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Ethnic Wear · Fashion
Self ServeConnected Planning

Vastramay transforms pre & in-season planning with TrueGradient

Vastramay, a growing ethnic wear brand, partnered with TrueGradient to move away from manual, spreadsheet-based planning — achieving 20% higher demand forecasting accuracy, minimised peak-season stockouts, and optimised inventory across their multi-echelon network.

Key Results
+20%Forecast Accuracy
Min.Peak-Season Stockouts
OptimisedMulti-Echelon Inventory
Vastramay transforms pre & in-season planning with TrueGradient
Company Overview

Vastramay is a growing ethnic wear brand for which weddings and festivals are critical revenue periods. The company faced significant complexities in managing demand during these peak periods, which are essential to annual performance. Previously relying on manual, spreadsheet-based planning, Vastramay partnered with TrueGradient to bring AI-driven structure to both pre-season and in-season planning.

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The Challenge

What Vastramay needed to solve

1

Inaccurate pre-season planning and manual BOM management

Pre-season demand plans were inaccurate, and bill of materials management was handled manually — creating misalignment between finished product demand and raw material procurement.

2

In-season stockouts during peak periods

Stockouts during weddings and festive seasons — the most critical revenue windows for the brand — directly impacted sales and customer experience.

3

Sub-optimal inventory across a multi-echelon network

Inventory levels were not optimally set across Vastramay's distribution network, resulting in excess stock in some locations and shortage in others simultaneously.

4

Ineffective pricing and markdown strategies

Without data-driven pricing and markdown tools, end-of-season liquidation was sub-optimal, eroding margins and leaving excess inventory unresolved.

How TrueGradient Helped

The approach

1

Vastramay moved away from manual, spreadsheet-based planning to adopt TrueGradient's AI-powered connected planning platform. The AI-driven forecasting engine utilises deep learning, machine learning, and econometrics to analyse both internal and external factors — including Indian wedding dates and festive events — to generate accurate demand forecasts.

2

TrueGradient's connected planning capability synchronises forecasts across bundles, individual styles, and raw materials, streamlining procurement and production planning. This gave Vastramay's buying and operations teams a unified view from finished product demand all the way down to raw material requirements.

3

Multi-echelon inventory optimisation tools and strategic pricing and markdown capabilities were deployed to address inventory positioning and end-of-season liquidation — replacing subjective decisions with data-driven recommendations.

What Was Deployed

TrueGradient capabilities in action

AI-driven demand forecasting

Deep learning, machine learning, and econometric models analyse internal sales data and external factors — including Indian wedding dates and festive events — to generate accurate pre-season and in-season forecasts.

Connected planning across styles and raw materials

Forecasts are synchronised across bundles, individual styles, and raw materials — streamlining procurement and aligning production with actual consumer demand.

Multi-echelon inventory optimisation

Inventory levels are optimised across the full distribution network simultaneously, reducing both excess stock and stockout risk across all locations.

Pricing and markdown optimisation

Strategic pricing and markdown tools maximise revenue and protect margins through data-driven end-of-season liquidation recommendations.

Results

Measurable outcomes for Vastramay

20% increase in demand forecasting accuracy

Enhanced forecasting for new products

Optimised inventory holding and more effective liquidation strategies

Improved production efficiency by aligning finished product demand with raw material requirements

Minimised stockout situations during critical peak seasons — weddings and festive periods

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