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Gender Analytics for Innovation

Approx. 8 hours to complete

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Course Summary

Discover how to use gender analytics to drive innovation and business success in this Coursera course. Learn how to analyze data to identify gender trends and biases, and use these insights to create more inclusive products and services.

Key Learning Points

Learn how to use data to uncover gender biases in your organization
Understand the importance of gender diversity in driving innovation and business success
Discover how to use gender analytics to create more inclusive products and services

Job Positions & Salaries of people who have taken this course might have

- USA: $78,000 - $128,000
- India: ₹5,00,000 - ₹15,00,000
- Spain: €30,000 - €50,000
- USA: $78,000 - $128,000
- India: ₹5,00,000 - ₹15,00,000
- Spain: €30,000 - €50,000
- USA: $90,000 - $140,000
- India: ₹12,00,000 - ₹22,00,000
- Spain: €40,000 - €60,000
- USA: $78,000 - $128,000
- India: ₹5,00,000 - ₹15,00,000
- Spain: €30,000 - €50,000
- USA: $90,000 - $140,000
- India: ₹12,00,000 - ₹22,00,000
- Spain: €40,000 - €60,000
- USA: $60,000 - $100,000
- India: ₹3,00,000 - ₹10,00,000
- Spain: €25,000 - €40,000

Learning Outcomes

Identify and analyze gender trends and biases in your organization
Develop strategies for creating more inclusive products and services
Apply gender analytics to drive innovation and business success

Prerequisites or good to have knowledge before taking this course

Basic understanding of data analysis
Familiarity with business strategy and product development

Course Difficulty Level

Intermediate

Course Format

Online
Self-paced

Similar Courses

Diversity and Inclusion for Success
Design Thinking
Data Analytics for Business

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Notable People in This Field

Director of User Experience at Google
CEO of Ellevest

Related Books

Description

Gender Analytics is a way to analyze your products, services, processes and policies with a gender lens to uncover hidden opportunities for innovation and effectiveness.

We'll answer questions such as: Why are women 47% more likely than men to be injured when they get in a car accident? Why do financial products fail to meet women’s needs across their life cycles? Why will automation and AI be more likely to impact women than men? Why are gender-neutral policies are not necessarily gender-equal? This is the introductory course in the 5-course Gender Analytics Specialization offered by the Institute for Gender and the Economy (GATE) at the University of Toronto's Rotman School of Management. In this course, you will build the foundations for conducting Gender Analytics. You will get comfortable with the concepts and terms associated with Gender Analytics, including sex, gender, gender identity, sexual orientation and intersectionality. You will examine how policies, products, services and processes may have unintentionally gendered outcomes that miss out on opportunities or create needless risks. You will learn to uncover assumptions underlying these policies, products, services and processes, and to break social, cultural, and or organizational norms that perpetuate exclusion and inequality. You will see how Gender Analytics can lead to transformational innovations. You will also evaluate your own competencies and start your Self Development Plan and begin your journey to build a workplan for your own Gender Analytics project.

Knowledge

Recognize ways in which policies, products, services and processes might be implicitly gendered, thus creating inequitable impact
Develop fluency in key concepts of Gender Analytics, including language associated with sex, gender, gender identity and intersectionality.
Evaluate options for using Gender Analytics to spur inclusive innovation, especially in areas not often considered gendered
Identify opportunities to build personal and organizational capabilities to conduct intersectional Gender Analytics effectively

Outline

Using Gender Analytics to create opportunities and mitigate risks
Introduction to the Gender Analytics specialization
Introduction to the Gender Analytics faculty
Gender Analytics learning philosophy
Gender Analytics to create opportunities
Case example: McCarthy Uniforms
Gender Analytics to avoid risks
Land Acknowledgement
Gender Analytics faculty biography for Course 1
Introduction to Case example: McCarthy Uniforms
Case example: McCarthy Uniforms
Assessment 1

Gender Analytics competencies
Gender Analysis Competency Framework introduction
Understanding the Gender Analysis Competency Framework
How the courses in the Specialization will build your competencies
Introduction to the next video
Gender Analysis Competency Framework
[Exercise] Gender Analysis Competency Self-Assessment
Assessment 2

Why gender and its intersections matter
Defining gender
Beyond the gender binary
Impact of intersectionality
[Multimedia resource] The risks of the “male default”
[Multimedia resource] The theory of intersectionality
[Multimedia resource] Case example: Bias in facial recognition technology
[Multimedia resource] How gender identity intersects with race
[Worksheet] Interrogating your own identities
Reviewing gender concepts
Assessment 3

Gender Analytics for inclusive innovation
Gender Analytics as innovation
Inclusive innovation is radical innovation
Inclusion as transformation
Application Spotlight: Application to your project workplan
Application Spotlight: Application to your Self Development Plan
End of Course Recap
Introduction to these interviews
Case example: inclusive innovation at Samagra
[Worksheet] Your own Gender Analytics project
[Worksheet] Gender Analytics Self Development Plan
Congratulations!
Assessment 4

Summary of User Reviews

Find out what previous learners thought of Gender Analytics & Innovation course on Coursera. Discover the key aspects that stood out to them and get an overall sense of the rating without the numbers.

Key Aspect Users Liked About This Course

Many users thought the course material was relevant and up-to-date.

Pros from User Reviews

Relevant and up-to-date course material
Engaging and knowledgeable instructors
Easy to navigate platform
Useful assignments and quizzes
Great support from Coursera team

Cons from User Reviews

Some technical issues with videos and quizzes
Content can be repetitive at times
Not enough emphasis on practical applications
Lack of interaction with other students
Some learners found the course too basic

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