Executive Program on “Supply Chain Analytics”
About Course
What is Supply Chain Analytics and Why it is essential for career growth?
- Supply Chain Analytics has the power to completely transform your business, especially if you are in the manufacturing, automotive, retail, FMCG, IT sectors …
- Supply chain analytics lets you make sense of the data in your supply chain, so you can make better decisions.
- In most organizations, the supply chains have grown and evolved over many years. Each one is a potentially data-creating monster and data can be in all sorts of places and in all sorts of formats
- The global nature of today’s business has led modern supply chains to become more intricate and diverse than anyone could have dreamed of only a few decades ago
- Most organizations have a network of supply chains connecting various suppliers and partners
This complex environment presents a number of critical challenges for a business, including
- Lack of real-time visibility across supply chain operations
- Lack of synchronization between business strategy and execution
- Inability to properly schedule production, leading to costly asset under-utilization
- Poor forecast accuracy, resulting in frequent stock-outs or excess inventory levels
- Lack of flexibility in the manufacturing, distribution and logistics
- Inability to properly assess and prepare for supply chain risks
Applying intelligent analytics is the key to addressing all these challenges
Taking a 360-degree view of the Supply Chain is the only way to collaborate effectively with top performing partners, improve business operations and drive revenue. That’s the high level. At the day-to-day level, it’s simply about getting your questions answered – questions like the following;
- Which material will become shortage for next week?
- What is optimized inventory level for product X/Customer Y?
- What is a better forecast for product X for next year?
- Why Inventory accuracy is poor?
- Which warehouse operatives will be absent on Monday?
- Which SKU will become obsolete?
Benefits of Supply chain analytics;
- Planning & Scheduling
- Improved responsiveness
- Improved demand planning
- Order optimization
- Real time supply chain execution
- Inventory management
- Replenishment planning
- Improved partner performance
- Improved cash performance
Course Content
Session 1 Supply Chain Analytics Introduction
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Supply Chain Evolution
40:08
Session 2 Multi-enterprise Supply Chain
Session 3 Global Optimisation
Session 4 Operating environment
Session 5 Manufacturing strategies
Session 6 Challenges
Session 7 Inputs to Material Planning
Session 8 Production Planning System
Session 9 Strategic Planning
Session 10 Strategic Business Plan
Session 11 Sales & Operations Planning
Session 12 Where does S&OP fit
Session 13 S&OP Processes
Session 14 MPS & MRP
Session 15 Capacity planning and other steps
Session 16 Time fences
Session 17 MPS algorithm using excel
Session 18 MRP
Session 19 Bill of Materials concepts
Session 20 MRP Logic
Session 21 Lead time offsetting
Session 22 Capacity Management
Session 23 Capacity terms
Session 24 Capacity vs load
Session 25 Capacity closed loop
Session 26 Case study
Session 27 Purchasing
Session 28 Types of enquires
Session 29 Purchasing functions
Session 30 Selecting Suppliers
Session 31 Forecasting & demand management
Session 32 Excel case study
Session 33 Forecasting techniques
Session 34 Quantitative methods
Session 35 Forecasting workout in excel
Session 36 Excel Forecasting methods
Session 37 Winter method of Forecasting
Session 38 Forecasting exercise contd..
Session 39 MySQL Exercises
Session 40 Inventory Fundamentals
Session 41 Flow of materials
Session 42 Inventory functions
Session 43 Financial reports
Session 44 Inventory costs
Session 45 Order quantities
Session 46 SQL Exercise
Session 47 SQL workout continued
Session 48 Project work in SQL
Session 49 Forecasting in the presence of special events
Session 50 Centered MA Forecasting method
Session 51 SQL exercise
Session 52 Python Introduction
Session 53 Ordering Systems
Session 54 Standard Deviation
Session 55 Python exercise
Session 56 Python datatypes
Session 57 Python exercises
Session 58 Python workout contd..
Session 59 Physical inventory & warehouse management
Session 60 Warehouse activites
Session 61 Python working
Session 62 Python exercises contd..
Session 63 Python exercise contd…
Session 64 Python exercises contd..
Session 65 Physical distribution
Session 66 Channels of Distribution
Session 67 Warehouse location problem
Session 68 Warehouse location exercise contd..
Session 69 Distribution exercise
Session 70 Vehicle routing problem
Session 71 Workforce allocation problems
Session 72 Inventory optimization problem
Session 73 Python Exercise continued
Session 74 Machine Learning basics
Session 75 Machine learning concepts
Session 76 Visualization
Session 77 Visualization contd…
Session 78 Data Science for Supply chain
Session 79 Data collection
Session 80 Visualization basics
Session 81 Machine learning
Session 82 Statistics by Dr Gita
Session 83 Data science for Supply chain
Session 84 Optimisation
Session 85 Supply chain metrics
Session 86 Python practice
Session 87 Supply chain metrics
Session 88 Statistics by Dr Gita
Session 89 Statistics contd
Session 90 Machine Learning
Session 91 Analytics & Analysis
Session 92 EDA
Session 93 EDA continued
Session 94 EDA Contd..
Session 95 Statistics by Dr Gita
Session 96 Statistics by Dr Gita
Session 97 Python – ML – Forecasting
Session 98 Python – ML – forecasting
Session 99 Python – ML – Forecasting
Session 100 Python – ML – forecasting
Session 101 Statistics – Dr Gita
Session 102 Statistics – Dr Gita
Session 103 Python – ML – Forecasting
Session 104 Python – ML – Forecasting
Session 105 Python – ML – Forecasting
Session 106 Python – ML – Forecasting
Session 107 Python – ML – Forecasting
Session 108 Statistics – Dr Gita
Session 109 Python – ML – Detailed Project
Session 110 Python – ML – Detailed Porject
Session 111 Python – ML – Detailed project
Session 112 – Python – ML – Detailed Project
Session 113 Python – ML – Detailed project
Session 114 Python – ML – Detailed Project
Session 115 Python – ML – Detailed project
Session 116 Python – ML -Detailed project
Session 117 Python – ML – Detailed project
Session 118 Python – ML – Detailed Project
Session 119 Python – ML – Detailed project
Session 120 Python – ML – Detailed project
Session 121 Python – ML – Detailed project
Session 122 Python – ML – Detailed Project
Session 123 Python – ML – Detailed project
Session 124 Python – ML – Detailed Project
Session 125 Python – ML – Detailed Project
Session 126 Python – ML – Detailed project
Session 127 Python – ML – Detailed project
Session 128 Python – ML – Detailed project
Session 129 Python – ML – Detailed project
Session 130 Python – ML – Detailed project
Session 131 Python – ML – Detailed Project
Session 132 Python – ML – Detailed project
Session 133 Python – ML – Detailed project
Session 134 Python – ML – Detailed project
Session 135 Python – ML – Detailed project
Session 136 Python – ML – Detailed project
Session 137 Python – ML – Detailed project
Session 138 Python – ML – Detailed project
Session 139 Python – ML – Detailed project
Session 140 Python – ML – Detailed project
Session 141 Python – ML – Detailed project
Session 142 Python – ML – Detailed project
Session 143 Python – ML – Detailed project
Session 144 Python – ML – Detailed project
Session 145 Python – ML – Detailed project
Session 146 Python – ML – Detailed project
Session 147 Python – ML – Detailed project
Session 148 Python – ML – Detailed project
Session 149 Python – ML – Detailed project
Session 150 Python – ML – Detailed project
Session 151 Python – ML – Detailed project
Session 152 Python – ML – Detailed project
Session 153 Python – ML – Detailed project
Session 154 Python – ML – Detailed project
Session 155 Python – ML – Detailed project
Session 156 Python – ML – Detailed project
Session 157 Python – ML – Detailed project
Session 158 Python – ML – Detailed project
Session 159 Python – ML – Detailed project
Session 160 Python – ML – Detailed project
Session 161 Python – ML – Detailed project
Session 162 Python – ML – Detailed project
Session 163 Python _ ML – detailed project
Student Ratings & Reviews
It was a really good program, and the team helped me with installing software and further enquires, Thanks to the Exxpertscm team
There are teaching everything using a real-time database for all projects also am a fresher their provided me internship unpaid only but worked in real-time project which has given me added advantage in my cv.
I have done so much research from this sca syllabus with others found this is best from others I took one month to do research and purchased this program really excellent syllabus and teaching.
I was in search of a course for my career change. Exxpert SCM gave me an opportunity to learn and supported me by assisting in placement. The course is easy to understand and it is fruitful, It\'s one of the excellent courses in the supply chain. Thank you Raman sir for directing me to this course according to my profile.
. This course did a great job explaining the assignments and had thorough explanations of the weekly concepts. I am interested to learn more about supply chain-related courses as I grow further in my career. Great course and the live recorded videos were well explained!
Very informative course on Supply Chain Analytics which clears SCM concepts in a clear and easy way. Also gives clarity on how data analytics can be used in making supply chain-related decisions.
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