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Decision Rights

Decision Rights in 2026: Frameworks, Governance Tools, and the Layer That’s Missing

Organizations invest heavily in defining who decides what. Frameworks assign roles. Governance tools track authority. Decision logs capture outcomes. But none of them answer the question that actually matters: did the decision hold?

By Growth Wise Research Team 11 min read

Decision rights is one of the most established concepts in organisational design. The premise is straightforward: when it’s clear who has the authority to make which decisions, organisations move faster and with less friction. When it’s unclear, decisions stall, get relitigated, or get made by whoever happens to be in the room.

The premise is correct, and the gap between necessary and sufficient is where most organisations lose more than they realise.

The decision rights landscape

Over the past two decades, the decision rights space has developed three distinct layers. The first assigns authority through frameworks. The second operationalises decision processes through governance tools. The third logs outcomes through capture tools. All three are useful. None of them are sufficient. And the gap between the third and reality is where decision failures accumulate.

Layer 1: Frameworks (defining who decides)

RACI (Responsible, Accountable, Consulted, Informed) was one of the first decision rights frameworks to gain traction. It maps decisions across a matrix, assigning each role a letter. It’s intuitive and portable. Every organization understands what it means to be “accountable” for a decision.

DACI (Driver, Approver, Contributors, Informed), popularized by Atlassian, updated the framework for modern teams. DACI treats driving to closure as a distinct role: not just being responsible, but actively moving the decision forward. It has been adopted widely in tech organizations where velocity matters.

RAPID (Recommend, Agree, Perform, Input, Decide), developed by Bain, focuses on the sequence of decision-making. It maps who recommends, who agrees, who performs, who provides input, and who decides. It’s particularly useful for organizations wrestling with delegation and consensus.

OVIS (Own, Veto, Influence, Support), BCG’s more recent contribution, addresses the reality that in matrix organisations, decision authority is rarely binary. It acknowledges that multiple stakeholders have legitimate but different levels of influence, and tries to make those gradations explicit.

SPADE (Setting, People, Alternatives, Decide, Explain) developed at Square and spread across the tech sector. Its differentiator is that it’s a process, not just a role assignment. It requires the decision-maker to document the setting (context and constraints), identify alternatives, make the call, and explain the reasoning.

These frameworks reduce ambiguity. They make it possible to have a conversation about how a particular decision should be made before you’re in the middle of trying to make it. They are blueprints, not execution.

Layer 2: Governance tools (operationalising decision processes)

Holaspirit (by Talkspirit) enables dynamic role mapping and transparent decision processes across 450+ organizations in 30 countries. It gives structure to how roles are assigned, decisions are tracked, and authority flows through organizations in real time.

Loomio originated in New Zealand’s civic movement as a tool for participatory democracy. It’s open source, GDPR-compliant, available in 30+ languages, and designed for groups that need to move from discussion to decision with genuine input. It operationalizes the participatory aspects of decision-making.

Murmur and similar tools implement the “advice process”: a lighter-weight decision-making model where anyone can make a decision as long as they’ve sought advice from those affected and those with expertise.

These governance tools solve a real problem: they operationalize decision processes so they’re not just ideas, but workflows. They log who was involved, what the timeline was, what the decision was. They create an artifact where before there was only conversation.

Layer 3: Capture tools (logging what was decided)

Atlassian Confluence lets teams embed DACI templates in their decision documentation, creating a searchable archive of who decided what and when.

Fellow turns meeting notes into decision logs, capturing action items, owners, and due dates alongside the decisions those meetings produced.

Hypercontext (acquired and rebranded as Spinach AI) automatically processes meeting outcomes and logs them alongside the organizational structures that own different decisions.

Notion decision logs let organizations maintain single sources of truth for decisions: who decided, when, what changed, what the decision was based on.

These capture tools solve the documentation problem. They answer: “What did we decide?” They create accountability through visibility. And they are valuable.

The structural gap

All three layers (frameworks, governance tools, and capture tools) share the same blind spot. They instrument the authority structure, not the coordination quality.

DACI says Sarah is the Driver. It doesn’t show whether Sarah actually drove to closure, or whether she let the meeting get hijacked by whoever spoke loudest. It doesn’t show whether she was exercising judgment or deferring to whoever sounded most confident.

The governance tool records that consensus was reached with no objections. It doesn’t show whether the absence of objections means genuine agreement, or whether people disengaged because they’d already decided the outcome was predetermined.

The decision log records the choice. It doesn’t show whether the decision held through the next sprint, or whether it was quietly reversed in a Slack thread two days later because new information emerged, or because the decision owner lost confidence, or because the shallow execution problem meant nobody ever actually committed to it.

Where decisions actually fail

Research from the Collective Intelligence Labs at the Stockholm School of Economics studied teams across 22 organisations. The research found that the teams whose coordination goes unobserved degrade. And the teams most at risk overrate their coordination quality.

Is the Driver actually driving? Is the Approver exercising judgment, or rubber-stamping because they’re busy and trust the Driver has done their homework? Are the Contributors actually contributing, or are they sitting in meetings waiting for the decision they know has already been made? Are the people marked Consulted actually getting consulted, or is that a formality?

These are coordination quality questions. No framework answers them. No governance tool surfaces them. No decision log captures them.

The verification layer

Decision reliability infrastructure addresses this. It instruments the coordination layer, making visible whether the decision rights architecture is actually functioning in practice.

The questions it asks are different in kind from the ones frameworks and governance tools ask. Who is accountable becomes: are the accountable people actually exercising that accountability? Was there consensus becomes: did the team genuinely integrate diverse perspectives, or did someone check the box? What did we decide becomes: what did we decide, and is it holding?

It completes the stack rather than replacing any part of it. Frameworks, governance tools, and capture processes all remain. What changes is whether you can trust them.

The AI governance dimension

Regulators are now asking the same question. The EU AI Act goes into enforcement in August 2026. CCPA ADMT regulations are expanding. Both require that human decision rights be genuinely exercised, not just formally assigned.

Alan Knox argues that regulators will increasingly distinguish between the checkpoint (the moment where a human has to approve something) and the decision owner (the person actually making the call). A DACI chart that says Sarah is the Approver satisfies the checkpoint requirement. Whether Sarah actually decided, or simply authorized what the Driver recommended, is a different question entirely.

Regulators won’t accept a DACI chart as evidence of genuine human oversight. They’ll want to see that the decision owner was actually present in the decision. That they integrated input. That they exercised judgment. That they were willing to override the recommendation if their judgment diverged.

The complete decision rights stack

Define → Operationalise → Capture → Verify

Define: Assign authority through frameworks (RACI, DACI, RAPID, OVIS, SPADE). Make it clear who decides what.

Operationalise: Use governance tools (Holaspirit, Loomio, Murmur) to make decision processes repeatable. Build them into workflows, not conversations.

Capture: Log decisions (Confluence, Fellow, Hypercontext, Notion). Create accountability through documentation.

Verify: Instrument the coordination layer. Show whether the authority structure is actually being exercised.

Without the fourth layer, the first three are aspirational. With it, they become trustworthy.

Decision rights are the formal or informal rules that determine who has authority to make specific decisions in an organisation — and who must be consulted, informed, or whose approval is required. When decision rights are clear, organisations move faster and revisit fewer choices. When they are ambiguous, decisions stall, get made by whoever is loudest in the room, or get relitigated after the fact. Most frameworks define decision rights. Fewer verify that those rights are actually being exercised.

Summary

The decision rights discipline has three mature layers: frameworks that assign authority (RACI, DACI, RAPID, OVIS, SPADE), governance tools that operationalise decision processes (Holaspirit, Loomio), and capture tools that log outcomes (Confluence, Fellow, Notion). All three are useful. All three share the same blind spot: they instrument the authority structure, not the coordination quality. Decision reliability infrastructure adds the verification layer — showing whether assigned authority is actually being exercised. With EU AI Act enforcement arriving in August 2026, that verification is no longer optional.

Frequently Asked Questions

What are decision rights frameworks?

Decision rights frameworks are tools for assigning and clarifying authority in organizations. RACI (Responsible, Accountable, Consulted, Informed), DACI (Driver, Approver, Contributors, Informed), RAPID (Recommend, Agree, Perform, Input, Decide), OVIS (Own, Veto, Influence, Support), and SPADE (Setting, People, Alternatives, Decide, Explain) are among the most widely adopted frameworks. Each provides a way to map decisions, define roles, and reduce ambiguity about who has decision authority.

What tools help track decision rights?

Governance tools operationalize decision processes and document outcomes. Holaspirit (used by 450+ organizations across 30 countries) enables transparent role mapping and decision tracking. Loomio (originated from New Zealand’s civic movement, open source, GDPR-compliant, available in 30+ languages) facilitates collaborative decision-making. Tools like Atlassian Confluence, Fellow, Hypercontext, and Notion help capture and log decisions. However, these tools operationalize and document decisions but don’t verify whether the coordination quality behind those decisions is actually sound.

Why do decision rights frameworks fail?

Decision rights frameworks define authority structure, but there’s a critical gap between assigned authority and exercised authority. The Driver doesn’t actually drive to closure. The Approver rubber-stamps without exercising judgment. Contributors marked for consultation are never meaningfully consulted. This shallow execution problem — where roles are assigned on paper but not actually performed — is where most organizational decision failures occur.

What is decision reliability infrastructure?

Decision reliability infrastructure instruments the coordination layer to show whether decision rights are actually being exercised in practice, not just formally assigned. Rather than replacing frameworks, tools, or capture processes, it makes visible the gap between documented decision authority and actual coordination quality — showing whether teams are genuinely integrating knowledge and exercising the authority assigned to them.

How do decision rights relate to AI governance?

As AI governance regulations expand — including EU AI Act enforcement (August 2026) and CCPA ADMT requirements — regulators require evidence that human decision rights are genuinely exercised, not just formally assigned. A DACI chart alone is insufficient for compliance. Organizations must be able to verify that the decision owner is actually making decisions, checkpoints are being observed, and human oversight is genuine. This makes decision reliability infrastructure a compliance requirement, not just an operational preference.

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