Certificate Program In
Supply Chain Management
Digitization has led to access of large amount of high speed data. However, insighting from this data remains elusive. This course enhances a supply chain professional’s familiarity with the analytics tools and technologies and shall enhance their data driven decision making skills – a critical skill for career growth.
Certificate Program In
Supply Chain Management
Key Learning Items
Equipment Needed
Who Should Attend
- Digital Transformation related roles
- IT Professionals
- Marketing Professionals
This course is designed for any professional who is part of the Digital Transformation projects in an organization or aims to part of such transformations. Professionals in the IT Department who make decisions on the analytics tools to be procured for supply chain planning and execution will benefit greatly from the course. The section on demand forecasting will be especially useful to the Marketing Professionals.
Competencies
Descriptive Data Analytics
Ability to discover problems in the supply chain with descriptive Data Analytics.
Forecast Demand
Forecast demand and apply the appropriate technique for demand forecast demand.
Analyze Outputs
Analyze data analysis outputs and take necessary action based on the analytics.
Course Overview
Supply Chain Digitization is the most important agenda in almost all organizations with the objective of improve innovation, efficiency and responsiveness. Digitization has led to the accumulation of large amount of high speed data that originate from unique sources. However, insighting from this data remains elusive. Supply Chain professionals in Organizations need to develop the skills to envision the potential of analytics, to tease out problems that may not be explicitly visible and discover hidden opportunities. This course aims to familiarize managers with different types of analytics possible from various data sources.
Learning Style
The course has a balanced mix of theories, models and analytical techniques and implementation challenges. Theories will be explained with the help of real life examples and will be in lecture model followed by interactive Q&A for doubts and clarifications. Relevant videos demonstrating a concept in action will be played and subsequently analyzed. Participants will be given small caselets on which they can apply the theories. The faculty shall demonstrate application of analytical techniques on excel or a software and provide the data to participants for hands-on practice. Participants will also learn to analyse different situations, choose the appropriate tools /techniques/technologies and partner for Analytics. There will be specific cases in which participants will need to suggest action based on the analysis presented. There may be some quizzes to test comprehension. Participants will be encouraged to share their personal experience of digitization projects that they are involved in.
Detailed Course Agenda
The Course is designed for 50 hrs over 8.5 weeks.
Each week classes will be held for 4.5 hrs across 2 days i.e 2 hrs 15 mins per day.
Module 1: Introduction to Supply Chain Strategy and Processes (6 Hrs)
- The Triple A framework of Supply Chain
- The link between Business Strategy and Supply Chain Strategy: Efficient vs Responsive Supply Chains
- Supply Chain Processes – Plan, Source, Make, Deliver and Sell
- New Business Models emerging from Value created by the Supply Chain
Pedagogy/Learning tools: Case Studies of New Business models
Module 2: Novel Data Sources for Supply Chain Analytics (3 hrs)
- Organization data from internal systems
- Data Available Outside Organization boundaries
- Unstructured Data from Reviews, Social media, blogs etc
- Data Sources from new technologies
- Internet of Things
- Blockchain
Pedagogy/Learning tools: Explanation of Concepts in lectures. Videos of new technologies that give rise to new data
Module 3: Descriptive Statistics (12 hrs)
- Process of Problem Discovery through Analytics
- Pre-processing of raw data from core Supply Chain Systems. Data Validation of Data from multiple core systems. Handling missing data, Collating data from different systems to make it meaningful for analysis.
- Descriptive Analytics, Supply Chain Metrics
- Spends/Sourcing Analytics
- Inventory Analytics: ABC XYZ Analysis
- Logistics Analytics: Delivery Cost and Service Level Metrics
- Production Analytics: Process, Capacity, Quality and Service Analytics metrics
- Customer Analytics: Customer Acquisition and Retention Metrics
Pedagogy/Learning tools: Demonstration of data pre-processing. Demonstration of Calculation of Metrics from Raw data, Visualization of Data based on Case studies. Excel files with data will be shared and students are expected to identify challenges in data.
Module 4: Predictive Analytics (12 hrs)
- What is Predictive Analytics
- Various Use Cases for Prescriptive Analytics
- Demand Forecasting
- Time Series Techniques
- Causal techniques
- Process of Predictive Modelling: From Building models to evaluating model fit.
- Supervised Models
- Predicting Customer Churn
- Based on Structured Data
- Based on Unstructured Data – Text Mining Topic Modelling
- Predicting Customer Churn
- Predicting Equipment Failure
- Unsupervised Models
- Dimensionality Reduction: Reducing number of variables to simplify model building.
- Clustering: Use cases in Recommender Systems and Segmentation
Pedagogy/Learning tools: Explanation of Concepts in lectures. Case Discussions. Demonstration of Developing a Predictive model with analytical tools.
Module 5: Prescriptive Analytics (8 hrs)
- What is Prescriptive Analytics?
- Examples of new age use cases of Real time Prescriptive Analytics in Supply Chain fuelled by Digitization. (Driving real time decisions in Manufacturing/ Inventory Management/Logistics or Sales Campaigns or Algorithmic Marketing)
- Analytical framework for specifying a trade-off problems and optimization problems
- Formulation a model for Prescriptive Analytics with hands on exercise e.g. Network Design
Pedagogy/Learning tools: Explanation of Concepts in lectures. Case Discussions. Demonstration of Developing a Prescriptive model.
Module 6: Technology for Supply Chain Analytics (8 Hrs)
- Datawarehousing and Data Center/AWS (including Extraction, Transformation, Loading)
- Modelling Tools: Implementation of Real Time System with Model Building – Case Studies of AWS.
- End to End Supply Chain Solutions.
- Internet of Things and BlockChain.
Pedagogy/Learning tools: Explanation of Concepts in lectures using visual representations. Interesting Videos showing application.
Added Value
Learning tools
Templates
White Papers
Industry Information Websites
Membership
Handbooks
Checklists
Self-assessment models
Academia & Experts As Instructors
Nilendra Singh Pawar
Professor - Operations & Supply Chain Management & Chairperson - PGPM
Nilendra Singh Pawar, an IIM Lucknow & IIT Roorkee alumnus, has a corporate career that spans nearly 20 years across companies like Asian Paints, Kohler and Aditya Birla Fashion & Retail. At SPJIMR, he is the Chairperson for the PGPM program & is an Assoc. Prof. in the Ops. & SCM area.
Interested in Pursuing Supply Chain Management?
Get Started Right Now!
- Or Else Contact Us At:
- 8369020480
- inquiry@knowerx.spjimr.com
- Mindscape, Malad West, Mumbai - 67