Model what happens next before the decision locks in a direction.
Forecast Lab models future scenarios, second-order consequences and risk pathways so leaders can test how a decision may land under different conditions. Decision Visibility traces whose futures are affected and whose are invisible in the modelling.
Scenario modelling and consequence pathways.
Forecast Lab uses AI-supported simulation and structured scenario analysis to test how decisions may play out under different conditions. The Context Engine tests the evidence base. The Risk Trajectory Engine traces how risk evolves, transfers and compounds under each scenario. Decision Visibility surfaces whose futures are affected and what cultural conditions shape the outcome under each pathway.
Explore all Labs →Map the key factors that could change the outcome: market conditions, stakeholder response, regulatory shifts, capability gaps, political conditions and cultural dynamics.
Build structured scenarios based on different condition combinations. AI-supported simulation tests each scenario against evidence, risk trajectory and stakeholder conditions.
Trace cascading effects, unintended consequences and compounding risks that emerge over time. The Risk Trajectory Engine tracks how risks compound and transfer under each scenario.
Convert scenario findings into monitoring requirements, contingency logic and decision conditions. Integrated findings from both practice systems in a single evidence-led output.
Use it when the decision has consequential futures you have not modelled.
Where the decision locks in a direction and leaders need to see what happens under different conditions before commitment hardens.
Where the business case assumes a single pathway and leaders need to see what happens if conditions change.
Where second-order effects, cascading consequences or compounding risks have not been mapped. The Risk Trajectory Engine traces how risk evolves under each scenario.
Where external conditions may shift and the decision needs to be tested against different regulatory futures.
Where the consequences of deployment depend on conditions that may change after go-live. Often pairs with the Decision Transparency Lab.
Where conditions have changed since the original decision and leaders need to reassess the forward pathway. The Retrospective Lab can examine what has changed and why.
Whose futures are affected. What cultural conditions change under each scenario.
Decision Visibility shapes how Forecast Lab models future scenarios. It traces whose futures are affected by the decision, what cultural conditions change under different outcomes, and where Māori futures perspectives extend beyond typical Western strategic planning horizons.
Forecast Lab FAQs
Common questions before using this Lab for forward-looking decisions.
Is this financial forecasting?
No. Forecast Lab models decision consequences, not financial projections. It tests what happens to the decision under different conditions: stakeholder response, regulatory change, capability shifts, cultural dynamics and second-order effects.
How does AI support the scenario modelling?
AI-supported simulation helps test more scenario combinations, surface patterns and model consequence at a pace not possible through manual analysis alone. Human judgement remains responsible for interpreting results and deciding which scenarios matter.
How does the Risk Trajectory Engine apply?
Each scenario carries a different risk trajectory. The Risk Trajectory Engine traces how risk evolves, transfers, compounds and drifts under each scenario, so leaders can see not just what might happen, but how the risks around it will change over time.
How does Decision Visibility apply to forecasting?
Decision Visibility traces whose futures are affected, what cultural conditions change under each scenario, and where Māori intergenerational planning horizons extend beyond typical strategic planning frameworks. It ensures scenarios are not built solely from an institutional perspective.
How does this relate to Retrospective Lab?
The Retrospective Lab examines decisions already made and conditions that have changed. Forecast Lab looks forward. They often work together: patterns from past decisions become inputs to future scenario modelling.
What do we receive?
Outputs may include scenario models, consequence maps, risk trajectory projections, decision conditions, monitoring requirements and contingency logic. Findings are brought together in one clear decision support package.
Need to see what happens next before the decision becomes locked in?
Bring the decision, investment, strategy or programme. Pūtake Labs helps you see the forward pathways before momentum and money are committed.