Industrial enterprises
Operations-heavy organizations with complex assets, sites, workflows, and legacy system realities.
Felix Schüßler
Düsseldorf, Germany
Enterprise Transformation Advisor
I help industrial enterprises operationalize AI through scalable processes, data foundations, and execution systems.
For senior leaders navigating the messy middle between strategy, operations, IT, governance, and adoption in enterprise-scale transformation.
Current focus
Trusted advisory and execution leadership for enterprise digital and AI transformation.
€4M
annual digital portfolio owned end to end
1,500+
turbines supported across global offshore operations
45
specialists orchestrated across international teams
18
global wind farms with data foundations established
Led digital portfolios across international offshore operations
€4M+ portfolio responsibility
1,500+ operational assets supported
45+ specialists coordinated
Enterprise product and operating model leadership
Positioning
Enterprise AI only creates value when the operating system can absorb it.
I help senior teams move from strategic digital and AI ambition to execution systems that work inside operational reality. The work starts with process clarity, aligns the data foundations behind it, and then turns the right digital and AI-enabled capabilities into governed, adopted workflows.
The sweet spot is high-stakes, cross-functional transformation: executives need strategic coherence, operations need practical workflows, IT needs architectural discipline, and users need tools that reduce friction. My role is to hold those demands together and create the rhythm that gets from alignment to impact.
Who I work with
Built for operationally complex enterprise environments.
Transformation leaders
CIO, COO-1/2, SVP Digital, VP Transformation, and Operations Excellence leaders moving from strategy to execution.
AI operationalization agendas
Organizations that need AI to become part of governed operational workflows, not another pilot portfolio.
Transformation narrative
From fragmented operations to an AI-ready execution rhythm.
Executive buyers need to see a path, not another promise. This is the conversion story: make the operating reality visible, turn it into a blueprint, ship capability, and keep learning.
01 · Before
Fragmented operating reality
Processes sit across teams, tools, legacy systems, and local workarounds. AI ideas stay abstract because the operating system is unclear.
Manual handoversUnclear ownershipDisconnected tools
02 · Focus
Executable transformation blueprint
The business problem is translated into process design, data needs, value pools, governance, and delivery workstreams.
Prioritized roadmapData foundation pathUser journeys
03 · Delivery
Shipped digital capability
Cross-functional teams ship integrated workflow products, automation, and decision support that fit real operational routines.
Fast incrementsAdoption rhythmValue tracking
04 · After
Learning operating system
Usage feedback, performance data, and new AI opportunities feed the next iteration instead of becoming a one-off project.
Feedback loopsReusable data layersScaled practices
Services
Three outcomes that make AI transformation operational.
The work deliberately starts before tooling and continues beyond launch, because lasting digital change needs the whole path.
Align the agenda
Executive Advisory
For leaders who need clarity on AI transformation priorities, operating model implications, portfolio focus, and business-IT alignment.
- Executive transformation narrative and decision logic
- Prioritized value pools and portfolio choices
- Governance model for senior business and IT stakeholders
Design the system
Transformation Blueprinting
For operations-heavy organizations that need process, data, governance, and AI readiness translated into an executable transformation architecture.
- Operating model and process blueprint
- Data foundation and AI-readiness workstreams
- Roadmap that connects strategy, systems, users, and value
Operationalize change
Execution Leadership
For transformation programs that need cross-functional delivery leadership, rollout orchestration, adoption management, and measurable operating impact.
- Delivery rhythm across business, IT, vendors, and users
- Integrated digital and AI-enabled capabilities shipped into operations
- Adoption, feedback loops, and value realization governance
Process blueprint
01
Value pools
02
Workflow
03
Decision rights
04
Adoption
Data readiness map
01
Sources
02
Quality
03
Ownership
04
AI use cases
Execution loop
01
MVP
02
Rollout
03
Feedback
04
Scale
Digital Operating System
Processes, data, AI products, and users should reinforce each other.
The point is not another standalone tool. The point is an integrated operating system: each layer produces the conditions the next layer needs, and user feedback restarts the loop.
Layer 01
Processes
Layer 02
Data Landscape
Layer 03
Digital & AI Products
Layer 04
Users & Customers
Strategy-to-execution loop
Select a layer to inspect inputs and outputs
Operating model
Processes
Start with how work should flow: roles, decisions, exceptions, incentives, and adoption moments.
Inputs
- Value pools
- Operational pain points
Outputs
- Workflow design
- Decision rights
User feedback and performance data cycle back into process improvement, so the system keeps learning instead of ending at launch.
Ecosystem over isolated tools
Digital and AI products should work as connected layers across processes, systems, and teams.
Business and IT in one rhythm
Executives, operators, data owners, IT, and delivery teams need shared priorities and fast decisions.
Ship quickly, learn deliberately
Launch useful increments early, measure adoption, and iterate toward durable operational change.
Low-code fluency, enterprise discipline
Move fast with pragmatic tools while keeping data, governance, security, and scale in view.
Enterprise proof
Battle-tested transformation work, described without inflated claims.
Compact examples of the operating environments, challenges, interventions, and outcomes behind the public proof points.
AI-ready planning suite for offshore operations
Legacy SAP integrationGlobal field-team workflowsAI-ready planning foundation
Context
International offshore operations with complex planning workflows, legacy SAP PM/MM integration needs, and globally distributed field teams.
Challenge
Operational planning was spread across fragmented data sources and local workflows, making it difficult to scale consistency across sites.
Intervention
Designed an AI-ready planning suite concept, created smart workflow layers, aligned legacy system integration needs, and coordinated execution across business and technical specialists.
Outcome
Established a proprietary operational workflow layer that improved planning usability, connected fragmented data, and created a foundation for decision-support use cases.
Digital operating model for product-led transformation
Product-led operating modelPortfolio governanceExecutive stakeholder alignment
Context
Enterprise offshore product landscape moving from legacy IT projects toward a higher-velocity product-led operating model.
Challenge
Digital initiatives lacked a unified operating rhythm, making prioritization, delivery ownership, and adoption harder to scale.
Intervention
Defined the digital ecosystem vision, introduced value-based prioritization, structured delivery workstreams, and clarified business-IT governance.
Outcome
Shifted transformation execution toward a product-led model with clearer ownership, faster decisions, and stronger connection to operational value.
Operational data foundations across global wind farms
18 wind farmsReusable data foundationsLLM knowledge retrieval enablement
Context
Global offshore portfolio expansion across international markets with inconsistent operational data structures and reporting needs.
Challenge
AI and decision-support use cases were constrained by fragmented operational data and inconsistent cross-site foundations.
Intervention
Structured data-foundation workstreams, aligned operational data needs with process design, and coordinated global stakeholders around reusable foundations.
Outcome
Established data foundations across 18 global wind farms, enabling stronger operational consistency and future AI-enabled knowledge retrieval use cases.
Scaled adoption of operational digital tools
1,000+ usersGoverned low-code rolloutOperational workflow adoption
Context
Enterprise-scale operational teams needing faster tooling, stronger governance, and practical digital workflows.
Challenge
Digital tools risked becoming local productivity experiments rather than governed operational capabilities adopted at scale.
Intervention
Introduced and scaled low-code operational tooling, embedded governance, supported user rollout, and connected tools to operational workflows.
Outcome
Scaled digital operational tools to 1,000+ users, improving workflow consistency and creating a pragmatic path from local need to enterprise adoption.
Perspective
Clear views on why enterprise AI succeeds or stalls.
Short executive viewpoints that signal how I think about the operating layer beneath digital and AI transformation.
AI transformation is mostly an operating model problem.
Models rarely fail in isolation. They fail when processes, ownership, data quality, governance, and adoption are not ready for them.
Process clarity should come before automation.
Automating unclear work usually hardens ambiguity. The better sequence is process intent, data foundation, product layer, then iteration.
Business and IT alignment breaks at the execution layer.
Strategy decks often align; delivery systems often do not. Transformation needs shared prioritization, decision rights, and value tracking.
Industrial adoption is earned in the workflow.
Operational users adopt tools when the product reduces friction in real work, respects constraints, and improves with their feedback.
AI use cases need reusable foundations, not isolated pilots.
The enterprise value comes when process knowledge, operational data, and delivery patterns become repeatable across sites and functions.
Proof
Enterprise scale, startup speed, and product-led execution.
The numbers are public-safe CV-level proof points, shown without implying client endorsement.
Portfolio control
€4M
annual digital portfolio
Scope
End-to-end ownership
Mechanism
Value-based prioritization
Signal
P&L impact tracking
Value-based prioritization, delivery governance, and P&L impact tracking.
Global rollout footprint
18
wind farms
Context
International offshore sites
Challenge
Fragmented legacy landscape
Outcome
Shared data foundations
Operational data foundations across international offshore sites.
Adoption at scale
1,000+
users reached
Audience
Operational users
Method
Enablement and feedback loops
Result
Scaled workflow adoption
Scaled tools and workflows with governance, enablement, and user engagement.
Executive collaboration
Partnered with VP/ELT stakeholders and senior operating leaders on digital and AI-readiness strategy.
Enterprise coordination
Orchestrated specialists across global backgrounds, business teams, IT, vendors, and operational users.
Transformation scope
Worked across multi-site environments, portfolio governance, operating model design, rollout, and adoption.
Experience
Built across energy, retail, logistics, aviation, and startups.
2019-present
RWE Offshore Wind & RWE Renewables
Senior Director, Head of Digital Product Management Offshore
Led enterprise operational digital transformation initiatives across international offshore operations, aligning process design, operational data foundations, portfolio governance, and cross-functional execution.
2018-2019
OBI Group Holding
Product Owner App & Microservice Platform
Contributed to app and microservice platform development while leading an internal startup team focused on reducing delivery friction, cost, and time to market.
2017
DHL
Innovation Project Manager & Startup Coach
Led enterprise innovation initiatives and coached international internal startup teams, translating ambiguous technology opportunities into executable business concepts.
2015-2017
locaneo.com
Co-Founder & CTO/CPO
Built a funded zero-to-one venture, owning product direction, customer discovery, technology choices, and operating model under high ambiguity.
How I work
Personal enough to engage users, structured enough to move an enterprise.
Start with the operating problem
I push for clarity on process, value, ownership, and adoption before the solution shape becomes fixed.
Build momentum without losing discipline
I like fast increments, but with enough governance, data thinking, and stakeholder alignment to survive scale.
Keep users close
Transformation only sticks when users see their reality in the design and feedback changes the product.
Protect enterprise coherence
I am not a software engineer or architect; I make sure the right technical experts can deliver inside a coherent business system.
Typical challenges
When the strategy is right, but the operating system cannot absorb it yet.
AI strategy not translating into operational workflows
Fragmented process landscape across sites or functions
Business and IT alignment breaking during execution
Low adoption of digital tools after launch
Disconnected operational systems and data sources
Delivery activity without measurable operational impact
Executive sparring and strategy translation
Roadmap and portfolio structuring
Product-led execution leadership
AI-readiness and data foundation workstreams
User adoption, rollout, and value realization
Discuss the transformation behind the roadmap.
If your organization has an AI, digital, or operating model agenda that is stuck between executive ambition, legacy systems, and operational adoption, I can help turn it into a credible execution path.
Start here
Start an executive conversation.
Send a short note about the transformation challenge, operating context, and leadership agenda. I will respond with a focused next step.
Discuss transformation challengeDüsseldorf, Germany · felix.schuessler@rwth-aachen.de