Data Analytics Essentials for Supply Chain and Logistics (DAESL)

Data Analytics Essentials for Supply Chain and Logistics (DAESL)

Data Analytics is transforming the supply chain and logistics industry. This is fast becoming a disruptive trend due to the growing number of companies looking for ways to integrate big data and advanced analytics into their business processes to help streamline operations.

With massive flow of goods daily, supply chain and logistics companies create vast amount of data, providing huge potential for improving operational efficiency, and customer experience. Companies are also beginning to learn how to turn large-scale quantities of data into competitive advantage by precisely forecasting market demand, and radically customize services to fully exploit any untapped data.

The shift in business model in the supply chain and logistics industry is evident and the future favours the utilization of data and technology. Enormous steps have been taken by companies in the past year to adopt Data Analytics as a new strategic objective. A recent study on supply chain and logistics industry trend has also stated that companies are planning to make massive investment in Data Analytics within the next 5 years. This presents professionals skilled in Data Analytics with first-mover advantage to advance their career in the supply chain and logistics industry.

LocationJan to MarApr to JunJul to SepOct to Dec
SingaporeNA19 Apr to 20 AprNANAEnrol Now
Course Objective
Data Analyics Essentials for Supply Chain and Logistics/strong> is designed for Supply Chain Professionals and Anyone interested in acquiring all essential knowledge and skills on how to utilize Data Analytics in as part of their organisation strategic decision making and planning.
Course Duration
16 hours / 2-Day
Course Outline
MODULE 1: FINTRODUCTION TO ANALYTICS  
  • Definition
  • Types of Analytics
  • DCOVA framework
  • Analytics in Supply Chain management & Logistics
    • Reporting
    • Real-time dashboards
    • Benchmarking
  • Introduction to Tools and Software’s commonly used in Analytics
  • Data Sources
MODULE 2: GETTING STARTED WITH R PROGRAMMING  
  • Introduction to ‘R’ Programming Interfaces: R console and R studio
  • Using R Commander Interface
  • MODULE 3: UNDERSTANDING DATA  
  • Population vs. Sample
  • Types of Data Variables
  • Probability Distributions
  • Summarizing data
  • Describe measure of central tendency/measure of location of data set
  • Describe spread/variability of data set
  • Symmetry and Skewness for the distribution of a data set
  • Data Collection
  • Outlier Treatment
  • Missing Value Imputation
  • MODULE 4: BASIC STATISTICS (R COMMANDER)  
  • Loading data
  • Data Exploration using R commander
  • Data Manipulation using R commander
  • MODULE 5: FPREDICTIVE ANALYTICS IN THE SUPPLY CHAIN  
  • IProcurement
  • In-Bound Logisticst
  • Parts Inventoryt
  • Manufacturingt
  • Finished Goods Inventoryt
  • Fulfilment (customer’s order to delivery)t
  • Out-Bound Logisticst
  • Introduction to Rattlet
  • Linear Regressiont
  • Case Study (using Rattle)t
  • Multivariate Linear Regressiont
  • Case Study (using Rattle)t
  • Logistic Regressiont
  • Case Study (using Rattle)t
  • MODULE 6: AN OVERVIEW OF THE DATA ANALYTICS AND BIG DATA ERA  
  • Demand Analytics
  • Finished Inventory Optimization
  • Replenishment Planning Analytics
  • Network Planning and Optimization
  • Transportation Analytics
  • Procurement Analytics
  • Predictive Analytics on the Factory Floor
  • Geospatial Analytics in Network Planning and Optimization
  • Pre-Requisite
    NA
    Examination
    NA
    Certification
    Participants will receive a Certificate of Attendance upon completing the course
    Who Will Benefit from the Course
    Data Analytics Essentials for Supply Chain and Logistics (DAESL) is designed for Supply Chain and Logistics Professionals or Anyone who are interested in aquiring the essential knowledge on how Data Analytics can be utilize to enhance business performance and decision making capabilitiess