Inventory Analytics

Build a system that helps you with inventory optimization and generates smart insights

Inventory Analytics

Why inventory analytics is important

Enterprises, especially manufacturers and retailers, are facing challenges in managing inventory effectively since with globalization, the supply chain has become much more complex than ever. Materials are imported from all over the globe and even the customers are spread across several countries. Due to this, making use of inventory data analytics to improve the supply chain’s effectiveness is becoming more important in the current global marketplace. By using inventory management solutions, you can eliminate the ambiguity of how to distribute the right inventory to the right locations at the right time.

How we helped a company implement a smarter inventory management system

One of our clients, who is a major manufacturer of electronics, was experiencing challenges in managing inventory, allocation, and replacement processes efficiently. The client’s current inventory management processes were ad-hoc in nature and every stage starting from data collection, reporting, till inventory analysis was done manually.

Our team of data scientists at Softweb performed inventory management analytics to anticipate the optimal inventory level to help the organization in decreasing loss, increasing sales, and improving overall profits. We helped the client in streamlining their supply chain and logistics processes to enable improved real-time decision making and better in-stock customer experience.

Webinar on Predictive Maintenance in Manufacturing

Data science-driven smart inventory management system for manufacturers

Agenda
  • Traditional inventory management in manufacturing
  • Limitations of traditional inventory management practices
  • Problems manufacturers face with traditional inventory management
  • What is Smart Inventory Management and how it overcomes the challenges that manufacturers face
  • Real-life examples and use cases
  • Core elements of this paradigm shift - Data Science and Machine Learning
  • How to get started
  • Q&A

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Outcomes

  • The company is on track to optimizing its inventory management systems all over the globe and has experienced an increase in sales by 10%.
  • The client is enjoying significant cost-savings with a reduction of excess inventory by 15%.
  • The system that we built for the company now helps its warehouse managers and decision makers keep track of where the goods are at any point of time.

How inventory analytics is useful to the manufacturing industry

  • Useful in managing physical and virtual assets for peak profitability.
  • Helpful in reducing working capital requirements with inventory management solutions.
  • Facilitates in identifying the accurate physical inventory for your supply chain.
  • Easily determine optimal purchase levels to support production facilities.
  • Calculate customer demand and provide detailed inventory insights.
  • Analysis can help in considering alternative inventory models.
  • Facilitate future consumption, sale or further processing/value addition.
  • Data science can help you undertake preventive measures to reduce supply disruption.
  • It can give demand-driven forecasting through a combination of structured and unstructured data.
  • It can generate route optimization and more efficient transportation using GPS-enabled big data telematics.
Let our data science team help you solve complex data and business problems