4 steps to build an ESG reporting focusing on CO2 emissions of your Distribution Network

Supply Chain Sustainability Reporting Methodology
Supply Chain Sustainability Reporting — (Image by Author)

The demand for transparency in sustainable development from investors and customers has grown over the years.

Investors have placed an increased emphasis on sustainability of the business when assessing the value and resiliency of an organization.

Therefore, more and more organizations invest resources to build capabilities for sustainability reporting and…

Perform a Chi-Squared Test to explain a shortage of drivers impacting your transportation network

Lean Six Sigma with Python — Chi-Squared Test for Driver Allocation Problem
Solve a Driver Allocation Problem with Chi-Squared Test — (Image by Author)

Lean Six Sigma is a method that can be defined as a stepwise approach to process improvements.

In a previous article, we used the Kruskal-Wallis Test to verify the hypothesis that a specific training positively impacts operators Inbound VAS productivity. (Link)

In this article, we will implement the Chi-Squared Test…

Understand the impacts of additional features related to stock-out, store closing date or cannibalization on a Machine Learning model for sales forecasting

Machine Learning for Retail Sales Forecasting — Features Engineering
Features Engineering for Machine Learning for Retail Sales Forecasting — (Image by Author)

Based on the feedbacks of the last Makridakis Forecasting Competitions, Machine Learning models can reduce the forecasting error by 20% to 60% compared to benchmark statistical models. (M5 Competition)

Their major advantage is the capacity to include external features that heavily impact the variability of your sales.

For example, e-commerce…

Simulate the impact of safety stock level on inventory management performance metrics assuming a normal distribution of your demand

Inventory Management for Retail — Stochastic Demand
Inventory Management with a Stochastic Demand — (Image by Author)

For most retailers, inventory management systems take a fixed, rule-based approach to forecast and replenishment orders management.

Considering the distribution of the demand, the objective is to build a replenishment policy that will minimize your ordering, holding and shortage costs.

In a previous article, we have built a simulation model…

Build a simple model to simulate the impact of several replenishment rules (Basic, EOQ) on the inventory costs and ordering costs

Inventory Management for Retail — Deterministic Demand
Inventory Management with a Deterministic Demand — (Image by Author)

For most retailers, inventory management systems take a fixed, rule-based approach to forecast and replenishment orders management.

Considering the distribution of the demand, the objective is to build a replenishment policy that will minimize your ordering, holding and shortage costs.

  • Ordering Costs: fixed cost to place an order due to…

Use sample data to estimate the average lead time to process customer orders in the customer service of an elevator parts supplier.

Statistical Sampling for Process Improvement using Python
Statistical Sampling to estimate the average order processing lead time — (Image by Author)

As a critical component of Supply Chain Management, Customer Service is where your company gives your customers a feel of the products and the business that you are selling.

An important performance indicator is the average lead time between the reception of a customer order and its transmission to the…

Apply several principles of the Queueing Theory with Python to design a parcel packing process for an e-commerce fulfilment centre

Supply Chain Process Design using the Queueing Theory
Design a Parcel Packing Process using Queueing Theory — (Image by Author)

Supply Chain can be defined as a network of processes and stock locations built to deliver services and goods to customers.

This network usually supports the business strategy of your company; its objectives can be diverse such as deliver the best quality products, the lowest cost or the most customized…

A statistical methodology to segment your products based on turnover and demand variability

Product Segmentation for Retail with Python
Use Statistics for Product Segmentation — (Image by Author)

Product segmentation refers to the activity of grouping products that have similar characteristics and serve a similar market. It is usually related to marketing (Sales Categories) or manufacturing (Production Processes).

However, as a Logistics Manager, you rarely care about the product itself when managing goods flows; except for the dangerous…

Use non-linear programming to find the optimal ordering policy that minimizes capital, transportation and storage costs

Procurement Process Optimization with Python
Optimize Store Procurement Strategy — (Image by Author)

Procurement management is a strategic approach to acquiring goods or services from preferred vendors, within your determined budget, either on or before a specific deadline.

Your target is to balance supply and demand in a manner to ensure a minimum level of inventory to meet your store demand.

In this…

Replace Minitab with Python to perform a Logistic Regression to estimate the minimum bonus needed to reach 75% of a productivity target

Lean Six Sigma with Python — Logistic Regression
Minimum Bonus Problem- — (Image by Author)

Lean Six Sigma is a method that can be defined as a stepwise approach to process improvements.

In a previous article, we used the Kruskal-Wallis Test to verify the hypothesis that a specific training positively impacts operators Inbound VAS productivity. (Link)

In this article, we will implement Logistic Regression with…

Samir Saci

Senior Supply Chain Engineer — http://samirsaci.com | Data Science for Warehousing📦, Transportation 🚚 and Demand Forecasting 📈

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