Data-Driven Process Improvement from Coursera

By the end of this course, learners are empowered to implement data-driven process improvement objectives at their organization. The course covers: the business case for IoT (Internet of Things), the strategic importance of aligning operations and performance goals, best practices for collecting data, and facilitating a process mapping activity to visualize and analyze a process’s flow of materials and information. Learners are prepared to focus efforts around business needs, evaluate what the organization should measure, discern between different types of IoT data and collect key performance indicators (KPIs) using IoT technology. Learners have the opportunity to implement process improvement objectives in a mock scenario and consider how the knowledge can be transferred to their own organizational contexts.

Material includes online lectures, videos, demos, project work, readings and discussions. This course is ideal for individuals keen on developing a data-driven mindset that derives powerful insights useful for improving a company’s bottom line. It is helpful if learners have some familiarity with reading reports, gathering and using data, and interpreting visualizations. It is the first course in the Data-Driven Decision Making (DDDM) specialization. To learn more about the specialization, check out a video overview at https://www.youtube.com/watch?v=Oi4mmeSWcVc&list=PLQvThJe-IglyYljMrdqwfsDzk56ncfoLx&index=11.

What's inside

Syllabus

Operations and Performance Goals

This module covers the business case for establishing a data strategy, including why it is important, from a strategic level, to align your operations and performance goals before you undertake implementation.

Data Collection

This module covers best practices for collecting data.

Process Mapping

This module will prepare you to develop current state process maps, prioritize data gaps, and formulate future state process maps.

Project: Data-Driven Process Improvement

This module provides an opportunity to bridge theory and practice. Learners apply knowledge from this course to solve a business problem.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Builds a solid foundation in aligning operations and performance goals

Provides knowledge and skills to collect reliable data for process improvement initiatives

Emphasizes practical application through mock scenarios, ensuring transferability of knowledge to learners' own organizational contexts

Facilitates a data-driven mindset, empowering learners to derive insights for optimizing organizational performance

Taught by industry experts, Akshay Sivadas and Peter Baumgartner, known for their contributions to data-driven process improvement

Part of the Data-Driven Decision Making (DDDM) specialization, offering a comprehensive pathway for developing data-driven decision-making skills

Reviews summary

Data-driven process improvement: positive course

Learners say this course on data-driven process improvement is well-structured and provides useful instruments. Some of its most notable features include an instructor peer assignment where students receive feedback. However, it should be noted that this feedback may sometimes experience unexpected delays.

The course is well-organized and easy to follow.

"It is a very well structured course."

"Course is very good but if the resource material can be converted to a video it will add more value."

"Well structured, easy to follow and compatible with ones' tight schedule."

Learners highly recommend this course's concepts.

"It's an insightful course on fundamental concepts of processes to collect meaningful data to pursue efficiently certain objectives."

"The course provides some useful instruments and very good guidance."

"The best part about the course is that in addition to the theory, there is a peer reviewed assignment that really helps you think about and put into practice the theory and then get feedback from likeminded people."

Peer review feedback may take longer than expected to receive.

"There are some delay with peer review, other than that everything about the course was great."

"All courses in this specialization are great. However, final activities are vaguely described and it's very difficult not only for the student but also for the graders. This makes very difficult to get a passing grade in the final projects even if students use correctly concepts in the course."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Data-Driven Process Improvement with these activities:

Attend an IoT Industry Meetup

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Connect with professionals in the IoT field to learn about current trends and best practices.

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Research industry meetups in your area.
Attend a meetup and introduce yourself to others.
Participate in discussions and ask questions.

Review and Organize Course Content

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Regularly reviewing and organizing your notes and materials will improve your retention and understanding of the course concepts.

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Review lecture notes, readings, and assignments.
Organize materials into a logical structure using folders or note-taking software.

Review Basic Statistics

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Review basic statistical concepts such as mean, median, mode, and standard deviation to strengthen your foundation for understanding data analysis and interpretation.

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Review notes or textbooks on basic statistics concepts.
Solve practice problems involving calculating measures of central tendency and dispersion.

Ten other activities

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Show all 13 activities

Volunteer at a Local Tech Event

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Get involved in the IoT community and apply your skills to help others.

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Find a local tech event or organization that needs volunteers.
Offer your assistance with tasks related to IoT or data analysis.

Review Data Collection Best Practices

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You will expand your knowledge of data collection best practices, which will be crucial to your success.

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Review the course syllabus.
Read online resources about data collection.
Discuss data collection techniques with a classmate or colleague.

IoT Resource Compilation

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Keep your knowledge organized by creating a repository of useful resources on IoT.

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Create a document or spreadsheet to store your resources.
Include links to articles, videos, websites, and other materials.
Organize your resources by topic or category.

Attend a Data Analytics Workshop

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Attending a workshop will provide you with hands-on experience and insights from industry experts.

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Research and identify relevant data analytics workshops.
Attend the workshop and actively participate in discussions and exercises.

Practice Process Mapping

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This will help you develop the ability to identify and analyze processes, which is essential for improving operations and performance.

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Use a whiteboard or online tool to create a process map.
Identify the steps and activities involved in a process.
Analyze the process for inefficiencies and bottlenecks.
Suggest improvements to the process.

Analyze Data Visualization Techniques

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Practicing data visualization techniques will enhance your ability to interpret and communicate data effectively.

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Identify and describe different types of data visualizations, such as bar charts, line graphs, and scatter plots.
Create visualizations using real-world data sets.
Analyze and interpret the results of your visualizations.

Build a Data-Driven Dashboard

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Building a data-driven dashboard will provide you with practical experience in applying the concepts learned in the course.

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Identify a specific business problem that can be addressed with a data-driven dashboard.
Design and develop the dashboard using appropriate visualization techniques.
Deploy the dashboard and monitor its effectiveness.

Develop a Data-Driven Process Improvement Plan

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Creating a data-driven process improvement plan will allow you to apply the concepts learned in the course to a real-world business scenario.

Browse courses on Process Improvement

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Identify a specific process within your organization that needs improvement.
Collect and analyze relevant data to understand the current state of the process.
Develop a plan to improve the process using data-driven insights.
Implement the plan and monitor its effectiveness.

IoT Data Process Improvement Project

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This comprehensive project will put your skills to the test in analyzing IoT data and using it to drive real-world improvements.

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Select a process to improve.
Collect data on the process.
Analyze the data to identify areas for improvement.
Implement the improvements and track their effectiveness.
Refine the improvements based on the results.

Mentor a Junior Data Analyst

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Mentoring others will reinforce your understanding of the concepts and help you develop your communication and leadership skills.

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Identify a junior data analyst who could benefit from your guidance.
Provide regular support and guidance on data analysis techniques and career development.

Career center

Learners who complete Data-Driven Process Improvement will develop knowledge and skills that may be useful to these careers:

Lean Six Sigma Specialist

A Lean Six Sigma Specialist uses Lean and Six Sigma methodologies to improve processes and reduce waste. This course would provide a Lean Six Sigma Specialist with the skills to implement data-driven process improvement, allowing them to better identify and reduce inefficiencies.

See salaries and explore the career path for Lean Six Sigma Specialist

Continuous Improvement Manager

A Continuous Improvement Manager leads and manages continuous improvement initiatives within an organization, working to enhance processes and increase efficiency. This course would provide a Continuous Improvement Manager with the skills to implement data-driven process improvement, leading to sustained performance improvements.

See salaries and explore the career path for Continuous Improvement Manager

Industrial Engineer

An Industrial Engineer designs and optimizes integrated systems of people, materials, and equipment. This course would provide an Industrial Engineer with the skills to implement data-driven process improvement, leading to increased productivity and efficiency in manufacturing and other industrial settings.

See salaries and explore the career path for Industrial Engineer

Operational Excellence Manager

An Operational Excellence Manager develops and implements strategies to improve the operational performance of an organization. This course may be helpful for an Operational Excellence Manager who wants to gain a deeper understanding of data-driven process improvement and its impact on overall business performance.

See salaries and explore the career path for Operational Excellence Manager

Data Analyst

A Data Analyst collects, analyzes, and interprets large amounts of data, communicating insights and driving business decisions. This course may be helpful for a Data Analyst who wants to specialize in data-driven process improvement, allowing them to better optimize existing processes and identify areas for improvement.

See salaries and explore the career path for Data Analyst

Performance Improvement Consultant

A Performance Improvement Consultant helps organizations improve their performance and achieve their goals. This course may be helpful for a Performance Improvement Consultant who wants to gain a deeper understanding of data-driven process improvement and its application in various industries.

See salaries and explore the career path for Performance Improvement Consultant

Data Scientist

A Data Scientist uses scientific methods and algorithms to extract insights from data. This course may be useful for a Data Scientist who wants to specialize in data-driven process improvement, allowing them to develop advanced analytical models and solutions.

See salaries and explore the career path for Data Scientist

Project Manager

A Project Manager plans, executes, and closes projects. This course may be helpful for a Project Manager who wants to learn about data-driven process improvement to enhance project planning, execution, and evaluation.

See salaries and explore the career path for Project Manager

Business Analyst

A Business Analyst analyzes an organization's business processes and systems, helping to improve efficiency and productivity. This course may be useful for a Business Analyst who wants to gain a deeper understanding of data-driven process improvement and its impact on business outcomes.

See salaries and explore the career path for Business Analyst

Process Engineer

A Process Engineer designs and improves processes within organizations, especially in manufacturing, pharmaceuticals, food processing, or other scientific industries. This course would provide a Process Engineer with the skills to implement data-driven process improvement initiatives, leading to increased efficiency and productivity.

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Quality Control Manager

A Quality Control Manager develops and implements quality control systems within an organization. This course may be useful for a Quality Control Manager who wants to gain a deeper understanding of data-driven process improvement and its impact on product or service quality.

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Manufacturing Engineer

A Manufacturing Engineer designs, develops, and implements manufacturing processes. This course may be useful for a Manufacturing Engineer who wants to optimize manufacturing processes using data-driven process improvement techniques, leading to increased production efficiency and reduced costs.

See salaries and explore the career path for Manufacturing Engineer

Quality Assurance Manager

A Quality Assurance Manager oversees the development and implementation of quality assurance systems and processes within an organization. This course may be helpful for a Quality Assurance Manager who wants to learn about data-driven process improvement to enhance product or service quality and meet regulatory requirements.

See salaries and explore the career path for Quality Assurance Manager

Process Safety Engineer

A Process Safety Engineer identifies and mitigates hazards associated with chemical processes. This course may be helpful for a Process Safety Engineer who wants to use data-driven process improvement to enhance safety and reduce risks within their processes.

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Operations Manager

An Operations Manager typically leads the Operations department, ensuring the smooth running of the business, often in a manufacturing or production setting. This course may be helpful for an Operations Manager who wants to learn about data-driven process improvement to better optimize equipment and processes.

See salaries and explore the career path for Operations Manager