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Smarter Decisions - The Intersection of Internet of Things and Decision Science

You're reading from   Smarter Decisions - The Intersection of Internet of Things and Decision Science A comprehensive guide for solving IoT business problems using decision science

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Product type Paperback
Published in Jul 2016
Publisher Packt
ISBN-13 9781785884191
Length 392 pages
Edition 1st Edition
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Author (1):
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Jojo Moolayil Jojo Moolayil
Author Profile Icon Jojo Moolayil
Jojo Moolayil
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Table of Contents (10) Chapters Close

Preface 1. IoT and Decision Science FREE CHAPTER 2. Studying the IoT Problem Universe and Designing a Use Case 3. The What and Why - Using Exploratory Decision Science for IoT 4. Experimenting Predictive Analytics for IoT 5. Enhancing Predictive Analytics with Machine Learning for IoT 6. Fast track Decision Science with IoT 7. Prescriptive Science and Decision Making 8. Disruptions in IoT 9. A Promising Future with IoT

Root Cause Analysis

We now begin our journey with answering the why question from all the insights we have gathered till now. Let's assimilate all our results that we have validated in our EDA exercise. Once we have all the results, let's try to simplify it to create a simple story that helps us in answering the questions in a more lucid way.

The following figure is an extended version of the DDH matrix we designed in the previous section along with the results we found during our exercise:

Hypothesis

Result

Insight

Line 1 has an overall higher chance of manufacturing more number of bad quality detergent products

FALSE

Assembly Line has no impact on the end quality of the detergent

Line 1 has an overall higher chance of deteriorating the Output Quality Parameters in the detergent

TRUE

Assembly line has an impact on Output Quality Parameter 2,3, and 4

As the deviation between Order Quantity and actual Produced Quantity increases, the chance of the bad quality detergent...

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