Technical and industrial operations staff need to ‘think like CEOs’ when it comes to successfully implementing IoT projects, according to Andre Schindler, director of business development at TeamViewer, an online support and collaboration software company.
In other words, a more wide-ranging view of how IoT data could be used by the business is needed, along with a greater focus on business outcomes.
“I would like to encourage firms to think beyond the ‘managed devices’ concept that the IoT champions, and look at the bigger operational opportunities that the IoT can bring,” says Schindler.
Staff at every level, in other words, should be considering how IoT could transform operational business models and improve company prospects.
Ten-part device harmony
For example, Schindler points out, monitoring production processes in a manufacturing plant using IoT sensors can be a highly complex endeavor.
“You will not find a device or machine with more than ten parts where all [of those] parts have been produced at the same location, by the same company, and then assembled by the same specialists. Parts are produced in different countries by different companies and then married and assembled in one place… and very often just in time for delivery,” Schindler points out.
This leads to incompatibilities, which in turn can lead to a potential disconnect in the IoT data supply chain. Schindler says that a more holistic view of devices (through a higher-level approach that uses ‘digital twins’) is needed to produce an accurate picture of industrial production status.
Things, Connect, Collect, Learn, Do
Schindler’s recommended reading on this subject is Dr Timothy Chou’s Precision: Principles, Practices and Solutions for the Internet of Things.
As Schindler explains: “[Chou’s] five-layer framework consists of: Things, Connect, Collect, Learn, Do. This has been a standard for some time now and propagated by most consultant and analyst agencies. This framework helps you to understand where in the value chain your company is and whether or not you are spanning multiple sectors of the value chain – and, indeed, whether you are a critical component of the process,” he says.
But according to Schindler, what Chou fails to do is point to a way to finding a strong value proposition for all IoT users/customers. He asks, it is great to know what your product is, but why is it important? What solution does your product provide to your customers and how does it support your clients on their journey?
“IoT is still only being implemented by organisations that have visionaries at the top,” he says. “The idea of collecting data on devices and acting out on that information is a concept that has been around for some time, but for legacy organizations to survive [in the IoT world], they need to take a step back and go beyond monitoring data and include machine learning – all in the spirit of the bottom line and making sure that the businesses costs are kept low and production is up.”
“But before this can happen, a strategic and complete vision for a company is needed to understand the value a connected world can create.”
Read more: IIoT held back by long project lead times, claims Asavie
A lesson to be learned
What TeamViewer’s Schindler is encouraging organizations to do is to look at the whole picture, when it comes to IoT data implementation. This may sound obvious, but Schindler reckons that when specific IoT devices are brought online, implementation teams tend to focus on a particular data stream or workflow pertaining to that device, rather than other roles the devices could play.
If a trucking firm, for example, starts to use tire sensors to gauge rubber-to-road data metrics, shouldn’t those sensors do more than simply alert the company when a new tire is needed? Couldn’t they also contribute to an analysis of whether there is a correlation between tire pressure and fuel consumption to save costs? Wherever possible, the answer, of course, should be yes.
Read more: AT&T gives wings to Red Bull IoT project