How Manufacturers Can Use Big Data to Improve Performance
July 13, 2017 — To stay competitive in the manufacturing industry, it’s essential to make smart and fast decisions on a variety of industry-specific needs, such as forecasting production downtime. However, U.S. manufacturers fall behind their international counterparts when it comes to using big data to gain an edge on the competition and achieve revenue goals.
What is big data? The term “big data” refers to large sets of data that can be analyzed to reveal patterns and trends. This is important for manufacturers because, when combined with predictive analytics, big data can be used to reveal potential weaknesses in their supply chains. These results can ultimately improve revenue and streamline manufacturing processes to result in a leaner operation.
There are three areas that illustrate how manufacturing operations are impacted by big data and predictive analytics:
1. Enhancing Supply Chain Management with Big Data
Manufacturers can use predictive analytics to guide better forecasting decisions based on what their customers are asking for now and what they may ask for in the future. The data can also indicate a product failures before customers experience them. Manufacturers can use this information to make better choices in real-time, optimize operating costs by reducing wasted resources, and predict the potential for experiencing downtime.
2. Unleashing the Power of Information with The Industrial Internet of Things (IIoT)
Maybe you’ve heard of the Internet of Things (IoT), the interconnection of everyday devices through the internet, enabling them to send and receive data. The Industrial Internet of Things operates in a similar fashion. Insights gained from collected data can improve manufacturing performance in your company. Among the top results reported by executives are reductions in equipment breakdowns and unscheduled downtime. Also reported are drops in unscheduled maintenance, supply chain management issues, reported safety incidents, off-spec products, near-miss safety issues and inadequate staffing.
3. The Importance of Analytics
Improving operational performance yields many benefits and should be every manufacturer’s goal. That’s why leveraging big data is critical. Big data leads manufacturers to be more efficient with how they use and manage resources. Take product failure, for example. Some companies use data analytics to predict product failures before customers experience them. In many cases, actual production is handled by offshore contract manufacturers, so analytics can help zero in on where the problems surfaced without being in direct proximity to them.
Data analysis can discover when a product is most likely to fail based on factors that include:
• Production line
• Batch size
• Day and month when it was made
• Number of engineering changes
• Consumer usage patterns
In warranty costs alone, money could be recaptured by making adjustments.
The time to adopt these new technologies is now. Manufacturers that do not use big data and predictive analytics will struggle to remain competitive and to deliver on-time, accurate orders. Customer demand for service anywhere and at any time isn’t going to change. But as a manufacturer, you can use big data to keep up with the demand—and reap the rewards as a result.
If you’re a manufacturer who is looking for solutions to tough business and accounting problems, please contact Redpath CPAs today!