With all the hype around IoT, you’ve been told over and over again that Big Data has the potential to change the supply chain. You already know that your devices are generating data, and you expect to yield all the benefits that Big Data has to offer.
But what exactly is Big Data, and how is it different than other data? How does Big Data deliver on the promises of the IoT to yield unforeseen operational benefits within the supply chain?
The key to answering these questions has more to do with the analytics than the data itself.
This doesn’t mean that data isn’t important; it just means that analytics are the key to making sense of really BIG data.
For example, every research project starts with a question in mind. We are taught that through data collection and evaluation, we are able to uncover a potential answer. So with sights set on finding an answer, we intentionally ask the right questions to get the information we need.
But what if the data you collected had more to offer? What questions would you ask? How would you handle the robustness of Big Data?
First, let’s start by looking at the not-so-Big data or “small” data. This is the moment-to-moment data that tells you what happened and when they happened. Driven by what you ask for, small data yields categorized and summarized information over a specific timeframe. It answers questions like:
- Which carrier had the best estimated time of arrival (ETA) this quarter?
- How did that compare to their ETA performance last quarter?
- Which carrier had the slowest growth?
Small data details what happened, while Big Data uncovers why it happened, what is going to happen, and what should you do about it? It answers questions like:
- Why did this carrier outperform the others?
- What will their ETA performance look like next quarter?
- How can we help the other carrier increase their ETA performance?
With this, we know that analytics are the only way to make sense of Big Data. Analytics identifies naturally occurring areas of value that were previously unknown to provide new knowledge. With advanced, machine-learning, analytics reveal trends and patterns that become smarter and more accurate over time in order to provide insight into what’s possible for growing your operations.
If you’re trying to uncover the value of Big Data and IoT in your organization, check out how Savi is using all kinds of data to transform the supply chain through better, more accurate ETA with our Estimated Time of Arrival-as-a-Service application.