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Advanced Measurement Strategies for Decision-Making

via Coursera

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Details

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Provider

Coursera
Pricing

Paid Course
Languages

English
Certificate

Certificate Available
Effort

6 weeks, 1 hour a week
Sessions

Self-Paced
Level

Advanced
Subtitles

English

Part of

How to Measure Anything: Finding the Intangibles

Overview

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Explore advanced strategies for measuring preferences, attitudes, and organizational performance, culminating in a universal framework for applied information economics. This course equips learners to tackle complex measurement challenges in management and beyond. You’ll learn sophisticated techniques, including sampling, Bayesian analysis, and evaluating subjective factors like preferences and human judgment. The course covers regression modeling, standardizing evaluations, and critically assessing measurement methods. It concludes with practical management applications and introduces a universal measurement approach that synthesizes all previous concepts, preparing you for real-world decision-making. With in-depth readings, real-world case studies, and targeted quizzes, this course fosters a comprehensive understanding of advanced measurement tools and their application in management. Learners will be guided to apply a holistic measurement framework to complex organizational challenges. This course is part three of a three-course Specialization designed to provide a comprehensive learning pathway in this subject area. While it delivers standalone value and practical skills, learners seeking a more integrated and in-depth progression may benefit from completing the full Specialization. This Specialization is based on the book How to Measure Anything: Finding the Value of “Intangibles“ in Business, by Douglas W. Hubbard. From How to Measure Anything Copyright © 2014 by Douglas W. Hubbard. All rights reserved. Used by arrangement with John Wiley & Sons, Inc.

Syllabus

Sampling Reality: How Observing Some Things Tells Us about All Things

This module introduces key sampling techniques for estimating population parameters, interpreting confidence intervals, and understanding statistical significance with limited data. Learners will explore practical examples, address sampling bias, and gain foundational skills in regression analysis for uncovering relationships in data. The module emphasizes informed decision-making when working with incomplete or imperfect information.

Bayes: Adding to What You Know Now

This module introduces Bayesian methods for integrating prior knowledge with new data to improve statistical inference and decision-making. Learners will explore real-world applications, such as market testing and risk assessment, and address common misconceptions about Bayesian reasoning. The module also examines the philosophical debates surrounding the use of prior probabilities.

Preference and Attitudes: The Softer Side of Measurement

This module delves into the complexities of measuring human preferences and attitudes, focusing on subjective valuation, risk tolerance, and the quantification of trade-offs in decision-making. Learners will explore practical tools and frameworks for translating intangible preferences into actionable data, and understand how these measurements inform both personal and business decisions.

The Ultimate Measurement Instrument: Human Judges

This module explores how human judgment serves as a measurement tool, examining its strengths, limitations, and the impact of biases and heuristics. Learners will discover structured models like Rasch and the Lens Model to enhance decision-making accuracy and reliability. Practical examples and comparisons of different evaluation methods are provided to illustrate best practices in measurement.

New Measurement Instruments for Management

This module explores innovative measurement tools and prediction markets, emphasizing their impact on decision-making and risk management in organizations. Learners will analyze real-world case studies, including the National Leisure Group and the DARPA 'Terrorism Market' project, to understand both the potential and challenges of these instruments.

A Universal Measurement Method: Applied Information Economics

This module introduces the principles and real-world applications of Applied Information Economics (AIE) for making data-driven decisions in IT and public sector projects. Learners will explore case studies on quantifying value, risk, and uncertainty, and practice methods for measuring intangible factors such as innovation and flexibility. By the end, participants will be equipped to apply AIE techniques to improve decision-making outcomes.