By Sebastian Spicker, Managing Director DACH at IFS
Many companies have invested heavily in digitalisation in recent years. While new platforms and AI solutions promise enormous potential in terms of productivity, efficiency and flexibility, quite a few companies are still groping in the dark. And why? Because they have long since lost track of their assets, processes and data – and with it the basis for sustainable, successful digitalisation. The result is strategic flying blind, which only increases the gap between them and their competitors.
This dilemma is particularly evident in manufacturing. Those who do not know when machines will break down, which spare parts are available and when, or how supply chains interact, will always act reactively rather than proactively. Predictive maintenance has long been the buzzword, but pure predictions from isolated systems alone are no longer sufficient. Competitive efficiency only arises when companies can actively calculate the best maintenance window – including factors such as capacity utilisation, weather, and technician availability. Those who have this information achieve less downtime and a real boost in productivity. Scenarios like these are no longer a dream of the future, but everyday practice. Provided that the data basis is correct and systems can communicate with each other.
A similar picture emerges in field service management. Many companies and service providers now plan their field service assignments with AI support. But planning only becomes truly intelligent when it is linked to asset management systems. This is the only way to incorporate all relevant information, from maintenance schedules and spare parts to the individual technical requirements of staff. Without this transparency, even the latest AI solution remains a blunt tool.
To achieve this, fundamental expectations of AI and technology must change. After all, they alone cannot solve all the issues currently facing business and industry. They are powerful and effective, no question. But only if companies have the courage to rethink their processes and have the necessary data at their disposal. Of course, this sounds like a mammoth task. But the alternative is more dangerous: those who cling to old processes lose not only efficiency but also competitiveness. Markets are setting new requirements in ever shorter cycles, and technologies are developing faster than many decision-makers can act.
So what can be done? First, companies must create transparency about assets and data flows and take a holistic digital view of processes. Secondly, they must rely on practical AI solutions that have been tested in specific industries instead of getting lost in the variety of standard software. Thirdly, managers should develop an AI-first mindset and involve their employees in the transformation. Only those who understand the added value that technology offers will accept and use it.
Ultimately, it is not a matter of blindly purchasing technologies and somehow integrating them into one’s own IT landscape, but rather of first turning on the light in one’s own systems. Those who succeed in doing so will gain clarity, efficiency and room for manoeuvre. All others will remain in the dark, for better or worse, and risk being overtaken by the competition.
