For many companies, the benefits, the possibilities and the added value, but also the changes that IoT, Augmented Reality, Data Analytics or Machine Learning offer, are at the top of the to-do list. However, in order for these to be used to best effect, they must be aligned with the company’s objectives and therefore be integrated into its overall strategy.
Today, companies can no longer avoid digital transformation, no matter to which industry they belong. It provides companies with tools, information and opportunities to optimize their processes, operate their machines more efficiently, tap new revenue streams, succeed with creative business models and continuously inspire their customers with added value. Smarter applications, processes and devices sustainably reduce costs, ensure that delivery deadlines are met, minimize unexpected failures, increase overall equipment efficiency, generate innovative service offerings, guarantee higher product quality and enable a shortened time-to-market.
Internet of Things solutions bring many competitive advantages to B2B or B2C markets and form the basis for the use of other technologies and methods. Industrial companies, for example, use IoT to implement a multitude of applications, such as remote monitoring and service or predictive maintenance, and to generate added value for themselves and their customers through innovative services.
New dimension of business innovation
IoT’s sole goal is to connect products, i.e. to equip devices and apparatus with additional sensors and software, and to connect them with the Internet using a connectivity module or a gateway. The data is then transmitted via different paths and collected centrally in a cloud. The decisive success factor here is how the data obtained with IoT is used. For this reason, the Internet of Things must be integrated into an overall digital strategy, with concrete goals from the outset, and be interdisciplinary in its approach.
It’s not just about connecting things. The intelligent connection of devices is only a means to an end. The aim must be to digitise existing processes in order to achieve quantum leaps in operational excellence and, in this way, to create and feed the data platform that will later pave the way for further services based on data science. Artificial intelligence methods such as machine learning help to open up new dimensions of business innovation to users with the existing and now continuously acquired data. Unprecedented insights and undreamt-of possibilities will follow, from the creation of transparency to the automation of decisions the unfolding of new business models.
A few examples:
- By connecting its parking meters to the Internet, Taxomex, the leading manufacturer of parking meters in Switzerland, obtains real-time information on the occupancy of parking spaces and the system status of its products, thereby significantly increasing both efficiency and transparency. The data is aggregated at a central location and can be accessed and managed at any time via the specially developed web portal.
- The development of an algorithm has enabled KSB, the manufacturer of pumps and valves, to monitor the condition and operating data of machines operating worldwide via a central web portal. An app provides pump operators with information at any time on whether a pump is running economically or with excessive energy consumption. While KSB can use the data for its customer service and the optimisation of its products, customers receive important information for resource planning and billing.
- On the basis of HoloLens, TK Elevator has developed a digitised sales process including 3D visualization and measurement directly on site at the end customer, thereby increasing efficiency and revolutionizing the customer experience. By linking the various interfaces such as mixed reality glasses, an app and the cloud, TK Elevator not only offers its customers a unique experience, but also shortens its own delivery time by a factor of four.
- With the help of digital services, Jungheinrich, the manufacturer of industrial trucks, is optimizing its repair processes and thus increasing its efficiency many times over. Technicians are supported by a mixed reality solution in the repair of machines and plants and are guided step-by-step through the entire process.
An overall concept is a prerequisite
It has long been clear to many of today’s companies that IoT is indispensable. But just like any other digitisation technology – be it Mixed Reality, Digital Twins or Machine Learning – IoT can only unfold its full potential if it is not an isolated solution, but part of an overall concept that demands a novel, hybrid IT architecture.
This does not mean, of course, that companies should not start with IoT on a small scale. Implementation can start with a small sub-project that is particularly easy to implement or brings a lot of benefits for little effort (low hanging fruits). This project would then need to be validated and, on the basis of initial experience, a functioning overall system could be developed step by step. It has been proven that the technology aspect is never the challenge. Often IoT projects do not go beyond the prototype status because concrete user scenarios are missing or a return on investment cannot be calculated in the first few years, let alone realized.
Added value only through connectivity
The value chain of an IoT solution consists of different technological elements, which are only partially comparable with regard to their conception or the required capabilities and costs, but can only become fully effective when combined. A promising approach would be to meticulously examine the needs, derive a sustainable architecture and then go on to realize the individual capabilities. The fact that these are multi-year projects in the low seven-figure range should also be considered.
What is important here is that for IoT to be successful, it must be part of a solution that satisfies a genuine customer need and is economically viable. Thus, consideration of the monetization of the solution is an important aspect of every IoT project and can lead to failure if neglected. In order to check the acceptance of the ideas as early as possible, the involvement of a limited user group, which is continuously surveyed and thus involved in the development of the services, has proven to be helpful. A prominent example is the Microsoft “Technology Adoption Program”, in which selected customers and suppliers use the software from the development stage onwards and regularly return feedback. This knowledge and experience can then be used as a competitive advantage in the market.
In order to exploit the full potential of the Internet of Things, it is therefore crucial to keep an eye on the big picture and not just focus on the technical aspects. In the same way, profitability must be evaluated at the outset and customer requirements and needs taken into account. On this basis, the further steps of use case driven projects can then be developed. In this way, bit by bit, a connected world can be created that generates real added value not only for the company itself, but also for its customers.
Peter Güntzer has many years of implementation experience in the field of connected products. Prior to joining Zühlke, he was technical project manager at Siemens cellular phones and for 14 years cofounder/CTO of a development and product provider for IoT, telematics & smart connected devices. His passion and responsibility at Zühlke lies in the successful combination of innovative technology with strategic and entrepreneurial goals, combined with a sense for what is technically feasible. Outside Zühlke, Mr Güntzer is involved pro bono in solar energy projects in Africa, both from Germany and locally.