Data is everywhere and it’s touching every industry. Integrating big data in manufacturing represents an opportunity to increase revenue streams.
Data is everywhere, and it’s touching every industry. However, integrating big data in manufacturing may have the biggest impact yet. Not only does data have the potential to serve as an avenue for organizations to improve profits and productivity, but, when it’s properly leveraged, it also opens the door for many manufacturers to provide value-added services — the type of services that may actually serve as new revenue streams.
Data is also coming from a growing number of sources. For instance, almost every machine has the ability to provide manufacturers with data, while mobile devices, social media and sensors provide data. In fact, data is growing faster than ever before and by the year 2020, about 1.7 megabytes of new information will be created every second for every human being on the planet. The key to success is being able to put all the data into context so that the organization can garner, and ultimately apply, the insights.
Monetizing Big Data in Manufacturing
According to a recent McKinsey report, when using big data in manufacturing, “operations managers can use advanced analytics to take a deep dive into historical process data, identify patterns and relationships among discrete process steps and inputs and then optimize the factors that prove to have the greatest effect on yield.” As the report demonstrates, the ability to capitalize on data isn’t restricted to inefficient organizations. Even those businesses who have embraced lean manufacturing — and remain committed to continuous improvement — often find meaningful insights when they’re open to both analyzing and implementing recommended changes.
There’s a growing number of firms who have “Uberized” their industries, by essentially monetizing the data they collect. Some organizations have recognized opportunities to take data they currently collect and use it to build out completely new offerings that add significant value to the customer.
Obviously, as data changes the business landscape, the skill base needs to adjust accordingly. For instance, manufacturers may turn to employees to regularly identify areas of opportunity for data-based improvements. Be able to recognize and point out areas of inefficiency. Naturally, this transition means a higher emphasis on strategic thinking, as well as the ability to seamlessly analyze and assess situations.
Fortunately, many of today’s analytic solutions are user-friendly, meaning it’s no longer necessary for everyone utilizing them to be data scientists. In fact, there is an ongoing trend for data analytics to become highly accessible, self-service tools as a means of helping organizations more effectively operationalize the data results.
If manufacturing organizations are willing to invest the time and resources into effectively expanding upon their big data capabilities, the potential is there to realistically separate themselves from competitors — not just in how effectively they produce products, but also in how they impact their industry as a whole.