When Big Data sets are enhanced with real time information from sensors everywhere (those tiny chips that track those billions of things connected invisibly over the Internet) companies can literally manage every asset they own – or lease, or sell – in the case of managed service offerings.
What enterprises can track depends on the type of business they are in. Just imagine a data center company with tens of thousands of servers, racks, power systems, cooling systems, physical security systems, and more. With a robust Data Center Information Management system, the cost savings associated with being able to manage, in real time, temperature, availability, processing shifts, and more can actually pay for the system itself.
Then there are logistics companies, who for decades have already been tracking the movements of planes, trains, trucks, ships, and packages down to the detailed delivery status. Now these same companies can automate even more, with super sensitive, low cost sensors that can feed more precise and specific information such as freight temperature (for example expensive cancer medications with critical needs for precise cooling and on-time delivery).
Governments are preparing applications for “Smart Cities” which can monitor many different things such as usage of parking spaces, stability of infrastructure, smartphones congestion to determine where to investment in public WiFi, and distribution of energy radiated by WiFi and cellular systems. “Things” can help Smart Cities reduce traffic congestion, provide safer and cheaper lighting, and even tell if the trash cans are full and ready to be emptied!
There are literally thousands, if not tens of thousands of use cases – so what should a CIO think about when it comes to the intersection of Big Data and IoT?
First – what problems do you wish to solve around the mobility and communications of your tools, staff and systems?
Second – how much data can you analyze after you collect it, and how do you act on that data? Do you create closed loop systems (example, set the policy so traffic in congested areas is rerouted through smart signs) or pure analysis (generating reports that human beings read and make recommendations based on)?
Third – what is the investment to implement IoT and what is the return on fixing the problem by solving it with sensors and data collection?
Fourth – how can IoT and Big Data not just save money, but improve service delivery and customer satisfaction and loyalty? Can you create a more sustainable solution using less energy or cleaner energy?
Fifth – how will your IoT and Big Data strategy evolve over time, as part of a longer-term road map for your entire enterprise data environment? Will it be part of your products and services? Can you make it an integral part of your whole business process?
Companies like SAS, SAP, AT&T, Duke Energy and other massive enterprises have been leading the way with what is more and more commonly becoming known as “The Industrial Internet.”
Sensors and microchips are being placed everywhere to create a network that connects devices and generates data, and the smartest CIOs are making sure their networks are not isolated, but rather part of a giant pool of Big Data.
What’s of great interest to me, as a CIO who became a CMO, and is looking at tons of technology as part of my next adventure, is how IoT and Big Data can be combined and harvested to make customers happier! For example, energy companies are offering customers mobile application which are linked to their smart meter. When the cost of energy hits a certain threshold it usually causes a higher monthly bill – a consumer using the app who has set as a budget goal will get an alert and can then touch a button to speak with an expert in the company, who can view that consumer’s usage and make recommendations through a quick voice or video chat.
This is where we surpass the “Machine to Machine” phase of the IoT evolution, and start to create “Machine to Machine to Human” solutions, in which case there is a third element – the human, contextual element.
Few technologies live in a vacuum these days – in fact non-contextual software is just going to fail. We’re in the age of SMAC (the crossroads of social, mobile, analytics, and cloud). The more things and people we connect, the more data we have, the more value we can drive through analysis of that data and actions/communications based on those analyses.
By 2018, Cisco predicts there will be 21 billion connected devices. TWENTY ONE BILLION! Any CIO – and his or her team – CFO, CMO, and CEO – who thinks they can ignore IoT and Big Data is going to suffer, and not just in the long term. Every enterprise needs to factor in how the Internet of Things is going to affect their business, and respond by establishing the right infrastructure to support more Big Data and analytics. It can positively impact the top and bottom line, and create differentiation where it counts, at the customer experience.
Keeping it human may be the most important tactic when it comes to all this connectivity. Computers can run detailed analytics on all these thousands of sensors, but only humans can take the analytics and make intelligent decisions, take quick actions and have the right communications. Putting the right minds to work – creatively, imaginatively, and actively – inside your company to find the human ways of using IoT data is where the real power lies.
A business can place millions of sensors and microchips everywhere, but human beings are going to have to figure out how all the Big Data can make a Big Difference in results.