P K Patel & Associates

Process Automation

Real-Time Pricing Engine for Manufacturing

How we built a real-time pricing application using Node.js and Python to eliminate quote delays caused by raw material price volatility.

Business explainer: automation.
By P K Patel & AssociatesPublished 7 min read
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Engagement at a glance

Industry
Manufacturing
Focus
Process Automation
Systems and work involved
Node.js · Python · BOM Engine · Web Application
On this page

The business context

A manufacturing company faced a recurring bottleneck in their sales process. Every time a customer asked for a quote, the sales executive had to approach the Sales Director. The Sales Director would then contact the purchase department to get the latest raw material prices, manually calculate the final product cost using BOM logic, add margins, and share the price back with the sales team. This back-and-forth consumed hours — sometimes days — especially when raw material prices fluctuated daily.

The challenge

Quote Turnaround Delays

Sales executives could not respond to customer pricing inquiries independently. Every quote required the Sales Director's involvement, creating a single point of failure.

Daily Raw Material Volatility

Metal and commodity prices changed daily. The purchase team tracked these manually, and there was no system to propagate updates to the pricing logic in real time.

Manual BOM Calculations

Bill of Materials calculations — including raw material costs, processing costs, overheads, and profit margins — were done manually in spreadsheets, prone to errors and inconsistency.

What we found

What we changed

Raw Material Price Portal

Built a simple web interface where purchase executives enter daily RM price updates. Each entry is timestamped and versioned for audit trail.

BOM & Cost Engine

Developed a Python-based calculation engine that takes the latest RM prices, applies predefined BOM structures (material quantities, waste factors), adds processing costs, overheads, and profit margins to compute the final offer price.

Sales Pricing Dashboard

A Node.js web application where sales executives can select a product, view the current offer price, and generate quotes instantly — no need to call anyone.

Admin Configuration Panel

Management can update BOM structures, margin percentages, overhead rates, and cost rules without touching code. Changes reflect immediately in pricing.

Implementation

  1. Week 1-2: Mapped the complete pricing workflow — from RM purchase to final customer quote. Documented all BOM structures, cost components, and margin rules.

  2. Week 3-4: Built the Python pricing engine with configurable BOM logic and cost calculation formulas.

  3. Week 5-6: Developed the Node.js web application with separate portals for purchase team (price entry) and sales team (quote generation).

  4. Week 7-8: Testing, parallel runs comparing app prices vs manual calculations, and team training.

  5. Week 9: Go-live with the purchase team entering prices daily and sales team generating quotes independently.

Outcomes

AreaResult described in this case
Quote TurnaroundReduced from hours/days to under 2 minutes
Sales Director DependencyEliminated for routine pricing — freed up for strategic decisions
Pricing ErrorsNear-zero calculation errors with automated BOM logic
Price Update PropagationDaily RM price changes reflected instantly across all product prices

The practical lesson

This material is general information. Apply it to your business only after checking the relevant facts, source documents and requirements.