Operations Analytics

Operational analytics is a more specific term for a type of business analytics which focuses on improving existing operations.

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Operational analytics is a more specific term for a type of business analytics which focuses on improving existing operations. This type of business analytics, like others, involves the use of various data mining and data aggregation tools to get more transparent information for business planning.

The demand for organizations to respond faster and with greater insights to ever changing events, both inside and outside is increasing. Cerebraix’s Operations Analytics helps our partners realize maximum potential from their analytics endeavours in operations.

Our Operations Analytics brings visibility across Production, Procurement, Asset Management & Supply Chain and helps you gain enhanced improvement in your operations to streamline processes, reduce spend, improve forecasting and so become more competitive.

Value: Synchronization across the supply chain; higher sales, reduced inventory holdings. Meet your customers’ demand irrespective of location or time, cost-effectively.
Aggregate and SKU-level demand forecasting that is critical to an efficient and effective Supply Chain operation. Demand Forecasting may be used in production planning, inventory management, assessing future capacity requirements.
Our predictive analytics-based models yield stable forecasts that integrate at all demand levels, and can be used as a basis for inventory management.
Critical to a well oiled Supply Chain, Demand Forecasting analysis may be used in production planning, assessing future capacity requirements, or in making decisions on whether to enter a new market. Further, your customers demand immediate responses irrespective of location or time and you need to meet these needs rapidly, and cost-effectively.
Our experts can help:
1. Use demand forecasting analysis techniques such as predictive algorithms to better forecast demand based on internal and external factors.
2. Explain the key explanatory variables that impact the demand at the most granular levels.
3. Establish the level of significance of the key explanatory variables.
4. Simulate various scenarios leveraging the explanatory variables to help shape demand.
5. Get a visibility on ROI from various marketing inputs such as promotions.
Value: Reduced inventory holdings, reduced costs and improved fill rates.
Inventory Analysis & Optimization, put simply, is a technique to balance capital requirements and constraints with service-level goals while managing demand and supply volatility. Conceptually, this is achieved by having the right amount of inventory, in just the right places, to meet customer service and revenue goals.
Radical improvements in demand and inventory synchronization could be brought about with an accurate, data-led forecast that aids in balancing inventory with demand.
Our experts can help:
1. Reduce inventory significantly, in some representative cases by 10% – 30%
2. Boost your bottomline by offering insights into supply and demand dynamics to prevent lost sales or excess stocks.
3. Deploy capital more efficiently by reducing inventory carrying costs and unlocking working capital from unnecessary inventory buffers.
4. Achieve larger number of inventory turns.
5. Leverage predictive modeling in Inventory Analysis and perform what-if analysis to establish the impact of different variables on the supply/demand balance.
6. Achieve lower obsolescence rates while increasing customer service performance.
Value: Optimized Transportation costs and improved realizations
Transport Logistics Optimization is the process of determining the most efficient means of moving product to the customer while maintaining a desired service level, given a static supply chain network.
Our experts can help:
1. Leverage advanced analytical algorithms to define optimized routes for efficient Transport Logistics.
2. Minimize the cost of inbound or outbound shipments, while keeping in sight realistic cost and constraint structures by leveraging Fleet Analytics.
3. Bring about possible strong ROI improvements by leveraging an analytics-driven approach to fleet management and dispatch & load planning.
4. Manage better the constant variances in routine demand patterns coupled with an exploding base of suppliers and fleet partners.
Value: Higher yields, reduced scrap and reduced cost of quality
That quality issues erode margins by leading to higher production costs, lower production yields, higher scrap rates and increased service issues, is very well established. Organizations have a scarcity of resources and tools to analyze process variables that can have the largest impact on quality. We could help you discover Quality Analytics experts that help you make the most out of limited resources by identifying and addressing issues that have the greatest impact on costs and customers.
Our experts can help:
1. Consistently improve product/process reliability leading to delighted customers and improved bottomline.
2. Help reduce operating costs by leveraging sophisticated Quality Analytics for control measurement, monitoring, tracking and reporting of Quality issues.
3. Facilitate generating optimized maintenance cycles in order to lower O&M costs while increasing asset uptimes.
4. Assist you perform root-cause analyses to troubleshoot and address exploding issues faster than what it takes to build your capabilities in-house.
5. Enable you harness your machine sensor data to predict unscheduled downtimes in advance.

Demand Forecasting
Value: Synchronization across the supply chain; higher sales, reduced inventory holdings. Meet your customers’ demand irrespective of location or time, cost-effectively.
Aggregate and SKU-level demand forecasting that is critical to an efficient and effective Supply Chain operation. Demand Forecasting may be used in production planning, inventory management, assessing future capacity requirements.
Our predictive analytics-based models yield stable forecasts that integrate at all demand levels, and can be used as a basis for inventory management.
Critical to a well oiled Supply Chain, Demand Forecasting analysis may be used in production planning, assessing future capacity requirements, or in making decisions on whether to enter a new market. Further, your customers demand immediate responses irrespective of location or time and you need to meet these needs rapidly, and cost-effectively.
Our experts can help:
1. Use demand forecasting analysis techniques such as predictive algorithms to better forecast demand based on internal and external factors.
2. Explain the key explanatory variables that impact the demand at the most granular levels.
3. Establish the level of significance of the key explanatory variables.
4. Simulate various scenarios leveraging the explanatory variables to help shape demand.
5. Get a visibility on ROI from various marketing inputs such as promotions.
Inventory Analytics
Value: Reduced inventory holdings, reduced costs and improved fill rates.
Inventory Analysis & Optimization, put simply, is a technique to balance capital requirements and constraints with service-level goals while managing demand and supply volatility. Conceptually, this is achieved by having the right amount of inventory, in just the right places, to meet customer service and revenue goals.
Radical improvements in demand and inventory synchronization could be brought about with an accurate, data-led forecast that aids in balancing inventory with demand.
Our experts can help:
1. Reduce inventory significantly, in some representative cases by 10% – 30%
2. Boost your bottomline by offering insights into supply and demand dynamics to prevent lost sales or excess stocks.
3. Deploy capital more efficiently by reducing inventory carrying costs and unlocking working capital from unnecessary inventory buffers.
4. Achieve larger number of inventory turns.
5. Leverage predictive modeling in Inventory Analysis and perform what-if analysis to establish the impact of different variables on the supply/demand balance.
6. Achieve lower obsolescence rates while increasing customer service performance.
Transport & Logistics Optimization
Value: Optimized Transportation costs and improved realizations
Transport Logistics Optimization is the process of determining the most efficient means of moving product to the customer while maintaining a desired service level, given a static supply chain network.
Our experts can help:
1. Leverage advanced analytical algorithms to define optimized routes for efficient Transport Logistics.
2. Minimize the cost of inbound or outbound shipments, while keeping in sight realistic cost and constraint structures by leveraging Fleet Analytics.
3. Bring about possible strong ROI improvements by leveraging an analytics-driven approach to fleet management and dispatch & load planning.
4. Manage better the constant variances in routine demand patterns coupled with an exploding base of suppliers and fleet partners.
Quality Analytics
Value: Higher yields, reduced scrap and reduced cost of quality
That quality issues erode margins by leading to higher production costs, lower production yields, higher scrap rates and increased service issues, is very well established. Organizations have a scarcity of resources and tools to analyze process variables that can have the largest impact on quality. We could help you discover Quality Analytics experts that help you make the most out of limited resources by identifying and addressing issues that have the greatest impact on costs and customers.
Our experts can help:
1. Consistently improve product/process reliability leading to delighted customers and improved bottomline.
2. Help reduce operating costs by leveraging sophisticated Quality Analytics for control measurement, monitoring, tracking and reporting of Quality issues.
3. Facilitate generating optimized maintenance cycles in order to lower O&M costs while increasing asset uptimes.
4. Assist you perform root-cause analyses to troubleshoot and address exploding issues faster than what it takes to build your capabilities in-house.
5. Enable you harness your machine sensor data to predict unscheduled downtimes in advance.