Published October 20, 2026 · Wyckham House

The Analytics
System

Designing Data Foundations, Metrics, and AI for Better Business Decisions.

A business management book by Gadiel Guadarrama on how organizations turn information into judgment, and judgment into economic consequence.

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§ 01 — About the Book

A reference work on how organizations design decision-grade analytics.

The Analytics System was published October 20, 2026. It is a book on the structural design of decision systems — the foundations, metrics, signal architectures, and governance pathways through which an organization converts information into judgment.

The book is organized in five Acts and twenty chapters. It begins by diagnosing why analytical investment so often fails to translate into better decisions, moves through the foundations and structural metrics that make a real analytics system possible, and culminates in the design of decision architectures and the AI augmentation built on top of them.

It is written for senior analytics, data, BI, and AI leaders, executives responsible for better decision-making, management consultants, and graduate readers in analytics and strategy. It is tool-agnostic, intellectually serious, and intended to remain useful beyond any current technological cycle.

First edition · Wyckham House · Dublin, Ireland
Published October 20, 2026

What is an analytics system? Read a brief introduction →

Amazon US · English edition. Find your market and format →

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§ 02 — The Argument

Organizations do not become analytically mature by accumulating dashboards.

They become mature by designing coherent systems that govern how decisions are made.

Most organizations have invested heavily in data platforms, reporting tools, and AI capabilities, yet decision quality has not improved at the same pace. Dashboards refresh. Models deploy. Metrics multiply. And still, the gap between what analytics reveals and what the organization actually does remains wide.

The Analytics System argues that this gap is not a failure of data, talent, or technology. It is a failure of architecture. The book introduces a unified framework for designing the structural conditions under which analytics, AI, and human judgment compound — across data foundations, metrics, signal systems, decision pathways, causal reasoning, economic contribution, and AI augmentation.

“Visibility is not leverage. The architecture is the system.”


§ 03 — What Readers Will Learn

Four shifts the book is designed to produce.

Diagnose

the structural reasons analytical investment so often fails to translate into better decisions, and why this failure is rarely visible from the dashboard.

Design

the foundations, metrics, and signal systems that make decision-grade analytics possible — including the conditions under which authored metrics earn their place.

Govern

the pathway from insight to decision through architecture rather than meetings, so that detection becomes intervention rather than dissolving into discussion.

Lead

analytics, AI, and human judgment as a single coherent system — and recognize the Decision-System Architect as the institutional role that holds it together.


§ 04 — Frameworks

Original frameworks introduced in the book.

Six contributions that anchor the architecture.

01

Effort Level

A structural metric expressing the share of disposable household income required to sustain a defined pattern of consumption. It measures economic strain as a boundary condition alongside elasticity: elasticity describes how behavior changes as strain manifests; Effort Level measures the strain itself.

02

Customer Love Quotient

A structural metric of customer attachment — the strength of the relational bond between a customer and a brand, distinct from satisfaction alone. It is designed to preserve driver logic and prevent meaningful differences from disappearing inside averages.

Explore Customer Love Quotient →

03

The Driver Truth Model

A framework for separating defensible drivers from narrative convenience in complex commercial systems. Proposed explanations must be quantified, supported by a plausible mechanism, and tested against competing forces before they are treated as decision-grade drivers.

04

The Analytics Nervous System

A variation-aware alerting architecture that determines which movements in performance reach human attention. It escalates deviations when they breach defined thresholds, focusing management attention on structural change rather than ordinary fluctuation.

05

The Value Life Cycle

A model of how analytical capability becomes durable business value: from acquiring and standardizing information through explanation, operationalization, monetization, and the preservation of trust. Each stage depends on the integrity of the one before it.

06

The Decision-System Architect

The role accountable for the coherence of the decision system as a whole — aligning models, metrics, evidence, economic intention, and governance so that analytical capability consistently produces better decisions.


§ 05 — Author

Gadiel Guadarrama.

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. Over more than a decade of enterprise practice, he has worked at the intersection of commercial strategy, advanced analytics and organizational design across international markets. His experience spans machine learning, business intelligence modernization, revenue growth management, market intelligence and data governance.

He is the originator of several frameworks introduced in The Analytics System, including Effort Level, the Customer Love Quotient, the Driver Truth Model, the Analytics Nervous System, and the Value Life Cycle. The book also defines the role of the Decision-System Architect. His broader work centers on how organizations design the structural conditions under which analytics, AI, and human judgment compound rather than dissipate.

His academic background includes M.Sc. studies in Computer Science & Artificial Intelligence at the University of Galway, postgraduate degrees in Business Analytics from University College Dublin and Marketing from EGADE Business School, and an engineering degree from Tecnológico de Monterrey.

Gadiel Analytics gadielanalytics.com · Consulting Explore consulting


§ 06 — Publisher

Published by Wyckham House.

Wyckham House is the publishing imprint behind The Analytics System. It exists to publish serious, atemporal reference works at the intersection of analytics, decision-making, and institutional design — works intended to remain useful beyond a single tool cycle or technological moment.

The Analytics System is its first title.

Editorial enquiries hello@theanalyticssystem.com


§ 07 — Publication

Choose how you read.

The Analytics System is available in paperback and Kindle eBook. Start with Amazon US, or find your local Amazon store.


§ 08 — Follow the Project

Editorial notes on analytics, AI and better decisions.