German companies making slow progress with IIoT

Data-based decisions and more agile production processes are two key benefits offered by the Industrial Internet of Things (IIoT). It enables companies to better respond to risks and unforeseen problems in their supply and value chains. But despite these undisputed benefits of IIoT, the implementation of IIoT projects in German industrial companies is stagnating. This is the conclusion of a recent study by IDC.

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Less than one-third with IIoT projects

According to the study, 29% of the companies surveyed have actively implemented IIoT projects to date. It is true that a large proportion of companies are definitely concerned with the Industrial Internet of Things and, according to their own statements, are in the research (20%), evaluation (30%) or planning (20%) phase. However, the step to action and actual implementation is obviously difficult for them.

One possible cause is the overall economic situation, which has been characterized by disrupted supply chains, high freight costs and rising energy prices over the past two years. The war in Ukraine adds to the uncertainty for companies. Accordingly, companies’ current focus is primarily on increasing profits and reducing costs (40%), increasing productivity (38%), and improving customer loyalty (29%). On the operational side, the focus is on reducing downtime (29%), lowering resource and energy costs (28%), and reducing scrap rates (26%).

Actually, it is the IIoT and a data-driven corporate culture that would create ideal conditions for effectively countering the uncertainties and short-term changes of the recent past and responding to them with new data-based products, services and business models. The low level of IIoT implementation is thus having a particularly detrimental effect on German companies in the current times.

Successes are measured too rarely

Among the companies that are using the Industrial Internet of Things, there is room for improvement in measuring success. Only a third of them are currently checking whether the benefits hoped for from the IIoT are actually being achieved. And only 13% of German industrial companies are pursuing a holistic data and analytics strategy that integrates all projects and data.

Such a strategy is an important prerequisite for the success of IIoT and the general success of the digital transformation. The biggest obstacles with regard to analytics and supporting technologies such as artificial intelligence or machine learning are high costs and lack of budget (30%), security and compliance (24%), and the lack of integration of data sources and data growth (20% each).

Ecosystems gain importance

Respondents to the IDC study see great potential in industry-wide or even cross-industry mergers of industrial companies in the sense of ecosystems. 75% say they are already part of such an ecosystem. Fast innovations (31%), new sales potential (29%), and the higher quality and safety of their own products (16%) play a particularly important role as arguments.

IDC expects that by 2026, almost one-third of all revenues of the largest companies worldwide will result from shared data, applications, and operational initiatives within such ecosystems. Prerequisites for successful data-based collaboration across corporate boundaries are flawless data management, protection of intellectual property, and control over data and data access.

Conclusion: Room for improvement with IIoT

When it comes to using the Industrial Internet of Things, German industrial companies still have considerable room for improvement. There are few pioneers, but there are many stragglers who have not yet decisively advanced the topic. The IIoT application scenarios that have been realized are geared more to optimizing the status quo than to transforming traditional processes and business models. The application of IIoT is an important step for industrial companies to remain relevant in their industry as well as to pursue data-based business models and operate agile value creation in ecosystems. The task is to expand existing approaches and place them in the context of a holistic digitization and data strategy.