Is the Internet of Things Really Happening?

Over the last few years there has been much speculation about the inevitable growth of the Internet of Things (or Internet of Everything). Forecasts have suggested anywhere from 30 to 50 billion devices will be connected by 2020. Cisco has estimated that the global IoT ecosystem will have a value of $14.4 trillion by 2022, and IDC has projected yearly IoT market revenue to increase to $1.7 trillion by 2020.

Here we are now in 2016, a few years into the future they were talking about back then, and it may be a good time to take a look the current state of the IoT and see how it measures up to all of these lofty expectations. Are people really embracing IoT technology at this rate? Is this money really being invested?


Connected Devices

First, let’s take a look at the number of connected devices. If we flash back to 2013, we find that Gartner released a report entitled “Forecast: The Internet of Things, Worldwide, 2013”. In this report, they predicted that the IoT will include 26 billion connected devices by 2020. Two years later, Gartner reported a total of 4.9 billion connected devices at the end of 2015, up from 3.8 billion in 2014. Gartner also revised their 2020 estimate, anticipating 20.7 billion connected devices by 2020, a decrease of 5.3 billion (20.4%) from their 2013 estimate. (It should be noted here that Cisco continues to anticipate as many as 50 billion by 2020).

So, according to Gartner, IoT adoption has not proceeded at the rate they had anticipated at the end of 2013.

One reason for the slower-than-expected growth is the difficulty faced when trying to implement IoT technology. In fact, Gartner anticipates that through 2018, 75% of IoT projects will take up to twice as long as planned.

Value of the IoT

Now, let’s consider the monetary value of the IoT and how that number has progressed. Cisco initially projected a value of $14.4 trillion by 2022. Within two years Cisco had increased this number to $19 trillion.


This highlights an interesting fact. Even though fewer connected devices are expected by this date, the total value of these devices and the underlying network is expected to be greater than it was when more devices were expected. Based on this, I think it’s safe to suggest that implementing IoT technology is turning out to be more expensive than originally thought.

This may be due in part to the fact that some enterprises are rushing headlong into IoT projects without the proper foresight and planning. Often it is a reaction to competitive pressure, based on a perception that a competitor is already moving forward with their IoT strategy, or simply in an effort to be the first and gain a competitive edge.

“I think it’s safe to suggest that implementing IoT technology is turning out to be more expensive than originally thought.”

Another answer may come from Gartner’s 2015 report: “Predicts 2015: The Internet of Things”, in which Gartner predicts that through 2018, there will be “no dominant IoT ecosystem platform”. They cite a lack of IoT standards and anticipate that IT leaders will be forced to compose solutions from multiple providers.


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Even when faced with these realities, however, enterprises are still moving forward with their IoT projects. The extra expense – though unanticipated – is not nearly enough to outweigh the potential benefits. The IoT is most certainly transforming the way businesses operate, and no one wants to be the last one to this dance.

IoT Investment

This is an important category as it will largely determine how quickly the industry moves to develop standards, and how motivated IoT solution providers will be to develop more powerful and more cost-effective solutions.
Recall IDC’s projection of annual market revenue reaching $1.7 trillion by 2020. It would stand to reason that if we are learning that IoT projects are coming in over budget and late, there is probably some distaste in the marketplace, and maybe IDC’s projection was a bit ambitious.

At the same time, though, if people are spending more on IoT initiatives than they had originally planned, perhaps IDC’s projection was a bit conservative. Let’s examine how things are taking shape.

In 2015, IDC reported that worldwide IoT spending reached $655.8 billion in 2014 and calculated a 16.9% CAGR (Compound Annual Growth Rate).

Well, 2015 is now in the books and we can see how IDC’s projections seem to be holding up. Their latest report indicates that spending in 2015 reached $698.6 billion, a CAGR over 2014 of only 6.53%. Had IDC’s anticipated CAGR proven accurate, 2015 revenue should have been closer to $766 billion.

Notwithstanding this fact, however, IDC continues to project a CAGR of 17% and an increase in spending to $1.3 billion by 2019, which would equal approximately $1.5 billion in 2020. It looks like IDC sees the IoT market cooling off a bit, though not much.

So, while the earlier projection has proven to be overly optimistic, it is clear that investments in IoT initiatives are continuing to increase with no end in sight.

If there is any kind of meaningful takeaway from all of this, I think it’s safe to surmise that IoT projects may be coming in late and over budget, but that doesn’t seem to have had much of an impact on continued investments. It is clear that business owners and executives see the value and have no interest in letting their competitor’s gain an edge.
So, was the IoT hyped a bit excessively over the last couple of years? Maybe a bit. But, it is also very real and happening right now.

Information Modeling as a Tool for Collaboration

In the spirit of the upcoming holiday season, let’s take a moment to examine one of the greatest and most appreciable qualities of a healthy organization: collaboration. In a world so full of information, where we are all so busy and so pressed for time, it seems collaboration has become something done more out of necessity than out of a desire for quality and efficiency.

Some of this reality may be due to the fact that there simply are no good tools for collaboration in the modern workplace. Sure, we have email and teleconferencing, web meetings and text messages – but for all of our technology, our endless need to compartmentalize and segment our business processes has left us no closer to a model of organic collaboration than we were in the past.

With relevant information stored in separate silos, decision-makers are still forced to rely on reports and statistics compiled from historical data and interpreted to support a specific agenda. There has really been no truly organic means analyzing real-time data alongside the historical data. Likewise, the available tools for integrating data from separate systems are limited in terms of their ability to create a real-time context and to display the appropriate data to decision-makers at the speed with which decisions must often be made.

While these tools may be useful for looking back and analyzing what has happened, it is another matter altogether when trying to look forward to make plans or predict outcomes.

Information Modeling

One of the ways this challenge can be overcome is by using an information model to organize and structure your organization’s data in a way that provides context and clarity in real time. Information modeling allows assets to be associated with all relevant information – regardless of where that information may reside.

For instance, a motor on your plant floor can have live data related to its RPM, temperature, throughput, or other process data – as well as a commission date, a maintenance schedule, troubleshooting documents and training videos. Properties of this motor can also include OEE (Overall Equipment Efficiency), Net Asset Value, or other performance and resource planning metrics. Some of this data may be coming from PLCs, some from databases like SQL Server, some from user input, and other data is coming from programmed calculations. In this situation, it is not important how this data is generated or where it is stored. What is important is that this data can be visualized at any time in whatever way suits your collaborative needs.

There are a number of different tools that can be used to create an information model for your organization. A few things to consider when choosing an information modeling tool:

  • Does the modeling software take into account both real-time AND historical data?
  • Does the modeling software allow you to include ALL relevant information from every source?
  • Is your modeled data logged in a relational database like SQL Server so it can be queried if additional information is needed?
  • Does your modeling software provide the tools you need to visualize your data in a useful way that supports decision-making?
Before you jump into a new software product and a new data management system, do some homework. As with everything there are pros and cons to the different products available.

Better HMIs for Better Decision-Making

Today’s workplace is much more automated than in the past, and work is increasingly done by computers and other machines. The role of the human worker has changed, with many relegated to operating the machines that do the work rather than doing the work themselves. It’s hard to argue that most production environments have become more efficient and more productive as a result of automation. Much research has been done to compare the value of using a SCADA (Supervisory Control and Data Acquisition) and HMI (Human Machine Interface) system to the value of not using a SCADA/HMI system. What is often overlooked, however, is the cost of using a poorly designed HMI system compared to the cost of using a well-designed, user-centered HMI system.

A recent study by OSHA in Europe has compiled statistics on HMI-related errors in the workplace. Interestingly, research shows that the majority of problems are caused by human error, but not entirely because of mental and physical fatigue. More often, errors are caused by poor decision-making related to the way that information is processed.

Source: European Agency for Safety and Health at Work

A certain amount of human error is to be expected, as is a certain amount of machine failure, but errors caused by a lack of information (i.e. common safety procedures, maintenance procedures and history, expected machine performance, etc.) should be nearly unheard of in today’s information-driven world. All of this information can and should be made available in real time to all operators and key decision makers. Poor HMI design may be acceptable when everything is working well and without any abnormal conditions, but when something abnormal or unexpected happens, the HMI needs to be as transparent as possible so human operators can see what they need to see to make quick decisions. Too often, the HMI serves as a barrier to problem-solving rather than an ally.

Learn more about the value of more intelligent HMIs at