Dave M

If you follow technology, you have undoubtedly been exposed to the Internet of Things (IoT). Even if it isn’t explicitly referred to as IoT, the plethora of connected products coming to market along with pundits promoting it as the next big thing are hard to miss. However, what qualifies as IoT is difficult to define.  Is it all about the “things”?  Or, is it the data those things generate?  As a business, what is the motivation to invest in this next technology wave?  Is it even a technology wave at all or more a business transformation movement?

Just like the cloud before it, IoT covers a large swath of technology and business benefits. Arguably, too much and within that lies the problem. Most IoT literature starts with generalizations about market potential and projections for growth of connected devices along with stratospheric estimates on the economic value they will contribute to society. While that might initially grab the reader’s attention, it doesn’t leave them with a clear understanding of what IoT is and how to achieve it.

This problem gets exacerbated by vendors selling products and solutions in this space. It’s no surprise they bend the definition of IoT to what they are peddling. In the consumer space, IoT companies put a significant emphasis on the thing itself. This is clearly evident in fitness wearables, home automation and other connected consumer products, where the physical design and usability of the device is critical to market acceptance. While it is implied that these products can participate in a larger connected ecosystem, the emphasis is really on the individual product.

In industrial environments, IoT is often used as a new marketing term for M2M, which has been around for years. As communication technology has become more ubiquitous and less expensive, new categories of equipment and devices are now being connected to the Internet, enabling companies to stockpile data in a corporate datacenter or cloud storage provider. For sellers of wireless modules or airtime, this may seem great, but businesses have struggled to extract value from existing M2M data, so giving it a new name and expanding its reach doesn’t help much.

To deal with this data glut, data analytics companies believe they have what constitutes an IoT solution. After achieving success with enterprises on Big Data projects, they are turning their tools and algorithms on this new source of data. After all, machine data couldn’t be much different than human generated data, could it? The pitch is that data analytics will be able to make sense of the mountain of accumulated data and unlock insights. The problem is that the insight itself isn’t always that insightful. In many cases, the output of the analysis can helpful for reporting on historical performance, but it doesn’t really help current operations.

The missing link is a method of integrating M2M data and data analytics insights into real-time business operations and workflows in order to achieve a specific business use case. For some companies, this could mean improving the up-time of mission critical equipment through the use of predictive failure and data-driven diagnostics, a combination known as prognostics. For others, the ability to understand how products are being used in the field can lead to improvements in R&D design and create the potential to offer new service-based offerings. For both, it is much more than collecting and analyzing data. Those are just components that are needed to achieve the real purpose of IoT: to improve business outcomes.