Primarily, the issue is of data security. I don’t have to bring up the numerous attacks on data over the last few years. These attacks have primarily occurred on “data at rest” which means databases and other repositories of data (shared and secure drives both on premises and online in the cloud). Now, compound this with constantly streaming analytic data spewed from a multitude of sensors and the issue becomes even more serious. These sensors open up additional points of vulnerability that hitherto did not exist. In addition to the technical challenge of securing sensor data, which by itself is an enormous undertaking, the additional legal ramifications are significant as well. Consider the situation of a connected television where viewing habits are tracked. Even with the data anonymized, viewers may still be uncomfortable with the threat of their viewing profile going viral. Another example that comes to mind is Internet radio channels such as “Spotify” or “Pandora”. Do I really want someone to know the kinds of cheesy songs that I listen to?

The second issue is more technical. There are no unifying standards on how such streaming data can be obtained or shared today. A few protocols exist today where emitters can transmit sensor data to subscribed receivers. Most IoT initiatives are proprietary to the enterprise and therefore not much thought has been put into developing a single standard sensor data sharing protocol. Unless standards of data sharing evolve, enterprises are likely to spend significant amounts on data integration which might make the entire IoT value proposition suspect.

Third, the ecosystem monetization model is still evolving and quite specific to a few industry verticals. There is certainly value to IoT when the sensor data is shared internally in the enterprise whether it is for business enablement, operational efficiency or safety. The value of IoT data is multiple orders of magnitude larger when it is able to be shared throughout the ecosystem of the business both upstream to the suppliers and downstream to the customers. This cannot happen unless there is trust and security throughout the system. Consider the example of a retail giant which shares its consumer trend data to its suppliers. While the sensor data is still anonymized, the data provider needs to have adequate liability protection in ways that has currently not been thought of today.

A fourth issue is that traditional business models are today not equipped to take advantage of this potential value stream. Companies are still trying to figure out how to price information and successfully integrate them with traditional revenue sources. Business models need to change/adapt before IoT monetization attempts are made. I am not sure enough thought leadership has been developed in this area. My future blog post will actually propose a value framework for IoT.

A fifth issue is the need to modify existing product designs. Some manufacturing designs have been developed decades ago with little or no need to change. Obviously, these products cannot stream data or connect to the Internet today. Incorporating additional sensors into these traditional devices means that products will need to be redesigned and tested in the market before any commercial monetization model is adopted or created.