Theory of Constraints
Where are you blocked?
Performance is governed by the binding bottleneck. COMPASS directs attention to the single most limiting constraint — instead of optimizing everything at once.
Goldratt, 1997Doctoral research · Signum Magnum College · 2026
COMPASS — the Constraint-Oriented Maturity Pathway for AI Strategic Success. An empirically grounded framework that helps mid-sized Mexican companies identify, prioritize, and overcome the constraints blocking AI-driven transformation.
Sources: AWS / Strand Partners, Unlocking Mexico's AI Potential (2025); McKinsey & Company, Superagency in the Workplace (2025)
Mid-sized companies are the backbone of the Mexican economy — the majority of formal employment, a significant share of GDP. Yet their AI adoption is structurally stalled: while 83% of Mexican adopters report revenue growth averaging 16%, only 3% of companies have reached advanced adoption. The gap is not a technology gap.
Existing research and consulting frameworks were built for large enterprises in developed economies — contexts that assume infrastructure stability, deep talent markets, and enterprise-grade budgets. Mid-sized Mexican companies operate under a different constraint profile, and generic playbooks routinely fail them.
COMPASS closes that gap. Developed through a qualitative multiple-case study of five organizations across Mexico City and Guadalajara, it is the first maturity-based, constraint-oriented strategic framework built specifically for this context.
“Constraint-aware, maturity-calibrated strategy — not technology selection — is the primary determinant of AI transformation success.”
— Central conclusion of the study
COMPASS synthesizes three established management theories into a single diagnostic-and-action architecture.
Where are you blocked?
Performance is governed by the binding bottleneck. COMPASS directs attention to the single most limiting constraint — instead of optimizing everything at once.
Goldratt, 1997What do you have?
Sustained advantage comes from resources that are valuable, rare, inimitable, and non-substitutable. COMPASS diagnoses which capabilities you hold — and which you must build.
Barney, 1991How do you move?
Organizations win by sensing opportunities, seizing them with committed resources, and transforming routines to sustain the gains in fast-moving environments.
Teece, 2007Across every case and every maturity level, executive sponsorship and understanding was the single variable most predictive of AI adoption progress. No amount of technical investment compensates for its absence. The study distinguishes commitment (willingness to sponsor) from literacy (understanding what AI can and cannot do in your business) — success requires both.
Universal, but different at every stage — from zero internal AI competence at early-stage firms to specialized role shortages at advanced organizations. AI talent is a textbook VRIN resource: valuable, rare, hard to imitate, impossible to substitute.
The most consistent technical barrier regardless of sector: fragmented architectures, incomplete master data, weak quality standards. COMPASS reframes it — a parallel workstream, not a prerequisite that delays your first pilot.
Rarely the open revolt the literature predicts. It shows up as cautious detachment in regulated sectors, passive non-engagement on the front line, and evaluation paralysis in the boardroom — each demanding a different countermeasure.
COMPASS locates your organization at one of three maturity stages, names the constraints that dominate that stage, and prescribes the responses proven to work there. Diagnostic first, prescriptive second.
Ten questions locate your stage and your likely binding constraint — and hand you the playbook above.
Organizations that encode lessons from each AI project into shared assets — playbooks, templates, SDKs — show dramatically greater adoption durability and scaling capacity.
One high-value, lower-complexity use case. Deploy it. Document the ROI. Use the evidence to fund the next move. Broad digitization pushes without a proof point uniformly stalled.
No single design decision was more consistently associated with success than a designated champion with real authority, leadership endorsement, and co-leadership of AI delivery.
Delivery-only consulting creates dependency. Engagements with structured knowledge transfer, champion co-leadership, and internalization milestones produce durable outcomes.
A qualitative multiple-case study in the Yin (2018) tradition, grounded in an interpretivist paradigm — designed for depth and analytical generalization.
The portfolio includes an embedded longitudinal action case at an advanced-maturity global technology unit, comparative cases at retail, real-estate, and consumer-goods firms, and an AI-native consultancy serving Mexican SMEs. Thematic analysis, member-checking, audit trail, and reflective bracketing support the trustworthiness of the findings.