I remember that moment like today. I was nine years old. I was standing in a huge electronics store, in front of a wall of flickering televisions. On each screen was something different – on one the broadcast of a match, on another the weather forecast, on another a TV series, and on another the news. A cacophony of images, a flurry of information. I was simultaneously fascinated and overwhelmed. A thought was rattling around in my head: “If all these transmissions were so combined into one coherent whole, how much could be learned, how much could be understood…”.
Today, looking at modern companies, I see exactly the same thing. Your company is such a wall of televisions. Each department broadcasts on a different frequency: production bombards you with performance data, marketing floods you with campaign statistics, sales inundates you with reports, and IT systems generate gigabytes of logs. Amidst this information noise, are you able to find a single consistent message to guide your business in the right direction?
Big Data is not just a trendy buzzword from technology conferences. The term refers to huge data sets that are generated at a rapid pace and collected from various sources. Imagine your machines, ERP systems or even social media providing daily information that can be crucial to the growth of your business. It used to be that data from a single production shift was enough. Today, we have access to real-time information. It’s like going from a black-and-white TV set to a color one – the difference is colossal!
And while we’re on the subject of television… I invite you to watch a video. It will consist of stop frames taken every eight hours. Admit it, it’s not the same as HD production. And what kind of film do you watch in your production facility? Do you choose the poor quality and classic approach of collecting data in the form of an eight-hour resolution report, or rather a full-length image recorded real-time? Big Data is precisely like a camera working non-stop. With it, you record every little detail and can analyze exactly what happened and why.
Take the example of an ordinary production machine. In the traditional approach, the operator records basic data after his shift: how much he produced, how much raw material he used, whether there were breakdowns. It’s like trying to describe a whole day in one sentence. Well, a lot of details escape.
Big Data is a completely new approach that allows you to:
Example: a production machine worked four hours during a shift, but the operator was paid for eight hours of work. What if there was a breakdown in the meantime that ruined efficiency? Without real-time data, you are unable to draw conclusions about what to do to avoid such losses in the future.
What can you apply Big Data to in business? Here are some areas:
As I mentioned earlier, in a manufacturing company you are dealing with a huge amount of data. Their sources are at least several, including:
When you combine data from all these sources, you get a complete picture of your business. You can see not only WHAT is happening, but also WHY and HOW it is affecting your profits.
What does this look like in practice? With e-commerce data, you can discover which products are actually profitable. Combine this with machine performance analysis, and you’ll know whether it pays to continue production.
The Rolls-Royce example shows how Big Data can reduce aircraft engine maintenance costs by 15%. Better anticipation of maintenance needs avoids costly flight delays.
💡 Tip: Start with a small pilot project – for example, by metering 5 key machines. This will allow you to test the solutions and see the first results!
Remember that you don’t have to implement everything at once. Start with small steps, see what works for your company, and gradually expand the system.
Big Data is not just a trendy buzzword – it’s a real opportunity to optimize your company’s processes. After all, in the era of Industry 4.0, data has become the new currency. By analyzing them, you can predict trends, optimize processes and make better decisions. After all, who wouldn’t want to know what will sell in a month?
Amazon makes excellent use of customer data to personalize offers.
How about you? What plans do you have for the future of your company?
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