6 Examples of How Manufacturing Data Analytics Will Improve Your Product

The success of manufacturing for a business depends on constantly finding new ways through which they can streamline their operations. While it may have meant reexamination of every process in the past, it doesn’t work that way anymore. After all, no organization has the time to spend months testing and retesting their innovative ideas before they can implement the changes. 

Trends, today, change rapidly. That makes it difficult for companies to extract insights from those trends and act on it, improving sales, etc. Something much speedier is necessary. A way that allows you to sift through extensive volumes of information. Data analytics is that alternative. It can improve and speed up most processes – and has been doing so. 

Manufacturing isn’t any different when it comes to the benefits of data analytics. Below, we present six aspects – with examples — of manufacturing that data analytics can improve:


1. Demand Forecasting to Manage Inventories

Firms that can reduce inventory distortion — caused due to out-of-stock and overstock situations — are the wins that will win retail 4.0! Take TJX Companies, for instance, this business creates a profit when they are dealing with excess inventory from other manufacturers. The latter can avoid the damage this may cause to their brand strategy by not depending on third-party discount retailers, like Amazon and TJX Companies. Leveraging data to build customer satisfaction programs is one way of doing so. Such programs can give exclusive access to the buyers themselves on discount inventory.


2. Understanding the Manufacturing Supply Chain 

For most companies, purchasing is a standard part of the supply chain. Easily ignored in favor of the other aspects. But even buying raw material from a supplier that charges you a few cents more than usual has consequences. That may not seem like the end of the world – just then. However, a cent here and there can quickly turn into thousands of dollars on the ledgers. Big data can help companies keep track of their purchases. 

Another great use of big data comes from the pharmaceutical industry. Without any discernible reason, the yield of medicines they produce can undergo a drastic change in each production run. The inability to predict can lead to the companies’ losing substantial amounts of money.

One of the main reasons why pharmaceuticals cannot predict the yield change is due to the involvement of multiple parameters in it. With manufacturing data analytics, a biopharmaceuticals manufacturer could track nine parameters most likely responsible for yield variation. Using manufacturing data analytics insight, the company now saves $5M-$10M annually on just that product. The company can allocate some of the savings into improving the vaccine.


3. Predicting Faults to Practice Preventive Maintenance

If a manufacturing company can forecast when the equipment will fail to perform, they can prevent it from affecting production. When engineers know a fault is coming, they can fix those in reduced reaction time.

The data from Intel’s factory equipment live-streams to a centralized location. They use data analytics for manufacturing it to recognize the patterns so that they can detect the faults before they happen. Doing so helped Intel save $100 million in 2017. The integration of data analytics and lean manufacturing will also fuel continuous improvement. 


4. Turning Product Customization Feasible

By tradition, manufacturing focuses on production at scale. Product customization was something that only enterprises that serve the niche market may do. These days, though, more and more companies survive because they appeal to a smaller group of customers. Can you imagine the uniqueness of the customer experience with such a high level of customization?

Since data analytics can detect changes in customer behavior, now manufacturers get more lead time to produce customized products. The data analytics manufacturing process is almost as efficient as the ones that provide goods at a greater scale. Product engineers can gather and analyze customer feedback in near-real time because of big data.

The manufactured-in- Germany Opel Adam is a car that isn’t like any other vehicle. Here’s why: it offers a total of 4 billion variants to its customers. Customers can design their own car from the base upward on their website. They may choose to use a model already available or one from the most popular combinations. The site pools all the data from the different models the customers chose to provide the preferred designs. They can also predict what a factory will require for production. 


5. Assessing Early-stage Quality

These aren’t the days when companies must wait to see how a new product/model fares in the market. They can begin assessing early-stage quality and produce better versions. Even in 2014, BMW was using data analytics in manufacturing to detect vulnerabilities in their prototypes. Data from the sensors on the cars would trickle down to the headquarters. 

Manufacturing data analytics allows BMW to spot weaknesses and error patterns in the prototypes before they even go into production. The fewer cars they have to recall; the higher the quality of vehicles that BMW can assure. Thus, they can lower warranty costs, save lives, and of course, boost brand reputation with manufacturing data analytics.


6. Offering After-Sales Services for Increased Customer Satisfaction 

Manufacturing data analytics lets you provide a higher level of service to your clients. With it, you can improve your brand’s reputation and establish yourself as a business that cares!

Industrial manufacturing data analytics and the benefits it offers to go well past the designing stage. Rolls-Royce uses them for after-sales support. Their operational centers get the data from the engines’ sensors and generate insights. Any defects that appear can be immediately acted against. Thus, Rolls-Royce increases its product quality, ensures safe flights, and significantly reduces costs.

Data is an asset to your organization. Like with any other asset, it is up to you to make sure it works in your favor. You can spend time understanding the intricacies of data analytics yourself. Then you will have to extract the insights from it – ones that allow improvement through immediate action. Or, you can have the experts do it for you.  

All you need is the right technology partner to make your company data-centric. Professionals who can devise a plan that meets your specific needs. Their solution should provide you with a real-time view of your business processes. 4sights is ready when you are to help you use your data intelligently. We guide manufacturers to deploy the insights they get from their own data to do business better. Call us for intelligent, data-driven solutions through manufacturing data analytics consulting that you can start implementing right away! 

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