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Unilever Team

In the Implementing Supply Chain Analytics: Descriptive, Diagnostic, Predictive and Prescriptive course, you’ll discover how implementing analytical methods, models, and tools helps decision-making become more efficient. You’ll use different types of methods, models, and tools, depending on specific business scenarios or needs, to help you analyze the current state of the supply chain and to lead you to insightful solutions. You’ll also explore the utilization of supply chain models to evaluate and question the data to optimize the flow of goods, information, and cost in a supply chain to help identify potential improvements, determine the most efficient or practical course of action, and to communicate the impact to the customer.

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In the Implementing Supply Chain Analytics: Descriptive, Diagnostic, Predictive and Prescriptive course, you’ll discover how implementing analytical methods, models, and tools helps decision-making become more efficient. You’ll use different types of methods, models, and tools, depending on specific business scenarios or needs, to help you analyze the current state of the supply chain and to lead you to insightful solutions. You’ll also explore the utilization of supply chain models to evaluate and question the data to optimize the flow of goods, information, and cost in a supply chain to help identify potential improvements, determine the most efficient or practical course of action, and to communicate the impact to the customer.

By the end of this course, you’ll be able to:

Interpret historical data effectively using descriptive analytics.

Forecast the most probable outcomes, projects, or future. scenarios, along with their business implications, using predictive analytics.

Collaborate and make recommendations that maximize business value, addressing problems through prescriptive analytics.

Describe the appropriate communication channels to display and summarize the data results and Supply Chain recommendations.

Use supply chain models to evaluate and optimize the flow of goods, information, and sots with a supply chain.

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What's inside

Syllabus

Progamming languages: Python and SQL
In this module, you will learn how programming languages such as Python and SQL assist in managing, cleaning, summarizing and manipulating data.Communicating Diagnostic Analytics You will also learn how to use programming languages to create meaningful data visualizations.
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Data analytics that drive impactful decision making
Data analytics is the practice of examining data to answer questions, identify trends, and extract insights. In this module, you will focus on the four levels of data anlytics that help answer questions about what happened and why, what might happen in the future, and what are the possible outcomes.
Supply chain models: Inventory, Continuous Flow, Fast Chain
There are several different types of Supply Chain models. Once you know the probem your trying to solve, you can select the type of model that will best help you find a solution. In this module you will learn how use the inventory model to describe inventory policies, inputs and outputs, operations related to inventory management, how to use the continuous flow model to describe the current state and current practices in the business operations to identify opportunities for improvement, and how to use the fast chain model to describe the current state and current practices in the business operations to identify opportunities for improvement.
Supply Chain Models: Efficient Chain, Agile, Custom-Configured, Flexible
There are several different types of Supply Chain models. Once you know the probem your trying to solve, you can select the type of model that will best help you find a solution. In this module you will learn how use the efficient chain model to identify optimal scenarios and best practices that could be translated into other environments, use the agile model to prepare for participating in cross-functional developments driven by the supply chain, use the custom-configured model to prepare cross-functional developments driven by the supply chain with a more flexible infrastructure to new projects or developments, and use the flexible model to build flexible structures and scenario planning.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Covers four levels of data analytics, which is industry standard
Employs Python and SQL, which are widely used in the industry
Leverages supply chain models for optimal flow of goods, information, and costs

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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 Implementing Supply Chain Analytics with these activities:
Refresh Your Background in Programming
Review key programming concepts and techniques to strengthen your foundation before starting the course.
Show steps
  • Review basic data types, variables, and control flow
  • Practice solving simple programming problems in Python
  • Complete online tutorials or exercises on SQL
Engage in Peer Discussions on Supply Chain Analytics
Collaborate with fellow students to discuss course concepts, share insights, and reinforce understanding.
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  • Join online forums or study groups related to supply chain analytics
  • Participate in regular discussions and contribute to group projects
  • Seek feedback from peers and offer constructive criticism
Data manipulation and analysis exercises
Enhance your data manipulation and analysis skills by practicing with exercises to reinforce the concepts learned in the course.
Browse courses on Python
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  • Work through practice problems and exercises
  • Apply Python and SQL for data cleaning and manipulation
  • Perform data analysis and interpretation
Six other activities
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Show all nine activities
Build a Small Python Script
Apply your understanding of Python to create a functional script that solves a specific problem.
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  • Identify a simple problem that can be solved using Python
  • Design a solution and write the code in Python
  • Test and debug the script to ensure it works correctly
Practice Data Analysis with Case Studies
Sharpen your data analysis skills by solving case studies that require you to analyze data and draw insights.
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  • Review real-world datasets and identify key variables
  • Apply descriptive analytics techniques to summarize and visualize data
  • Use predictive analytics to forecast outcomes and identify trends
Develop a data-driven supply chain model
Develop a supply chain model using the techniques and concepts learned in the course to enhance your understanding and problem-solving skills.
Browse courses on Inventory Control
Show steps
  • Define the problem and goals of the project
  • Gather and analyze data relevant to the project
  • Select and apply appropriate analytical techniques and models
  • Develop and implement the supply chain model
  • Evaluate and refine the model based on results
Explore Advanced Supply Chain Models
Expand your knowledge of supply chain models by following expert-led tutorials that cover advanced concepts.
Show steps
  • Review different types of supply chain models (e.g., Efficient Chain, Agile, Custom-Configured)
  • Understand how to select the appropriate model for specific business scenarios
  • Practice using simulations to evaluate and optimize supply chain models
Develop a Data Visualization Dashboard
Showcase your data analysis skills by creating an interactive dashboard that visualizes supply chain data.
Show steps
  • Gather and clean supply chain data from multiple sources
  • Choose appropriate data visualization techniques to present insights
  • Develop an interactive dashboard using visualization tools (e.g., Tableau, Power BI)
Mentor Junior Supply Chain Professionals
Strengthen your understanding by sharing knowledge and providing guidance to individuals starting their careers in supply chain.
Show steps
  • Identify opportunities to mentor junior professionals through online platforms or local organizations
  • Share your experiences, insights, and best practices
  • Provide feedback and support to help mentees develop their skills

Career center

Learners who complete Implementing Supply Chain Analytics will develop knowledge and skills that may be useful to these careers:
Data Analyst
Data Analysts are responsible for collecting, cleaning, and analyzing data to help organizations make informed decisions. This course provides a strong foundation in data analytics, including data management, data visualization, and statistical analysis. These skills are essential for Data Analysts, who need to be able to interpret data and communicate findings effectively.
Business Analyst
Business Analysts help organizations improve their business processes and make better decisions. This course provides a strong foundation in data analytics, which is essential for Business Analysts. The course covers topics such as data management, data visualization, and statistical analysis. These skills can help Business Analysts identify opportunities for improvement and develop solutions to business problems.
Operations Research Analyst
Operations Research Analysts use mathematical and analytical techniques to solve complex business problems. This course provides a strong foundation in data analytics, which is essential for Operations Research Analysts. The course covers topics such as data management, data visualization, and statistical analysis. These skills can help Operations Research Analysts develop and evaluate solutions to business problems.
Management Consultant
Management Consultants help organizations improve their performance. This course provides a strong foundation in data analytics, which is essential for Management Consultants. The course covers topics such as data management, data visualization, and statistical analysis. These skills can help Management Consultants identify opportunities for improvement and develop solutions to business problems.
Financial Analyst
Financial Analysts help businesses and individuals make investment decisions. This course provides a strong foundation in data analytics, which is essential for Financial Analysts. The course covers topics such as data management, data visualization, and statistical analysis. These skills can help Financial Analysts analyze financial data and make informed investment decisions.
Supply Chain Manager
Supply Chain Managers oversee the flow of goods and services from suppliers to customers. This course provides a strong foundation in data analytics, which is essential for Supply Chain Managers. The course covers topics such as data management, data visualization, and statistical analysis. These skills can help Supply Chain Managers identify inefficiencies and improve the efficiency of the supply chain.
Project Manager
Project Managers oversee the planning, execution, and closure of projects. This course provides a strong foundation in data analytics, which can be helpful for Project Managers. The course covers topics such as data management, data visualization, and statistical analysis. These skills can help Project Managers track project progress and identify potential risks.
Product Manager
Product Managers are responsible for the development and management of products. This course provides a strong foundation in data analytics, which can be helpful for Product Managers. The course covers topics such as data management, data visualization, and statistical analysis. These skills can help Product Managers understand customer needs and develop products that meet those needs.
Marketing Manager
Marketing Managers oversee the development and execution of marketing campaigns. This course provides a strong foundation in data analytics, which can be helpful for Marketing Managers. The course covers topics such as data management, data visualization, and statistical analysis. These skills can help Marketing Managers track campaign performance and identify areas for improvement.
Sales Manager
Sales Managers oversee the sales team and are responsible for generating revenue. This course provides a strong foundation in data analytics, which can be helpful for Sales Managers. The course covers topics such as data management, data visualization, and statistical analysis. These skills can help Sales Managers track sales performance and identify opportunities for growth.
Data Scientist
Data Scientists use data to solve complex business problems. This course provides a strong foundation in data analytics, which is essential for Data Scientists. The course covers topics such as data management, data visualization, and statistical analysis. These skills can help Data Scientists develop and evaluate solutions to business problems.
Software Engineer
Software Engineers design, develop, and maintain software systems. This course provides a strong foundation in data analytics, which can be helpful for Software Engineers. The course covers topics such as data management, data visualization, and statistical analysis. These skills can help Software Engineers develop software systems that are efficient and effective.
Database Administrator
Database Administrators are responsible for the management and maintenance of databases. This course provides a strong foundation in data analytics, which can be helpful for Database Administrators. The course covers topics such as data management, data visualization, and statistical analysis. These skills can help Database Administrators ensure that databases are running smoothly and efficiently.
Data Engineer
Data Engineers design, develop, and maintain data pipelines. This course provides a strong foundation in data analytics, which can be helpful for Data Engineers. The course covers topics such as data management, data visualization, and statistical analysis. These skills can help Data Engineers build and maintain data pipelines that are efficient and effective.
Statistician
Statisticians collect, analyze, and interpret data. This course provides a strong foundation in data analytics, which is essential for Statisticians. The course covers topics such as data management, data visualization, and statistical analysis. These skills can help Statisticians develop and evaluate statistical models.

Reading list

We've selected 12 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Implementing Supply Chain Analytics.
Specifically explores data analytics techniques in the context of supply chain management.
Provides a comprehensive overview of supply chain management, including planning, operations, and analytics.
Covers statistical methods and techniques used in supply chain analysis, including descriptive, inferential, and predictive analytics.
Discusses the use of blockchain technology to improve transparency, traceability, and efficiency in supply chains, complementing supply chain analytics efforts.
Provides a general overview of data science techniques and their applications in various business contexts.
Serves as a practical guide to using Python for data analysis and manipulation, providing a foundation for implementing supply chain analytics techniques.
Offers a hands-on introduction to SQL for data analysis, providing learners with the necessary skills to query and manage data in supply chain analytics.

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