Cover of Competing on Analytics by Davenport and Harris, featuring abstract data visualization imagery on a clean editorial background

Pages

243

Published

2007

Data Analytics ✨ New

Competing on Analytics

How Organizations Build Competitive Advantage Through Data and Analytics

Learn how leading organizations embed analytics into their strategy and use data as a genuine competitive weapon, not just a reporting tool.

J Jeanne G. Harris T Thomas H. Davenport

Published in 2007, this landmark work by Thomas H. Davenport and Jeanne G. Harris examines how a select group of companies have turned data and statistical analysis into a core strategic differentiator. Drawing on dozens of real case studies, the book maps the five stages of analytical maturity and gives executives and practitioners a clear framework for building an analytics-driven organization — from securing leadership commitment to scaling analytical talent and infrastructure.

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About this book

Most organizations collect data. A small number of them compete on it. In this book, Thomas H. Davenport and Jeanne G. Harris study the companies that have made analytics a source of sustained competitive advantage — businesses like Capital One, Marriott, and the Oakland Athletics — and distill what separates them from peers who treat reporting as an end in itself.

The central argument is precise: when analytical capability is embedded in strategy, supported by senior leadership, and executed at scale, it becomes genuinely difficult for rivals to replicate. The authors call these organizations "analytical competitors," and they are not defined by the size of their IT budget. They are defined by the questions they ask, the decisions they delegate to data, and the discipline they apply to measuring what matters.

The book introduces the Analytics Competitor framework and the five-stage Analytical Maturity Model, which gives any organization — from a regional insurer to a global retailer — a practical map of where it stands and what it must do to advance. Davenport and Harris are specific about the four building blocks that separate stage-five competitors from the rest: distinctive analytical capabilities tied to a strategic target, enterprise-wide data and technology infrastructure, a critical mass of analytical talent, and visible executive sponsorship.

You will also find candid treatment of the barriers most organizations actually face: siloed data, scarce quantitative talent, political resistance from managers who distrust models, and the temptation to confuse dashboards with insight. The authors do not paper over these difficulties; they explain how leading firms worked through them.

  • Case studies drawn from financial services, retail, sports, hospitality, and healthcare show how the principles apply across sectors
  • The Analytical Maturity Model gives you a precise language for diagnosing your organization's current state
  • Talent strategy guidance covers how to hire, retain, and organize analysts for maximum impact
  • Technology and data infrastructure requirements are explained without vendor advocacy
  • The leadership chapter addresses what executives must do differently — and stop doing — to make analytics a real priority

This book was published in 2007, which means some of the technology context reflects that era. What has not dated is the strategic logic: competitive advantage from analytics depends far more on organizational choices than on any particular tool or platform. Readers who internalize that argument will apply it just as readily to cloud data warehouses and machine learning pipelines as to the systems described in the original case studies.

🎯 What you'll learn

  • Distinguish between organizations that use data for reporting and those that genuinely compete on analytics
  • Apply the five-stage Analytical Maturity Model to diagnose your own organization's current capabilities
  • Identify the specific strategic target your analytics investments should reinforce
  • Build the four organizational building blocks — strategy, data, technology, and talent — that analytical competitors share
  • Recognize and address the political and structural barriers that prevent analytics from influencing real decisions
  • Structure analytical talent across a business to maximize leverage without creating isolated centers of excellence
  • Make the executive-level case for sustained investment in analytics as a strategic, not operational, priority

👤 Who is this book for?

  • Business leaders and executives who want to understand how data-driven strategy translates into measurable competitive advantage
  • Data and analytics managers looking for a framework to diagnose where their organization sits and what it should prioritize next
  • Strategy consultants and MBA students who need a rigorous, case-study-backed model for analytical maturity
  • Technical practitioners — data engineers, analysts, data scientists — who want to understand the organizational and strategic context their work operates in
  • Chief Data Officers and analytics function heads building the case for executive sponsorship and investment

Table of contents

  1. 01

    The Nature of Analytical Competition

    Introduces the concept of the analytical competitor and explains why some organizations convert data into durable advantage while others merely collect it. Sets up the strategic framework the rest of the book builds on.

  2. 02

    What Makes an Analytical Competitor

    Examines the specific characteristics — leadership commitment, enterprise scope, and distinctive analytical capabilities — shared by the companies that consistently outperform through data-driven decisions.

  3. 03

    Analytics and Business Performance

    Presents empirical evidence linking analytical maturity to financial and operational outcomes, drawing on research across multiple industries to show what the performance differential actually looks like.

  4. 04

    Competing on Analytics in Your Industry

    Applies the analytical competition framework to specific sectors including financial services, retail, sports, and healthcare, showing how the same strategic logic produces different tactical priorities depending on the competitive landscape.

  5. 05

    The Analytical Maturity Model

    Introduces the five-stage model — from analytically impaired through analytical competitor — and gives you a diagnostic tool for placing your own organization on the spectrum and identifying the next stage's requirements.

  6. 06

    Building an Analytical Capability

    Explains the practical steps organizations take to advance their maturity, covering data infrastructure, technology choices, and the governance structures that keep analytical efforts aligned with strategic goals.

  7. 07

    Managing Analytical People

    Addresses the talent challenge directly: how to identify, hire, retain, and organize quantitative professionals, and how to manage the cultural tension between analytical and intuition-driven decision-makers.

  8. 08

    The Future of Analytical Competition

    Looks at how analytical competition is likely to evolve as data volumes grow and tooling matures, and argues that the organizational and leadership factors — not the technology — will remain the decisive differentiator.

Frequently asked questions

Do I need a technical or quantitative background to get value from this book?

No. The book is written for business leaders and strategists, not data scientists. Quantitative concepts are explained in plain language and the emphasis is on organizational strategy, not statistical methods.

The book was published in 2007 — is it still relevant?

The strategic framework and organizational arguments have held up well and are still widely taught in business schools. Some technology examples reflect 2007-era tools, but the core logic about leadership, talent, and competitive positioning applies directly to modern analytics environments.

Is this a case-study book or does it provide actionable frameworks?

Both. Case studies from companies like Capital One, Marriott, and the Oakland Athletics illustrate the arguments, but the book also provides explicit frameworks — most notably the five-stage Analytical Maturity Model — that you can apply to your own organization.

How long does it take to read?

At 243 pages, most readers finish it in four to six hours. The writing is dense with argument rather than filler, so it rewards a second pass if you are applying the maturity model diagnostically.

Is this book suitable for a team or executive reading group?

It works well in that format. Each chapter addresses a distinct aspect of analytical strategy, making it practical to assign chapters to individual leaders and use the maturity model as a shared discussion framework.

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