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Data Analytics: A Catalyst for Change in Service Life-cycle Management

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The past few years have seen manufacturers look at their aftermarket services management in a completely new way. While technology and digitization have largely driven this change, the recent global pandemic has rocketed the drive for remote yet effective service support to ensure that customer requirement are still seamlessly met.

Tech Innovations and the Flood Called Data

The inadvertent result of this upsurge in digitization has been the data. Data, which is often collected from disparate sources, is now becoming a big challenge and an opportunity for manufacturers. With the adaptation of technology, many manufacturers can capture and utilize data but fail to do so.

Why Measurement Matters

Data-driven manufacturing is in the realm of being seen as a strategic necessity that can help manufacturers compete effectively. And with the application of analytics, manufacturers, suppliers, and distributors can achieve significant value in speed and operational efficiency.

The ability to measure and use data is also leading manufacturers to offer services based on usage, uptime/downtime, and create value for customers through personalization.

Let’s look at some of the key uses of data analytics and how it will impact manufacturers.

Manage Demand and Supply Chains

Data analytics is helping manufacturers understand the cost and efficiency of every aspect of the product lifecycle, from suppliers to customer usage. By analyzing the parameters and conditions that impact the supply chain from all angles, businesses can uncover problems such as hidden bottlenecks or unprofitable production lines. As a result, they gain insight into the conditions that affect the complete profitability of an integrated supply chain and learn how best to capitalize on given conditions.

Forecast Demand for Products & Services

Manufacturers can combine data with predictive analytical tools to create an accurate projection of purchasing trends. Insights driven by analytics can even help manufacturers understand how well lines are operating, enabling smarter risk management decisions. The ability to analyze when warranties are expiring can also result in additional service revenue channels for manufacturers.

IoT solutions for asset management offer real-time alerts, enabling manufacturers to act quickly, and minimize losses from delayed, damaged, or lost goods.

Proactive System Maintenance 

Predictive maintenance is helping manufacturers increase their product lifetimes while preventing downtimes. It analyzes the historical performance data to forecast potential failure and further identify the cause of the problem.

This is particularly effective in field service management, where predictive maintenance can result in tremendous savings. According to McKinsey, manufacturers using predictive maintenance typically reduce machine downtime by 30 to 50 percent and increase machine life by 20 to 40 percent.

Optimize Machine Efficiencies and Utilization 

Data analytics can significantly improve assembly-line efficiency by identifying bottlenecks and defects. With advanced analytics, manufacturers can ensure that machines operate at high efficiency, resulting in improved quality and increased productivity.

Optimize Inventory and Warehouse Costs Efficiently

Advanced analytics can be applied to improve product flow management, which positively impacts inventory operations while reducing unnecessary expenditure. For example, manufacturers can assess fill rates which can reduce stock-outs. Improved insights can help manufacturers know which locations/equipment are operating at an optimized level and improve other production centers and address warehousing deficiencies if any.

Final Thoughts

Enhancements Across the Service Life-cycle

Analytics is enabling manufacturers to scale cloud-based operational intelligence, AI-enabled monitoring, diagnostics, and asset lifecycle management. AI-enabled digital technologies are seamlessly addressing service life-cycle challenges, increasing transparency across the process and functions, and creating a seamless and rich experience for the customers.

SOURCES:

http://www.wonderware.es/wp-content/uploads/2017/02/WhitePaper_InvensysandMicrosoft.pdf

https://www.mckinsey.com/business-functions/operations/our-insights/manufacturing-analytics-unleashes-productivity-and-profitability 

 

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