Network Optimization for Contract Manufacturer-Controlled ... · PDF fileChallenge The leading...

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Challenge The leading joss sticks manufacturer in India is challenged by a highly volatile demand due to the nature and typical use of joss sticks (also known as incense sticks or ‘agarbattis’). This leads to frequent changes in production planning and distribution scheduling. As production is managed by contract manufacturers, any change in planning and scheduling has a high impact on the contract manufacturer framework, and leads to sub-optimal network utilization. The company needed to identify a cost-efficient fixed supply chain network which would be adaptive to market volatility, considering direct and indirect cost implications and inherent constraints of the existing value chain. Solution The solution has helped the company design a supply chain framework with end-to-end network cost visibility. The optimization considered all of the cost elements of supply, production and logistics coupled with inherent value chain constraints, credit rules and the complex tax structure in India. The solution also incorporated complexities related to supplier capacity constraints, procurement contracts, multi-BOM scenario, production activity wise capacity constraints, product mix constraints, inventory policies, truckload constraints, serviceability factors and transportation policies. The optimization model was built using LLamasoft ® Supply Chain Guru ® , which enabled incorporation of all aforesaid data elements and constraints. > Volatile demand leads to frequent changes in production planning and distribution scheduling in contract-manufacturer heavy network > Goal: Identify a cost-ef- ficient fixed supply chain network and contract-man- ufacturer agreement framework which would be adaptive to market volatility > Network optimization considered all of the cost elements of supply, pro- duction and logistics cou- pled with inherent value chain constraints, contract structure, credit rules and the complex tax structure in India Network Optimization for Contract Manufacturer-Controlled Production CASE STUDY: CONSUMER GOODS INDUSTRY CONSUMER GOODS INDUSTRY - Network Optimization Case Study

Transcript of Network Optimization for Contract Manufacturer-Controlled ... · PDF fileChallenge The leading...

ChallengeThe leading joss sticks manufacturer in India is challenged by a highly volatile demand due to the nature and typical use of joss sticks (also known as incense sticks or ‘agarbattis’). This leads to frequent changes in production planning and distribution scheduling. As production is managed by contract manufacturers, any change in planning and scheduling has a high impact on the contract manufacturer framework, and leads to sub-optimal network utilization. The company needed to identify a cost-efficient fixed supply chain network which would be adaptive to market volatility, considering direct and indirect cost implications and inherent constraints of the existing value chain.

SolutionThe solution has helped the company design a supply chain framework with end-to-end network cost visibility. The optimization considered all of the cost elements of supply, production and logistics coupled with inherent value chain constraints, credit rules and the complex tax structure in India. The solution also incorporated complexities related to supplier capacity constraints, procurement contracts, multi-BOM scenario, production activity wise capacity constraints, product mix constraints, inventory policies, truckload constraints, serviceability factors and transportation policies. The optimization model was built using LLamasoft® Supply Chain Guru®, which enabled incorporation of all aforesaid data elements and constraints.

> Volatile demand leads to frequent changes in production planning and distribution scheduling in contract-manufacturer heavy network

> Goal: Identify a cost-ef-ficient fixed supply chain network and contract-man-ufacturer agreement framework which would be adaptive to market volatility

> Network optimization considered all of the cost elements of supply, pro-duction and logistics cou-pled with inherent value chain constraints, contract structure, credit rules and the complex tax structure in India

Network Optimization for Contract Manufacturer-Controlled Production

CASE STUDY: CONSUMER GOODS INDUSTRY CONSUMER GOODS INDUSTRY - Network Optimization Case Study

LLamasoft, Inc.

201 South Main Street, Suite 400 Ann Arbor, Michigan 48104, USA

Phone: +1 866.598.9831LLamasoft.com

[email protected]

© 2014 LLamasoft, Inc. All rights reserved. v.04012014

CONSUMER GOODS INDUSTRY - Network Optimization Case Study

ResultsThe solution provided a framework which helped the company reduce its network complexity and reduce costs. Measurable benefits include:

LLamasoft, Inc.

201 South Main Street, Suite 400 Ann Arbor, Michigan 48104, USA

Phone: +1 866.598.9831LLamasoft.com

[email protected]

© 2014 LLamasoft, Inc. All rights reserved. v.05142014

• Production mix with 85 percent firm and 15 percent flexible based on market

exceptions

• Firm distribution network to the tune of 90 percent and 10 percent flexible

network with two supply options to answer changing market dynamics

without violating constraints present

• Increase of direct delivery to regional warehouses from 29 percent to 50 percent

• Twenty-five percent reduction in outbound transportation cost

• Overall cost savings of 2.5 percent

• Defined pre-build inventory strategy: Recommended inventory turns increased

from six to 10

Soft benefits include:

• Reduction in month-on-month production

and procurement requirement deviations

• Reduction in inventory write-off of the

raw material at manufacturing premises

• Less variation in production planning led

to more visibility of dispatch planning

from manufacturing premises

• More visibility to the business for

negotiating contracts with contract

manufacturers and logistics providers

• More visibility of space required at

manufacturing premises for raw material

and finished goods

• Better production adherence in relation to the demand plan