Coursera

Create a Value versus Complexity Matrix in Google Sheets (Coursera)

Offered by Coursera Project Network,
Create a Value versus Complexity Matrix in Google Sheets (Coursera)

In this 2-hour long project-based course, you will create a Value versus Complexity Matrix in Google Sheets and learn how to interpret the outcomes to prioritize product features. In the process, you will review the basics of this prioritization framework as well as Google Sheets functionality such as lookup tables, data validation, and charts. Because time and resources are limited, prioritization is a critical skill that product managers must master in order to optimize product value and minimize development time and costs.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

There are several frameworks for prioritization which can be used individually or in combination. The Value versus Complexity/Cost Matrix is one commonly used framework that helps provide objectivity in the decision making process.

In this Free Guided Project, you will:

  • Understand what a value vs complexity matrix is and how to use it to prioritize features.
  • Create lookup tables, use data validation, and create charts in Google Sheets.
  • Showcase this hands-on experience in an interview

Learn step-by-step

  • Review the Value versus Complexity Matrix purpose and determine measures of value and complexity.
  • Create a lookup table of standard variables for the Value and Complexity measures.
  • Create a features data table and populate it with sample data.
  • Generate a Value versus Complexity Matrix using the Bubble chart type in Google Sheets
  • Interpret the Value versus Complexity chart to determine feature priorities and calculate value to complexity ratios to determine priority order of features.
Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Practical Predictive Analytics: Models and Methods (Coursera) Coursera
University of Washington

Practical Predictive Analytics: Models and Methods (Coursera)

Statistics & Data Analysis Data Science

Statistical experiment design and analytics are at the heart of data science. In this course you will design statistical experiments and analyze the results using modern methods. You will also explore the common pitfalls in interpreting statistical arguments, especially those associated with big data. Collectively, this course will help you internalize a core set of practical and effective machine learning methods and concepts, and apply them to solve some real world problems.

Jun 22nd 2026
4 Weeks
Machine Learning Models Methods
Details
Introduction to Data Analysis Using Excel (Coursera) Coursera
Rice University

Introduction to Data Analysis Using Excel (Coursera)

Statistics & Data Analysis

The use of Excel is widespread in the industry. It is a very powerful data analysis tool and almost all big and small businesses use Excel in their day to day functioning. This course is designed to give you a working knowledge of Excel with the aim of getting to use it for more advance topics in Business Statistics. The course is designed keeping in mind two kinds of learners - those who have very little functional knowledge of Excel and those who use Excel regularly but at a peripheral level and wish to enhance their skills.

Jun 22nd 2026
4 Weeks
Spreadsheets Excel Data Analysis
Details
Bayesian Statistics: From Concept to Data Analysis (Coursera) Coursera
University of California, Santa Cruz

Bayesian Statistics: From Concept to Data Analysis (Coursera)

Statistics & Data Analysis Data Science

This course introduces the Bayesian approach to statistics, starting with the concept of probability and moving to the analysis of data. We will learn about the philosophy of the Bayesian approach as well as how to implement it for common types of data. We will compare the Bayesian approach to the more commonly-taught Frequentist approach, and see some of the benefits of the Bayesian approach.

Jun 22nd 2026
4 Weeks
Statistics Probability Data Analysis
Details
Brand and Product Management (Coursera) Coursera
IE Business School

Brand and Product Management (Coursera)

Management & Leadership Marketing & Communication

Identify the critical information needed to develop a product and brand strategy that generates both quick-wins and long-term value. By completing this course, you will be in position to create an activity plan to bring your brand strategy to life - both externally towards consumers and internally to employees. You will be able to define the right metrics for determining success in the implementation of your product and brand strategy, considering any adjustments that may need to be made under a test and learn methodology.

Jun 22nd 2026
4 Weeks
Marketing Brand Management Brand
Details
Foundations of strategic business analytics (Coursera) Coursera
ESSEC Business School

Foundations of strategic business analytics (Coursera)

Management & Leadership Business

Who is this course for? This course is designed for students, business analysts, and data scientists who want to apply statistical knowledge and techniques to business contexts. For example, it may be suited to experienced statisticians, analysts, engineers who want to move more into a business role. You will find this course exciting and rewarding if you already have a background in statistics, can use R or another programming language and are familiar with databases and data analysis techniques such as regression, classification, and clustering.

Jun 22nd 2026
4 Weeks
Data Analysis Analytics Presentations
Details
Exploratory Data Analysis (Coursera) Coursera
Johns Hopkins University

Exploratory Data Analysis (Coursera)

Statistics & Data Analysis Data Science

This course covers the essential exploratory techniques for summarizing data. These techniques are typically applied before formal modeling commences and can help inform the development of more complex statistical models. Exploratory techniques are also important for eliminating or sharpening potential hypotheses about the world that can be addressed by the data.

Jun 22nd 2026
4 Weeks
Statistics Data Analysis Data Science
Details
Introduction to Probability and Data with R (Coursera) Coursera
Duke University

Introduction to Probability and Data with R (Coursera)

Statistics & Data Analysis Data Science

This course introduces you to sampling and exploring data, as well as basic probability theory and Bayes' rule. You will examine various types of sampling methods, and discuss how such methods can impact the scope of inference. A variety of exploratory data analysis techniques will be covered, including numeric summary statistics and basic data visualization.

Jun 22nd 2026
5-12 Weeks
Statistics Probability Inference
Details
Market Research and Consumer Behavior (Coursera) Coursera
IE Business School

Market Research and Consumer Behavior (Coursera)

Management & Leadership Marketing & Communication

Your marketing quest begins here! The first course in this specialization lays the neccessary groundwork for an overall successful marketing strategy. It is separated into two sections: Market Research and Consumer Behavior. Gain the tools and techniques to translate a decision problem into a research question in the Market Research module. Learn how to design a research plan, analyze the data gathered and accurately interpret and communicate survey reports, translating the results into practical recommendations.

Jun 22nd 2026
4 Weeks
Marketing Data Analysis Marketing Strategy
Details
Leadership Through Marketing (Coursera) Coursera
Northwestern University

Leadership Through Marketing (Coursera)

Management & Leadership

The success of every organization depends on attracting and retaining customers. Although the marketing concepts for doing so are well established, digital technology has empowered customers, while producing massive amounts of data, revolutionizing the processes through which organizations attract and retain customers. In this course, students will learn how to identify new opportunities to create value for empowered consumers, develop strategies that yield an advantage over rivals, and develop the data science skills to lead more effectively, allocate resources, and to confront this very challenging environment with confidence.

Jun 28th 2026
4 Weeks
Marketing Strategy Leadership
Details