organizational forms—where semi-autonomous units possess end-to-end responsibility within defined domains—represents one promising structural alternative. Research on modular organizations in software development, manufacturing, and professional services suggests faster adaptation cycles and higher innovation rates compared to traditional functional hierarchies (Baldwin & Clark, 2000). However, modularity introduces its own coordination challenges, particularly regarding interdependencies that span unit boundaries. Effective modular structures require sophisticated interface specifications and governance mechanisms to manage cross-module integration.
Organizational and Individual Consequences of Structural Misalignment
Organizational Performance Impacts
The performance consequences of structural misalignment between environmental demands and hierarchical architecture are substantial and empirically documented. Organizations with hierarchical structures face systematic disadvantages in dynamic environments along several dimensions: decision latency, information quality, adaptive capacity, and innovation productivity.
Decision latency—the time elapsed between information availability and action—increases with hierarchical layers when decision authority resides at senior levels. Studies of product development processes indicate that approval requirements and hierarchical coordination create delays that compound in fast-moving markets where competitive advantage depends on rapid iteration based on market feedback. These delays prove particularly costly when customer preferences shift quickly or when technological opportunities require rapid response.
Information quality can degrade as signals traverse hierarchical levels. Research on organizational communication demonstrates that critical operational information becomes distorted or delayed as it moves through management layers, with frontline observations frequently failing to reach decision-makers with full contextual richness (Edmondson, 1999). Similar patterns appear in customer service operations where frontline insights about product failures or service gaps get filtered or summarized through management layers, losing detail that would inform effective responses.
Adaptive capacity—the organizational ability to reconfigure resources in response to changing conditions—appears constrained by hierarchical rigidity. Organizations with decentralized decision authority tend to demonstrate faster responses to demand volatility and market changes compared to centrally controlled counterparts, as operational teams can adjust without requiring corporate approval cycles. The structural difference enables adaptive responses at operational levels where information about changing conditions first appears.
Innovation productivity faces constraints under hierarchical approval requirements for experimentation and resource allocation. Research across industries suggests that centralized control over exploratory projects can reduce both the quantity and novelty of innovation attempts, as hierarchical approval processes filter out unconventional ideas and create disincentives for risky experimentation (Henderson & Clark, 1990).
Organizations that successfully restructure toward flatter hierarchies and more distributed decision authority often show improved financial performance over time. This performance advantage appears attributable to faster growth and improved operational metrics rather than cost reduction alone, suggesting structural flattening enables revenue-generating capabilities beyond efficiency gains.
Individual Wellbeing and Stakeholder Impacts
Structural configurations profoundly influence employee experience, engagement, and wellbeing through mechanisms often attributed to culture or leadership style. Research using network analysis to map actual communication patterns—rather than formal reporting relationships—reveals systematic differences in how hierarchical versus flat structures shape daily work experience.
Psychological safety—the belief that one can take interpersonal risks without negative career consequences—varies significantly by structural position. Employees in hierarchical organizations report different levels of psychological safety depending on their structural distance from decision authority, even when leadership behavior appears consistent (Edmondson, 1999). This pattern reflects that proposing unconventional ideas or challenging assumptions carries different implications when decisions must traverse multiple management layers versus when authority resides closer to operational work.
Autonomy and mastery—key drivers of intrinsic motivation according to self-determination theory—correlate with structural role design. Research on knowledge workers suggests that perceived autonomy depends substantially on decision rights formally granted to roles, with structural authority explaining significant variance in employee engagement and satisfaction (Hackman & Oldham, 1976). Employees in structurally empowered roles—those with formal authority to make consequential decisions—report higher job satisfaction and demonstrate lower turnover.
Role clarity can improve rather than deteriorate when organizations flatten hierarchies and adopt modular structures, contrary to common concerns about coordination chaos. Clear interface specifications between modules—defining what each unit delivers and requires from others—can provide greater role clarity than traditional functional hierarchies where responsibilities frequently overlap and accountability diffuses across approval chains.
Customer and partner experience also reflect structural configurations. Organizations with decision authority positioned near customer interactions demonstrate faster issue resolution and higher customer satisfaction. Service organizations where frontline teams possess authority to resolve complaints locally achieve higher first-contact resolution rates compared to those requiring corporate approval for comparable issues. Customer satisfaction metrics often diverge accordingly, with structurally empowered locations achieving notably higher scores.
For ecosystem partners—suppliers, distributors, complementors—organizational structure determines collaboration effectiveness. Partners working with hierarchically rigid firms report frustration with slow decision cycles, frequent requirement changes as proposals escalate through approval layers, and difficulty identifying decision-makers with actual authority (Dyer & Singh, 1998). These friction costs discourage partnership investment and innovation contribution. Conversely, structurally modular organizations with clear unit-level decision authority enable partners to build stable relationships with empowered counterparts, facilitating the trust and knowledge sharing that characterize effective ecosystems.
Evidence-Based Organizational Responses
Table 1: Organizational Case Studies in Structural Redesign and Agility
Organization Name | Industry Sector | Structural Model or Framework | Key Structural Changes Implemented | Decision Authority Distribution | Information Transparency Mechanism | Observed Performance Outcomes | Reported Employee/Customer Impacts |
Haier | Manufacturing (Appliances) | Rendanheyi (Extreme Structural Modularity) | Dissolved functional hierarchy into thousands of microenterprises (10-15 employees) with market-based contracting. | Microenterprises possess hiring authority, budget control, and strategic decision rights. | Market-based performance contracts with internal and external customers. | Strong revenue growth in the 2010s and expansion into numerous product categories. | Units missing targets restructure or dissolve; high innovation velocity. |
ING (Netherlands) | Banking / Financial Services | Agile Transformation (Modular Restructuring) | Dissolved departmental hierarchies for 350 squads organized into 13 tribes. | Squads possess budget authority, hiring decisions, and product roadmap control. | Transparent performance metrics and explicit governance forums for cross-tribe dependencies. | Reduced time-to-market for new features from months to weeks. | Improved employee engagement. |
Spotify | Technology / Digital Services | Squad-Tribe-Chapter Model (Modular Architecture) | Organized into cross-functional squads and tribes with dual affiliations (chapters) for functional standards. | Squad level for product choices; chapter level for technical standards; minimal hierarchical oversight. | Distributed structural adaptation training and modular interface specifications. | Rapid deployment cycles and autonomous experimentation while scaling from dozens to thousands of employees. | Squad leads regularly adjust team compositions locally. |
Morning Star | Manufacturing (Food Processing) | Self-Management / Peer-Based Accountability | No formal managers; Colleague Letters of Understanding (CLOUs) replace supervisor-subordinate relationships. | Individuals authorize capital expenditures; teams recruit and select colleagues and redesign workflows. | Web of peer-based accountability through negotiated commitment letters. | High operational efficiency and cost competitiveness while processing a substantial portion of California's tomato harvest. | Employee compensation remains above industry averages. |
Buurtzorg | Healthcare Delivery | Self-Managing Teams | No middle management; self-managing nursing teams of 10-12 professionals handle all operations. | Teams hold rights for care protocols, scheduling, hiring, dismissal, and financial budgets. | Not in source | Competitive operational costs despite higher wages and more time per patient visit. | Patient satisfaction scores substantially higher than traditional providers; employee engagement >90%. |
Valve Corporation | Technology / Video Game Development | Hierarchy-less / Fluid Structure | No formal managers; employees choose their own projects based on assessed value. | Individual contributors' assessment of value and personal interest. | Comprehensive company-wide transparency of project data, financial performance, and user metrics. | Consistent success of games (Half-Life, Portal) and dominance of the Steam platform. | Not in source |
Bridgewater Associates | Investment Management / Financial Services | Radical Transparency / Believability-Weighted Decision-Making | Information access decoupled from hierarchical position. | Distributed via 'believability weights' based on track records, supported by universal data access. | Radical transparency: all meetings recorded; all decision rationale and analyses accessible to all. | Maintained performance through multiple market cycles; became one of the world's largest hedge funds. | Not in source |
Zara | Fashion / Retail | Ecosystem Interface Management | Direct integration with suppliers; design teams co-located with manufacturers, bypassing procurement departments. | Design teams and supplier teams coordinate directly on production adjustments. | Suppliers access real-time point-of-sale data; shared information systems. | Design-to-retail cycles as brief as two weeks. | Not in source |
Toyota | Manufacturing (Automotive) | Supplier Development System / Ecosystem Coordination | Peer-to-peer structural integration with suppliers (resident engineers, joint improvement teams). | Peer-to-peer between engineering and production teams across firm boundaries. | Shared production schedules, engineering specifications, and joint problem-solving platforms. | Superior quality levels and innovation rates compared to competitors. | Not in source |
Netflix | Technology / Streaming Entertainment | Hierarchical Flattening | Maintaining 4-5 hierarchical layers between CEO and contributors while scaling headcount. | To the teams closest to relevant information (product teams launch features; content teams make acquisitions). | Not in source | Rapid global expansion to 190 countries and ability to pivot business models quickly. | Not in source |
Hierarchical Flattening and Span of Control Expansion
Reducing hierarchical layers while expanding managerial span of control represents the most direct structural intervention for redistributing authority and accelerating information flow. The theoretical logic is straightforward: fewer layers mean shorter communication paths between information sources and decision points, while wider spans force delegation because managers cannot directly supervise larger teams (Puranam et al., 2014).
Evidence Summary: Research on organizational delayering indicates that hierarchy reduction can improve decision cycle times and employee engagement when implemented with genuine authority redistribution. Studies tracking organizations through restructuring processes found that performance benefits materialized when role redesign accompanied structural change—specifically, when decision rights formally transferred to lower organizational levels rather than remaining implicitly centralized despite fewer layers (Guadalupe et al., 2014). Organizations that merely removed management positions without redistributing decision authority often experienced confusion and performance disruption rather than the intended empowerment.
Effective Approaches for Hierarchical Flattening:
Radical span expansion: Increase direct reports from typical ranges to significantly larger numbers (12-20 or more), forcing delegation of operational decisions while managers focus on strategic coordination, team development, and cross-unit integration
Layer elimination campaigns: Target substantial reductions in hierarchical levels between CEO and frontline employees, compressing approval chains and decision escalation paths
Role-based authority mapping: Explicitly document which decisions transfer to which roles during delayering, preventing ambiguity that undermines structural intent
Manager role redefinition: Shift managerial focus from operational control and approval authority toward coaching, capability development, and strategic context-setting as spans expand beyond direct supervision capacity
Netflix exemplifies hierarchical flattening linked to operational agility. The streaming platform maintains remarkably few hierarchical layers—typically four to five levels between CEO and individual contributors—even as headcount has grown substantially. This flat structure combines with explicit management philosophy where decision authority resides with teams closest to relevant information. Product teams possess authority to launch features, marketing teams control campaign decisions, and content teams make acquisition choices within strategic parameters but without executive approval for individual decisions. This structural configuration enabled Netflix to expand from domestic DVD rental to global streaming with original content across 190 countries while maintaining decision velocity. The company's ability to respond rapidly to competitive threats—launching advertising tiers, adjusting content strategy by region, pivoting business models—reflects structural enablement rather than simply aggressive culture.
Haier, the Chinese appliance manufacturer, implemented perhaps the most radical hierarchical flattening among large industrial firms. CEO Zhang Ruimin dissolved Haier's traditional functional organization in favor of thousands of microenterprises (small teams of 10-15 employees) with end-to-end responsibility for specific product lines or market segments. The corporate hierarchy essentially disappeared, replaced by market-based contracting between microenterprises and minimal coordinating infrastructure. Individual microenterprises possess hiring authority, budget control, and strategic decision rights within their domains. This extreme structural modularity enabled Haier to enter numerous product categories, expand internationally to become among the world's largest appliance makers by volume, and maintain innovation velocity despite massive scale. Traditional hierarchical structures would require corporate approval for the product experiments and market entries that Haier's microenterprises execute routinely. Performance data from the company indicate strong revenue growth throughout the 2010s while traditional competitors experienced slower expansion.
Modular Organizational Architecture and Interface Design
Modular structures decompose organizations into semi-autonomous units that own complete workflows within defined domains, coordinating through standardized interfaces rather than hierarchical oversight. This architecture borrows principles from engineering—where modular product designs enable component independence and parallel development—and applies them to organizational design (Baldwin & Clark, 2000).
Evidence Summary: Research on modular organizations demonstrates advantages in adaptive capacity and innovation productivity. Studies of software development have found that modular organizational structures—where teams possessed end-to-end responsibility for distinct product modules—enabled faster feature development and more rapid problem resolution compared to functionally organized counterparts (MacCormack et al., 2006). The performance differential stemmed from reduced coordination overhead and faster iteration cycles within modules. However, modular structures require careful attention to integration challenges, with significant effort devoted to interface management and cross-module compatibility.
Effective Approaches for Modular Design:
End-to-end accountability units: Design modules around complete customer journeys, product lines, or market segments rather than functional specialties, ensuring each unit controls all capabilities needed to deliver value independently
Explicit interface specifications: Document what each module provides to and requires from other modules—the organizational equivalent of API contracts in software—to enable independent operation while maintaining system integration
Architectural authority separation: Distinguish between module-level decisions (delegated to unit teams) and architectural decisions affecting multiple modules (managed through lightweight governance forums)
Market-based coordination: Allow modules to negotiate priorities, resource allocation, and integration schedules through structured dialog rather than hierarchical mandate, surfacing trade-offs explicitly
Spotify's squad-tribe-chapter model illustrates modular organizational architecture in digital services. The music streaming company organizes work into squads (small cross-functional teams) that own specific features or user experiences end-to-end. Multiple related squads form tribes (broader organizational modules) that coordinate around shared missions like discovery or platform infrastructure. Individuals maintain dual affiliations—squad membership for operational work and chapter membership for functional specialty coordination (all iOS developers form a chapter, all data scientists form another). This structure remains fundamentally modular because decision authority resides at squad level for product choices and at chapter level for technical standards, with minimal hierarchical oversight. The architecture enabled Spotify to scale from dozens to thousands of employees while maintaining rapid deployment cycles and autonomous experimentation. When squads need capabilities outside their module—design support, infrastructure changes, data pipeline modifications—they coordinate through structured requests to other squads rather than escalating to management.
ING's agile transformation in the Netherlands provides a banking example of modular restructuring. The financial services company dissolved traditional departmental hierarchies in favor of approximately 350 squads organized into 13 tribes, each focused on distinct customer needs or product domains (mortgages, payments, investments). Individual squads possess budget authority, hiring decisions, and product roadmap control within strategic parameters. The modular structure reportedly reduced time-to-market for new features from months to weeks post-transformation, while employee engagement improved. Notably, ING designed explicit governance for cross-tribe dependencies: architectural decisions affecting multiple squads require consensus in designated forums, but implementation proceeds at squad level once interfaces are agreed. This separation between architectural coordination and execution autonomy enables both module independence and system integration—the core tension modular structures must manage.
Distributed Decision Authority and Empowerment Mechanisms
Redistributing formal decision rights from hierarchical levels to operational edges represents the crucial enabler that makes structural flattening and modularity effective. Without explicit authority transfer, structural changes risk creating confusion rather than empowerment, as employees remain uncertain about their actual decision latitude.
Evidence Summary: Research distinguishes between perceived empowerment—employees' subjective sense of autonomy—and structural empowerment—formal authority to make consequential decisions without approval. Studies consistently show that structural empowerment drives performance outcomes while perceived empowerment without decision authority can generate frustration. Healthcare research has found that structurally empowered nursing teams (those with formal authority over staffing, scheduling, and clinical protocols) achieved better patient outcomes and higher patient satisfaction than teams with equivalent training and supportive leadership but lacking formal decision authority (Kanter, 1977). The difference reflected structural enablement: empowered teams could immediately adjust care protocols in response to patient conditions rather than awaiting approval.
Effective Approaches for Authority Distribution:
Decision authority matrices: Create explicit frameworks documenting which roles hold decision rights for which choice types (hiring, budgets, product features, vendor selection), eliminating ambiguity and preventing implicit recentralization
Consent-based governance: Implement decision protocols where proposals proceed unless objections are raised (consent) rather than requiring affirmative approval (consensus), shifting default from "no until approved" to "yes unless blocked"
Financial authority delegation: Grant budget control to operational units commensurate with their accountability, enabling resource allocation decisions without corporate approval cycles
Escalation redesign: Transform escalation from approval-seeking (upward delegation) to consultation-seeking (advice gathering while retaining decision authority), maintaining lower-level ownership while accessing senior expertise
Buurtzorg, the Dutch home healthcare provider, demonstrates radical decision authority redistribution in professional services. The organization operates through self-managing nursing teams of 10-12 professionals who collectively hold all operational decisions: client acceptance, care protocols, scheduling, quality improvement, hiring, and dismissal of team members. No middle management layer exists between nurses and a minimal corporate staff supporting thousands of employees. Decision authority includes financial choices—teams manage budgets and can authorize equipment purchases or process changes without approval. This structural empowerment has produced notable outcomes: Buurtzorg achieves patient satisfaction scores substantially higher than traditional healthcare providers, employee engagement rates exceeding 90%, and competitive operational costs despite higher wage levels and more time per patient visit. The performance advantage stems from eliminating approval delays: when a nurse identifies a patient need for different equipment or a care protocol adjustment, implementation occurs immediately rather than queuing for administrator approval.
Morning Star, a California-based tomato processing company, extends distributed authority to manufacturing contexts traditionally considered unsuitable for empowerment. The organization operates without formal managers or hierarchical levels. Individual employees negotiate "Colleague Letters of Understanding" that specify their commitments to other colleagues, creating a web of peer-based accountability rather than supervisor-subordinate relationships. Decision authority includes significant choices: equipment purchases (individuals can authorize capital expenditures up to certain thresholds without approval), hiring (teams recruit and select new colleagues), and operational improvements (employees redesign workflows based on their judgment). This structural configuration has enabled Morning Star to achieve cost competitiveness while maintaining quality standards and employee compensation above industry averages. The company processes a substantial portion of California's tomato harvest with operational efficiency despite lacking the management hierarchy typically considered necessary for coordinating complex manufacturing. Employees cite the decision authority—the structural empowerment to implement improvements immediately—as a primary driver of continuous productivity gains.
Real-Time Information Transparency and Feedback Loops
Structural interventions succeed only when information flows match decision authority distribution. Traditional hierarchies concentrate decision rights at senior levels partly because information aggregates upward through reporting systems designed for top-down control. Redistributing authority requires redesigning information architecture to deliver operational signals directly to empowered decision-makers (Galbraith, 2014).
Evidence Summary: Organizations that combine structural empowerment with transparent information access demonstrate superior performance versus those implementing either change independently. Research indicates that delegating decisions to operational teams improves outcomes when accompanied by comprehensive data visibility, but produces limited improvement when teams lack information access despite formal authority. The pattern reflects that effective decisions require both authority and information—structural empowerment without information transparency leaves decision-makers operating with incomplete context.
Effective Approaches for Information Architecture:
Universal dashboard access: Provide frontline teams with same operational, financial, and customer data available to executives, eliminating information asymmetries that justify hierarchical decision retention
Closed-loop feedback systems: Connect operational decisions directly to outcome visibility, enabling rapid iteration as teams observe consequences and adjust without management intermediation
Customer signal amplification: Structure direct channels between customers and operating teams (support forums, user research access, sales data dashboards) rather than filtering customer information through account management or marketing hierarchies
Comparative performance transparency: Make performance metrics visible across teams to enable peer learning and social accountability rather than relying solely on managerial monitoring
Valve Corporation, the video game developer, exemplifies information transparency supporting distributed decision authority. The company operates without formal managers or hierarchical reporting relationships. Employees choose which projects to join based on their assessment of value and personal interest rather than management assignment. This structural fluidity requires comprehensive information transparency to function: project data, financial performance, user metrics, and strategic priorities are visible company-wide. Employees make informed project choices and resource allocation decisions because they access information executives would use in traditional hierarchies. This transparency-enabled structure has produced consistently successful games (Half-Life, Portal, Dota 2) and the dominant PC gaming platform (Steam) despite unconventional organization. The information architecture makes decentralized decision-making viable—employees can assess project viability and allocate their effort effectively because relevant data flows transparently rather than being hierarchically controlled.
Bridgewater Associates, the investment management firm, combines information transparency with distributed decision authority in financial services contexts typically hierarchical. The company's "radical transparency" principle makes nearly all information accessible to all employees: meeting recordings, decision rationale, performance evaluations, and investment analyses. This transparency supports what Bridgewater calls "believability-weighted decision-making"—individuals with stronger track records in specific domains receive greater decision weight, but information access ensures all employees can contribute evidence and reasoning regardless of hierarchical position. The structure enabled Bridgewater to become among the world's largest hedge funds while maintaining performance through multiple market cycles. Critically, the information transparency serves structural purpose rather than cultural symbolism—it enables distributed decision-making by ensuring participants possess data needed for informed contributions. Without comprehensive information access, the distributed authority would produce uninformed decisions; without authority distribution, information transparency would remain symbolic rather than structurally functional.
Cross-Boundary Coordination and Ecosystem Interface Management
As organizations adopt modular structures and distribute decision authority, coordination increasingly happens peer-to-peer across unit boundaries rather than through hierarchical oversight. This coordination pattern naturally extends beyond organizational boundaries to suppliers, partners, and customers, creating ecosystem dynamics (Jacobides et al., 2018). Structural design must therefore address inter-organizational coordination mechanisms, not just internal architecture.
Evidence Summary: Research on organizational ecosystems demonstrates that governance structures enabling rapid, low-friction coordination across firm boundaries create competitive advantages in innovation speed and adaptive capacity. Studies of automotive supply networks found that manufacturers using modular coordination mechanisms—where supplier teams interacted directly with assembly teams through standardized interfaces rather than through purchasing departments—achieved faster new model development and lower development costs than traditional hierarchical procurement models (Dyer & Nobeoka, 2000). The structural difference enabled real-time problem-solving and design iteration without waiting for issues to escalate through both firms' hierarchies before solutions could be negotiated.
Effective Approaches for Ecosystem Coordination:
Team-to-team coordination protocols: Establish direct relationships between internal operational teams and external partner teams, bypassing traditional boundary-spanning roles (sales, procurement, alliance management) for routine coordination
Shared information platforms: Extend transparency and feedback systems to ecosystem partners, providing suppliers and collaborators with same visibility into demand signals, quality metrics, and strategic priorities that internal teams access
Modular contracting: Structure partnership agreements around outcome delivery and interface specifications rather than activity control, enabling partner autonomy within agreed parameters while maintaining system integration
Ecosystem governance forums: Create lightweight coordination mechanisms for decisions affecting multiple ecosystem participants, separating these architectural choices from execution autonomy that remains distributed to individual firms and teams
Zara, the fashion retailer, demonstrates cross-boundary coordination enabling ecosystem responsiveness. The company maintains remarkably short design-to-retail cycles—as brief as two weeks from concept to store availability—through structural integration with suppliers and manufacturers. Rather than traditional buyer-supplier relationships mediated through procurement departments, Zara's design teams work directly with fabric suppliers and contract manufacturers through co-located offices and shared information systems. Suppliers access Zara's point-of-sale data in real-time, observing which items sell rapidly and which languish, enabling production adjustments without formal forecasts or orders. Manufacturing partners maintain capacity commitments rather than volume contracts, adjusting output based on sales signals. This structural coordination—direct team-to-team communication, shared information, outcome-based agreements—enables ecosystem-level responsiveness that competitors with traditional hierarchical supplier management struggle to match. The structural enabler is elimination of hierarchical mediation: design teams and suppliers coordinate directly rather than negotiating through purchasing departments, and information flows without filtering through corporate reporting systems.
Toyota's supplier development system illustrates ecosystem coordination in manufacturing. The automotive company maintains structural integration with key suppliers through multiple mechanisms: resident engineers from suppliers work on-site at Toyota facilities; joint improvement teams address quality and cost issues collaboratively; suppliers access Toyota's production schedules and engineering specifications through shared systems. Crucially, this integration operates peer-to-peer between engineering and production teams rather than hierarchically through purchasing and legal departments. The structural approach enabled Toyota to achieve quality levels and innovation rates competitors struggled to match despite similar supplier access. Research on Toyota's supplier network found that structural integration mechanisms—direct engineer-to-engineer collaboration, shared information systems, joint problem-solving teams—explained much of Toyota's supplier performance advantage over competitors (Dyer & Nobeoka, 2000). The coordination structure creates ecosystem-level capabilities that transcend individual firm boundaries while maintaining modular autonomy for independent innovation within interface constraints.
Building Long-Term Organizational Architecture and Governance Capability
Structural Mindset Development and Design Competency
Sustaining adaptive organizational structures requires developing management capabilities in architectural thinking—the ability to diagnose structural constraints on desired behaviors and redesign organizational elements accordingly (Galbraith, 2014). Most management education emphasizes strategy formulation, financial analysis, and people leadership while providing minimal training in structural design. This capability gap means well-intentioned restructuring often recreates hierarchical patterns despite surface changes.
Organizations building durable structural adaptability invest in developing architectural competency as a core leadership skill. This involves training managers to analyze work dependencies and information flows rather than simply drawing reporting relationships, to distinguish between decisions requiring coordination versus those better delegated, and to design interfaces between organizational units that enable both autonomy and integration. The goal is equipping leaders to continuously adjust structure in response to changing environmental demands rather than treating organizational design as an episodic event managed by consultants.
Effective approaches include dedicated training in organizational design principles, structured experimentation with alternative coordination mechanisms, and explicit accountability for structural adaptation as part of leadership responsibilities. Organizations that build this capability demonstrate greater resilience when market conditions shift, as leaders throughout the organization can diagnose structural misalignments and implement adjustments locally rather than waiting for corporate mandates.
Spotify exemplifies structural competency development through leadership training in architectural thinking. The company educates managers in distinguishing between architectural decisions (those affecting multiple squads) and local decisions (contained within squads), designing clear interfaces between organizational modules, and identifying when coordination costs justify structural changes. This training enables distributed structural adaptation—squad leads regularly adjust team compositions and responsibilities rather than waiting for corporate reorganization mandates. The capability investment sustains Spotify's modular architecture because leaders throughout the organization understand structural principles and can apply them in their domains. Without this distributed design competency, the modular structure would likely collapse back toward hierarchy as managers revert to familiar control patterns when facing coordination challenges.
Dynamic Restructuring Capacity and Evolutionary Design
Traditional organizational structures are designed for stability, with restructuring treated as disruptive events to be minimized. Adaptive organizations invert this assumption, developing capacity for continuous structural adjustment in response to market evolution, technology changes, and strategic pivots (Worley & Lawler, 2010). This requires governance mechanisms that permit structural fluidity without creating chaos, and normalization of reorganization as a regular management activity rather than a crisis response.
Dynamic restructuring capability rests on several enabling conditions: modular architectures that allow local structural changes without system-wide disruption; clear criteria for when structural adjustment is warranted (growth thresholds, coordination cost increases, strategic pivots); and transition protocols that minimize disruption during changes. Organizations with this capability can rapidly reallocate resources, reconfigure team compositions, and adjust accountability structures to match emerging opportunities or challenges—treating structure as a variable to be optimized continuously rather than a constraint to be endured.
Effective practices include establishing thresholds that trigger structural review (team size exceeding effective coordination limits, decision cycle times degrading beyond acceptable ranges, coordination costs consuming excessive resources), creating lightweight processes for structural experimentation within defined boundaries, and developing transition playbooks that enable rapid restructuring without operational disruption.
Haier's rendanheyi model exemplifies dynamic restructuring as normal operations. The company's microenterprise structure permits continuous creation, merger, and dissolution of organizational units based on market performance. Microenterprises that fail to achieve market validation dissolve, with members joining other units or forming new ventures. Successful microenterprises split when scale exceeds effective team size, creating new autonomous units. This structural fluidity—with a significant portion of microenterprises restructuring substantially each year—enables Haier to reallocate resources rapidly toward emerging opportunities without corporate reorganization mandates. The governance mechanism is straightforward: each microenterprise negotiates performance contracts with internal or external customers; units meeting commitments continue independently, units missing targets either restructure or dissolve. This market-based governance permits structural evolution without hierarchical planning, treating organizational architecture as continuously adaptive rather than periodically redesigned.
Capability Portability and Structural Knowledge Transfer
Organizations investing in structural experimentation face challenges transferring learnings across units and contexts. Structural interventions that succeed in one division may encounter difficulties in another despite similar conditions, suggesting knowledge transfer gaps (Szulanski, 1996). Building architectural capability at organizational level requires mechanisms for codifying structural knowledge—documenting what works, under what conditions, and why—and transferring these insights across contexts.
Effective structural knowledge transfer distinguishes between superficial features (specific reporting relationships, team compositions) and underlying principles (decision authority distribution, information architecture, coordination mechanisms). Organizations that successfully propagate structural innovations focus on transferring principles rather than copying specific designs, enabling adaptation to local contexts while maintaining core architectural elements that drive performance benefits.
Key practices include creating centers of expertise that capture structural learnings and coach units through transitions, documenting design patterns that codify successful structural solutions to recurring coordination challenges, establishing communities of practice where managers share experiences with structural experimentation, and developing assessment frameworks that help diagnose when particular structural patterns fit specific contexts.
ING's agile transformation illustrates structured knowledge transfer across organizational units. The Dutch bank piloted squad-based modular structures in one division before expanding enterprise-wide. Rather than mandating identical structures everywhere, ING codified core principles—cross-functional teams with end-to-end accountability, distributed decision authority, transparent performance metrics—while permitting local variation in implementation details. Each division adapted the architectural principles to their specific context: retail banking organized squads around customer journeys, wholesale banking structured tribes around corporate client segments, technology operations configured modules around platform capabilities. A centralized team captured learnings, documented structural patterns, and coached divisions through transitions rather than dictating uniform designs. This approach enabled structural knowledge transfer while avoiding the rigidity that typically undermines restructuring efforts when corporate mandates ignore local contexts. The result was the majority of ING's Netherlands operations transitioning to agile structures within approximately 18 months while maintaining operational continuity and achieving performance improvements.
Conclusion
Organizations face a fundamental choice: acknowledge that structure drives behavior and redesign accordingly, or continue attributing adaptation failures to culture and incentives while leaving hierarchical architectures intact. The evidence strongly supports the former path. Hierarchical structures systematically constrain adaptive behaviors regardless of cultural interventions or incentive adjustments, while structural changes toward flatter hierarchies, modular designs, and distributed decision authority enable behaviors that resist cultivation under pyramid architectures.
The practical implications are clear. Organizations seeking adaptability, innovation, and ecosystem collaboration must begin with structural diagnosis: where does hierarchical architecture create bottlenecks, slow decision cycles, or prevent teams from responding to market signals? Once structural constraints are identified, redesign becomes possible—selectively flattening hierarchies, creating modular units with end-to-end accountability, redistributing decision authority to operational edges, and ensuring information transparency supports distributed decision-making.
Critically, these structural interventions do not require comprehensive organizational transformation or culture change initiatives. Selective experimentation within divisions or product lines can demonstrate benefits and build organizational capability before broader rollout. The modular approaches described—whether Spotify's squads, Haier's microenterprises, or Buurtzorg's self-managing teams—can start small and expand as learning accumulates.
The ecosystems dimension reinforces urgency. As value creation increasingly depends on coordinating across firm boundaries, internal hierarchical structures become even more constraining. Organizations cannot participate effectively in platform economies, innovation ecosystems, or agile supply networks while maintaining pyramid structures that prevent teams from engaging peer-to-peer with external partners. Structural modularity internally creates organizational capacity for ecosystem participation externally—the coordination patterns and decision authority distributions that work across internal unit boundaries translate naturally to cross-organizational collaboration.
For leaders navigating organizational adaptation, the question shifts from "How do we change culture?" to "What structural changes enable the behaviors we need?" This architectural framing focuses attention on actionable levers—decision authority redistribution, information architecture redesign, coordination mechanism adjustment—rather than aspirational culture statements. People follow structure because structure determines what behaviors are possible, practical, and rewarded within formal organizational systems. Change the structure, and behavior changes—whether leaders plan it comprehensively or not.
Research Infographic
References
Baldwin, C. Y., & Clark, K. B. (2000). Design rules: The power of modularity. MIT Press.
Chandler, A. D. (1962). Strategy and structure: Chapters in the history of the American industrial enterprise. MIT Press.
Dyer, J. H., & Nobeoka, K. (2000). Creating and managing a high-performance knowledge-sharing network: The Toyota case. Strategic Management Journal, 21(3), 345-367.
Dyer, J. H., & Singh, H. (1998). The relational view: Cooperative strategy and sources of interorganizational competitive advantage. Academy of Management Review, 23(4), 660-679.
Edmondson, A. (1999). Psychological safety and learning behavior in work teams. Administrative Science Quarterly, 44(2), 350-383.
Galbraith, J. R. (2014). Designing organizations: Strategy, structure, and process at the business unit and enterprise levels (3rd ed.). Jossey-Bass.
Guadalupe, M., Li, H., & Wulf, J. (2014). Who lives in the C-suite? Organizational structure and the division of labor in top management. Management Science, 60(4), 824-844.
Hackman, J. R., & Oldham, G. R. (1976). Motivation through the design of work: Test of a theory. Organizational Behavior and Human Performance, 16(2), 250-279.
Henderson, R. M., & Clark, K. B. (1990). Architectural innovation: The reconfiguration of existing product technologies and the failure of established firms. Administrative Science Quarterly, 35(1), 9-30.
Jacobides, M. G., Cennamo, C., & Gawer, A. (2018). Towards a theory of ecosystems. Strategic Management Journal, 39(8), 2255-2276.
Kanter, R. M. (1977). Men and women of the corporation. Basic Books.
Kotter, J. P. (1995). Leading change: Why transformation efforts fail. Harvard Business Review, 73(2), 59-67.
MacCormack, A., Rusnak, J., & Baldwin, C. Y. (2006). Exploring the structure of complex software designs: An empirical study of open source and proprietary code. Management Science, 52(7), 1015-1030.
Puranam, P., Alexy, O., & Reitzig, M. (2014). What's "new" about new forms of organizing? Academy of Management Review, 39(2), 162-180.
Szulanski, G. (1996). Exploring internal stickiness: Impediments to the transfer of best practice within the firm. Strategic Management Journal, 17(S2), 27-43.
Worley, C. G., & Lawler, E. E. (2010). Agility and organization design: A diagnostic framework. Organizational Dynamics, 39(2), 194-204.
Jonathan H. Westover, PhD is Chief Research Officer (Nexus Institute for Work and AI); Associate Dean and Director of HR Academic Programs (WGU); Professor, Organizational Leadership (UVU); OD/HR/Leadership Consultant (Human Capital Innovations). Read Jonathan Westover's executive profile here.
Suggested Citation: Westover, J. H. (2026). People Don't Follow Strategy—They Follow Structure: Why Organizational Design Drives Adaptation More Than Culture or Incentives. Human Capital Leadership Review, 32(2). doi.org/10.70175/hclreview.2020.32.2.6
