The Top 3 Big Data Myths for the Manufacturing Industry

Big Data means different things for different companies. For manufacturing and supply chain companies, it's a relatively new area of focus. But it's growing rapidly. Put simply, Big Data is huge volumes of hard-to-process data. The data can be highly complex or unstructured, it can be accumulated at high speed via the web, or it requires heavy analysis. Indeed, the faster you want to analyze data, the "bigger" it becomes.

Companies are increasingly looking to harness Big Data for many reasons. Managing this challenge can improve supply chain efficiency, reduce costs, and move your company to a fully data-driven organization with the ability to make real-time decisions.

Logistics and transportation providers in particular are operating on increasingly thinning margins. Every detail matters. Inefficiencies and mistakes can end up severely hurting profitability, customer relationships, and competitiveness. In such a highly fragmented industry, Big Data analytics is the key to competitive advantages.

For many though, this seems like a daunting task. The stream of information is never-ending, the complexities are many, and the majority of manufacturing and supply chain professionals still lack a sound understanding of the Big Data concepts, tools, processes, and overall importance.

So let's take a look at four of the most common myths of Big Data and why this is a wave you need to be riding.

Myth #1: Big data is only useful for the Marketing Department.

Big Data Truth: This myth is wrong on two levels. First, as I mentioned above, Big Data isn't just external data, such as social media sentiment. It can be any other type of differently shaped data, including your own internal data being processed in real-time.  That includes your RFID sensors, upstream and downstream data, ...