Data for Sustainability & Productivity
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🚚 Supply Chain

In the supply chain section, you can access for free the 65+ articles of my medium blog followed by 3.2k+ people with:

  • A statement of the problem to solve based on an actual project
  • Introduction of the mathematical concept used to solve the problem
  • Implementation using Python, VBA or javascript

The goal is to provide all the keys to understanding the concepts and everything you need to adapt the solution to your problem.

❓ Purpose

It all started with problems faced by operations, a customer request for solution design or mathematical concepts I learned.

🚀 Introduction Article

What is Supply Chain Analytics?

What is Supply Chain Analytics?
Use data analytics to improve operational efficiency by enabling data-driven diagnostics and decisions at strategic and operational levels
Samir SaciSamir Saci

🌳 Sustainable Supply Chain

Use Data Analytics to measure the environmental impact of your supply chain and support initiatives for a green transformation roadmap.

This image compares two key concepts: Data Analytics for Supply Chain Sustainability and Life Cycle Assessment. The left side highlights sustainability, including metrics like CO2 emissions (72k tons) and the impact of air freight on supply chain decisions. The right side provides an overview of a Life Cycle Assessment (LCA) for fast-fashion products, tracing their journey from production to disposal, and evaluating environmental impacts such as CO2 emissions and water usage.

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Sustainability - Samir Saci
A technical blog focusing on Data Science, Personal Productivity, Automation, Operations Research and Sustainable Supply Chain.
Samir SaciSamir Saci

📦 Warehousing Operations

I started my career designing warehousing solutions (layout, inbound/outbound process, ...).

This image presents two optimization challenges. On the left, the design of a pathfinding algorithm using Google AI is showcased with graphs illustrating the Traveling Salesman Problem. On the right, the workforce planning problem is depicted with flow diagrams explaining how to manage temporary workers while balancing workload and retention.

Therefore, the first articles focus on solutions to answer operational issues occurring in a warehouse.

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Warehousing Operations - Samir Saci
Warehousing Operations Continuous Improvement
Samir SaciSamir Saci

🚛 Transportation Operations

If you want to reduce lead times or cut logistic costs, transportation optimization is the easiest way.

This image explains several Lean Six Sigma problems. In the top left, the productivity bonus problem shows employees working with transportation and logistics while managers oversee their performance. The top right focuses on VAS (Value-Added Services) operators training (employees learning how to handle garments). The bottom image shows the driver dispatch problem, where a supervisor manages truck drivers' schedules for efficient delivery.The left side of the image illustrates a last-mile delivery problem, showing a map with routes optimized for minimal driver usage. The dispatch center and routes are marked with different colors. The right side presents a road transportation network visualization, highlighting the performance of Full Truck Load (FTL) routes, including delivery costs and truck size utilization across different regions in China.

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Transportation Operations - Samir Saci
Road Transportation Network Design and Optimization using Visualization, Linear Programming and Graph Theory.
Samir SaciSamir Saci

🔗 Supply Chain Optimization

A step further is to leave the local scope of a warehouse and approach the problem from a Supply Chain point of view.

The left side shows a supply chain network design using Monte Carlo Simulation to account for demand fluctuations. It features global market demand and manufacturing capabilities per region. The right side displays a supply planning problem with a visual of two plants and cross-docking locations, optimizing the route to deliver goods to multiple stores with the cheapest cost.

Improve your overall end-to-end performance by optimizing DC Networks, Supply Planning, Inventory Management or anything related to the flow of goods.

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Supply Chain Optimization - Samir Saci
Optimize the Flow of Goods with Network Design, Planning Optimization, Process Mining and Modelisation Tools like Digital Twins.
Samir SaciSamir Saci

📊 Reporting and Automation

Automate the tasks of data extraction and processing from ERPs, WMS or unstructured data using Visual Basic or Python.

This image illustrates two automation scenarios. On the left, the purchase order creation automation showcases the process of generating purchase orders using Excel data, which is integrated into SAP. The right side demonstrates the design of automation tools for Excel users, featuring a flow diagram explaining how Python can automate calculations and generate executable files for colleagues with no coding knowledge.

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Automation & Reporting - Samir Saci
Use Data Analytics Tools (Python, VBA, Javascript) to Design Solutions for Reporting, Visualizations and Tasks Automation.
Samir SaciSamir Saci

⛩️ Lean Six Sigma

Lean Six Sigma (LSS) is a method based on a stepwise approach to process improvements.

This image covers two operational challenges. On the left, it explains the Central Limit Theorem for process improvement, estimating the average number of items returned in cartons with a normal distribution assumption. The right side presents the driver allocation problem, showing an unbalanced allocation of drivers between warehouses and transportation companies using an ERP system to manage routes and schedules.

This approach usually follows 5 steps (Define, Measure, Analyze, Improve and Control) for improving existing process problems with unknown causes.

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Lean Six Sigma - Samir Saci
Replace Minitab with Python to Implement Statistical Tools used for the Lean Six Sigma Approach of Continuous Improvement.
Samir SaciSamir Saci

📦 Inventory Management

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

The left side describes feature engineering for machine learning models, with a focus on improving retail sales forecasts. It includes inputs like maximum sales quantity, pricing trends, and stock-outs. The right side explains inventory management with stochastic demand, featuring graphs that illustrate demand, replenishment cycles, and safety stock levels to optimize performance metrics.

In this section, you can find insights and tips to optimize the inventory, forecast the demand and reduce stock-outs.

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Inventory Management - Samir Saci
Implement Models to Visualization, Simulate and Optimize Inventory Management and Demand Forecasting.
Samir SaciSamir Saci

📤 Logistic Performance Management

Implement operational indicators to measure the performance of your distribution network, audit your supply chain reliability and reduce incidents.

This image covers supply chain resilience and performance management. The left side shows the sources of lead time variability (such as shipment, air freight, and last-mile delivery) and their impact on inventory management. The right side presents a logistic performance management timeline, using data analytics to monitor and improve operations from order creation to store receiving time.

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Performance Management - Samir Saci
Implement Data Analytics Tools (Python, PowerBI, Excel) to Monitor, Diagnose and Improve your Supply Chain Performance.
Samir SaciSamir Saci

📩 Get the articles by Email

This banner encourages users to join a newsletter focused on data analytics, supply chain, and productivity. It features a button to subscribe for free, along with visuals of articles related to topics like transportation network analysis, supply chain optimization, and parcel packing problems.