Flying blind is not a strategy

In recent years, many companies have invested heavily in their digitalization. While new platforms and AI solutions promise enormous potential in terms of productivity, efficiency, and flexibility, many businesses are still in the dark. Why? Because they have long lost track of their assets, processes, and data—and thus the foundation for sustainable successful digitalization. The consequence is a strategic blind flight that only increases the gap with competitors.

This dilemma is particularly evident in manufacturing. Those who do not know when machines will fail, which spare parts are available when, or how supply chains interact, always act reactively instead of proactively. Predictive maintenance was long the buzzword, but now mere predictions from isolated systems are hardly enough. Competitive efficiency only arises when companies can actively calculate the best maintenance window—including factors such as workload, weather, or technician availability. Those who possess this information achieve less downtime and a real boost in productivity. Scenarios like these are no longer a thing of the future but a lived practice. Provided 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 today plan their field service operations with AI support. But planning only becomes truly intelligent when it is connected to asset management systems. Only then do all relevant information flow in, from the maintenance plan to spare parts to the individual technical requirements of the personnel. Without this transparency, even the latest AI solution remains a blunt tool.

First and foremost, the fundamental expectation of AI and technology must change. Because they alone do not solve all the questions that currently occupy the economy 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 basis. Of course, this sounds like a mammoth task. But the alternative is more dangerous: Those who stick to old processes not only lose efficiency but also competitiveness. Markets set new requirements in ever shorter cycles, technologies develop faster than many decision-makers act.

So what to do? First: Companies must create transparency over assets and data flows and view processes holistically digitally. Second: They must rely on practical AI solutions that are industry-specific tested, instead of getting lost in the variety of standard software. Third: Leaders should develop an AI-first mindset and involve their employees in the transformation. Only those who understand the added value technology offers will accept and use it.

In the end, it's not about blindly buying technologies and somehow nailing them to your own IT landscape, but first turning on the light in your own systems. Those who succeed gain clarity, efficiency, and room for maneuver. All others remain in the dark—willingly or not—and risk being overtaken by the competition.