Technology -> Big Data
By: Rob Bamforth, Principal Analyst, Quocirca
Published: 5th February 2014
Copyright Quocirca © 2014
It is getting hard to find presentations, press releases, or events in the ICT sector that make no reference to the fabled Internet of Things (IoT), or M2M (machine to machine) to give it an older, slightly more techie, hype handle. It's everywhere (as some of the press releases might even say) but still too much of the emphasis is on futuristic technology—admittedly sometimes very shiny or with sci-fi styling—rather than business benefits.
This is nothing new for the technology sector, but for IoT to really take off, the story has to move on. Today, the main word that accompanies the phrase IoT is 'platform'. What this tells you is that everyone thinks that everything is going to be connected, but they have not quite worked out what for. This brings up an important issue for IoT—what are the other prime considerations in the cost/benefit equation?
Unlike the 'Internet of People', where the distractions and diversions of browsing, entertainment, advertising and communication for no reason other than to say "hi" form a large amount of the traffic (and derived value, especially for service providers), the ‘things’ on the internet have little need for such ephemeral IP packets. They want data with specific meaning, for a purpose or application, and often nowhere near as much of it as the average user surfing for content. However this data has to be more reliably delivered and the price point has to be sufficiently low to encourage the connection of 'everything'—or at least as many things as possible.
It also has to be delivered somewhere useful, i.e. into part of a business process and this generally means some significant integration work into existing IT and probably some process re-evaluation, if not complete process re-engineering (this IoT is meant to be disruptive after all!)
Both of these critical aspects—reliable delivery and integration—are oriented around people and procedures at least as much, and probably more than, technology.
First how do you ensure data delivery? This might seem to be solely the domain of network operators and telcos, who certainly have been making a big play for the M2M space. While this is true for the switching on of global SIMs for mobile M2M devices and the ongoing transmission of data, there will generally need to be a setup and commissioning process. Unless this is something that can be embedded during manufacturing, it will involve human effort, otherwise we are limiting the IoT to be the internet of 'new' things. This might be fine for applications involving other new and fast paced technology, such as embedding low-level communication capability into e-readers, but many 'things' in the real world evolve or are replaced over a longer period of time.
For example, if smart meters (the oft quoted poster child of M2M) or building management systems (BMS) are going to be deployed to assess and control energy usage and the working environment of existing buildings, networks of sensors and energy meters need to be deployed and tested. This will involve electricians, and in the case of BMS, IT and facilities management people. The human part is critical as it will determine the quality and veracity of the data subsequently delivered.
Second, integration. Another often-described example of the value of connected things is the vending machine (or fridge) that requests its own replenishment. The integration to a stock control system is relatively straightforward, but physical goods require integration into logistics and delivery processes, which will be human intensive if only for checking and exception handling and, after all, even Amazon, a great example of streamlining and automation, uses people to pick stock.
Then there are the 'softer' human qualities that are harder to automate, such as relationship building and spotting opportunities to up sell. This is the highly visible end of the service sector, which, if badly automated, starts to lose its differentiation and effectiveness. There is also the human ability to identify and diagnose problems early, which again, in theory and with sufficient (big) data, can be automated, but what dictates how much and what type of data should be gathered? Business processes, strategy and ultimately, people.
There are further reasons why this human quality impacts on integration and evolution of the business process—the vested interest and (sometimes not so) hidden agendas of individuals, pressure groups and departmental alignments. In the hyper-connected utopia where everyone collaborates and shares based on open, transparently and instantly accessible information, this shouldn't be an issue, but in the real world, it is. People and process are at least as much of a challenge as the technology when it comes to smart connected devices automating the world.
It turns out that even 'machines' and 'things' need to be involved in the internal and sometimes external politics of organisations, otherwise their promised productivity boost might be wiped out by an accidental kick of an off-switch. So the next time someone purporting to be an IoT thought leader offers you a platform, ask who or what is driving their trains (of thought).
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Published by: electronicdawn Ltd.