University of Missouri – Marketing Supply Chain Analytics 2017-12-07T11:44:05+00:00

Project Description

Marketing Supply Chain Analytics

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Summary

This course focusses on applying data analytic tools and techniques at various supply chain stages, specifically focusing on retailers. At the end of the course, the students will develop supply chain analytical skills for solving several marketing supply chain problems such as demand forecasting, inventory management, and sales & operations planning.

Student Insights

# StudentsDegreeField of StudyCollaboration Period (days)International Students (%)
32BachelorBusiness,Economics9725

Description

Relying on traditional supply chain execution systems is becoming increasingly more difficult, with a mix of global operating systems, pricing pressures and ever increasing customer expectations. There are also recent economic impacts such as rising fuel costs, the global recession, supplier bases that have shrunk or moved off-shore, as well as increased competition from low-cost outsourcers. All of these challenges potentially create waste in your supply chain. That’s where data analytics comes in.

Data analytics is the science of examining raw data to help draw conclusions about information. It is used in many industries to allow companies and organization to make better business decisions and in the sciences to verify (or disprove) existing models or theories.

  1. Introduction to Data Analytics
    – Data extraction
    – Data cleansing
    – Database management
  2. Introduction to Supply Chain
    – Definition of supply chain
    – Cases in supply chain
    – Successful strategies followed by top 25 supply chains
    – Issues in supply chain and its impact on customers
  3. Product Demand Forecasting
    – Forecast demand for different types of products using historical demand pattern
    – Sales promotion and discounts
  4. Sales and Operations Planning using Association Rule Mining
    – Analyze customers’ buying behavior
    – Discover relationships between unrelated variables
    – Propose merchandising strategies to improve sales
  5. Customer Review Analysis for Sales Improvement
    – Analyze online customer reviews (OCR) using topic modelling
    – Propose solutions to retailers to improve sales based on OCR
  6. Capacity Planning and Staffing Problems
    – Staffing decisions at Retailers
    – Automated End-to- End Inventory Management of Products at Retailers
  7. Multiple Criteria Decision Making in Supply Chains
    – Analyze several conflicting criteria such as supply chain responsiveness, risk and
    efficiency
  8. Different types of supply chain
    – Cases in healthcare supply chain, financial supply chain and food supply chain

Objectives

By the end of the class, students will be able to:
1) Understand the special challenges in supply chain management in industry and service sectors
2) Know how to use data analytical skills for solving real world supply chain problems
3) Develop marketing and corporate strategies for the retailers
4) Interpret business analytics results and propose managerial implications

Expected solution proposals

Reports / Analysis

Methods

– Data extraction
– Data cleansing
– Database management

Top Competencies

CommunicationCritical thinking / problem-solvingJudgement and Decision Making