Business and Supply Chain management professional with over 12 years of rich experience in orchestrating and optimizing end to end supply chain solutions. Aided with world class business education from Cranfield University, Micro master’s in supply chain management (MIT) and certification from APICS CPIM, have enabled me to create solutions for business in improving bottom line results for the companies I have worked for. My expertise lies in designing and building global supply chain networks, Demand and Supply Planning, Inventory & Warehouse Management, Commercial Operations, Customer Service, and E-commerce order fulfillment.

You can checkout my LinkedIn profile at https://www.linkedin.com/in/ashwinmoorkoth/

End to End supply chain management- Process, People and System

Laying down the canvas for Digital journey- especially Supply Chain Function

Demand Planning- Forecasting, Supply Planning, MRP

Inventory and SLOB management

Sales and Operational Planning

Budgeting

Technical Skills: Supply Chain Planning / Business Intelligence / Oracle JDE / SAP / Tableau / Python / Data Science

Time Series forecasting is a very important technique used in the demand planning process. Predicting future demand is one of the most valuable activities the organizations can undertake. A demand plan’s impact is felt throughout the business, from sales and marketing to manufacturing and distribution. When forecasting models are built correctly, demand planning can position the company in a great position to deliver superior customer service while meeting their financial objectives. Blow is a project to display its capabilities using Tableau's SuperStore dataset. It gives an understanding into model selection evaluation and forecasting into the future.

Forecasting Using Time Series Methods Link

Forecasting of Freight Rates done using regression methods (This gives us an insight into the process of doing regression)

Forecasting Using Regression Link

This project focusus on the application of discrete optimization on procurement function the example looks at frieght procurement. This model can be extended in procureing any services or products. The optimization is run on Excel with a new Python based solver which can manage a lot more decision variables. We also look into to the process of decision making which running these models.

Procurement Optimization Link

The model created for Optimization can be downloaded here

ABC Segmentation Link

Supply Planning Summary Link

Supply Planning Logic Link

1. Forecasting using time series

   • Updating the current book to include error tracking
   • Automatic Forecasting - With a few products, and a few forecasting models we put in mechanisms to select the best model and forecast baseline. Grid search for ARIMA models.
     • Best Fit
     • Bayesian Blend

2. Production Optimization

   • Simple Huristics : Level Producton Strategy; Chase Producton Strategy
   • Specialized Heuristcs : Silver Meal Algorithm
   • Discreate Optimization : Mixed integer linear programming

3. Multi-Echelon Inventory Optimization