New technologies are only as good as the added value they can deliver. For the Digital Tranformation in general, and for IoT – the “Internet of Things” – in particular, that path has been slow. The first IoT implementations date back to the mid-’80s. The uptake of this technology, however, only recently started. Several factors have contributed, including costs. As costs have come down dramatically since those early days and continue to fall, more and more applications come into reach. Total evaluated costs for some use cases can be below $10 per “thing” per year. These prices imply high ROI considering the value of the collected data. One of the reasons why IoT is taking off traces to this – affordability is here now.
Challenge of IoT implementations
Costs, however, are not the only explanation. Two other factors delayed the uptake and contributed to the classical “hype cycle” as Gartner defines it. The first is related to the complexity of the implementation. IoT is not in itself a technology, but rather a combination of different technologies. Each of these requires its expertise. Compared to many IT implementations, IoT is much more complicated. As a result, although many companies claim they can deliver adequate IoT solutions, only very few possess the complete set of capabilities needed. That set should also include experience in operating IoT systems, as some of the unique challenges in that area need to be taken into account during the design phase. Many IoT projects are not set up well from the start. The fact that the planning for the period after technical completion is often forgotten, further challenges this suboptimal set up. At its core, introducing IoT means a change of work processes and organizations. This change affects people. As everyone who has tried to introduce a change in an organization knows – this is always difficult. As a result, many IoT projects have failed.
Standardization of end-to-end IoT solutions
Interoperability between elements of the IoT “stack” has improved through standardization. This process will continue. This means that creating IoT solutions by combining different components delivered by specialized companies has become a viable path. As these individual elements are delivered at scale to many applications, this approach lowers overall project risk compared to the traditional bespoke solutions. It also reduces the lead time to value significantly.
Identifying more applications through data
A second factor has to do with the delivery of value. IoT projects that complete the first hurdles – the technical implementation and the successful acceptance by the organization – often deliver more value than anticipated. This outcome is related to “the value of data”. In a typical case, an IoT project may start by delivering a “point solution” – with a singular objective that is easy to understand and for which the business case is explained in simple terms. Once the system is active and starts accumulating data in the cloud, the organization identifies new applications that use this data. With the acceleration in advanced data processing that uses AI and Machine Learning, data will become ever more valuable.
A classic example where IoT found traction early is the distribution of liquid goods used as raw materials in production processes or critical operations like hospitals. Without remote monitoring, the supplier has to rely on historical information (which may not be reliable) or frequent personal contact with the end-user. By adding monitoring through an IoT implementation, the tank level can be tracked remotely from a central control center, alerts can be automated, and refills can be organized in time. That is sufficient justification for the project if a “run-out” has significant consequences in risks or costs. Once this system is up and running, the real-time inventory data can also be used for optimizing the distribution organization, planning of production, and rationalizing (often delaying) the need for investments in distribution equipment or production equipment. Although this seems straightforward, it is often difficult for organizations to include these benefits in their decision process – which makes IoT projects look a lot less attractive than they are. In most cases, a significantly larger part of the value-added is delivered by the broader digital transition than by the original point solution that justified it.
Better understanding of the value of data
The success rate of IoT projects is increasing because suppliers and users understand the factors described here better. This rate is also related to the fact that many senior managers in companies now understand the potential of data-driven decisions and digital transformation and direct planning of their IoT projects accordingly. As the costs of IoT keep going down and data becomes more valuable through advances in data processing technologies, the speed of IoT implementation will further accelerate.