B-Cognizance
IIITA e-Magazine
October - December 2006 Vol 2 Issue 11
Supply chain Analytics is composed of two words: Supply chain and Analytics
Supply chain management (SCM) is the process of planning, implementing, and controlling the operations of the supply chain with the purpose to satisfy customer requirements as efficiently as possible. Supply chain management spans all movement and storage of raw materials, work-in-process inventory, and finished goods from point-of-origin to point-of-consumption.
Analytics is the power to know by combining and integrating all functional and data parts of a system.
Supply chain Analytics (SCA)is the Application of Business Intelligence to various SCM functions and product life cycles on a strategic scale to optimize the results of these functions by means of enhancing the ability to produce cost effective products. Leading ERP and SCM systems have proven useful in automation of transaction related processes of the supply chain, however these systems have not provided the ability to adequately analyze the operational effectiveness across the supply chain. Current day supply chains are extremely complex environments whose operating state can affect companys ability to operate effectively and profitably. It has become essential to closely examine and measure the effectiveness of supply chain processes in taking intelligent decisions. SCA offers the mechanisms that facilitate this view.
SCA requires the ability to analyze products, processes, components, and materials. This demands a data integration infrastructure, which provides capability to extract, transform and load data acquired from multiple enterprise sources like ERP source data, SCM source data, CRM source data, customer data, supplier data, product manufacturing / testing data, quality management data, shop floor manufacturing data sources, legacy system data sources, data from online industry trading exchanges, market places & auction, demographics and marketing data purchased from third party data suppliers. SCA requires tighter integration of manufacturing into analytics. And, information resulting from the integration is critical to the identification of design issues and costs through out the product life cycle.
SCAs objective is application of DW and BI techniques on a strategic, enterprise scale across the supply chain and product life cycle. Working as an integral part of SCM, SCA is intended to enhance the ability of manufacturing processes to produce cost effective products by applying BI to supply, operations, logistics, demand and customer support processes.
The broad goals are to
Establish metrics Use of mutually agreed upon metrics to evaluate progress and measure the supply chains contribution.
Manage exceptions Create a vehicle for managing exceptions related to demand and inventory.
Communicate Inform supply chain partners about time sensitive information.
Plan collaboratively Perform collaborative planning with the supply chain partners.
Following are the derived goals.
Reduce the inventory across the supply chain.
Improve product quality.
Enhance yield and asset usage.
Identify top performing suppliers, measure performance over time, negotiate performance based agreements.
Measure and improve demand forecasting performance.
Improve forecasting accuracy of items not meeting acceptable levels, enable better management of raw materials, inventory, and production planning and finished goods.
Measure accuracy of production plan for a given time period.
Identify products that may affect customer service levels and alert sales functions to proactively manage customer relationship.
Measure delivery performance of customer orders.
Reduction of decision cycle processes.
by Kishore Kunal, MBA 2nd Yr IIITA.
X' Pressions
Supply Chain Analytics
Supply chain Analytics is composed of two words: Supply chain and AnalyticsSupply chain management (SCM) is the process of planning, implementing, and controlling the operations of the supply chain with the purpose to satisfy customer requirements as efficiently as possible. Supply chain management spans all movement and storage of raw materials, work-in-process inventory, and finished goods from point-of-origin to point-of-consumption.
Analytics is the power to know by combining and integrating all functional and data parts of a system.
Supply chain Analytics (SCA)is the Application of Business Intelligence to various SCM functions and product life cycles on a strategic scale to optimize the results of these functions by means of enhancing the ability to produce cost effective products. Leading ERP and SCM systems have proven useful in automation of transaction related processes of the supply chain, however these systems have not provided the ability to adequately analyze the operational effectiveness across the supply chain. Current day supply chains are extremely complex environments whose operating state can affect companys ability to operate effectively and profitably. It has become essential to closely examine and measure the effectiveness of supply chain processes in taking intelligent decisions. SCA offers the mechanisms that facilitate this view.
SCA requires the ability to analyze products, processes, components, and materials. This demands a data integration infrastructure, which provides capability to extract, transform and load data acquired from multiple enterprise sources like ERP source data, SCM source data, CRM source data, customer data, supplier data, product manufacturing / testing data, quality management data, shop floor manufacturing data sources, legacy system data sources, data from online industry trading exchanges, market places & auction, demographics and marketing data purchased from third party data suppliers. SCA requires tighter integration of manufacturing into analytics. And, information resulting from the integration is critical to the identification of design issues and costs through out the product life cycle.
SCAs objective is application of DW and BI techniques on a strategic, enterprise scale across the supply chain and product life cycle. Working as an integral part of SCM, SCA is intended to enhance the ability of manufacturing processes to produce cost effective products by applying BI to supply, operations, logistics, demand and customer support processes.
The broad goals are to
Establish metrics Use of mutually agreed upon metrics to evaluate progress and measure the supply chains contribution.
Manage exceptions Create a vehicle for managing exceptions related to demand and inventory.
Communicate Inform supply chain partners about time sensitive information.
Plan collaboratively Perform collaborative planning with the supply chain partners.
Following are the derived goals.
Reduce the inventory across the supply chain.
Improve product quality.
Enhance yield and asset usage.
Identify top performing suppliers, measure performance over time, negotiate performance based agreements.
Measure and improve demand forecasting performance.
Improve forecasting accuracy of items not meeting acceptable levels, enable better management of raw materials, inventory, and production planning and finished goods.
Measure accuracy of production plan for a given time period.
Identify products that may affect customer service levels and alert sales functions to proactively manage customer relationship.
Measure delivery performance of customer orders.
Reduction of decision cycle processes.
by Kishore Kunal, MBA 2nd Yr IIITA.