1. Experiences with Business Analytics Curriculum Implementation
Ina Markham, Susan Palocsay, & Scott Stevens
James Madison University

2. BSAN Admissions Process
Prerequisite competency courses:
One introductory calculus course
One statistics course
One introductory management science course
Grade of B- or higher
One economics course
BSAN minor application form
Recommendation letter from MS instructor
Cohort of 30 juniors selected each fall

3. Analyst Definitions (Davenport & Harris, 2007)
Analytical champions
Executive decision-makers who depend heavily on data analyses to make business decisions
Analytical professionals
Create advanced analytical applications to be used by others in the organization
Analytical semi-professionals
Apply the models and algorithms developed by professionals for routine or specialized decision-making
Analytical amateurs
Knowledgeable consumers of analytics who can apply analytical insights to their work (70-80% of an organization’s analytical talent)

4. Analytics Talent Needed (McKinsey Global Institute, 2011 & 2016; Cegielski & Jones-Farmer, 2016)
Data scientist
Deep knowledge analyst with training in advanced mathematics/statistics/OR
IT support specialist
Technology skills for hardware & software associated with big data
Business translator
Data-savvy with industry/functional expertise
Link data science team and practical business applications
Demand for 2-4 million in US over next decade

5. Categories of Analytics
Descriptive
Predictive
Prescriptive
Information
What happened?
What could happen in the future?
What is the best course of action?
Actions
Prepare & analyze historical data, identify patterns, and report
Predict future probabilities & trends, find hidden relationships in data
Evaluate & determine new ways to operate, balance constraints, and target objectives
Insight
How and why did it happen?
What’s the next best action?
What’s the best/worst that can happen?
Techniques
Data modeling and visualization
Data mining and forecasting
Mathematical optimization and simulation

6. Business Analytics Minor
Required Courses:
COB 191-Business Analytics I (statistics)
COB 291-Business Analytics II (management science)
BSAN 391-Quantitative Business Modeling
BSAN 392-Descriptive and Predictive Analytics
BSAN 393-Predictive Analytics and Data Mining
One Elective:
CIS 463-Business Intelligence
CS/ISAT 344-Intelligent Systems
ECON 385-Econometrics
FIN 475-Financial Modeling and Risk Analysis
MATH 322-Applied Linear Regression
MKTG 482-Marketing Analytics

7. BSAN Courses BSAN 390: Statistical Modeling for Business Analytics
Data visualization, inferential statistics, regression analysis, and ANOVA
BSAN 391: Decision Modeling for Business Analytics
Optimization, sensitivity analysis, multi-objective decision analysis, and simulation
BSAN 393: Data Mining for Business Analytics
Supervised and unsupervised machine learning and statistical techniques

8. BSAN Minor Graduates

9. BI/BSAN Framework [adapted from Klimberg and Miori, 2010]

10. BSAN Major? BBA degree with business core CIS courses BSAN courses
Principles of Programming (Python)
Intermediate Programming (Java)
Database Design and Application
Business Intelligence
BSAN courses
Decision Modeling
Statistical Modeling
Data Mining
New courses?
Open to ideas
Capstone

11. Challenges Students for BSAN minor Teaching classes in computer labs
Limited quantitative capabilities
Strong job market without BSAN
Teaching classes in computer labs
Finding additional course materials
Business data sets for statistics/predictive analytics
BSAN major
Job placement?
Student enrollment?
Faculty resources?