Research

Data Management Platforms and Audience Building

By Michael Koved, May 21, 2018

Available to Research & Advisory Network Clients Only

To identify customers and potential customers, Marketers use a Data Management Platform (DMP) to build audiences and track campaign results. This paper provides an overview of how DMPs work and share practitioner tips for leveraging DMPs and getting the best from yours.

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Organizing Analytics

By Robert Morison, May 16, 2018

Available to Research & Advisory Network Clients Only

This research brief describes and offers guidance on:

  • The fundamental goals of organizational structure
  • Six basic models for organizing analytics
  • Mechanisms for coordinating across organizational boundaries
  • Design variables that enable or constrain organizational shape
  • How analytics organizations commonly evolve
  • How to assess readiness for greater centralization
  • Structural variations driven by technological and business change
  • Questions to ask in planning your next structural move

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Enterprise AI Primer: Build on Your Strengths

By Thomas H. Davenport, Kris Hammond, Apr 16, 2018

Available to Research & Advisory Network Clients Only

This brief is based on the premise that there’s a general confusion when it comes to AI impact, strategy, investment options, and even terminology. A significant factor is that for many companies, AI can and should be viewed as a natural progression of their existing business analytics capabilities. We believe that positioning AI as a natural evolutionary outgrowth of analytics, thus benefitting from already established analytics capabilities, provides the best and easiest path for most companies to successfully “step into” AI.

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How to Self-Assess the UI/UX Design of Analytics Solutions

By Brian O’Neill, Apr 05, 2018

Available to Research & Advisory Network Clients Only

As internally developed analytics solutions become increasingly sophisticated, analytics teams are faced with many of the design challenges seen in commercial, analytics-driven software. After years of working with a variety of different clients on analytics-driven software products, the display of quantitative data, and dashboards, Brian O’Neill developed a set of axioms you can ask yourself to help you begin evaluating the design of analytics solutions for internal customers.

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Analytics Maturity Transition Guide: Stage 3 to Stage 4

By Robert Morison, Mar 14, 2018

Available to Research & Advisory Network Clients Only

Advancing the analytical maturity of an enterprise requires coordinated progress across a variety of capabilities. We track enterprise maturity with a 5-stage model, and we group capabilities into the five elements of the DELTA framework – Data, Enterprise, Leadership, Targets, and Analysts. These two models, introduced in Competing on Analytics and Analytics at Work, continue to stand the test of time. This guide focuses on the core DELTA components and presents context and recommendations for moving from maturity Stage 3, “Analytical Aspirations,” to Stage 4, “Analytical Companies.”

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Analytics Maturity Transition Guide: Stage 2 to Stage 3

By Robert Morison, Mar 07, 2018

Available to Research & Advisory Network Clients Only

Advancing the analytical maturity of an enterprise requires coordinated progress across a variety of capabilities. We track enterprise maturity with a 5-stage model, and we group capabilities into the five elements of the DELTA framework – Data, Enterprise, Leadership, Targets, and Analysts. These two models, introduced in Competing on Analytics and Analytics at Work, continue to stand the test of time. This guide focuses on the core DELTA components and presents context and recommendations for moving from maturity Stage 2, “Localized Analytics,” to Stage 3, “Analytical Aspirations.”

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Analytics Maturity Transition Guide: Stage 1 to Stage 2

By Robert Morison, Feb 28, 2018

Available to Research & Advisory Network Clients Only

Advancing the analytical maturity of an enterprise requires coordinated progress across a variety of capabilities. We track enterprise maturity with a 5-stage model, and we group capabilities into the five elements of the DELTA framework – Data, Enterprise, Leadership, Targets, and Analysts. These two models, introduced in Competing on Analytics and Analytics at Work, continue to stand the test of time. This guide focuses on the core DELTA components and presents context and recommendations for moving from maturity Stage 1, “Analytically Impaired,” to Stage 2, “Localized Analytics.”

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Operationalizing Analytics for Intelligent Fraud Detection and Case Management

By Michael Ames, Robert Morison, Jan 31, 2018

Available to Research & Advisory Network Clients Only

Fraud is widespread and continues to grow, especially online. It’s a major problem in a variety of industries and government agencies far beyond the familiar areas of financial and retail fraud, where credit card information is compromised and fraudsters use it for online purchases. The problem worsens as criminals get more organized and technologically sophisticated and operate at greater scale. As fraudsters innovate and scale up, fraud prevention and investigation become more challenging, and advanced analytics become a bigger part of the solution.

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Improving Analytics Measurement 

By Robert Morison, Jan 10, 2018

Available to Research & Advisory Network Clients Only

This five-part research brief is designed to assist analytics leaders in taking stock of their analytics measurement programs, recognizing and filling any significant gaps, and raising their ability to communicate with the business and its leadership about analytics. This brief provides background and summarizes results and recommendations across the four measurement categories. A separate brief on each category details its findings. In this research, we surveyed 19 enterprises and asked, in each of the four categories, what metrics they use, what they’re good at and what they struggle with, and whether their measures incorporate five common methods or inputs: trends over time, internal customer views, external customer views, external benchmarks, and lessons learned.

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Improving Analytics Measurement Part 5 of 5 – Analytics Health

By Robert Morison, Dec 20, 2017

Available to Research & Advisory Network Clients Only

Analytics Health metrics address the question, “Are we maintaining and building the right capabilities to meet business demand and perform better in the future?” These capabilities can include people and skills, processes for execution and management, technologies and techniques, and data assets for analytics.

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