Data is important. However, even more important is the critical Analytics which the data drives. Information needs to enable decision making, either through rules-based/automated decisions, or by people taking decisions based on the analytics presented to them. It is not only the zettabyte of data captured which matters, but what is done with it that defines success or failure.
IoT is gaining significant momentum. As per Cisco, 250 things will connect every second by 2020: that means 7.9 billion things will connect in 2020 alone! Imagine the data which these things will generate! IDC predicts 212 billion things will be connected by 2020 and global data volume will reach a staggering 40 zettabyte by 2020. Around 40% of this data will be generated by things and devices compared to just 11% in 2005. We are and will continue to live in a data deluged era!
In a meeting with a Global 500 manufacturing company this month, two key points grabbed my attention. The first was whether the company could derive a more effective sense of the data they already have, i.e. the continuous stream of data from their shop floor which is already well-integrated into the manufacturing systems. For them, this is the opportunity to move away from using data for post-facto or root cause analysis, towards proactive data analysis which could alert the systems, robots, tools and people to act based on real-time analysis of what could most likely happen. This analysis is possible with data and sensors which exist today. For example, it could be that bins are not loaded to capacity, conveyor belts are likely to yield or aligning shop floor data to real business outcomes on revenue, profitability and customer satisfaction. The system architecture, big data structure and analytics engine need to change and incorporate the new thinking.
Secondly, IoT is enabling their products with sensors that will create a colossal amount of data with the massive potential to create a completely new avenue that can lead to driving new customer experience and, eventually, additional service monetization. Although MRO is traditionally a highly profitable service line for manufacturing companies, the new age of sensors, software and integrating intelligent service monetization layers open new and exciting avenues for them.
Clearly, the value of analytics is greater than the data per se. Similarly, the value of services created and delivered is more than just the device which enable these services. For example, in an IoT world with a connected microwave, conventional oven and refrigerator: the refrigerator checks its contents, suggests various culinary delights and recipes, recommends whether to use the microwave or conventional oven, and also has the oven preheated and ready. In such a world, how would you buy white goods? Could it be free and you pay based on the recipes downloaded or if you liked what you made? The business models could take any form of the unlimited imagination! The same will also be true for industrial products, where the value will be created not just by the machine but by harnessing the data which the sensors will capture and the software analytics engine will process.
Insights from financial, customer and enterprise data have always created and driven successful businesses. We are now going to yet another dimension, where data from devices and things will provide the next set of opportunities and drive new analytical thinking and business growth. It is not just the data but what you can do with it that will define the winners…
Very informative article. and i think where billions of data are generated in a second from IoT, we have to make a good Analytitical platform to process those data. and we have consider more about data processing(it includes Speed, Time, and Accuracy).