Blue Yonder Case Studies Mahindra & Mahindra Drives Profitability via Dynamic Segmentation

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	Mahindra & Mahindra Drives Profitability via Dynamic Segmentation Blue Yonder

Mahindra & Mahindra Drives Profitability via Dynamic Segmentation

Blue Yonder

Technology Category	Platform as a Service (PaaS) - Data Management Platforms Analytics & Modeling - Machine Learning
Applicable Industries	Automotive
Applicable Functions	Logistics & Transportation
Use Cases	Inventory Management Supply Chain Visibility
Services	Data Science Services
Challenge	Mahindra & Mahindra Farm Equipment, part of the $20 billion Mahindra Group, is the world’s number-one tractor company by volume. Its automotive business competes in almost every segment of the industry. The Spares Business Unit (SBU) provides genuine vehicle and tractor spare parts via advanced capabilities in sourcing, assembling, warehousing and distribution. To maximize supply chain efficiencies and service, Mahindra & Mahindra constantly evaluates scientific methods to tweak demand forecasting, inventory management and replenishment planning strategies to ensure that the right parts are available at the right place and time. However, their traditional, manually driven segmentation processes and tools often resulted in inefficient allocation, high safety inventory levels and less-than-optimal service levels. Read More
About Customer	Mahindra & Mahindra Farm Equipment is part of the $20 billion Mahindra Group. It is the world’s number-one tractor company by volume, and its automotive business competes in almost every segment of the industry. The Spares Business Unit (SBU) provides genuine vehicle and tractor spare parts via advanced capabilities in sourcing, assembling, warehousing and distribution. The company constantly evaluates scientific methods to tweak demand forecasting, inventory management and replenishment planning strategies to ensure that the right parts are available at the right place and time. Read More
Solution	Mahindra & Mahindra SBU leverages Blue Yonder Luminate Platform, which applies machine learning (ML) to both systematically classify spare parts into unique demand clusters and establish the significance of demand attributes. The result is built-in visibility, intelligence, context and collaboration tools that enable increased allocation efficiency and profitability. Via optimization techniques, powered by ML, service levels are assigned to demand clusters, with the goal of minimizing safety inventory costs. In addition, ML and artificial intelligence algorithms accurately estimate lead times and further optimize the cost-to-serve from both a customer service and inventory cost perspective. Instead of making manual decisions, the SBU can analyze data at scale, identify critical demand variables and autonomously optimize the supply chain for specified profitability goals. Read More Log in to view content
Contents

Technology Category

Platform as a Service (PaaS) - Data Management Platforms

Analytics & Modeling - Machine Learning

Applicable Industries

Automotive

Applicable Functions

Logistics & Transportation

Use Cases

Inventory Management

Supply Chain Visibility

Services

Data Science Services

Challenge

Mahindra & Mahindra Farm Equipment, part of the $20 billion Mahindra Group, is the world’s number-one tractor company by volume. Its automotive business competes in almost every segment of the industry. The Spares Business Unit (SBU) provides genuine vehicle and tractor spare parts via advanced capabilities in sourcing, assembling, warehousing and distribution. To maximize supply chain efficiencies and service, Mahindra & Mahindra constantly evaluates scientific methods to tweak demand forecasting, inventory management and replenishment planning strategies to ensure that the right parts are available at the right place and time. However, their traditional, manually driven segmentation processes and tools often resulted in inefficient allocation, high safety inventory levels and less-than-optimal service levels.

About Customer

Mahindra & Mahindra Farm Equipment is part of the $20 billion Mahindra Group. It is the world’s number-one tractor company by volume, and its automotive business competes in almost every segment of the industry. The Spares Business Unit (SBU) provides genuine vehicle and tractor spare parts via advanced capabilities in sourcing, assembling, warehousing and distribution. The company constantly evaluates scientific methods to tweak demand forecasting, inventory management and replenishment planning strategies to ensure that the right parts are available at the right place and time.

Solution

Mahindra & Mahindra SBU leverages Blue Yonder Luminate Platform, which applies machine learning (ML) to both systematically classify spare parts into unique demand clusters and establish the significance of demand attributes. The result is built-in visibility, intelligence, context and collaboration tools that enable increased allocation efficiency and profitability. Via optimization techniques, powered by ML, service levels are assigned to demand clusters, with the goal of minimizing safety inventory costs. In addition, ML and artificial intelligence algorithms accurately estimate lead times and further optimize the cost-to-serve from both a customer service and inventory cost perspective. Instead of making manual decisions, the SBU can analyze data at scale, identify critical demand variables and autonomously optimize the supply chain for specified profitability goals.

Impact #1	Overall 10% reduction in inventory quantity
Impact #2	6% reduction of inventory value
Impact #3	4% reduction of inventory quantity

Impact #1

Overall 10% reduction in inventory quantity

Impact #2

6% reduction of inventory value

Impact #3

4% reduction of inventory quantity

Benefit #1	10% Overall reduction in inventory quantity
Benefit #2	6% reduction of inventory value
Benefit #3	4% reduction of inventory quantity

Benefit #1

10% Overall reduction in inventory quantity

Benefit #2

6% reduction of inventory value

Benefit #3

4% reduction of inventory quantity

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Overview

Mahindra & Mahindra Drives Profitability via Dynamic Segmentation

Operational Impact

Quantitative Benefit