Behavioral Shift Through Decision-Making & Governance Redesign

This case study examines the shift from traditional forecasting and budgeting to dynamic capital allocation within a mid-sized holding company. Conducted over the course of a year through an advisory engagement, the intervention sought to reduce internal political behavior and friction at the managerial level.

Grounded in applied systems science and organizational theory, and informed, among others, by the work of Ackoff, Schein, and Stafford Beer, the author advised the leadership team in diagnosing systemic constraints, exploring possibilities and their trade-offs, and making informed structural decisions on the implementation of the dynamic capital allocation model, requiring a redesign of the decision-making systems and governance structures.

This report follows a naturalistic single-case design informed by practice-based theorizing and contributes to practice-based governance literature by demonstrating how structural redesign can shape behavior, increase transparency, foster real-time learning, and improve organizational coherence.

By enabling capital allocation proposals from all levels and embedding feedback loops, peer review, predefined thresholds, cross-functional evaluation, and statistics-based sampling for audit purposes, the case illustrates a hybrid yet adaptive governance structure that balances centralized oversight with decentralized initiative.

While the initiative was not intended as an organizational culture change effort, notable behavioral and cultural shifts emerged as second-order effects of the new structure. Limitations, contextual boundaries, and considerations for replication are addressed to support both theoretical relevance and practical applicability.

Parraghy, D. (2025). Behavioral Shift Through Decision-Making & Governance Redesign: How Dynamic Capital Allocation Led to Hybrid Decision-Making and Adaptive Governance (Version 1.2). Parraghy Advisory.

This study was produced with the partner organization's explicit consent and pre-publication editorial approval of its scope, framing, and level of detail. Upon publication, all copyright and intellectual-property rights rest solely with Parraghy Advisory. No further amendments or supplementary disclosures may be made without the partner organization's prior written consent, and any information not included herein remains confidential.

This document may be cited under normal fair-quotation standards; reproduction beyond fair use requires Parraghy Advisory's prior written permission. Neither Parraghy Advisory nor the partner organization accepts liability for actions taken on the basis of the material herein.

Intellectual Property and Copyright Notice
© 2025 Daniel Parraghy | Parraghy Advisory. All rights reserved.

Part I: Context & Approach
1. Executive Summary
2. How to Approach This Case
3. Context and Organizational Background
4. Methodology
4.1. Role and Data Collection

Part II: Design & Intervention
5. Theoretical Positioning and Contribution
6. Problem Definition
7. Intervention and System Redesign
8. Intervention Theory: How Structure Shapes Behavior

Part III: Outcomes & Implications
9. Early Outcomes and Behavioral Shifts
10. Strategic Insight and Implication
11. Scientific Perspective on Governance Dynamics
12. Closing Reflection

Part IV: Addendum
13. Author Biography
14. References
15. Appendix

One of my partners permitted me to share the rationale and early outcomes behind their decision to shift away from traditional top-down forecasting and budgeting. Like many mid-sized holding companies, they were spending too much time negotiating who gets what slice of the budget and too little time allocating capital where it created the most value. Internal politics, turf wars, and relational power games were shaping the resource flow more than market data or operational need.

In response, they introduced a dynamic, bottom-up capital allocation model based on clear, shared metrics. Every employee is now permitted to request funding, provided the proposal demonstrates a measurable impact on revenue, cost, throughput, or efficiency. Decision logic is tiered by provability and predefined thresholds, backed by peer validation, cross-functional evaluation, embedded feedback loops, statistics-based sampling for audit purposes, and transparent documentation.

Initial results show increased engagement from frontline employees, spontaneous cross-functional collaboration, and reduced political behavior at the managerial level. While the full rollout is ongoing, the leadership team already considers it a foundational shift in how the organization surfaces relevant information, allocates power, and learns from its decisions and mistakes.

This case study is not intended as a prescriptive model to be copied without context. It presents a systems-level intervention, a redesign of decision-making systems and governance structures, designed to reduce internal politics and influence power distribution, decision dynamics, and interdepartmental alignment. Readers are encouraged to approach the material through multiple disciplinary lenses, including governance science, behavioral economics, organizational science, decision theory, and sociotechnical systems theory.

This case is particularly relevant for the following stakeholders:

• Board members
• C-suite executives
• Founders and serial entrepreneurs
• Organizational designers
• Family Offices and Limited Partners holding majority stakes in holding companies or operating businesses

It explores how funding systems affect collaboration, control, and institutional learning. The case combines real organizational practice with concepts from applied business science and systems thinking. Readers should consider both the practical outcomes and the structural assumptions that guided design decisions, including how metrics, logic, and transparency shape behavior.

The company operates as a holding structure with multiple business units and more than 1,000 employees. While not a global corporation, the size and structural complexity were already enough to trigger the usual challenges: budgeting cycles driven by influence rather than real demand, frontline insights getting lost in translation, and internal systems that reinforced hierarchy over information.

The company followed traditional annual forecasting and budgeting, unit-based allocations, and negotiations between business unit leaders. Over time, this approach turned budgeting into a political exercise: managers used relational capital to secure funding, often prioritizing pet projects while cost centers remained underfunded. Despite internal frustrations, the default response remained structural inertia.

The breakthrough came when the leadership team examined the relational dynamics underneath. It became clear that the budgeting process was not just inefficient; it was shaping the wrong behaviors across the organization. Initial internal testing showed that previously invisible insights began surfacing once the new structure was introduced. The organization began to investigate how many known issues had historically reached decision-makers, and what this implied for upstream visibility.

The author operated during the confidential advisory engagement in a dual role as external advisor and researcher. The primary mandate was to support the leadership team in diagnosing systemic constraints, exploring possible interventions and their trade-offs, and informing structural decisions to reduce internal politics at the managerial level. Once a direction was chosen, the role included providing strategic input on the implementation of the dynamic capital allocation model, which required a redesign of the organization's decision-making systems and governance structures.

The engagement did not follow a formal academic research protocol (e.g., IRB review) but was conducted in accordance with international standards of professional ethics, confidentiality, and methodological transparency consistent with an advisory-partner relationship.

The author was not embedded in operational teams, did not hold decision-making authority, and maintained an independent advisory position throughout the engagement. All insights presented here were developed through iterative discussion and analysis with the partner organization's leadership.

Data sources included:

• Confidential strategic conversations with the executive leadership team across multiple sessions.
• Review of selected internal documents (where permitted).
• Observation of informal relational patterns across the organization, including who communicated with whom (via email, calls, messaging), as well as who spent time together or avoided each other during informal settings such as breaks.
• Review of transcripts and recordings of exit interviews and reflective conversations with selected employees who had previously demonstrated strong engagement and later disengaged, and with individuals who left the organization of their own will.

All findings were shared with and are subject to the editorial oversight of the holding company's leadership team.

This case study was constructed retrospectively with permission from the partner organization. No formal sampling logic or generalizability claim is made; materials and perspectives were selected based on relevance, access, and strategic value as determined by the leadership team. The engagement spanned close to a year and involved extensive strategic discussions with executive leadership, analysis of internal documents, and review of approximately two dozen employee interviews.

Given the advisor's role, the insights reflect an independent, external perspective shaped by advisory interaction rather than participatory observation.

This case study was not originally intended as a formal research project, but emerged from a long-term advisory engagement aimed at helping a partner organization identify and address structural sources of friction. The intervention was shaped by the author's applied expertise in systems science, organizational science, governance and organizational design. While no formal research questions or hypotheses were defined ex ante, the process and outcomes were deeply informed by theory throughout.

The work draws conceptual influence from a range of thinkers, including Russell Ackoff (systems thinking and purposeful systems), Edgar Schein (organizational culture and assumptions), Ludwig von Bertalanffy (general system theory), Ervin Laszlo, Stafford Beer (cybernetics), Tushman & O'Reilly (ambidexterity), Clayton Christensen (disruption theory), Argyris & Schön (organizational learning and double-loop learning), Robert Burgelman (strategy evolution), Peter Senge (learning organizations), Fritjof Capra (complexity and systems), and Donella Meadows (leverage points in systems).

From a methodological standpoint, this is a retrospective embedded case study. The author did not apply formal sampling logic or theory-building protocols during the engagement. However, the unique combination of governance structures, decision-making system, peer accountability, and post-decision feedback mechanisms represents an emergent pattern that, to the author's current knowledge, has not been documented in comparable form elsewhere.

The primary contribution of this case lies in its theory-informed practical application: it demonstrates how abstract principles from systems and organizational theory can be operationalized to redesign core governance structures in complex organizational environments. While generalizability is limited by context and sampling, the case invites future research to explore replication across settings, including under which conditions such designs yield similar or divergent outcomes.

In this regard, the case contributes to both applied systems science, applied organizational science and the practice of governance redesign, particularly for holding companies, founder-led firms, and organizations seeking to transition from static hierarchy toward more adaptive, transparent decision-making systems.

Forecasting and budgeting had shifted from planning tools to mechanisms of positional control. Managers were implicitly incentivized to argue for their own funding share rather than aligning around collective goals. This created spiraling effects across the organization, where underfunded cost centers and support functions could not improve throughput, poorly justified high-cost, low-impact projects consumed disproportionate resources and persisted due to sunk cost fallacies and internal influence, and those closest to real market dynamics had the least influence on capital decisions.

The budgeting process had become a proxy for political power, actively distorting behavior across the organization. The leadership team concluded they were facing a structural governance problem, one that rewarded positional bargaining over the performance of the organization. Any credible solution required redesigning the capital allocation process and neutralizing implicit and explicit incentives that favored power plays over measurable impact.

Subsequent diagnostic work (see Section 9) would later uncover additional visibility gaps, but those were symptoms, not the initial presenting problem.

Rather than incrementally tweaking the budgeting process, the leadership team agreed to initiate a limited-scope trial of a fundamentally different model, shifting from a traditional top-down forecasting and budget model to a bottom-up dynamic capital allocation model. The pilot involved two independent teams per business unit and was grounded in shared outcome metrics.

The headquarters defined four key impact categories:

1. Top-line growth
2. Bottom-line improvement
3. Reduction in defects and rework
4. Throughput or efficiency gains

Any employee in the organization can request funding, provided the proposal fits one of these categories and is supported by evidence or a clear line of reasoning.

To prioritize limited resources effectively, proposals are ranked by their calculated impact on the organization's performance. The higher the anticipated effect, the higher the priority for funding. This ensured that capital was not distributed based on hierarchy or persuasion, but on measurable contribution to the company's strategic and operational goals.

Decision pathways are divided into three tiers:

1. Provable impact

If the proposal demonstrates a clear, measurable effect that exceeds the defined threshold, funding is granted without delay.

2. Borderline cases

If the proposal shows impact close to, but not conclusively above, the threshold, it is treated as a grey zone. A senior leader must review the request, along with at least one leader from another division. They assess the reasoning for and against, ensuring the logic holds up across functional boundaries. All arguments and judgments are documented in a centralized system.

3. Uncertain impact

When the outcome cannot be reliably calculated or falls below threshold, decisions can still proceed under the same scrutiny as borderline cases, provided the rationale is documented and passes peer review.

To ensure accountability, the company replaced its prior RACI structure with a nested feedback loop. Each decision is recorded in a centralized decision database, including:

• The identity of the decision-maker
• The rationale for or against the proposal
• The expected results
• The identity of peer reviewers
• The identity of the senior manager approving the proposal
• The identity of the cross-divisional peer validator
• If sampled for audit, the identity of the sampler

Post-investment, actual results are collected at fixed intervals and compared against initial expectations. To assess performance objectively, results are evaluated using statistical comparisons to historical and similar investments, applying a 95% confidence interval to determine whether observed differences are significant.

Deviations beyond a predefined threshold trigger a structured review. Honest errors of both, omission and commission, are accepted as part of the learning process, but intentional manipulation or malicious behavior leads to disciplinary action, which may or may not include termination and legal consequences.

After the company tested the model with encouraging results, the system was fully implemented in one business unit as a proof of concept. Based on that experience and insights gained, a new model was improved, and a phased rollout was initiated across additional units. Currently, three business units operate under the new model, with full adoption across the holding expected by the end of Q2 2026.

This case study demonstrates how intentional structural redesign can influence behaviors, relationships, and power dynamics. The intervention was not introduced as a neutral process but as a systemic governance shift intended to align individual initiative with systemic accountability and institutional learning. The following scientific and theoretical lenses frame the intervention:

1. Systems Thinking (Russell L. Ackoff)

The partner organization's case reflects Ackoff's principle that systems are not simply the sum of their parts, but defined by their interrelations. By redesigning the decision-making system and governance structures of capital allocation, the leadership team changed how individuals interact with the organization, and with each other.

2. Purposeful Systems (C. West Churchman)

Unlike deterministic systems, this organization is treated as a purposeful system made up of purposeful or purpose-seeking agents acting with intent. Giving each employee the opportunity to request funding based on predefined metrics recognizes their agency and role in shaping outcomes, not just executing tasks.

3. Learning Organizations (P. Senge)

The introduction of a transparent, centralized decision-database creates a formalized feedback mechanism that enables organizational learning. Patterns of success and failure become visible, traceable, and reviewable. This allows the organization to evolve through real-time insight rather than post-hoc analysis.

4. Behavioral Science and Power Dynamics

The redesign was grounded in the realization that resource allocation is inherently political. Thus, structural redesign aimed to realign influence by rewarding proposal quality over position. The shift away from rigid, top-down budgeting disincentivized internal politics and rewarded merit-based proposals.

5. Accountability Without Fear

The organization integrated safeguards to maintain accountability while distinguishing mistakes from misconduct. This encouraged risk-informed decisions over risk-avoidant compliance and reinforced trust and responsibility. By shifting from top-down to bottom-up capital allocation, the intervention removed a key managerial bottleneck. Those who had once relied on political, positional, or relational leverage could no longer steer funding decisions to serve their agendas.

6. Uniqueness of this Case

The intervention is distinguished by its distinctive integration of decentralized capital access with structured peer validation, post-investment-based performance-linked sampling, and centralized decision documentation, which is a convergence not found in professional literature.

While traditional oversight structures often rely on hierarchical gatekeeping and positional authority, this intervention reconfigured governance without eliminating accountability. Instead of removing oversight, it redistributed it through a structured, traceable process that ensured decision quality, transparency, and integrity, without reverting to command-and-control.

Initial Test Phase

As expected, the initial resistance came from those who had the most to lose, mid- and senior managers who controlled profit centers and whose power was tied to budget authority. Despite this, the behavioral shift among the members of the isolated teams was immediate.

Employees began submitting funding requests based on actual market feedback, operational friction, and performance improvement ideas. These were not theoretical suggestions but grounded, tangible, and highly relevant inputs drawn from daily operational experience.

The leadership team was surprised by the volume and speed of proposal submissions. In follow-up conversations, team members explained that many of these issues had existed for months or even years and had already been reported. However, these concerns never reached the executive level, revealing a systemic gap in upward visibility, as key insights were either filtered, aggregated, deprioritized, delayed or lost as they moved up the hierarchy.

In response, to trace the visibility of issues through the system, additional fields were added to the funding proposal request form, asking whether the issue being addressed was new or previously known, and if so, for how long, and whether it had ever been reported.

Phased Rollout

During the rollout in the first business unit, additional resistance emerged. A minority of employees rejected the accompanying changes to their contracts, KPIs, and incentive structures, measures designed to evaluate, reward, and hold individuals accountable for their contributions or lack thereof. Leadership accepted that a small percentage of employees would not adapt to the new model and exit the organization.

The redesigned system was rolled out sequentially across three business units. What caught leadership off guard was the emergence of organic, cross-functional collaboration. Individuals and teams that previously had minimal interaction began partnering to co-develop funding requests. In addition to the four defined categories, these proposals included ideas targeting adjustments to incentives, procedures, processes, and KPIs.

The updated proposal format created a new layer of traceability, allowing leadership to systematically track not only what was being proposed, but also what had previously remained invisible. Combined with the adjustments made to incentives and metrics, it shifted the focus from blame to shared learning. The information gathered was then compared to the number of improvement ideas that had historically reached leadership.

Across time periods, the analysis revealed that, on average, only about 2 percent of operational issues known to frontline employees ever made it to executive leadership. Key insights were being filtered, aggregated, deprioritized, delayed or lost altogether as they moved upward through the hierarchy. The issue was not who decided, but what the system made visible in the first place.

Just as traditional budgeting had shaped defensive, siloed behaviors, the new dynamic capital allocation system enabled transparency, agency, and systems-level insight. The key takeaway for leadership is that structure does not guide behavior alone, but defines what is visible, actionable, and valued within the system.

Budgeting systems are often treated as financial infrastructure, necessary, technical, and neutral. But they are not, as they are part of the social system. They distribute power, define who gets heard, who has influence, and shape what the organization becomes over time.

When capital allocation follows political, positional, or relational power instead of operational priorities and relevance, decision quality suffers and internal politics may thrive. But when funding is linked to shared metrics and transparent reasoning, combined with additional supportive measures, different behaviors appear.

One of these is the initiative from the edge of the organization, when people are systemically empowered to contribute their knowledge and influence decisions directly. Peer validation, feedback (whether honest or not), and real-time learning do not arise by chance. They happen as a direct response to individual initiative and are built into the structure of the system.

This shift allocates power to merit and aligns intent with information, allowing decisions to be judged not just by who made them, but by why and how they were made.

From a systems science perspective, this transformation reflects key principles of cybernetics, organizational learning, decision science, and sociotechnical design:

Cybernetics and Feedback Control
The redesigned system incorporates continuous feedback loops, enabling the organization to detect deviations and respond not only reactively but through structural adjustment (Wiener, 1948).

Double-loop learning
The company is no longer limited to adjusting actions, as it has developed the capacity to revisit and revise its underlying decision premises, metrics, and assumptions. These are core characteristics of double-loop learning as defined by Argyris and Schön (1978).

Decision Science and Behavioral Economics
Concepts from decision science and behavioral economics, such as bounded rationality (Simon), prospect theory (Kahneman and Tversky), and the sunk cost fallacy, offer insight into previous decision patterns. These help explain why the old system reinforced suboptimal behavior and how the redesigned structure reduces the influence of such cognitive biases.

Sociotechnical Coherence
By redesigning workflows and governance mechanisms around complexity and interdependence, the firm better aligns authority with information (Emery and Trist, 1965).

Organizational Culture and Value Inference
Following Edgar Schein's model, observed behaviors and practices surfaced implicit assumptions, most notably that budgeting functioned as a proxy for power. As the underlying logic of the process was redesigned, those assumptions and their associated values began to shift.

Together, these elements create a learning infrastructure that evolves with the organization, reinforcing informed risk-taking, accountability, transparency, and adaptability.

This case study operates within a constructivist-pragmatist paradigm. It assumes that social and organizational realities are co-constructed through interaction and that knowledge is evaluated based on its utility in guiding action. Rather than seeking universal laws, the focus lies on practical adequacy: what works, for whom, and under which conditions.

If some behaviors in an organization are undesirable, they are not necessarily the result of culture alone. As Edgar Schein's work suggests, behaviors reflect the underlying value system and implicit assumptions of the organization. These assumptions can be inferred by observing how things are done, what actions are permitted or prohibited, and what one must implicitly value to act in a certain way.

Resource allocation does not fully reveal what is valued but does uncover one dimension of influence, specifically, how financial power is distributed. True power and influence are multi-layered and cannot be understood from budgets alone. However, by analyzing how decisions are made, which actors are involved, and what structures are in place to reinforce or challenge those decisions, one can begin to trace the systemic patterns that shape behavior.

The author hopes that, at some point in the future, the partner organization may choose to disclose additional currently confidential information, or potentially even allow full disclosure, to enable other organizations, whether operating in similar or entirely different contexts, to experiment and observe whether the results converge or diverge. This hope is grounded in the intent to contribute not only to the advancement of theory and practice, but also to the improvement of everyday working conditions for those exposed to political maneuvering and other dysfunctional organizational dynamics.

What makes this case distinctive is not the adoption of any one theory or practice, but the deliberate integration of multiple principles, governance design, structured accountability, peer review, and feedback loops, into a unified, functional, and adaptive decision-making system.

It illustrates how cultural evolution can emerge from the redesigned decision-making system that shift what is visible, valued, and actionable within the organization.

Daniel Parraghy is the Founder and Managing Director of Parraghy Advisory, a Swiss advisory firm that applies systems and organizational science to advise boards, executives, and institutions on improving decision-making systems, governance structures, and organizational design.

Over the past two decades, he was involved in about seventy organizations, first as a serial entrepreneur (three profitable exits), then as a fractional chief strategy, technology, and product officer, and transformation lead of large-scale initiatives, spanning all growth stages across SaaS, logistics, manufacturing, eCommerce, and deep-tech sectors like BioTech, FinTech, DefenseTech, MedTech, and SatTech.

Parraghy serves on the boards of Chambers Capital Ventures Inc. and an early-stage SatCom defense startup. The author reports no conflicting financial interests.

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This appendix outlines the primary thinkers and conceptual frameworks that informed the structural and behavioral dimensions of the intervention. These frameworks were not applied in a linear or deductive fashion but served as lenses to interpret context, guide redesign decisions, and anticipate system dynamics across the engagement.