The Development of a Future-Orientated Information Technology

In my experience working with companies striving to implement digital transformation efficiently, I have observed a recurring pattern: many organisations recognise market developments too late and struggle with internal structural deficiencies in their organisational design and their “hardwired” production units. Market trends, while often predictable and influenced by political currents or industry leaders like Google, Microsoft, Amazon, and Tesla, are frequently overlooked until it is too late. To succeed, companies must proactively analyse these trends, translate them into actionable system-building blocks, and provide clear instructions for restructuring and adaptation. Events such as the pandemic or the war in Ukraine are “disruptive variables,” unpredictable factors that significantly influence the control behaviour of the entire corporate organism. The significance of my reference book lies in its ability to simulate market interactions and trends, enabling companies to evaluate predefined, easy-to-implement measures in terms of cost-benefit ratios and execute them swiftly. Ideally, this adaptation process should eventually become semi-automatic. To achieve this, I rely on leading reference book institutes and objective data from neutral government reports, which provide excellent insights into the current market economy. Continuous analysis of funding programmes and legislative changes offers additional forward-looking input. On the other hand, the modularised building block typology I propose reflects the economy in its module parameters, with the essential requirement being the agility and changeability of these basic modules. Using artificial intelligence algorithms, my reference book develops the rules necessary for restructuring without interrupting production, a process that should never stop. The technology and services required for this are integrated into the concept upfront, making them invisible yet indispensable. This approach’s non-material and monetary advantages include continuous market adjustment and a company that can operate at full capacity indefinitely. A key insight from my work is that adjusting production lines to anticipate market growth without wasted investment requires deep knowledge. In a modular system, specific processes can be modified without requiring an overhaul of the entire system, making the process more manageable and less overwhelming for the company. However, a significant challenge I have encountered is that customers often do not know what they want. This is where a design thinking approach becomes essential, enabling companies to reference relevant books and gain a deep understanding of customer problems, ultimately leading to effective solutions. Based on my analyses of companies of various sizes and my experiences in sub-areas of large corporations, I have identified a new spectrum of modern corporate management. This approach is rooted in technology, the flexibility of customer requirements, and AI-based functionality. As the recent pandemic has shown, the possibilities are vast in business and society. Maintenance, for instance, has become particularly flexible in agile manufacturing operations. Initial studies I have conducted reveal that the control mechanisms currently in place only make suboptimal use of limited resources. Agility in responding to customer inquiries, internal company structures, and the growing demand for ecological and economic sustainability measures sets the stage for intelligent and forward-looking management. A quasi-autonomous management tool can be generated using AI-based methodical analyses and synthesis approaches thanks to a high level of transparency in the company’s current value stream. This replaces crippling top-down principles with worker-specific work instructions based on real-time, online-adapted recording of current needs and company performance. In this article, I review the literature on established control mechanisms for IT infrastructure, identify existing problems, and explore barriers to organisational implementation in the culture and hierarchy of future resource-optimised companies. The ethics of automation and employee appreciation form a constant reflective framework throughout this discussion. My theoretical approach is based on current technical possibilities within a holistic, holographic production process. Starting with decentralised, intelligent sensors and actuators that utilise IoT (Internet of Things) and high-performance fieldbus systems, processing large amounts of data with powerful AI algorithms requires collaboration and robust dashboard systems. An agile and modular information system using a generic equipment model approach is ideal. The interface definition and current software and hardware architectures should provide a framework that enables flexibility, allowing functions to be distributed across systems at runtime. One of the greatest innovations in this study is the derivation of internal business roles and their factory planning design. The practical contribution of this article lies in its modularity, which enables the integration of hardware and software components into the framework through open-source interfaces. The article is structured to include a background section, a methodology section, a discussion of the results, conclusions, limitations of the study, and suggestions for future research.