Latest predictions foresee 20 to 40 billion connected devices deployed by 2020. About 40% of these new sensors are expected to be installed in an industrial context.
A often overlooked consequence of this growth in connected devices is the necessity of 5 million new software applications to make sense of the newly collected data. This is a lot of new software and apps which will be required and need to be developed to manage this multitude of data.
When approaching Industrial Internet of Things (IIoT), it is a common trend for companies to set their development focus on sensors and devices, however the actual challenge is achieving sustainable value adding at the application level. Hence, achievement of successful IIoT application require a mindset switch that can be achieved through a simple two-stepped approach.
Sensors are becoming cheaper and cheaper, and are basically easy to integrate in products from a design perspective. However, large sensors installed bases that pump huge datasets into the cloud make no sense without a clear underlying application that is able to make value adding sense of this data.
Value adding IIoT applications are uniquely characterized by the ability of autonomously trigger actions or decisions, without the need of user intervention. However, under many circumstances, the development of IIoT solutions start from the question "where and how can we collect data?" rather than a more application centered approach: "we have a clear business challenge, what data should we collect to address it?".
This is exactly the stage at which most of the companies embracing IIoT struggle in articulating its benefits. The real challenge is developing the applications and real business cases which actually make sense of the data, and only in a second step design the systems required to measure and collect the value adding piece of information required.
The correct approach for IIoT is to begin with a real problem, and understand what data and information is necessary to address it. In a later phase, start think about what sensors are necessary. Through this approach, IIoT solutions end up being less complex, more manageable and require less sensors to achieve the desired value adding.
IIoT applications need to be contextualized and become solutions to real problems. When real problems are identified, it becomes easier to collect and make sense of the necessary data, but it also become possible to define measurable metrics to estimate the benefits and build a business case.
IIoT applications are a complex balance between technology, processes and people. They are subject to a great extent of uncertainty, and unpredictability. Hence, they require a development approach dominated by agility.
When a target problem is clearly defined, the next step is to create a pilot to validate the business case and the Return-on-Investment (ROI). Right now there is practically no historical data or calculation models to estimate a priori the costs and precisely describe the financial benefits of IIoT. There are some examples of successful deployments, which however lack of publicly available financial reports and metrics. This means you will have to prove the added value of your IIoT application and approximate its related costs by creating a pilot project. The main goal of a pilot is not only to reduce business risk and minimize the upfront investment, but also to obtain insights in required technologies, partners and suppliers your organization needs to collaborate with to achieve a successful implementation. In this context, a pilot project represents an actual implementation of the working application with real customers, albeit on a limited scale and complexity, therefore achievable with an effort of few weeks.
To conclude, the development of more manageable, less complex and value adding IIoT applications is obtained by first focusing on real business challenges and second, by validating the related business case by means of a pilot project, where the complexity is reduced to the bare minimum, and the project is verified with lead users.