From OODA to GDSD: Why Federal Contractors Should Rethink Data, Decisions, and Risk
Federal contractors face a paradox: more data than ever, yet less clarity about what to do with it. In their report, Daniel J. Finkenstadt, Rob Handfield, and Peter Guinto argue that the way organizations—especially those operating in high-stakes public procurements—approach risk, insight, and execution must change. They propose replacing a default reliance on observation-first models (like Boyd’s OODA loop) with a purpose-first framework they call GDSD: Goals, Decisions, Signals, Data. The sequence matters. Rather than admiring data and hoping meaning emerges, GDSD insists that leaders start by specifying the mission outcome, determine what decisions will actually move that outcome, identify the signals that would inform those decisions, and only then curate the minimum viable data needed to generate those signals.
The significance for federal government contractors is immediate and practical. First, the COVID-19 supply chain response revealed how fragmented goals, noisy indicators, and inconsistent data hygiene can derail performance even when volumes of information abound. Contractors working in defense, healthcare, and logistics are often asked to fuse operational realities with regulatory constraints, cybersecurity requirements, and rapid policy shifts. GDSD offers a disciplined way to cut through that complexity—aligning contract performance metrics to clear outcomes (e.g., readiness, continuity of operations, on-time delivery) and then back-propagating what decisions, signals, and datasets are truly necessary. This prevents over-collecting, reduces compliance and cyber exposure, and lowers total lifecycle cost of data management.
Second, the model reframes market intelligence and supplier surveillance. Many contractors struggle to separate spurious vendor claims from actionable risk cues, and to detect fraud, overcharges, or conflicts across sprawling subcontractor networks. By formalizing “signals” (for example, delivery-slip patterns, anomalous vendor overlaps, or tier-2 material chokepoints) before building data lakes, firms can invest in targeted feeds, automate monitoring where it matters, and evidence decisions to contracting officers with traceable logic. That improves negotiation leverage for remedies (e.g., equitable adjustments), strengthens CPARS outcomes, and enhances defensibility in audits, protests, or investigations.
Third, the report links value stream mapping to data strategy, a move with particular resonance under federal performance regimes. When contractors visualize the end-to-end flow—from raw materials to mission use—they clarify where contractual flexibilities (e.g., substitution clauses, surge options, alternate sourcing) should be activated and what telemetry must be gathered to justify them. In a world of Buy American, supply-chain security, counterfeit risk, and cyber attestations, the ability to cite the right data at the right time—rather than collecting everything—can be the difference between proactive adjustments and expensive non-conformances.
Fourth, GDSD encourages cultural change. Contractors frequently operate across siloed functions—capture, compliance, operations, IT, supply chain—each with different appetites for data and different thresholds for action. Starting with goals forces cross-functional consensus about “what good looks like,” which then stabilizes the downstream choices of tools, dashboards, and controls. It reduces the temptation to chase eye-catching but low-utility metrics and replaces them with signal-driven governance that aligns with contract deliverables and risk allocations.
Finally, the model has policy and ethics implications. Excessive data collection invites privacy, security, and false-precision risks that can conflict with federal rules or agency expectations. GDSD’s insistence on sufficiency—only the data needed to generate a validated signal—helps contractors meet obligations like least privilege, data minimization, and verifiability without starving decision-makers. In doing so, it preserves agility for urgent circumstances while maintaining audit-ready discipline.
In short, GDSD is not another analytics buzzword. It is an operating philosophy that reorders how federal contractors translate mission intent into measurable, defensible action. For firms seeking to improve win probability, performance ratings, and risk posture in volatile environments, adopting a goals-to-data pipeline may be the most consequential step they can take.
Disclaimer: This summary is provided for informational purposes only and does not constitute legal, regulatory, or contracting advice. While efforts were made to ensure accuracy, you should consult the source document and qualified advisors before making decisions.