Supply Chain Data Analytics

Optimize your supply chain process with data and AI

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Streamline supply chain operations with advanced data analytics

Increasing complexities and fragmented demand make it difficult for supply chain leaders to optimize operations. Being one of the leading supply chain analytics companies, our solutions offer businesses with timely and actionable intelligence for accurate demand planning, route optimization, and inventory management. With real-time visibility across the supply chain, companies can take measures to mitigate risks, reduce procurement spending, and eliminate stockouts. With the help of advanced data analytics in supply chain management solutions, you can optimize your procurement spending, manage resources and ensure supplier relationships. Sigmoid's supply chain predictive analytics enables forecasting demand to ensure delivery of the right products and in the right quantities avoiding stockouts and overstocking.

Enable visibility with integrated supply chain operations

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Demand and Supply Planning

  • Improve efficiency of supply chain operations and inventory planning by building ML models that identify shifts in consumer behaviour and enable SKU-level optimization for e-commerce.

  • Supply chain analytics solutions align sales and production operations to ensure better inventory control, efficient production scheduling, improved on-shelf availability, while minimizing stockouts and overstock situations.

  • Minimize stockouts, maintain optimal inventory levels and reduce excess inventory by leveraging end-to-end supply chain analytics services.

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Production and Inventory Planning

  • Build automated preventive maintenance models for efficient equipment upkeep. Proactive maintenance powered by supply chain analytics solutions mitigates the risk of equipment breakdown and significantly reduces downtime.

  • Data analytics in supply chain, real-time visibility, and ML models for procurement analysis enable precise material requirement calculations, efficient supplier collaboration, and demand forecasting.

  • ML algorithms can continuously evaluate and optimize reorder points and order quantities to minimize carrying costs while ensuring that products are always in stock.

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Real-time Operations and Monitoring

  • Harnesses the power of supply chain management analytics, predictive modeling, and AI-driven algorithms for real-time visibility into every aspect of supply chain processes such as procurement, logistics, and inventory planning.

  • Minimize transportation costs, reduce delivery times, and enhance overall operational efficiency by analyzing data about vehicle location, speed, and fuel consumption in real-time with IoT sensors.

  • Improve quality control, align production with demand, and manage inventory effectively by implementing ML models with features such as demand forecasting, real-time monitoring, and root cause analysis.

Supply chain management KPIs dashboard

Low visibility into supply chain processes makes it difficult to predict demand fluctuations, manage procurement bottlenecks, and track inefficient logistics operations. A Supply Chain Control Tower is the ultimate tool designed to empower businesses with real-time visibility into every aspect of supply chain processes such as procurement, logistics, and inventory planning. It harnesses the power of supply chain data analytics, predictive modeling, and AI-driven algorithms to optimize operations, enhance decision-making, and mitigate risks.

Supply chain data analytics KPI dashboard
Whitepaper

Maximizing on-shelf availability for CPGs

On-shelf availability (OSA) and the accuracy of reported inventory is a challenge which is increasingly becoming a primary focus area for a number of manufacturers. Find out how CPGs can solve pertinent problems with the quality of OSA using machine learning.

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On-shelf availability for CPGs

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Get 10% increased throughput and revenue growth!

Build a resilient supply chain with control towers and digital twins to improve operational efficiency.

FAQs

Supply chain analytics enables organizations to gain insights into their supply chain processes, identify areas for improvement, and make data-driven decisions. By leveraging advanced analytics techniques, organizations can understand the performance of suppliers, logistics providers, and internal operations. It allows them to identify bottlenecks, optimize production schedules, and identify potential risks in the supply chain, such as disruptions due to weather or geopolitical events. Supply chain analytics can help you to improve customer service by providing organizations with better visibility into delivery schedules. Finally, analytics can be used to identify opportunities for cost savings by optimizing transportation routes and improving efficiency in the supply chain.

Supply chain analytics can enhance the decision-making process by providing organizations with access to real-time data and insights. It provides greater visibility into the supply chain operations to identify patterns and make data-driven decisions. This visibility enables informed decisions on supply chain strategies, such as which suppliers to work with, what transportation modes to use, and how to optimize inventory levels. Supply chain management services help in proactively identifying potential risks and taking steps to mitigate them. Furthermore, by analyzing delivery and customer feedback data, organizations can gain a better understanding of customer preferences and make informed decisions about delivery schedules and inventory management.

Demand planning and forecasting are key to modern supply chains as it supports key operational procedures like demand-driven material resource planning (DDMRP), inbound logistics, production, financial planning, and risk assessment. Predictive analytics in supply chain can help organizations estimate the expected demand for products, plan their production schedules and procurement activities accordingly. It reduces the likelihood of overstocking or understocking, saving higher storage costs and inefficient use of resources. It also improves efficiency of supply chain operations and inventory planning by building ML models that identify shifts in consumer behaviour and enable SKU-level optimization for eCommerce.

AI-powered supply chain helps in inventory optimization by providing real-time data and insights into inventory levels and demand patterns. Analyzing data such as historical sales trends, lead times, and supplier performance can help make data-driven decisions to optimize the inventory levels. This includes setting appropriate safety stock levels, identifying slow-moving or excess inventory, and forecasting demand to ensure that inventory levels are sufficient to meet customer demand.

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Get 10% increased throughput and revenue growth!

Build a resilient supply chain with control towers and digital twins to improve operational efficiency.