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The Internet of Things with Obstacles

April 6, 2015 by Andreas Schmitz 0

Greater efficiency and productivity, increased throughput in production, less machine downtime: Everyone is raving about the Internet of Things (IoT). However, we aren’t quite there yet.

Thirty percent higher productivity in automation and production, elimination of downtimes in power plants, higher throughput in production: The Internet of Things connects machines and sensors, generating huge amounts of data whose analysis provides valuable new insight, potentially streamlines processes, reduces costs, and protects resources.

IT consulting firm Accenture cites predictive maintenance as a concrete example. Because damage can be detected at an early stage, necessary repairs can be carried out in good time before the damage gets worse. This reduces repair costs by an average of 12%, total maintenance effort by 30%, and machine downtime by 70%, the SAP partner says.

Meanwhile, market researchers at IDC, predict that in five years’ time, 40% of all data will come from machines that communicate and exchange information with one another. Almost all analysts are certain that IoT will become a trillion dollar market.

Despite all these wonderful prognoses, reality in the business world today is quite different. According to consultants at Capgemini, less than one third of all companies today are generating revenue from new services for their connected product. It’s still early days for most company IoT projects, apparently, with most industries currently languishing at the first level of Capgemini’s three-level “maturity model.”

At the first level machines send information upon special request to a smart phone, but the device is not able to do anything with that information. At the second maturity level, technical devices can at least be configured and controlled externally. The third level comes closest to the vision of IoT, with companies using the sensor data to carry out predictive maintenance or improve productivity.

According to Capgemini’s analyses, 58% of all companies are currently at level one, 27% at level two, and 34% at level 3. The frontrunners are in the manufacturing industry and the medical devices industry. The pharmaceutical industry and insurance companies are still in their infancy in terms of IoT.

Internet of Things: Does utopia have to wait?

The penetration of appropriate technology is still relatively low, note Aelita Skarzauskiene and Marius Kalinauskas of the Mykolas Romeris University in Lithuania. What’s more, the researchers point out, there is a lack of standards, suitable protocols for data transfer, and compatible middleware, and data security continues to be major concern as well. The utopia of a gentle and quiet networked world is still a long way away.

Accenture likewise believes that the main challenge lies in getting current technology up to speed to accomodate the IoT. Software and sensors are often antiquated and no longer upgradeable. Poor integration of internal systems and those of external partners create data silos. Another problem is that outdated operating systems and technologies pose security risks but cannot be easily scrapped. Plus, there’s hardly any “embedded computing” in the applications and products.

The six main Internet of Things obstacles according to Capgemini

Ultimately, it’s a combination of technical and personal obstacles that are preventing companies from embracing the Internet of Things. Capgemini has identified the most significant.

Existing IT infrastructures are not cut out for the ever-increasing volumes of sensor data

According to Capgemini, 60% of all British companies in a recent study felt they were not in a position to process sensor date in real time. There is urgent need for action here, especially since the proportion of sensor data among all digital data is expected to increase five-fold by 2020.

Companies lack appropriate analysis tools that could help them gain new insights from the new datasets

The real-time processing of data in particular is frequently an unsatisfactorily resolved problem, as are the integration, analysis, and visualization of data.

IoT forces companies to address the issues of data security and data privacy

In a recent US survey of IT decision-makers, only half of those questioned believed they were ready for the networked world in this regard.

Product-centric organizations lack development and marketing thinking

IoT demands new services and sales models that stand out from those of the classic portfolio. Companies often lack the appropriate competencies at first.

Most sales departments are still relatively unfamiliar with IoT services

The new class of services requires a special training that focuses on the networked services and the new opportunities they bring.

The new services demand new capacities in customer support

Customer queries are becoming increasingly complex. Nevertheless, customers expect quick response times.

There is a lack of Big Data experts who are able to interpret sensor data

Data scientists are rare and in great demand. It is difficult to find and hire well-trained specialists.

No matter how differentiated these reasons appear to be, though, perhaps the greatest hurdle to IoT adoption is what IDC identified in its recent study — the up-front investment.

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