Prescriptive Analytics Project Ideation from Coursera

Prescriptive Analytics Project Ideation is about the art of transforming data into actionable optimal strategies. This course begins with an overview of prescriptive analytics, exploring key methods like optimization and simulations. You'll then delve into real-world applications across various industries, with applications in investing and staffing optimization. The course also includes a comprehensive sprint phase for problem identification and solutions mapping, culminating in a final project plan review and insights from industry experts.

Learning objectives:

- Examine how prescriptive analytics methods are used by businesses to make optimal decisions.

- Formulate optimization models to solve portfolio investment and staffing decisions

- Analyze business needs and define a prescriptive analytics project plan

What's inside

Syllabus

Course Overview

Module 1: Overview of Prescriptive Analytics

This module introduces prescriptive analytics, covering key methods like optimization and simulations, and the essential features of optimization problems. It also explores practical applications of prescriptive analytics across various industries, including manufacturing, supply chain, marketing, finance, transportation, and logistics.

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Explores prescriptive analytics, which is used to transform data into actionable strategies, making it highly relevant for professionals in data analysis and business strategy

Formulates optimization models to solve portfolio investment and staffing decisions, which are core skills for professionals in finance and operations management

Analyzes business needs and defines a prescriptive analytics project plan, which is useful for students and professionals looking to apply data-driven decision-making in real-world scenarios

Includes insights from an industry expert on optimization in the airline industry, which may be of particular interest to learners in the field of aviation and transportation

Begins with an overview of prescriptive analytics, exploring key methods like optimization and simulations, which builds a strong foundation for beginners

Uses PICK charts for prioritizing business needs, which is a tool that may be unfamiliar to some students and professionals

Reviews summary

Prescriptive analytics project ideation framework

According to learners, this course provides a practical framework for project ideation in prescriptive analytics. Students particularly appreciate the structured approach to problem identification using tools like SCQ and PICK charts, finding the methods highly applicable across industries. The real-world examples, especially in investment and staffing, are highlighted as very relevant. However, some students note that the analytics content is relatively high-level and lacks hands-on implementation details. The course focuses strongly on the business problem side of prescriptive analytics projects, meaning learners seeking deep model-building skills may need supplementary resources. Overall, it's seen as a solid foundation for understanding how to approach and plan such projects.

Strong focus on the business side of project planning.

"The project ideation framework is useful."

"Focus is heavily on the *business problem* side, less on the *analytics solution* side."

"Useful for ideation but you'll need other resources for implementation."

Examples and applications are relevant to business.

"The real-world examples were helpful."

"The staffing and investment examples were very relevant."

"Excellent course for anyone looking to apply analytics to business problems."

Offers useful frameworks for project ideation.

"Great course, very practical framework (SCQ, PICK)."

"The structured approach to problem identification was the highlight."

"The frameworks taught for problem identification and solution mapping are applicable across industries."

Analytics content is high-level, lacks implementation.

"Could use more hands-on coding examples for the models, rather than just the theory."

"Didn't really teach *how* to build the models, just *what* they are and *where* to apply them."

"If you're already familiar with basic optimization, you won't learn much new there."

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 Prescriptive Analytics Project Ideation with these activities:

Review Linear Algebra Fundamentals

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Reinforce your understanding of linear algebra, which is fundamental to understanding optimization techniques used in prescriptive analytics.

Browse courses on Linear Programming

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Review key concepts like vectors, matrices, and linear transformations.
Practice solving systems of linear equations.
Understand the geometric interpretation of linear algebra concepts.

Read 'Optimization Modeling with Spreadsheets'

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Learn how to use spreadsheets to build and solve optimization models, a practical skill for prescriptive analytics.

View Optimization Modeling with Spreadsheets on Amazon

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Work through the examples in the book.
Experiment with different optimization models.
Apply the techniques to real-world problems.

Read 'Business Analytics: The Science of Data-Driven Decision Making'

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Gain a broader understanding of business analytics and how prescriptive analytics fits into the larger picture.

View Business Analytics on Amazon

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Read the chapters related to optimization and simulation.
Take notes on key concepts and examples.
Reflect on how these concepts apply to real-world business problems.

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Optimize a Simple Investment Portfolio

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Apply optimization techniques learned in the course to a practical investment portfolio problem.

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Define the investment universe and objectives.
Gather historical data on asset returns and risks.
Formulate an optimization model to maximize returns while minimizing risk.
Solve the optimization model using a solver like Excel Solver or Python libraries.
Analyze the results and interpret the optimal portfolio allocation.

Write a Blog Post on Prescriptive Analytics Applications

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Solidify your understanding of prescriptive analytics by explaining its applications in a clear and concise manner.

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Research different applications of prescriptive analytics across industries.
Choose a specific application to focus on.
Write a blog post explaining the application, its benefits, and challenges.
Include real-world examples and case studies.

Develop a Staffing Optimization Model

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Create a model to optimize staffing levels based on demand forecasts and cost considerations.

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Gather data on historical demand and staffing levels.
Develop a forecasting model to predict future demand.
Formulate an optimization model to minimize staffing costs while meeting demand requirements.
Implement the model using a spreadsheet or programming language.
Present the model and results to stakeholders.

Complete a Discrete Event Simulation Tutorial

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Gain hands-on experience with discrete event simulation, a key method in prescriptive analytics.

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Find an online tutorial on discrete event simulation using a software like AnyLogic or Simio.
Follow the tutorial step-by-step to build a simulation model.
Experiment with different parameters and scenarios.
Analyze the results and draw conclusions.

Career center

Learners who complete Prescriptive Analytics Project Ideation will develop knowledge and skills that may be useful to these careers:

Staffing Manager

A Staffing Manager oversees employee recruitment, placement, and retention. This role involves optimizing staffing levels, managing employee schedules, and ensuring compliance with labor laws. This course helps learn how to formulate optimization models to solve staffing decisions. The examination of prescriptive analytics methods, simulations, and their real-world applications in staffing are valuable in optimizing staffing strategies. The sprint phases on problem identification and solutions mapping can provide a framework for success. This may require a master's degree.

See salaries and explore the career path for Staffing Manager

Investment Strategist

An Investment Strategist develops investment strategies and recommendations for institutional or individual clients. This role requires a deep understanding of financial markets, economic trends, and investment instruments. This course helps learn how to formulate optimization models to solve portfolio investment decisions. The module on optimization and simulations, with its focus on investment optimization through SCQ analysis, will provide practical tools and techniques. The real-world applications of prescriptive analytics in finance are valuable in developing effective investment strategies. The course will set an aspiring Investment Strategist up for success.

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Operations Research Analyst

An Operations Research Analyst uses optimization and simulation techniques to improve organizational efficiency. This role involves analyzing complex problems and developing mathematical models to identify optimal solutions. This course, with its focus on prescriptive analytics, helps build a foundation for understanding and applying these methods. The modules on optimization and simulations, along with real-world applications across various industries, provide practical insights. The project plan review will be helpful for presenting potential solutions with data to back up the recommendations. Developing skills in problem identification and solutions mapping will set up an aspiring Operations Research Analyst for success.

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Revenue Manager

A Revenue Manager optimizes pricing and inventory to maximize revenue for a business, often in industries like hospitality or airlines. This course helps understand how prescriptive analytics can be applied to make optimal decisions related to revenue management. The focus on optimization and simulations, coupled with the real-world applications in the airline industry, provide valuable insights. The prescriptive analytics sprint phases on problem identification and solutions mapping can help in identifying revenue management challenges and developing data-driven solutions. The final project plan review and insights from industry experts are particularly useful.

See salaries and explore the career path for Revenue Manager

Financial Analyst

A Financial Analyst provides guidance to businesses and individuals making investment decisions. This role often involves analyzing financial data, identifying investment opportunities, and developing financial models. This course helps learn how to use prescriptive analytics to formulate optimization models for portfolio investment decisions. The course's examination of prescriptive analytics methods and real-world applications in finance are helpful for success in the financial industry. The prescriptive analytics sprint phases on problem identification and solutions mapping are also useful in approaching financial challenges from a data-driven perspective. The optimization and simulations module may be useful in the work of a Financial Analyst.

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Management Consultant

A Management Consultant advises organizations on how to improve their performance and efficiency. The role often involves analyzing business needs and developing strategies for optimization. Knowing prescriptive analytics can be useful in consulting work. This course helps in learning the use of prescriptive analytics in making optimal decisions. The prescriptive analytics sprint phases on problem identification and solutions mapping will provide a structured approach to tackle business challenges. The final project plan review and insights from industry experts will give helpful real-world context. A Management Consultant may find the material on optimization modeling for portfolio investment and staffing decisions directly applicable.

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Pricing Analyst

A Pricing Analyst determines optimal pricing strategies for products or services to maximize revenue and profitability. This role involves analyzing market data, customer behavior, and competitor pricing. Prescriptive analytics can play a critical role in optimizing price. This course helps learn the skills needed to formulate optimization models and analyze business needs. The prescriptive analytics sprint phases on problem identification and solutions mapping are useful for addressing pricing challenges. The real-world applications of prescriptive analytics across various industries provide valuable insights. A Pricing Analyst may find the optimization tools and methodologies to be directly relevant.

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Data Scientist

A Data Scientist analyzes large datasets to extract meaningful insights and develop predictive models. While not exclusively focused on prediction, prescriptive analytics plays a crucial role in guiding decision-making based on data insights. This course helps build skills in prescriptive analytics methods and their application to various industries. The modules on optimization and simulations, coupled with the sprint phases for problem identification and solutions mapping, are helpful for building a data-driven decision-making skillset. The real-world examples and industry expert insights provided in the course are valuable in understanding data science in a business context. Many data scientists require a master's degree or a phd.

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Supply Chain Analyst

A Supply Chain Analyst manages and optimizes the flow of goods and services from suppliers to customers. Prescriptive analytics can be applied to several areas within supply chain management. This course helps gain familiarity with optimization and simulation methods, which are essential for optimizing supply chain processes. The course's exploration of real-world applications across various industries, including supply chain management, provides practical insights. The modules on problem identification and solutions mapping are also helpful for identifying and addressing supply chain challenges. The course can set up a Supply Chain Analyst for success.

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Logistics Manager

A Logistics Manager oversees the transportation, warehousing, and distribution of goods. This role involves optimizing logistics operations, managing inventory levels, and ensuring on-time delivery. This course helps understand how prescriptive analytics can be applied to optimize logistics processes. The module on problem identification and solutions mapping is useful for identifying and addressing logistics challenges. The real-world applications of prescriptive analytics across various industries, including transportation and logistics, are valuable in understanding best practices. A Logistics Manager may find the optimization and simulation tools to be immediately relevant.

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Business Intelligence Analyst

A Business Intelligence Analyst examines data to identify trends and insights that can improve business decisions. This course may be useful for understanding how prescriptive analytics can be incorporated into business intelligence strategies to recommend optimal courses of action. The course's exploration of prescriptive analytics methods and their applications across industries can give a professional insight into different areas of business. The focus on problem identification and solutions mapping can help in translating data insights into actionable strategies. The sprint phases in the course can help develop the critical thinking and analytical skills necessary for success as a Business Intelligence Analyst.

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Quantitative Analyst

A Quantitative Analyst, often working in finance, develops and implements mathematical models for pricing, risk management, and trading strategies. This role demands a strong background in mathematics, statistics, and computer programming. This course may be useful as it introduces optimization and simulation methods, as well as their applications in investment. The focus on formulating optimization models to solve portfolio investment decisions aligns with the work of a Quantitative Analyst. This career often requires a master's degree or a phd.

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Project Manager

A Project Manager plans, executes, and closes projects, ensuring they are completed on time and within budget. While project management is broad, knowledge of prescriptive analytics can be applied to resource allocation and optimization of project timelines. This course may be helpful in understanding how to apply prescriptive analytics to optimize project-related decisions. The prescriptive analytics sprint phases on problem identification and solutions mapping provide a structured approach to project planning. The final project plan review can reinforce key project management skills. A project manager may find the tools taught to be helpful.

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Business Development Manager

A Business Development Manager identifies and pursues new business opportunities to drive revenue growth. While not strictly analytical, understanding prescriptive analytics can give a Business Development Manager a competitive edge in identifying and evaluating opportunities. This course may be useful as it explores how prescriptive analytics methods are used by businesses to make optimal decisions. The sprint phases on problem identification and solutions mapping will provide a structured approach to evaluating potential business ventures. The real-world applications of prescriptive analytics across various industries will provide valuable insights. Knowledge of prescriptive analytics can make a Business Development Manager more effective.

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Data Analyst

A Data Analyst gathers, cleans, and analyzes data to identify trends, patterns, and insights that can inform business decisions. While data analysis is a broad field, knowledge of prescriptive analytics can help a data analyst develop more actionable recommendations. This course may be useful as it provides an overview of prescriptive analytics methods, optimization, and simulations. The sprint phases on problem identification and solutions mapping can help with translating data insights into actionable strategies. This course may be useful.

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Prescriptive Analytics Project Ideation

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