Gadiel Guadarrama · Strategy, Architecture & Advisory
Decision Intelligence & Enterprise AI.
Governed semantic layers. Conversational analytics. Better commercial decisions. I help enterprise leaders connect AI ambition with the systems that make it useful.
Gadiel Guadarrama, M.Sc.
About
An analytics, data, and AI strategy leader working at the intersection of system design and executive judgment.
Gadiel Guadarrama is an analytics, data science, and AI strategy leader whose work focuses on the design of decision systems, structural metrics, and enterprise data architectures that improve how organizations turn information into judgment.
His practice draws on more than a decade of enterprise experience across advanced analytics, business intelligence modernization, analytics engineering, and AI enablement — including commercial-analytics work inside one of the world's largest FMCG beverage ecosystems and enterprise analytics across finance and insurance environments. The throughline is consistent: how organizations design the structural conditions under which analytics, AI, and human judgment compound rather than dissipate.
He is the originator of several frameworks introduced in The Analytics System, including Effort Level, the Customer Love Quotient system, the Driver Truth Model, and the Analytics Nervous System architecture for variation-aware alerting. He writes, consults, and builds at the intersection of advanced analytics, AI, and the architecture of better business decisions.
- Education
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M.Sc. Computer Science & Artificial Intelligence · University of Galway (in progress)
M.Sc. Business Analytics · University College Dublin, Michael Smurfit Graduate Business School
M.Sc. Marketing · Monterrey Institute of Technology, EGADE Business School
B.Eng. Biotechnology · Monterrey Institute of Technology (ITESM) - Practice Areas
- Decision-system architecture · Data foundations & governance · AI & analytics strategy · BI modernization · Analytics engineering · Commercial analytics & RGM
- Selected Frameworks
- Effort Level · Customer Love Quotient · Driver Truth Model · Analytics Nervous System · Value Life Cycle · The Decision-System Architect
Expertise
Six territories of practice.
Each represents a class of problem rather than a fixed deliverable. Engagements move across them depending on the structural maturity of the analytics environment.
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01
Decision-System Architecture
Designing how data foundations, metrics, AI, and managerial judgment connect into a single coherent loop. The system that produces decisions, not the dashboard that reports them.
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02
Data Foundations & Governance
Semantic models, master data, ownership, lineage, and the structural pre-conditions that make downstream analytics trustworthy enough to act on.
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03
AI & Analytics Strategy
Practical AI adoption inside enterprise environments. LLMs, generative tooling, and ML positioned as layers within a system — never as a substitute for one.
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04
BI Modernization
Lakehouse, semantic-layer, and analytics-engineering modernization for organizations whose reporting stack has outgrown its architecture.
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05
Commercial Analytics & RGM
Pricing architecture, promotional effectiveness, customer loyalty, and revenue growth management — the operating end of analytics, where decisions translate directly into economic consequence.
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06
Metrics & KPI Redesign
Replacing decorative KPI suites with structural metrics — the ones that respect causality, surface signal, and survive executive scrutiny.
Selected Work
Systems that run, not slideware.
Explore the live products first. Each system pairs an inspectable end product with the technical implementation behind it — from commercial price intelligence and hierarchical forecasting to decision-system design. Research and forthcoming work remain documented in the full portfolio.
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FMCG Price Intelligence
A daily revenue-growth-management price signal. Shelf prices are normalised to price per litre, matched like-for-like by pack format, and persisted as a versioned fact table. The signature output is the sugar-tax spread — an observable affordability boundary for commercial pricing decisions.
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Hierarchical Demand Forecasting System
A 28-day demand-planning system built around coherent forecasts: store, category and total reconcile before anything is published. Forecast error is translated into expected revenue and asymmetric business cost, because a stockout and an overstock are not the same mistake.
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Matchday Intelligence
A public decision-system application across six European competitions. It reports freshness and provenance explicitly, returns unknown rather than zero when evidence cannot support a statistic, and documents the architectural trade-offs behind the product.
Flagship Intellectual Asset
The Analytics System
Designing Data Foundations, Metrics, and AI for Better Business Decisions.
Publishing October 20, 2026 · Pre-order now on Amazon.
A serious business book on how organizations design the structures through which information becomes judgment, and judgment becomes economic consequence. It is not a book about dashboards, tools, or platforms; AI appears throughout, situated deliberately where it belongs — as a layer within a system, never as the system itself.
Five Acts, twenty chapters. The book introduces six original contributions: Effort Level, the Customer Love Quotient system, the Driver Truth Model, the Analytics Nervous System architecture for variation-aware alerting, the Value Life Cycle, and the role of The Decision-System Architect.
For leaders designing the relationship between data, AI and managerial judgment. Explore the book’s argument →
Published by Wyckham House · Dublin, Ireland.
Paperback ISBN 978-1-0666557-1-7
eBook ISBN 978-1-0666557-2-4
Gadiel Analytics Labs
A working surface for technical documentation, lightweight applications, and framework explainers.
Companion documentation, framework explainers, micro-tools, and Cloudflare-deployed prototypes that extend the writing and the book into things you can actually run. Releases will be added here as they reach production quality.
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L · 01
Planned
Framework explainer pages
Single-page explainers for the named frameworks introduced in the book — diagrams, definitions, and worked examples.
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L · 02
Planned
Metric design micro-tools
Small interactive tools to pressure-test KPI definitions against structural-metric criteria.
Consulting & Advisory
Selective advisory engagements for organizations whose analytics problems are structural.
Engagements tend to address the underlying architecture of decision-making rather than discrete deliverables. Typical entry points include:
Explore services and engagement options →
- Decision-system audits. How analytics, metrics, AI, and managerial judgment currently connect — and where they don't.
- Data-foundations & governance review. Semantic discipline, master data, ownership, and the structural pre-conditions for trustworthy downstream analytics.
- BI & analytics-engineering modernization. Lakehouse, semantic layer, dbt-style metrics-as-code, and the transition from report sprawl to a coherent architecture.
- AI strategy & augmentation design. Where and how to insert AI inside an existing decision architecture without weakening it.
- Executive metrics & KPI redesign. Replacing decorative scorecards with structural metrics that respect causality and survive scrutiny.
A small publishing imprint with the production discipline of a serious studio.
Wyckham House publishes considered, technology-enabled non-fiction. Its inaugural title is The Analytics System. Selected author projects beyond Gadiel's own work are considered on a private referral basis.
Writing
Essays and framework notes on analytics, AI, and decision design.
A long-form writing track focused on structural problems in analytics and AI — what compounds, what dissipates, and why. Anchor essays will be published progressively.
- Sep 2026
Agentic AI governance: reliability, safety & security.
What enterprise leaders should establish before giving analytical agents access to business data, tools and decisions.
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Sep 2026
From dashboards to decision systems.
Why analytical maturity rarely follows from analytical investment, and what to design instead.
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Forthcoming
Metrics as interfaces, not verdicts.
A short argument for treating metrics as cognitive tools rather than performance gavels.
Contact & Collaboration
For advisory work, leadership opportunities, speaking, or collaboration.
Brief introductions are welcome by email or through the professional channels below. Use email for advisory, speaking, media, publishing, or collaboration inquiries; LinkedIn for professional context; GitHub for technical collaboration.
Contact is routed through professional channels by design. Please include the business challenge or leadership mandate in your introduction.
Follow
Public channels.