Generative Decision Intelligence™
Simply put, Generative Decision Intelligence™ combines generative AI, decision science, and adaptive workflows to guide every phase of complex decisions—from framing the need to capturing post‑decision insights. Unlike standalone BI or ML tools, it weaves together quantitative models, qualitative risk factors, and human rationale into one seamless process.
Why Generative DI Matters
Complexity & Uncertainty: Traditional tools stop at analytics; Generative DI carries you through to action.
Holistic Insight: Models non‑quantifiable risks (e.g., human bias, change impact) alongside data.
Speed & Rigor: Accelerates decision cycles with AI‑assisted dynamic activity planning and execution templates, while preserving governance and traceability.
How Generative DI Works
Intent Elicitation: Use AI‑assisted workshops to crystallize objectives, constraints, and success metrics.
Structured Definition: Generate decision criteria, requirements, and rules from Copilot templates.
Adaptive Planning: Build and customize low‑code workflows, ingest diverse data, and simulate scenarios.
Guided Execution: Receive real‑time, AI‑driven prompts and risk‑alerts as you make decisions.
Review & Learn: Gate‑based approvals, audit logs, and auto‑generated “lessons learned” reports close the loop.
Understanding Generative Decision Intelligence™
A decision space is the universe of every possible choice you could make. When only a few options exist, you can list them all—but as complexity grows, relying solely on past experience means you inevitably overlook promising possibilities.
Most complex decisions—whether crafting a product roadmap, configuring a manufacturing process, or planning a marketing campaign—are built from smaller decision components (e.g., feature sets, resource allocations, channel mixes) and a finite set of assembly rules (how components combine). By modeling these underlying components and their composition grammar, you capture an otherwise unmanageable decision space in a concise, structured form.
Generative Decision Intelligence™ uses advanced search algorithms (like genetic algorithms) to:
Interpret your decision‑space model—the defined components and rules
Generate new alternatives by recombining components toward your objectives
Surface dominant solutions—options that satisfy all evaluation criteria and aren’t outperformed by any other
Illustration: When selecting a new EV powertrain, instead of enumerating every conceivable combination of battery type, motor size, and control software, you define each component and how they fit together. GDI then explores that space, proposing novel, high‑performance configurations you might never have considered.
Ensures you move beyond familiar territory to discover superior, viable solutions across any complex decision landscape.
The Power of GDI
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Creating a Multitude of Alternatives
GDI empowers decision-makers to access a vast array of choices beyond what conventional analysis can offer. Instead of a limited number of preconceived alternatives, the system generates numerous possibilities, enhancing decision quality by expanding the range and depth of options.
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Providing Contextual Understanding
GDI systems consider various factors that influence decisions, such as time, location, political climate, socio-economic factors, and more. They process these complexities to create contextually grounded alternatives, increasing the likelihood of success.
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Iterative Learning
Like all intelligent and adaptive systems, GDI continually learns from feedback, refining the generated alternatives over time. This ensures a continuous improvement in decision quality.
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Set-based Design Support
GDI facilitates set-based design decision-making methodology by expanding the set of alternatives and systematically aiding evaluation and elimination of options.
Real‑World Use Cases
Market Research Studies
Automate competitive scans and customer segmentation with AI‑augmented reports.
Strategic Choice Projects
Evaluate powertrain or platform alternatives under regulatory, cost, and risk constraints.
Decision Programs
Orchestrate multi‑project portfolios—e.g., new EV launches—tracking interdependencies and outcomes.