Decision Making for Leaders: Leveraging Data from Udemy

If you are a manufacturing professional looking to advance your data analysis skillset so that you can advance your business career, then this is the class for you.

In this second course in its series course, "Decision Making for Leaders: Leveraging Data", you will learn beginner and intermediate level skills from 3 important areas of business data analysis:

Understanding and Analyzing Data Variation
Making Statistically Confirmed Decisions
Utilizing Leading and Lagging Indicators to Monitor Business Processes

Each of these sections are "bite sized" lessons that a busy professional can watch in one or two lunch breaks or evenings.

In the first section, Understanding and Analyzing Data Variation, you will learn:

The value of visualizing your data on a time-based run chart
How to calculate control limits as a means of characterizing the normal range of your process
How to use Cpk as a business indicator

In the second section, Making Statistically Confirmed Decisions, you will learn:

How statistical tools like hypothesis testing can improve your decision-making abilities.
How to measure to two sources of error, alpha and beta.
How to perform one-, two-, and both-tailed hypothesis tests using both the t and Z statistic.

And in the third section, Utilizing Leading and Lagging Indicators to Monitor Business Processes, you will learn:

The value of both leading and lagging indicators in monitoring your business processes
Real life examples of both types of indicators
Connecting leading and lagging indicators for greater business success

In addition to over 3 1/2 hours of high-quality video, this class also offers several downloadable resources including:

The slide deck for each of the three lessons (. )

If you are going to be successful in business or operations, you must know how to extract useful insights from your organization's data. Complement your managerial and people skills today with "Decision Making for Leaders: Leveraging Data", and take your career to its next level.

See you in class.

What's inside

Learning objectives

How to use your organization's data to make better decisions
The nature and sources of variation in business data
Common cause versus special cause variation
How to calculate and use a capability index
How to start making statistically confirmed decisions
An overview of designed experiments
Types of hypothesis errors
Hypothesis testing steps
T tests and z tests

One way and two way anova
An overview of design of experiments (doe)
An understanding of leading and lagging indicators
The 10 steps toward building a quality operating system (qos)
Qos examples in manufacturing
Excel-based, downloadable spreadsheets
Show more
Show less

How to use your organization's data to make better decisions
The nature and sources of variation in business data
Common cause versus special cause variation
How to calculate and use a capability index
How to start making statistically confirmed decisions
An overview of designed experiments
Types of hypothesis errors
Hypothesis testing steps
T tests and z tests
One way and two way anova
An overview of design of experiments (doe)
An understanding of leading and lagging indicators
The 10 steps toward building a quality operating system (qos)
Qos examples in manufacturing
Excel-based, downloadable spreadsheets
Show more
Show less

Syllabus

Introduction

Introduction to the Course

Slides for the Entire Course

The Nature of Variation in Decision Making

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Teaches skills in data analysis, which are useful for professionals looking to advance their careers in the manufacturing industry

Explores leading and lagging indicators, which are useful for monitoring business processes and driving greater business success

Includes downloadable, Excel-based spreadsheets, which can be used to perform calculations and analyses taught in the course

Requires learners to use Excel, which may require a separate purchase for those who do not already have access to it

Focuses on hypothesis testing using t and Z statistics, which are foundational concepts in statistical analysis and decision-making

Reviews summary

Data-driven decisions for leaders

According to learners, this course provides a solid foundation and practical application of data analysis techniques for leaders. Students particularly appreciate the clear explanations of complex statistical concepts like hypothesis testing and variation analysis, making them accessible even for those without a strong statistics background. The downloadable Excel spreadsheets are frequently highlighted as very helpful resources for applying the concepts learned. While some learners note the pace is suitable for beginners, a few found certain sections could benefit from more depth or examples for intermediate users. Overall, it is described as a highly valuable course for improving data-driven decision-making skills in a business context.

Generally suitable for beginners, maybe less depth for advanced.

"The pace was perfect for me as a beginner in data analysis for business."

"While a great intro, I felt some topics could have gone into slightly more advanced detail."

"It covers the fundamentals well, making it accessible, but don't expect advanced statistical modeling."

Designed for busy professionals with bite-sized lessons.

"The 'bite-sized' lessons structure was excellent for fitting study into my busy work schedule."

"I liked that I could complete a module during a lunch break or in a short evening session."

"The short lecture format makes it easy to revisit specific topics quickly."

The QOS section is highlighted as valuable.

"The section on the Quality Operating System and leading/lagging indicators was particularly insightful."

"Understanding QOS tied the statistical methods together with practical business management."

"I found the real-life QOS examples very helpful for understanding implementation."

Downloadable spreadsheets are highly beneficial.

"The Excel spreadsheets provided were invaluable for practicing the statistical calculations."

"Having the downloadable resources, especially the Cpk and hypothesis testing sheets, was a great help."

"I rely on the provided spreadsheets regularly to perform the analysis learned in the course."

Simplifies complex statistical concepts effectively.

"The instructor explains difficult concepts like hypothesis testing in a way that's easy to understand."

"I appreciated how the course broke down variation analysis into digestible parts with clear examples."

"Even without a statistics background, I could follow the explanations on Z and t tests clearly."

Focuses on real-world use cases and applicability.

"The course provides practical tools and strategies that I could apply immediately to my work."

"I found the examples highly relevant to real business scenarios, which made learning much easier."

"This isn't just theory; it shows you how to actually use data to make better business decisions."

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 Decision Making for Leaders: Leveraging Data with these activities:

Review Basic Statistics Concepts

Show steps

Reinforce your understanding of fundamental statistical concepts to better grasp the hypothesis testing and data analysis techniques covered in the course.

Browse courses on Hypothesis Testing

Show steps

Review definitions of key statistical terms.
Work through practice problems on hypothesis testing.
Familiarize yourself with different types of statistical distributions.

Review 'Statistics for Managers Using Microsoft Excel'

Show steps

Supplement your understanding of statistical analysis by referencing a book that focuses on practical application using Microsoft Excel.

View Even You Can Learn Statistics and Analytics: An... on Amazon

Show steps

Read the chapters related to hypothesis testing and ANOVA.
Work through the examples provided in the book using Excel.
Compare the book's approach to the methods taught in the course.

Perform Hypothesis Testing Exercises

Show steps

Solidify your understanding of hypothesis testing by working through a series of practical exercises.

Show steps

Find datasets online related to manufacturing processes.
Formulate null and alternative hypotheses for each dataset.
Perform t-tests and Z-tests using Excel or other statistical software.
Interpret the results and draw conclusions based on the p-values.

Four other activities

Expand to see all activities and additional details

Show all seven activities

Develop a Control Chart Dashboard

Show steps

Apply your knowledge of control charts and data visualization to create a dashboard that monitors key business processes.

Show steps

Identify relevant leading and lagging indicators for a specific business process.
Collect historical data for these indicators.
Create control charts for each indicator using Excel or other data visualization tools.
Design a dashboard that displays the control charts and highlights any out-of-control points.

Analyze Variation in a Real-World Process

Show steps

Deepen your understanding of data variation by analyzing a real-world process and identifying sources of variability.

Show steps

Choose a manufacturing process to analyze.
Collect data on key process parameters.
Create run charts and control charts to visualize the data.
Identify common cause and special cause variation.
Propose solutions to reduce variation and improve process capability.

Review 'Understanding Variation: The Key to Managing Chaos'

Show steps

Expand your knowledge of variation analysis by reading a book dedicated to understanding and managing variation in business processes.

View Understanding Variation on Amazon

Show steps

Read the chapters on common cause and special cause variation.
Study the examples of control chart applications in different industries.
Reflect on how the concepts in the book relate to your own work experience.

Tutor other students

Show steps

Reinforce your understanding of the course material by helping other students who are struggling with the concepts.

Show steps

Offer to help classmates with homework assignments.
Explain difficult concepts in your own words.
Answer questions in online discussion forums.

Career center

Learners who complete Decision Making for Leaders: Leveraging Data will develop knowledge and skills that may be useful to these careers:

Quality Assurance Manager

The quality assurance manager is responsible for ensuring that products or services meet certain standards of quality. This course is highly relevant, as it covers understanding and analyzing data variation, making statistically confirmed decisions, and utilizing leading and lagging indicators, all of which are crucial aspects of quality control. You can apply the knowledge gained to monitor processes, identify defects, and implement corrective actions. Skills such as calculating control limits and performing hypothesis tests enable quality assurance managers to make data-driven decisions and maintain high levels of quality. Take this course in particular to prepare yourself for quality assurance management.

See salaries and explore the career path for Quality Assurance Manager

Process Improvement Specialist

A process improvement specialist focuses on analyzing and optimizing business processes to enhance efficiency, reduce waste, and improve overall performance. This course on leveraging data equips you with the skills to understand data variation, make statistically confirmed decisions, and utilize leading and lagging indicators. These competencies are crucial for identifying areas needing improvement and implementing data-driven solutions. Specifically, learning to calculate control limits and use Cpk as a business indicator helps a process improvement specialist monitor and control process performance, while hypothesis testing skills support confident decision-making based on statistical evidence. One who wants to be a process improvement specialist should take this course.

See salaries and explore the career path for Process Improvement Specialist

Operations Manager

An operations manager oversees the production of goods or provision of services, ensuring that processes run smoothly and efficiently. This course offers valuable skills for operations managers, including the ability to analyze data variation, make statistically confirmed decisions, and utilize leading and lagging indicators to monitor business processes. You can apply the techniques learned to identify and address bottlenecks, improve productivity, and reduce costs. Understanding control limits and using Cpk as a business indicator allows you to maintain quality standards and optimize operational performance. An operations manager would find value in this course.

See salaries and explore the career path for Operations Manager

Business Analyst

The business analyst identifies business needs and determines solutions to business problems. This course can help you better understand data variation, make statistically confirmed decisions, and utilize leading and lagging indicators to monitor business processes. These skills are crucial for analyzing business performance, identifying areas for improvement, and recommending data-driven solutions. You can apply techniques such as hypothesis testing to validate proposed solutions and ensure they meet business requirements. A business analyst should enroll in this course.

See salaries and explore the career path for Business Analyst

Business Intelligence Analyst

The business intelligence analyst interprets data and transforms it into actionable insights that inform strategic and tactical business decisions. This course helps you develop the skills to analyze data variation, make statistically confirmed decisions, and utilize leading and lagging indicators, all of which are vital for a business intelligence analyst. You can apply your knowledge of control limits and capability indices to monitor business performance and identify areas for improvement. The course provides practical tools and techniques such as hypothesis testing, enabling you to make data-driven recommendations confidently. One should take this course in particular to prepare themself in business intelligence analysis.

See salaries and explore the career path for Business Intelligence Analyst

Project Manager

A project manager plan, executes, and closes projects, defining the project objectives and overseeing quality control throughout the project lifecycle. This course helps project managers especially as it teaches beginning to intermediate level skills in understanding and analyzing data variation, making statistically confirmed decisions, and utilizing leading and lagging indicators to monitor business processes. These skills are relevant for assessing project performance, identifying risks and opportunities, and ensuring projects are on track to meet their objectives. A project manager will benefit from this course.

See salaries and explore the career path for Project Manager

Supply Chain Analyst

A supply chain analyst examines and optimizes the flow of goods and information from suppliers to customers. This course can help a future supply chain analyst tremendously, as it teaches you how to understand data variation, make statistically confirmed decisions, and utilize leading and lagging indicators to monitor business processes. The course helps you analyze supply chain performance, identify inefficiencies, and recommend improvements. Learning how to calculate control limits and use business indicators enables supply chain analysts to track key metrics and ensure timely delivery of products. A supply chain analyst should enroll in this course.

See salaries and explore the career path for Supply Chain Analyst

Statistician

A statistician collects, analyzes, and interprets numerical data to identify trends and solve problems. This role usually requires an advanced degree. This course, with its emphasis on understanding data variation, making statistically confirmed decisions, and utilizing leading and lagging indicators, provides a solid foundation, especially when it comes to decision making. Learning how to perform hypothesis tests using t and Z statistics, as well as understanding the different types of errors, enable statisticians to draw meaningful conclusions from data and make accurate predictions. Statisticians should enroll in this course in particular.

See salaries and explore the career path for Statistician

Data Analyst

The data analyst is responsible for collecting, cleaning, analyzing, and interpreting large datasets to provide insights and support decision-making. This course, with its focus on understanding and analyzing data variation and using statistical tools, provides a strong foundation for a career as a data analyst. You will learn how to visualize data using time-based run charts and how to perform hypothesis tests using t and Z statistics. These techniques enable data analysts to draw meaningful conclusions from data. Moreover, the course's emphasis on leading and lagging indicators helps data analysts monitor business processes and identify trends. This course may be helpful if you want to be a data analyst.

See salaries and explore the career path for Data Analyst

Manufacturing Engineer

The manufacturing engineer designs and improves manufacturing processes to enhance efficiency and reduce costs. This course can help with this, as it focuses on understanding data variation and making statistically confirmed decisions, providing essential tools for optimizing manufacturing operations. Skills such as calculating control limits and using Cpk as a business indicator help manufacturing engineers monitor process performance and identify areas for improvement. You can also apply hypothesis testing to validate process changes and ensure they lead to statistically significant improvements. Someone preparing for manufacturing engineering may find this course useful.

See salaries and explore the career path for Manufacturing Engineer

Market Research Analyst

The market research analyst studies market conditions to examine potential sales of a product or service. This course may be helpful as it teaches you how to understand data variation, make statistically confirmed decisions, and utilize leading and lagging indicators to monitor trends in customer behavior. These skills are crucial for interpreting market research data, identifying target markets, and evaluating the effectiveness of marketing campaigns. Employ the skills learned in this course, such as how to perform hypothesis tests and how to analyze data variation, to gain more insights into the markets. Market research analysts should enroll in this course.

See salaries and explore the career path for Market Research Analyst

Statistical Analyst

A statistical analyst collects, analyzes, and interprets numerical data to identify trends and solve problems. This course, with its emphasis on understanding data variation, making statistically confirmed decisions, and utilizing leading and lagging indicators, provides a solid foundation for a career as a statistical analyst. Learning how to perform hypothesis tests using t and Z statistics, as well as understanding the different types of errors, enables statistical analysts to draw meaningful conclusions from data and make accurate predictions. This course may be useful for you.

See salaries and explore the career path for Statistical Analyst

Data Scientist

The data scientist analyzes complex data sets, develops algorithms, and builds predictive models to solve business problems. Typically, this role requires an advanced degree. This course, by providing a foundation in understanding data variation, making statistically confirmed decisions, and utilizing leading and lagging indicators, proves useful for a data scientist. You can employ your knowledge of hypothesis testing and statistical analysis to develop accurate models and extract meaningful insights from data. Data scientists can improve their decision-making skills following this course.

See salaries and explore the career path for Data Scientist

Management Consultant

Management consultants advise organizations on how to improve their performance and efficiency. This course helps you become a management consultant by teaching crucial business principles and techniques such as understanding data variation, making statistically confirmed decisions, and utilizing leading and lagging indicators. The ability to analyze data, identify key performance indicators, and recommend data-driven solutions is essential for consultants. Skills learned in this course, such as performing t-tests and Z-tests, provide a quantitative edge in assessing business problems and formulating effective strategies. This course may prove itself to be useful for you.

See salaries and explore the career path for Management Consultant

Financial Analyst

The financial analyst provides guidance to businesses and individuals making investment decisions. This course might be helpful as it teaches you how to understand data variation, make better decisions, and utilize leading and lagging indicators to monitor business processes. These skills are crucial for interpreting financial data, identifying trends, and making informed investment recommendations. Apply the techniques you learn from this course, such as how to calculate a capability index and how to visualize data on a time-based run chart, to analyze financial performance and assess investment risks. A financial analyst may gain some new skills in this course.

See salaries and explore the career path for Financial Analyst

Decision Making for Leaders

Leveraging Data

What's inside

Learning objectives

Syllabus

Traffic lights

Save this course

Reviews summary

Data-driven decisions for leaders

Activities

Career center

Reading list

Share

Similar courses