-
Supplier Pricing Prediction and Segmentation
Introduction
This case study is about a construction equipment manufacturing company who rely on a variety of suppliers to manufacture product assemblies for their equipment. They use these assemblies to lift, load and transport heavy construction loads for their customers.
Our goal was to build and train a model that can predict how much a supplier will quote for a given product assembly based on historical supplier pricing, and use this information to further categorize product assemblies and suppliers based on varying business requirements such as recency, frequency, total spend, supplier rebates so that needs can be accurately classified and responded with appropriate supplier strategy.
Approach
To solve this problem, project was divided in 2 section in the Jupyter Notebook:
-
Section 1: Predicting Supplier Price.
-
Section 2: Categorizing Assembly & Suppliers.
-
Performed data wrangling, EDA to find enhanced features
-
Applied ML models such as Linear, Trees and Clustering to draw insights.
2. Feasibility study for setting up a child care Facility in Calgary Alberta
Introduction
A client wanted to set up a child care facility as a business and was looking for a stable income for future, had limited financial resources and limited knowledge of child care industry.
Approach
BPS worked with client to understand needs and develop plan.
-
Market Study: Customers, Competitors, Regulators, New Trends in education
-
Business Model Selection: Franchise, Own, Home based
-
Financial Modeling: Revenues, Costs, Investment
-
Facility Negotiation: Location identification, Contract Negotiation
-
Closeout