Supply Chain and Operational Analytics

Supply Chain and Operational Analytics

Mitigate supply risks and drive operational efficiencies through econometrics-driven demand-supply models and performance-based supplier selection.

 

Supply-Demand Balance

• Identify demand drivers and forecast demand through time-series models with both endogenous and exogenous factors
• Plan capacity and predict cost using econometric models
• Monitor actual vs. planned flow across the value chain and optimize lead time

 

Supplier and Partner Performance

• Score and track supplier performance, evaluate supplier fitment, and take critical decisions based on risk and spend analytics

 

Inventory and Logistics Optimization

• Monitor and optimize space/volume utilization and transportation routes

 

IoT and Sensor Analytics

• Reduce operational downtime through predictive maintenance and automated quality control (fault detection)
• Identify ideal operational conditions and optimize parameters based on changing environment variables

 

Store Analytics

• Analyze in-store or store-lab traffic, engagement, and conversion
• Optimize store staffing, and store and shelf layouts

 

Customer Helpdesk Analytics

• Track service agent performance and measure customer satisfaction
• Identify customer pain points through ticket text analytics

 

Cybersecurity

• Improve fraud and spam detection algorithms through sample testing and ML code improvement

 

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Case Studies

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Customer Behavior, Risk, and Association Analytics for a Bank’s Credit Card Offerings

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Financial Planning and Scenario Analytics, including Exogenous Factors

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Overcoming Inventory Stagnation Through Dynamic Demand-Based Ordering Decisions

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Increasing Customer Satisfaction and Ensuring Process Improvement for a Customer Helpdesk

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Mitigating Churn for an Automotive Manufacturer’s Subscription Service

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Personalized marketing strategy to reduce customer churn

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