Strategic target picture
Enterprise capabilities · priorities · governance
CONCEPTUAL BACKGROUND
From isolated digital projects to the intelligent organization
Enterprise transformation is more than the sum of individual digital projects. It requires a strategic target picture, a coherent structure and a roadmap connecting technology, organization and value creation.
01 / ORIGIN
Starting point: the doctoral research proposal
The starting point is the proposal developed in 2022 and revised in 2023, “Strategic Transformation towards the Intelligent Enterprise in the Automotive and Transport Industry”. Its central concern was how technological and organizational domains, often treated separately, could be connected in a holistic and strategically manageable transformation model.
CORE QUESTION
The guiding research question
How can an enterprise’s transition towards an intelligent enterprise be structured strategically, so that relevant domains are identified, connected in a feasible way and translated into transformation through an overarching planning methodology?
02 / THE CHALLENGE
The structural challenge
Individual technologies, platforms and operational methods often evolve from a bottom-up perspective. What can be missing is the overarching top-down view: Which capabilities does the enterprise need? How are the domains interdependent? Which prerequisites, dependencies and sequences determine feasibility?
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Technology & operational initiatives
Platforms · use cases · processes · implementation
03 / RESEARCH LOGIC
An integrative approach in three perspectives
Research & strategic intent
Identify relevant themes, trends, success factors and normative requirements to establish a reasoned transformation target picture.
Technology & market structures
Assess technologies and platforms for how they can consolidate domains and translate them into feasible structures.
Practice & organizational feasibility
Add insights from enterprise practice, critically evaluate them and consolidate the findings into an integrated action model.
04 / ACTION DOMAINS
Core transformation domains
The proposal did not treat intelligent enterprise transformation as an IT or ERP initiative alone. It connected several interdependent perspectives:
Intelligent enterprise systems
ERP, cloud platforms and integrated information, planning and application systems.
Innovation technologies
Including RPA, machine learning, AI and data-driven applications.
Digital business & value-chain processes
Especially logistics and finance as well as end-to-end process chains.
Organization & work design
Operating structures, roles, capabilities, adaptability and human interaction.
Experience & design
Human-centred work and digital interaction as drivers of productivity.
Strategy, steering & metrics
Target systems, transparency, plausibility and assessment of qualitative and economic effects.
Industry-specific scope
The original research scope focused on the automotive and transport industry, particularly passenger cars, trucks and buses, as well as logistics and finance processes. The sector provides a concrete context: value creation, product strategy, supply chains and technological change shape requirements. The model is therefore not a universal blueprint; it must be adapted to each industry and organization.
05 / DESIGN TRANSFER
From model to transformation roadmap
A key intended design outcome was a strategic roadmap. It translates structured domains into connected transformation streams, makes prerequisites and dependencies visible and supports a feasible sequence. Operational methods for individual initiatives are not replaced; they are embedded in an overarching plan.
STRATEGIC INTENT→TRANSFORMATION STREAMS→ROADMAP & DELIVERY→OUTCOMES & LEARNING
06 / LATER CONCEPTUAL DEVELOPMENT
Conceptual evolution
The original question can now be extended with a dynamic perspective: transformation does not end when a platform is implemented or a program is closed. Technologies, markets, products and organizational conditions continue to change. A one-time target model therefore becomes a learning transformation system.
Operational intelligence
Automation of individual tasks and processes through RPA, intelligent workflows, document processing and robotics.
Intelligent enterprise systems
Connected data, integrated platforms and AI capabilities across ERP, finance, production and supply chain.
Intelligent transformation management
AI-supported monitoring, analysis and preparation of portfolio and strategy decisions under human accountability.
Human accountability and AI support
The later development follows a Human-Governed, AI-enabled principle: AI can monitor information, structure evidence, develop scenarios, identify dependencies and prepare recommendations. Strategic decisions, priorities, budgets and binding approvals remain with accountable people and governance bodies.
Transformation Scan: the continuous feedback loop
A complementary concept is the Transformation Scan. It compares strategic objectives and assumptions with new market, technology, product and portfolio information. Deviations and opportunities are surfaced and translated into options and decision briefs. Strategy is not changed automatically; accountable decision-makers assess whether adaptation is required.
07 / STATUS & TRANSPARENCY
Status and research qualification
This presentation connects material from the original proposal with later conceptual developments. It describes a personal working model, not a completed doctorate or an empirically validated or universally tested framework. The original proposal planned theoretical grounding, qualitative practice research and a design-oriented transfer. Additions here – especially the Transformation Scan and AI-enabled orchestration – are identified as later conceptual extensions.
Guiding idea: technology creates possibilities. Sustainable enterprise transformation emerges when those possibilities are connected strategically, organizationally and methodologically.