Requirements
- Having Basic Statistics knowledge is preferred
- Exposure basic quantitative techniques such as Operations Research is advantage
- Having knowledge of SCM is an added advantage
- Exposure to SCM AI/ML tools is not required
Features
- Foundation on SCM basics built from beginning
- Problem solving approach
- Hands on experience on Analytical Tools
- Case Studies to experience the real world
- Online Learning Management Systems (LMS support)
Target audiences
- Working professionals from Consulting , Manufacturing Logistics and E Commerce
- IT Manager and Project Managers
- Solution Designers and Consultants
- Business Managers
- Engineering Professionals and Management Professionals
- Logistics and E commerce professionals
Background: Development and Implementation of Supply Chain Solutions in the present digital world requires a deep understanding about the basics of the subject together with an exposition of the application areas where such solutions are presently in use. Accenture has been at the forefront of continually developing such state-of-the-art solutions for its esteemed clients. Needless to say developing digital products requires the use of diversified teams who could be involved in Business Development, System Design or Coding. This course on Supply Chain Analytics will try to bring such diverse groups to a common knowledge platform further strengthening the teams’ digital product development capabilities.
Objective of the Workshop: Build analytics foundation and model building capability for the SCM professionals in consulting areas including systems designers and business development teams.
Who should attend: IT system designers, Business Development Managers, and Analytics professionals to build integrated AI/ML platforms in Supply Chain Areas.
Course Features
- Lectures 24
- Quizzes 0
- Duration 26 weeks
- Skill level All levels
- Language English
- Students 15
- Certificate No
- Assessments Yes
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Module I
This is basic introduction to Supply Chain Analytics and cover SCM basics, SCM Challenges and Overview of Analytics in SCM.
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Module II
In this module, we will be introducing Demand Forecasting Techniques. And also we will be working on few problems and cases related to demand forecasting model accuracy.
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Module III
In this module, we are tryin to cover Inventory Management related concepts such as Models, Techniques and Cost Implications on Supply Chain Management.
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Module IV
Logistics and Transportation Models
- Logistics and Transportation Models – Session 07 Part 01
- Transportation Models – Manual Methods Session 08 Part 02
- Solving Transportation problems using Solver Session 09 Part 03
- Solving Assignment problems using Solver Session 10 Part 04
- Techniques & Decisions related to Plant / Warehouse/Retail Locations Session 11 Part 05
- Transportation & Assignment Problems
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Module V
LP formulation and solving problems using excel solver, SCM Modeling and Sensitivity Analysis
- Introduction to LP Formulations – Session 12
- LP Formulation Assignment #0501
- LP Formulation Case #0501
- Solving LP Problems using Excel Solver – Session 13
- LP Formulation Case #0502
- LP Formulation Farm Management Case #0503
- LP Formulation Diet Case #0504
- LP Applications – Session 14
- LP Applications Shipping Wood to Market – Case #0505
- LP Application – Solving Diet Case #0504 – Session 15
- Sensitivity Analysis using solver solution – Part 01 Session 16
- Sensitivity Analysis – a case discussion – Part 02 Session 17
- Solving Business Problems using Integer LP – Session 18
- SCM Modeling using IBP (Binary Integer Programming) Cases #0507 & #5009 -Session 19
- Supply Chain Modeling – Farm Management Case #0509
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Module VI
AI & ML Applications in Supply Chain Management (SCM)
This course is designed for any degree professionals and not specific to Technology or Engineering.
This course is designed for different professionals from different sectors and not specific to IT field.