Business Analytics: A Customized Version of Spreadsheet Modeling for Business Decisions, Fifth Edition by John F. Kros. Designed Specifically for The Ohio State University
Author(s): Terry Klinker
Edition: 1
Copyright: 2016
The field of data analytics has its roots in the 1940’s, primarily in wartime logistics. Since then, data analytic techniques and expanded methodologies are increasingly implemented into the business world. Decisions based on operations research models are proven to increase revenues, decrease costs, and significantly impact the fiscal health of business organizations. Famously, Data Analytics were successfully used by Major League Baseball’s Oakland Athletics in the 1970s, as documented in the film “Moneyball”.
Data analytics models are not limited to operations or production. Data analytics are used finance, tax, marketing, human resources, materials, and logistics. Professions in health care, government, and transportation organizations benefit from the use of these models, and the ability to construct them. Recent computer software developments, combined with the rapidity with which data may now be collected, transferred, and shared, has opened the floodgates to the use of data analytics. Most CEOs of the Forbes Top 50 companies have several data analytics books on their list of required reading for senior executives. Students who master the material presented in the course will have a competitive advantage over their peers both in school and in their future careers.
Business Analytics introduces students to several major decision modeling techniques, demonstrates how to gather data for such models, how to derive and assemble the models, and how to interpret the results and make decisions using the results. Several of the techniques taught are currently used in major corporations on very large scales. In addition, the integration of Microsoft EXCEL (along with the “Goal Seek” and “Solver” add-ins) makes this course an important foundation for future courses at Fisher as well as various business careers.
Part 1 - Decision Analysis
Chapter 1 – The Art and Science of Becoming a More Effective and Efficient Problem Solver
Chapter 2 – Decision Analysis: Building the Structure for Solving the Problem
Part 2 - Optimization Modeling
Chapter 3 – Introduction to Optimization Models
Part 3 - Simulation
Chapter 4 – Simulation Modeling [Chapter 5 from Kros]
Part 4 - Project Management
Chapter 5 – Project Management: PERT/CPM
The field of data analytics has its roots in the 1940’s, primarily in wartime logistics. Since then, data analytic techniques and expanded methodologies are increasingly implemented into the business world. Decisions based on operations research models are proven to increase revenues, decrease costs, and significantly impact the fiscal health of business organizations. Famously, Data Analytics were successfully used by Major League Baseball’s Oakland Athletics in the 1970s, as documented in the film “Moneyball”.
Data analytics models are not limited to operations or production. Data analytics are used finance, tax, marketing, human resources, materials, and logistics. Professions in health care, government, and transportation organizations benefit from the use of these models, and the ability to construct them. Recent computer software developments, combined with the rapidity with which data may now be collected, transferred, and shared, has opened the floodgates to the use of data analytics. Most CEOs of the Forbes Top 50 companies have several data analytics books on their list of required reading for senior executives. Students who master the material presented in the course will have a competitive advantage over their peers both in school and in their future careers.
Business Analytics introduces students to several major decision modeling techniques, demonstrates how to gather data for such models, how to derive and assemble the models, and how to interpret the results and make decisions using the results. Several of the techniques taught are currently used in major corporations on very large scales. In addition, the integration of Microsoft EXCEL (along with the “Goal Seek” and “Solver” add-ins) makes this course an important foundation for future courses at Fisher as well as various business careers.
Part 1 - Decision Analysis
Chapter 1 – The Art and Science of Becoming a More Effective and Efficient Problem Solver
Chapter 2 – Decision Analysis: Building the Structure for Solving the Problem
Part 2 - Optimization Modeling
Chapter 3 – Introduction to Optimization Models
Part 3 - Simulation
Chapter 4 – Simulation Modeling [Chapter 5 from Kros]
Part 4 - Project Management
Chapter 5 – Project Management: PERT/CPM