In the era of Big Data, we are collecting enormous amounts of information. The amount of new data generated every day is said to be growing exponentially, and for quite some time this amount has exceeded our understanding. Such information comes from different sources and contains data in a variety of ways.
As we pointed out in a previous blog, use of Big Data covers things like predictive analytics, recommendation engines, fraud analysis and customer behavior analysis. However, sometimes we may just have a vague idea that the data we own could be very valuable to our business, but we do not know how. Nevertheless, we collect it just in case.
Big Data can be hard to interpret from time to time. It may contain information that is hard to grasp in IT; it may be non-structured and contain information that is hard to process by computers. However, a large part of the data that we are collecting contains simple, understandable events that successfully describe well how our business processes are working.
Take logistics processes for an example. Let’s say you are a manufacturer or a merchant, and a crucial part of your business process is to deliver goods to your consumers globally in a timely manner. There is a lot of information that is collected from the logistics process over the whole delivery line. Every time a parcel is scanned in different places across the delivery line, there is a piece of information left somewhere. This information can be utilized in a variety of ways; you can, for instance, provide tracking information to your end customer, or compare different logistics providers’ performance based on these events.
However, today, a majority of this information is still used only when problems arise. If we continue our logistics example, you will inevitably find that one of your 100 000 daily shipments ends up broken, lost, stuck in the customs, or some other issues. And often times, you will only find out that something has happened when you receive a call from the end customer waiting for the delivery.
It is good that we have all that data available for finding out what happened. But fixing problems is always a reactive act. What if we could discover potential problems before anyone can even notice them?
Based on the same events, it is possible to find out anomalies in your business processes before they escalate into larger problems. In logistics, proactive alerting can be implemented to monitor the event flow of different parcels, and send configurable alerts whenever e.g. a parcel does not move from point A to point B in pre-defined time frame. In addition, when this is done automatically as a part of your analytics solution, you will not only receive alerts of individual errors in the process, but also utilize the analytics solution to find out systematic errors in your processes – ultimately allowing you to fine-tune your processes.
Of course, one challenge may be to receive all the information from the right places; these events can be logged in a variety of applications across different organizations. Thankfully, modern cloud integration solutions make it possible to integrate this information into a manageable and transparent solution. The key to logistics efficiency, is in fact, proactive alerting.