SAP Analytics Cloud Experts in Munich

• Providing expertise in management consulting to support the improvement of frontier AI models for a leading AI lab

AI Assistance and Target Vision for Partially Autonomous Energy Portfolio Management

Building an AI control layer directly on the up-to-date daily live portfolio of a large energy provider — not as an isolated pilot, but as an operational extension of the existing DB1 and portfolio management. The goal is the gradual development from assistance through monitoring/alerting to analysis agents with Human-in-the-Loop approvals, supplemented by a role-specific System of Engagement alongside the BI System of Record. At the same time, the business case, target vision and management pitch compared with static monthly reporting are being developed.

• AI control layer: Design and build on the existing live portfolio data product (several million contracts) — development stages assistance → monitoring/alerting → agents with Human-in-the-Loop approvals.
• LLM-supported data analysis: Semantic queries, SQL/tool integration and additional RAG components based on portfolio, plan-versus-actual and data quality data (Azure OpenAI, Snowflake), with drill-downs to individual contract level.
• Analysis agents: Multi-stage agents for variance and driver analyses of churn, price adjustments, volumes and procurement costs.
• Views concept: Role-specific interfaces for business units, management and C-level as a System of Engagement alongside the BI System of Record.
• Business case & pitch: Target vision and cost-benefit argumentation compared with static monthly reporting.
• LLM setup (privacy & security): Coordination with IT Security and Data Protection — EU region, data separation and approval processes.
• Agent architecture: Multi-stage agent pipelines (analysis → validation → summary) with documented data sources, tool calls, review steps and source references for each statement.
• Data foundation: Built on the up-to-date daily DB1 data product (Snowflake, dbt) — portfolio, plan-versus-actual and data quality metrics as the common basis for all AI analyses.
• Guardrails & evaluation: Evaluation and approval processes for LLM responses relating to management-relevant statements — test sets, metrics and human review.
• Prototyping & validation: Iterative validation of agent responses with the business unit — test question catalogue, feedback loops and response quality for each release.
• Roadmap & development stages: Detailed stages from assistance → monitoring/alerting → partially autonomous management, including transition criteria and governance for each stage.
• Integration: Integration into the existing BI and data landscape — BI remains the System of Record, while the AI layer provides interactive drill-down paths as the System of Engagement.
• Enablement: Enablement of business users — prompting guides, training and an operating model for ongoing use.
• Management: Coordination of business units, Data Engineering, IT Security and Data Protection.
• Change Management: Communication and expectation management with business units and management throughout the development stages.

Results:

• Built on an existing up-to-date daily data product with several million contracts
• Established an LLM setup coordinated with Data Protection and IT Security in the EU region, including data separation and approvals
• Defined three development stages through to partially autonomous management
• Designed role-specific views for business units, management and C-level
• Developed the business case and management pitch for the development stages
• Established an iterative response-quality validation process with the business unit
• Designed the operating model for assistance operations and initiated validation

Stack: Azure OpenAI, Azure AI Foundry, Snowflake, dbt, React, TypeScript, Entra ID, RAG, Agentic AI, analysis agents, Human-in-the-Loop, Prompt Engineering, LLM Evaluation, LLMOps, GDPR / EU region, Azure DevOps, Python, SQL, Change Management

• Developed organization, task descriptions, processes and systems of the controlling system to improve activities.
• Harmonized ERP software within the group across IT procurement, plan data, controlling and reporting.
• Designed the basis for an agile and modern IT control system.
• Set up budget plans and supported master data and planning.
• Monitored and validated projects in the PM tool Sciforma, covering OPEX and CAPEX in line with legal requirements and group rules.
• Performed PMO assistance activities including meeting minutes, presentations and reports.
• Tools: SAP FI/CO, SAP MM, SAP PPM, PM-Tool Sciforma, MS Office 365.

• Creation of the profit center report and statistical metrics report
• Gathering and analysis of requirements regarding the forecast for revenue and costs
• Implementation of various time series analyses and optimization of forecasts
• SAP process knowledge, SQL, Python
• Python with various libraries for time series analysis and Machine Learning

Streamline – implementation of S/4 HANA Utilities in cooperation with Accenture

• Consulting and coaching of program management (OPL)

• Planning and support in executing all organizational and system technical activities to migrate from SAP IS-U to SAP S/4 HANA Utilities

• Communication and coordination with involved stakeholders and committees (core team, program management, steering committee)

• Project and process management

• Coaching of the stream leads in the main project

• Requirements management for interface connection of ancillary systems (non-SAP systems)

• Risk management

• Resource and capacity planning

• Consulting the existing migration, test, interface/ancillary system, and training teams

• Consulting on managing the SAP systems cut-over

• Planning and management including necessary post-migration activities (e.g., verification, documentation, adjustments)

• Team coaching & servant leadership: supporting one or more Scrum teams as coach, facilitator, and servant leader

• Promoting self-organization, personal responsibility, and continuous improvement

• Facilitation and continuous improvement of Scrum events (daily, planning, review, retrospective)

• Ensuring adherence to Scrum values, principles, and practices

• Identifying and actively managing impediments to ensure team productivity

• Working with product owners, agile coaches, and leaders to resolve structural hurdles

• Supporting agile scaling in frameworks such as SAFe, LeSS, or Nexus

• Co-designing agile transitions as part of MVV's digital strategy

• Building an agile mindset in the organization through training, workshops, and active role modeling of agile principles

• Collaborating with other Scrum Masters and agile coaches in the company-wide agile chapter

• IT systems: ERP: SAP IS-U, SAP S/4 HANA Utilities

• Building the company with a focus on connectivity for IIoT and Industry 4.0, iRPA/process automation, advanced robotics and smart systems, sensors and services
• Project management and software architecture for IoT gateway development (since 2020) with protocol translation, IT/OT convergence and GRC
• Developing RPA bots for automating and monitoring industrial processes with an agent-based AI approach (since 2020)
• Implementing unsupervised clustering and anomaly detection for time series data in big data streaming pipelines (since 2021)
• Introducing a Docker-based release train for OTA updates with DevSecOps and CI/CD (since 2018)