Expanded Library

Approaches to Data Enabled Decision Making

by Janani Ravi

This course will teach you how decision-making in an enterprise setting can be grounded in data. Important data-driven decision-making frameworks will be introduced and case studies applying data-driven decision-making will be explored.

What you'll learn

Making an informed data-driven decision is important. In this course, Approaches to Data Enabled Decision Making, you’ll learn to structure decision-making in an enterprise setting to be grounded in data.

First, you will explore the different types of data-enabled decision-making such as data-inspired, data-informed, and data-driven decision making and understand the similarities and differences between these. You will also learn the basic steps involved in data-driven decision-making and how they can be applied in an organization.

Next, you will explore some common frameworks for data-enabled decision making such as the BADI framework, multiple-criteria decision making using goal programming, and the analytic hierarchy process. You will also learn how to relate to workflows in analytics, such as CRISP-DM, and the build-test-deploy lifecycle of an ML model. You will also study Porter’s five forces framework to analyze competitive forces in any industry.

Finally, you will explore real-world organizational case studies that use data to structure both tactical and strategic decisions. Case studies will cover the hospitality industry, a financial management firm, and a wedding and wine event management company.

When you’re finished with this course, you’ll have the skills and knowledge of data-driven decision-making needed to effectively structure and drive decision-making in your organization.

About the author

A problem solver at heart, Janani has a Masters degree from Stanford and worked for 7+ years at Google. She was one of the original engineers on Google Docs and holds 4 patents for its real-time collaborative editing framework.

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