Historical data, customer journeys, facts and figures, long-term trends, predictive analytics, data management software … and that’s just the beginning. Welcome to the world of big data.
These buzzwords continue to make the rounds on the global business landscape in sectors ranging from energy and healthcare to manufacturing and retail – and everything in between.
What Exactly Is “Big Data?”
While definitions differ to a degree, in simplest terms, big data is all the information a company has on paper, servers, and in the digital universe. It’s photos, tweets, and emails. It’s online searches, social media updates, manufacturing processes, sensor data, and error rates. Essentially, it's is all the data a company owns in its myriad forms.
According to Gartner Inc., the world's leading information technology research company, big data is often defined in terms of the “three Vs” – volume, velocity and variety. And while data collection is not new, what we do with it is.
Raw and unorganized, all this data is useless. The intrinsic magic lies in decoding monumental amounts of structured and unstructured data to unearth cryptic insights, trends, patterns, and relationships which can ultimately be used to enhance process automation, make better decisions, realize cost savings, and achieve maximum efficiency.
When it comes to manufacturing, big data plays a significant role which likely will become even more critical as time goes on. According to industry experts, if companies are not tapping into the potential of big data, they are losing ground fast.
ID Your Competitive Edge
When it comes to harnessing big data within the realm of manufacturing, there are countless ways information can be utilized to improve operations. Here are just a few insights from industry insiders:
- Take note of when and how often your line manufactures certain types of products and then use tools to track the time and effort required to generate meaningful output for each.
- When does your factory produce its greatest output? What days? What hours? At what mix and with who on the floor? The idea is to study the conditions that lead to the very best outcomes and then seek to reproduce those outcomes on a regular basis.
- Use analytics tools to improve workforce efficiency by studying error rates and then correlating the results by product and employee.
- Advanced analytics often make information accessible in real time. This can help manufacturers provide a more accurate timeline to customers regarding when to expect their product.
- For companies that offer custom products, big data can reveal what the most popular custom items are and how much they sell for, which ones are not making the company money, etc. In other words, big data can help determine what changes should be made to save the company time, money, and supplies.
- Use big data to manage risks such as weather-related delays in deliveries and shipments by identifying potential problems before they happen.
- When manufacturing companies install computerized sensors on assembly lines, this allows for analytics to be generated that can be used to significantly improve the quality and safety of manufacturing processes.
- A manufacturing organization can use analytics to enhance collaboration and develop a customized synergistic flow of information throughout its entire infrastructure, including its machine operators, engineers, quality control department, and other facets of the company.
- Big data helps reduce the cost of production as well as the expenses accompanied with packaging. Furthermore, it helps decrease the amount of money spent on transporting products and storing them in warehouses. All of this leads to a reduction in inventory costs, which can result in higher profit margins.
At the end of the day, big data is changing how companies compete and redefining just how powerful intelligent business solutions can be. Analytics strategies are no longer optional but rather necessary in today’s rapid-fire business environment.
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