Our Thinking
The Decision Quality Series
These ten papers are the intellectual foundation of how we work—the decision-science principles behind our Decision Quality practice and the DQ CoPilot tool. Together they cover the full arc of a quality decision as set out in the Strategic Decisions Group's Decision Quality framework: framing, alternatives, information, values, reasoning, and commitment—plus structured dissent, bounded rationality, and the cognitive-science research that makes the framework work in practice. Each is written to be used, not just read.
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Decision Quality
The overview
How six requirements — and the weakest-link principle — decide whether a strategic choice is sound.
The Six Requirements
01 Framing the Strategic Question
Settling what decision you're really making, and what counts as success, before the analysis starts.
02 Creative, Feasible Alternatives
Getting three to five genuinely different options on the table before evaluating any of them.
03 Relevant & Reliable Information
Finding the evidence that bears on the choice, judging what to trust, and knowing when to stop gathering.
Clear Priorities & Trade-offs
04
Turning what the enterprise values into measures you can score against, and stating the trade-off in magnitudes, not slogans.
05
Sound Reasoning
Making the logic that connects evidence to choice explicit and auditable, before the outcome is known.
06
Commitment to Action
Turning a reasoned choice into work people own, resource, and carry through once the room empties.
Extensions & Applications
The research and cross-cutting disciplines that make the method hold.
Productive Conflict & Constructive Dissent
Challenging assumptions and testing reasoning without letting disagreement turn personal.
Bounded Rationality in the Age of AI
What AI changes, and what it leaves untouched, about the limits of managerial judgment.
Two Lenses on Strategic Choice
Combining Decision Quality with hypothesis-driven analysis to get both speed and robustness.
Peer Reviewed Research
Alongside our practitioner work, we conduct academic research on human–AI decision-making with collaborators at the University of Pittsburgh. This research examines how AI changes the quality of strategic reasoning, the cognitive demands placed on decision-makers, and the processes through which people and AI reach better choices.
Liu, Shuqing; Manson, Kerr; Ware, Thomas III; Galletta, Dennis; and Ramasubbu, Narayan, "Shaping The Tool Or Shaping The Mind: An Investigation Of Dual Pathways In Human-AI Strategic Decision-Making" (2026). ECIS 2026 Proceedings. 21.
Liu, Shuqing; Manson, Kerr; Galletta, Dennis; and Ware, Thomas, "Beyond the Recommender: How AI Role Configurations Shape Complex Managerial Decisions" (2026). AMCIS 2026 Proceedings. 8.