We’ve all heard countless examples of how big data can help companies with their marketing efforts and getting a better view of the consumer, but there are many other industries that big data can influence. The manufacturing industry, in particular, has been collecting a slew of information for years.
We’ve all heard countless examples of how big data can help companies with their marketing efforts and getting a better view of the consumer, but there are many other industries that big data can influence. The manufacturing industry, in particular, has been collecting a slew of information for years. The amount of data collected is dramatically increasing as machine-to-machine and person-to-machine data becomes more prevalent, thanks to the Internet of things, making the manufacturing industry an ideal candidate for a big data solution.
History of Manufacturing Data
Data analytics is not new to the manufacturing industry. For the past 20 years, manufacturers have relied on software such as Enterprise Resource Planning and Product Lifecycle Management to improve efficiency and ensure product quality. However, much of the data that was collected and stored ended up losing its value because it was not delivered fast enough to be acted on or the data was siloed in the organization so that players who may have acted on the data did not have access to the information. For many organizations, data analysis was used as a means to react to problems that arose, rather than to proactively stop glitches before they occurred or had continued too far down the line.
How a Big Data Solution Can Help
By using an enterprise Hadoop solution, manufacturers can not only manage the growing data volume from sensor data and automated processes, but also better analyze and share that data, so issues can be addressed quickly and valuable pro-active insights can be gained. In the area of service management, manufacturers can install and monitor sensors to track how the product is used and gain visibility to service requirements the product might need. Using data effectively could impact other areas of the business, such as by enabling targeted offerings to customers based off of how they use the product. In the arena of operations, Hadoop can also help with the post-sales maintenance process. Sensors collect data on how well equipment is operating, allowing manufacturers to conduct maintenance when needed and catch bugs early, boosting service quality while cutting costs.
Industry Examples
Duke Energy used to monitor its fleet of generating plants by sending monitoring specialists with a handheld device to each site to collect data. Due to this method, the specialists spent 80 percent of their time collecting data and only 20 percent analyzing the data. By implementing a big data solution, Duke Energy was able to keep its specialists in a remote location where they monitored the data coming in from the equipment for any abnormalities and were able to fix the problems much faster.
Conclusion
Big data solutions provide a huge opportunity for manufacturers to cut costs, improve efficiency and ultimately improve the quality of their product by catching problems faster and adapting their products based on how it is actually used by the consumer. As the Internet of things continues to expand, the opportunity for manufacturers to benefit from this data will only continue to grow.
