#26 - Decision Intelligence Process

⁠Click here to read the article⁠. The Decision Intelligence (DI) methodology is a structured, nine-step process across five phases designed to enhance data-driven decision-making within organisations. The methodology begins with Phase A: Decision Requirements, which sets the stage by aligning the team around the decision to be made. The first step involves crafting a Decision Objective Statement (A1) - a clear articulation of the core decision without delving into specifics. This statement acts as a guiding principle for the entire process. Subsequently, Decision Framing (A2) takes place, where the team establishes the boundaries, constraints, and desired outcomes of the decision, ensuring its suitability for the DI approach. Phase B: Decision Modelling is where the team visualises the decision-making process. Decision Design (B1) focuses on creating a Causal Decision Diagram (CDD), a blueprint mapping actions to outcomes through intermediate steps, dependencies, and external factors. Decision Asset Investigation (B2) follows, where existing data, models, and expertise are identified and integrated into the CDD, transforming it into a "decision digital twin." Phase C: Decision Reasoning, the team leverages the CDD for simulation and assessment. Decision Simulation (C1) involves creating scenarios and running simulations to predict potential outcomes based on different actions and assumptions. Decision Assessment (C2) then evaluates the model's fidelity, accuracy, risks, and uncertainties, guiding potential refinements and iterations. Phase D: Decision Action marks the transition to real-world implementation. Decision Monitoring (D1) involves systematically tracking the implemented decision's results. By monitoring key metrics, the team can identify deviations, make adjustments, and ensure the decision's continued effectiveness in a dynamic environment. Finally, Phase E: Decision Review focuses on learning and continuous improvement. Decision Artefacts Retention (E1) ensures the preservation of all information and documentation generated throughout the process, creating a valuable knowledge repository. Lastly, the Decision Retrospective (E2) involves reflecting on the entire experience, identifying lessons learned, and refining decision-making processes for the future.The DI methodology provides a powerful framework for navigating complex decisions, leveraging data, expertise, and simulation to make more informed and effective choices. By embracing this iterative and collaborative process, organizations can move beyond simply making decisions to actively managing them, maximizing their effectiveness, and cultivating a culture of continuous learning and improvement.

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