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Almost 20 years after the phrase “big data” was coined, manufacturers have come to realize that the secret to getting the most out of big data isn’t quantity but quality. By ensuring that the data collected and the analytics performed align closely with the company’s objectives, businesses can improve their operations and remain competitive.
Well-optimized big data systems have been proven to help achieve new product development, smarter decision-making, and both time and cost reductions. Intel, one of the world’s largest manufacturers of processors, estimated a savings of $30 million by streamlining its quality-assurance processes as a result of big data analytics.
According to Actify.com, 33 percent of all data could be useful when analyzed. However, companies only process 0.5 percent of all data. By incorporating an enterprise data strategy, organizations can make certain that they are processing useful data and that time is not wasted on the rest. A good data strategy will also ensure processes are universal across a business so that data is managed, handled and processed well.
To create an enterprise data strategy, there are four key principles to consider. First, the strategy must be practical and easy to implement. It also should be relevant and tailored specifically to the company’s goals, as well as evolutionary and adaptable to keep up with current trends. Finally, the strategy must be universally applied across the business and easy to update when necessary.
Using smart sensor technology, manufacturers can capture and analyze data from almost any type of machinery involved in their processes. This information can be used to monitor individual parts, such as motors or gaskets, to predict upcoming mechanical failures. In turn, these predictions can prevent unnecessary downtime and costs related to emergency maintenance, because manufacturers are able to deal with an issue before it causes any problems.
The benefit of knowing when your equipment is likely to break down means necessary maintenance or ordering a specific part can be planned well in advance, ensuring your systems run smoothly without any surprise faults. This is an improvement over just planned maintenance alone, as it means maintenance is only performed when it is required.
Big data, often defined by Doug Laney’s three V’s, has led to great strategic and operational improvements. However, to get the best results for your organization, remember to consider the fourth V — value. Making sure your big data is relevant and of high quality will always be more important than the quantity.
Mark Howard is the director of EU Automation, an industrial equipment supplier.