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5 Ways Manufacturers are Using Data for Better Business Results

Aug 17, 2018 12:59:39 AM / by Aravindan Umshankar

 2018-08-16

By now, you probably know that big data is instrumental in helping your business not only survive but thrive for years to come. In recent articles, we’ve explained how Smart Manufacturing is transforming the industry, and how transportation & logistics companies need to not only collect data but use it to make better decisions and improve their business.
In this article, we’ll show you five examples of how you can use the data you’re collecting to improve your business results. Each of these applications will touch on a different aspect of the manufacturing value chain, but each will depend on having access to reliable, accurate, and real-time data. These examples will help you identify the areas where big data can have the most impact on your business.

Real-Time Supply Chain Forecasting

Today’s supply chains are complex, interconnected, and difficult to manage, and companies lack the visibility needed to see what is happening in any part of the process. The average manufacturing company can have up to 45 percent of their working capital tied up in their supply chain. With so much on the line, why are so many companies still relying on analog and paper records to track the flow of goods through them?

With data and advanced analytics software, you can start to get a complete, real-time view of your entire supply chain – from component to customer. With this information, you can see where problems most often occur, where materials are in the production process, and where improvements can be made. Moreover, data allows you to identify any dependencies that you may have on suppliers so that you can schedule delivery to ensure production is never interrupted. One estimate suggests that a digital supply chain can lead to a 20 percent decrease in procurement costs, a 50 percent decrease in supply chain costs, and an increase in revenue of 10 percent.  

Improving Asset Performance

Unexpected downtime and maintenance is a big expense. A recent survey by Honeywell found that 40 percent of manufacturers rank unscheduled downtime as the biggest threat to maximizing revenue. But with the internet of things and connected sensors, you can detect small anomalies or issues, diagnose them, and alert a technician before a major incident occurs.

Similarly, you can use data to build more accurate predictive maintenance schedules to further reduce downtime. The same survey showed effective use of data can reduce breakdowns by 26 percent, and cut unscheduled downtime by nearly 25 percent.

Reducing Defects and Quality Concerns

Defects are costly. They lead to waste and can damage your reputation with customers. That’s why companies spend so much on quality assurance and testing. But big data can help here as well. Tata Consulting found that improving product quality and defect tracking was the number one potential benefit of big data for manufacturing companies.

Using analytics software, you can identify where in the process defects are most likely to occur and take action to fix the problem. Some companies have taken this a step further by monitoring the production process in real-time and identifying anomalies before they reach the finished product. This reduces the need for quality assurance and testing at the end of the line - one large company estimates they will save more than $30 million by reducing the number of tests they conduct.  

Optimizing Delivery Routes

The transportation & logistics industry will certainly benefit from increased access to data. Companies can now monitor where vehicles and products are in real-time with telematics and fleet management technologies. These systems, and the data they collect allow you to schedule deliveries more accurately and even improve safety by detecting if a vehicle is speeding or driving dangerously. One of the most exciting applications of big data, however, is to optimize delivery routes to save time, money, and fuel.

The American Transportation Research Institute found that congestion and traffic costs the industry nearly $50 billion a year. Broken down into more meaningful numbers, they found that an average truck that travels 150,000 miles annually loses $26,625. These delays impact other areas of production and can essentially grind the entire operation to a halt. Data can help optimize delivery routes and avoid congestion to mitigate the risk of delays as much as possible.

Predicting Staffing Requirements

Today’s manufacturing relies on a mix of humans and advanced robotics working alongside each other in a safe and efficient manner. But staffing can be a major concern for companies who do not have accurate forecasting information. The same Honeywell survey shows that inadequate staffing was the third biggest threat to maximizing revenue.

Big data can help by improving demand predictions and forecasts so that you can more accurately schedule production. Supervisors on the shop floor can use real-time information, delivered to a wearable or other mobile device, to identify issues and allocate people to the most critical areas. This information can also be used to improve worker safety by ensuring workers are following safety protocols at all times.

Your Digital Future Depends on Data

These are just some examples of how manufacturing companies will benefit from collecting and using data. Regardless of how you choose to use the data you have available to you, the important thing to remember is that now is the time to embrace it. Digital transformation is now a necessity for survival, and successfully transforming your business means using data to make stronger, more informed decisions.


Remember, digital transformation is about more than new technology - it is about seeing new ways to do business. Contact Optimized Solutions to define your business model, understand how you are making money today, and anticipate how your business would be different in the digital economy of tomorrow.

 

Download: The 6 Key Technologies and Innovations That Are Changing an Industry

 

Topics: digital transformation, manufacturing, transportation and logistics, warehousing, IIot, Industrial internet of things

Aravindan Umshankar

Written by Aravindan Umshankar

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