goodjorx / price-elasticity-thesis

Schneider Electric Iberia: Pricing Optimization and Sales Forecasting Project

This repository contains the implementation of an advanced data science project that aims to optimize product pricing and forecast sales for Schneider Electric Iberia. The project, undertaken as part of an MSc thesis, applies various data science techniques to facilitate efficient decision-making and strategic planning.

Overview

The project begins with a meticulous investigation of Schneider Electric Iberia's prevailing pricing and sales forecasting systems to identify potential limitations and areas of improvement. Subsequently, potent data science techniques such as econometrics, causality analysis, and transformer models are explored and leveraged to develop a pricing model and sales forecasting model.

Objectives

The key objectives of this project are:

1. Understanding the existing pricing and sales forecasting systems at Schneider Electric Iberia.
2. Identifying advanced data science techniques suitable for pricing optimization and sales forecasting.
3. Developing a robust pricing model to maximize either revenue or sales volume based on strategic priorities.
4. Implementing the pricing model for accurate sales forecasting.
5. Evaluating the model's transformative impact on operational processes, profitability, and strategic decision-making.

Private Access

For access, please send a request to email address. The private thesis repository can be found here.