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Big Data in Manufacturing: 5 Game Changing Use Cases

Posted by Marjorie Dunn

Big Data in Manufacturing Use Cases Concept

For leading manufacturers, the ability to collect, manage, and assess large volumes of data is critical to successful operations. However, as companies grow and diversify their offerings, the type of data that is required becomes increasingly more complex as well. Big data solutions can be used to improve operational efficiency and provide a greater view of how the organization is functioning.

Here are 5 ways that big data solutions lead to better outcomes for manufacturers:

1. Cost Tracking

Tracking and understanding the causes of overhead costs in the manufacturing industry is essential to the profitability of your operation. By using data driven processes to track these expenses, you can see which activities are productive and which ones are raising overhead costs and impacting profitability.

Additionally, capturing accurate labor costs can be enabled through big data capabilities. For example, tracking devices that communicate with employee badges can be placed at workstations to identify the actions employees are taking. Collecting and visualizing this type of data requires distributed processing and computing.

2. Mass Customization

Manufacturing products to order is a hugely efficient and profitable way to run a business. However, it takes keen insight and awareness of your customers’ buying patterns to pull this off. Big data analytics allow companies to analyze customer behavior and develop a method of delivering products in the most timely and efficient way possible.

3. Reducing Supply Chain Risk

Supply chain dependencies can be major sources of risk and can have a significant effect in the supply chain if your business is not prepared. Although these impacts, generally, cannot be fully avoided, they can be greatly reduced with the right planning, processes, and tools. For example, big data analytics can be used to map out potential delays or weather patterns that might have an effect on the shipment of a product.

4. Improve Operational Efficiency

Identifying irregularities in sales patterns and pinpointing the inconsistencies between actual and expected outcomes can be achieved with big data. By analyzing information related to product quality, you can improve your operational efficiency. Sources like social media can be useful in learning about customer behavior and attitudes which can help with load forecasting.

5. Warranty and Support Costs

Product warranty and recall costs can be significant and have a major impact on a business’s bottom line if you do not make efforts to control them. Since these expenses are often directly related to the quality of manufacturing, big data systems can be useful in the critical analysis of manufacturing processes to determine if both the cost and quality perceptions are being contained.

Why Big Data?

Gaining insight through new information is crucial for organizations that wish to maintain or grow their market share. In fact, it has been proven that companies who successfully utilize big data solutions to enhance their operations can successfully set themselves apart from the competition. This is especially true for manufacturing and other process-based industries.

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Topics: Manufacturing Technology

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