Industry 4.0 is in the spotlight. And rightly so. The possibilities are great: higher productivity, a better customer experience, lower costs and perhaps a new business strategy with innovative products and services. And there is an outright need: without Industry 4.0 a company has a limited future.
Unfortunately, many implementations get stuck. Let’s find out why this happens and how to prevent it happening to you.
There can be three issues with data: not good, not available, poor quality. This is often due to IT systems not being set up properly, data not being entered or being entered incorrectly, log switches to register log data not being set correctly, or the data entered being of poor quality.
In addition, the knowledge of business processes is seldom up to standard. How do processes behave in daily practice? How should they run? This means that people are unclear as to which data should be captured and how the data should be managed.
It is therefore important to know the business processes and how they work both in theory and in practice. This is the basis for a good KPI and reporting structure. Getting this right will ensure clarity around which data must be collected, which information is required for whom at what time and how to manage the processes for maximum effect. It will also mean that data availability and quality will increase – thus building the foundation for Industry 4.0.
Many companies still have a strong departmental orientation instead of an end-to-end process focus. This leads to limited insight into and understanding of the interdependencies between functions and departments. A strong departmental orientation also means that data is locked up in silos.
Industry 4.0 focuses on the integrated control of the end-to-end processes that run through various departments and even across company boundaries. That is why departments are asked to work together seamlessly and to share data and information. An effective IT infrastructure facilitates this.
Capabilities to collect and use data
The introduction of Industry 4.0 requires a significantly higher level of knowledge of the industry, of business processes and of analysis applications. At every level in the company and within every position, people must be able to handle data well and be skilled in its analysis.
The technical structure of these cyber-physical systems is becoming more complex, and more and more decisions are being made by algorithms. Therefore, it is important that companies develop the knowledge and skills to build applications and assess the behaviour of algorithms and the insights they provide. The introduction of Industry 4.0 requires intensive collaboration between departments and disciplines to develop people and resources at pace.
Vision and organisational alignment
The introduction of Industry 4.0 affects all aspects of an operating model. The top team needs a shared vision about the value that is required for various stakeholders, and how that value is delivered – the operating model.
Too often, a joint vision is ill-considered and not adequately thought through, resulting in insufficient alignment with the roadmap. In such a situation, an implementation inevitably comes to a standstill.
The human factor
The biggest challenge in an Industry 4.0 implementation is not so much choosing the right technology, but dealing with the absence of a data-based and digital performance culture and the corresponding skills gap in the organisation. Investing in the right technologies is important – but success or failure ultimately does not depend on specific sensors, algorithms or analysis programs. The crux lies in a wide range of people-oriented factors.
Since Industry 4.0 transcends not only internal departments but also the boundaries of the company, its success is predominantly dependent on skilful change management.
In essence, the issues with the introduction of Industry 4.0 are no different than with other company-wide transformations whose aim is to create a sustainably high-performing organisation. It will not surprise you that the chance of failure is roughly the same: 70%.
Therefore, in the first instance, do not focus too much on just the technical side of the transformation. Instead, concentrate on skilful change management. The technological content side of the transformation is not your main problem. The development of a data-based and digital performance culture and the corresponding skills set is.