Map stakeholder power, trust and alignment before the decision depends on people.
Engage Lab reveals the human landscape around a decision: who holds power, who carries influence, who will resist, who is absent and what conditions shape support or opposition. Decision Visibility surfaces whose voice carries weight, whose is missing and what mandate each voice holds.
Stakeholder intelligence for consequential decisions.
Engage Lab maps stakeholder power, trust, resistance, influence and alignment so leaders can see the human landscape around a decision before approval or engagement begins. The Context Engine tests the evidence behind stakeholder claims. The Risk Trajectory Engine tracks how stakeholder risk may evolve after commitment.
Decision Visibility reveals whose voice carries weight, whose is absent, what mandate each voice holds, and whether Māori stakeholder structures (which do not map neatly onto Western stakeholder categories) are genuinely represented in the decision process.
Explore all Labs →Identify affected groups, influencers, decision-makers, blockers, allies, resisters and silent stakeholders. Include iwi, hapū, whānau, rūnanga, mandated bodies, kaumatūa and rangatahi where Māori interests are in scope.
Assess each group’s power, influence, trust level, likely position and conditions for support or resistance. Decision Visibility surfaces hidden and invisible power alongside formal authority.
Model how different stakeholder groups may respond under different conditions. AI-supported simulation tests engagement approaches, timing and sequencing before they are tried in practice.
Stakeholder map, engagement logic, sequencing, risk mitigation and decision conditions. Integrated findings from both practice systems in a single evidence-led output.
Use it when the decision depends on people you have not yet mapped.
Where the decision needs stakeholder confidence that has not been tested or where opposition may surface after approval.
Where engagement needs to be proportional, credible and grounded in a real understanding of the stakeholder landscape. Often pairs with Civic Lab.
Where adoption depends on people whose alignment has not been assessed. Often pairs with Change Lab.
Where opposition, confusion or disengagement is emerging and leaders need to understand the conditions driving it.
Where the decision depends on external parties whose power, interests and alignment need to be understood before commitment.
Where confidence has been lost and leaders need to understand what happened, who was affected and what conditions would support recovery. The Retrospective Lab can help learn from what went wrong.
Whose voice carries weight. Whose is absent. What mandate each voice holds.
Decision Visibility shapes how Engage Lab examines stakeholder landscapes. It reveals power dynamics, cultural conditions and structural exclusion that traditional stakeholder mapping misses. Where Māori interests are in scope, the Kaupapa Methodology Module governs how stakeholder engagement is conducted.
Engage Lab FAQs
Common questions before using this Lab for stakeholder-sensitive decisions.
Is this stakeholder engagement or stakeholder analysis?
Analysis. Engage Lab maps the stakeholder landscape and tests engagement approaches before they are tried. It does not run the engagement itself, though it can design the architecture, sequencing and risk mitigation for one.
How does Decision Visibility apply to stakeholder work?
Decision Visibility reveals whose voice carries weight, whose is absent, what mandate each voice holds and whether Māori stakeholder structures are genuinely represented. It shapes what the Lab examines and how, from the first conversation.
How does this relate to Civic Lab?
Civic Lab focuses on public consequence, community trust and civic legitimacy. Engage Lab focuses on the broader stakeholder landscape. Complex decisions with public consequences often need both.
How does this relate to Change Lab?
Change Lab tests whether people can adopt the change. Engage Lab tests whether the people the decision depends on are aligned, resistant or absent. Adoption-sensitive change may need both.
How does the Risk Trajectory Engine apply?
Stakeholder risk evolves after commitment. The Risk Trajectory Engine tracks where risk transfers to stakeholder groups who were not at the table, where compound stakeholder risks may emerge, and where the organisation has drifted from its stated engagement commitments.
What do we receive?
Outputs may include a stakeholder landscape map, power and alignment assessment, response scenario models, engagement architecture, decision conditions and recommended sequencing. Findings are brought together in one clear decision support package.
Need to see the stakeholder landscape before commitment hardens?
Bring the decision, programme or engagement challenge. Pūtake Labs helps you see the human landscape before momentum, money and trust are committed.