• Company restructuring and enhancement of shareholder value by optimizing cost structures and streamlining the organizational setup.
• Automation of accounting and controlling through BI applications.
• Setup of a data warehouse and a forecast system with AI support.
• Increase of revenue due to the identification of new market segments.
• Improvement of EBITDA margin by more than 15 percentag points.

• Financial restructuring of a web3 incubation hub by platformizing the investment process and reducing the fixed cost by more than 50%.
• Valuation of a pre-clinical biotech company by creating a top-down market model to support the funding rounds.
• Advisory for a major pharmaceutical company regarding transfer pricing (residual profit-split approach according to OECD guidelines).
• Support of the IFRS impairment test of an MDAX company.
• Financial restructuring of an entertainment company by renegotiating contracts, streamlining finance processes, and supporting the investment rounds (quality and cost improvement of more than 25%).
• Contracted CFO for an AI agent?based marketing platform.

Case Study: Financial & Operational Restructuring of a Mid-Sized Company

Situation

The company was facing imminent insolvency. Revenues were volatile, profitability and reserves were non-existent, and poor organizational structures created a severe management bottleneck. Key statutory deadlines such as VAT filings were repeatedly missed, and the absence of reliable data led to poor planning accuracy and decision paralysis.

Approach

Upon entering as CFO, I conducted a comprehensive status-quo analysis of all cost and revenue positions, prioritizing processes by materiality and business impact. Based on this assessment, I designed and executed a company-wide restructuring and growth plan covering both the cost base and the topline.

?Organizational redesign: Defined new accountability areas, reassigned staff according to strengths, and supplemented missing expertise through targeted hires.

?Personnel costs: Introduced a new workforce planning process rooted in operational efficiency feedback; optimized shift allocation and reduced headcount without increasing workload.

?Supplier contracts: Benchmarked all major suppliers, renegotiated terms, and exited unfavorable agreements where possible.

?Working capital optimization: Reduced inventory levels by 50% via a new ERP system linking stock levels to product turnover and minimum thresholds.

?Shrinkage reduction: Implemented digital tracking of goods outflow to reduce inventory losses.

?Operating expenses: Cut other operating expenses by 40% by renegotiating insurance, license, and rent agreements.

?Controlling & forecasting: Established automated cost-center accounting and a monthly rolling forecast, significantly improving planning accuracy.

?Market expansion: Extended the company?s business model into additional growth markets, strengthening revenue outlook and long-term scalability.

?Marketing efficiency: Reduced marketing expenses by developing a more targeted customer communication strategy.

?Automation & AI integration: Introduced AI-supported planning and procurement processes and automated recurring workflows such as VAT pre-filing and payroll administration.

Outcome

?Fixed costs reduced by ~40% through structural and supplier-side efficiency gains.

?EBITDA margin improved from negative to sustainably positive levels.

?Liquidity stabilized and data-driven management processes established.

?Management and employee workload drastically reduced through streamlined processes and clear accountability structures.

?Enhanced growth perspective through entry into new markets and improved customer acquisition efficiency.

?The company was transformed into a profitable, scalable, and technologically enabled organization with robust governance and sustainable profitability.

Outlook: Sustaining Long-Term Success

?To ensure the long-term sustainability of the restructuring results, I implemented several cultural and structural initiatives aimed at continuous improvement, employee engagement, and leadership excellence:

?Continuous Improvement Culture: Every employee participates in a short monthly stand-up meeting to share observed inefficiencies or process bottlenecks within their area of responsibility. These insights form the basis for targeted improvement measures, creating a self-reinforcing learning loop.

?Highest Performing Team Program: Regular assessments are conducted to ensure each employee is satisfied with their current responsibilities and that tasks are allocated to those best suited to execute them. This strengthens ownership, performance, and engagement.

?Leadership Culture: Senior management regularly joins operational teams in their day-to-day work to demonstrate appreciation and respect for all roles within the organization. This initiative bridges hierarchy gaps and fosters a collaborative spirit.

?Incentive Structures: A new incentive framework was introduced allowing employees who identify or help create new revenue streams to receive a one-time participation bonus linked to the resulting sales. This program rewards entrepreneurial behavior and aligns individual motivation with company growth.

A data-driven framework for investors and founders in life sciences

An early-stage biotech venture with three drug candidates in pre-clinical and Phase 1 stages sought a robust valuation to determine whether to continue with another equity financing round. The company had no market revenues yet and a high R&D burn rate. The investor required an evidence-based view of the economic potential of the assets, despite substantial clinical and regulatory uncertainty.
Determine the probability-adjusted enterprise value (rNPV) of the pipeline and calculate sensitivity-based scenarios to support an informed investment decision.

The valuation framework applies a sophisticated top-down epidemiological and economic modelling approach commonly used in life-science finance:
? Population growth projections and demographic breakdown by region and country.
? Estimation of incidence, prevalence and suitability rates to derive the addressable patient population.
? Application of phase-specific success probabilities (PoS) for each development stage.
? Pricing and revenue forecasting per treatment and per geography based on product life-cycle-curves.
? Cost modelling for manufacturing, fixed and SG&A costs.
? Risk-adjusted discounted cash flow (rNPV) to estimate the asset value.
? Calculate assuming a deterministic environment.

Using available market benchmarks and probability-of-success (PoS) data from established sources to generate asset values for three anonymized candidates:

Total pipeline indicative value (rNPV): approx. ?250?675 million.

Sensitivity analysis quantified how significantly the improvements in success probability due to passing milestones can increase the enterprise value.

? Unique integration of epidemiological modelling and corporate finance logic.
? Applicable to venture valuation, early-stage M&A, or grant applications.
? Fully transparent Excel-based model with modular structure and sensitivity analysis.
? Enables data-driven investment decisions in high-risk biotech environments.

The framework bridges the gap between medical uncertainty and financial valuation, providing investors, founders and corporate decision-makers with a clear, quantitative understanding of potential market value. It allows a realistic discussion about funding requirements, dilution, and exit potential ? even in early clinical stages.

The valuation approached based on a top-down market assessment is transferable to other business sectors or used to evaluate a go-to-market decision for various products.

Case Study: Digitalization and Optimization of a Finance Department

Situation

The finance department of a mid-sized subsidiary faced significant structural and process inefficiencies across its core controlling functions ? monthly closing, management reporting, and rolling forecasts. The monthly closing took two days longer than management?s target, generating extreme workload and stress within the controlling team. After each reporting cycle, employees needed several recovery days, leaving no capacity for continuous improvement. Management reporting was highly manual, time-consuming, and prone to errors due to numerous intermediate Excel steps. Reports lacked the data granularity and flexibility that management required for ad hoc analysis. The rolling forecast process was one-dimensional, derived top-down, lacked detail at product or business-unit level, and provided limited predictive accuracy.

Approach

As CFO, I initiated a comprehensive finance transformation program focused on digitalizing and optimizing the department?s key controlling processes ? Fast Close, Management Reporting, and Rolling Forecast.

1. Fast Close Optimization

? Conducted a full analysis of data flows across subsidiaries.

? Defined the minimum viable level of data granularity required for monthly consolidation.

? Standardized data transfer through unified templates linked directly to local ERP systems.

? Streamlined data collection so that all entities delivered identical, structured datasets every month.

? Implemented an automated consolidation model at corporate level to minimize manual workload and human error.

? Introduced automation tools (Macros, UIPath) to accelerate repetitive tasks.

? Result: Reduced month-end closing cycle from five to three days, significantly lowering stress levels and error rates.

2. Management Reporting Digitalization

? Developed a standardized data model across subsidiaries, ensuring consistent structure and reporting logic.

? Leveraged BI tools (Power BI, Power Query) to integrate large data volumes into a multidimensional data cube.

? Built an interactive management dashboard allowing both standard report views and dynamic drill-downs for ad hoc analysis.

? Increased efficiency and decision quality by enabling faster, data-driven insights with fewer resources.

? Result: Higher reporting accuracy, improved management visibility, and reduced reporting time by more than 50%.

3. Rolling Forecast & Budgeting Transformation

? Implemented a new BI-based planning tool built on data cube and matrix logic.

? Reconstructed the company?s revenue model within the system and defined structured input tables automatically fed with income statement (IS) data.

? The model consolidates data into a unified cube and generates multiple forecast scenarios ? including base, upside, downside, and shock cases ? based on predefined growth and risk assumptions.

? Each scenario can be sliced and analyzed dynamically via interactive dashboards.

? The main challenge was to translate the complex business model into system logic and create an efficient monthly data integration workflow to ensure the model could be updated rapidly.

? Result: A fully automated forecasting environment with flexible scenario modeling, reduced forecast cycle times, and higher predictive accuracy.

Outcome

? Monthly closing time reduced from five to three days.

? Reporting accuracy and transparency significantly increased.

? Employee workload and stress levels drastically decreased, enabling continuous improvement initiatives.

? Management gained real-time access to financial and operational KPIs through interactive dashboards.

? The finance function transitioned from a manual, reactive reporting unit to a digitally enabled, data-driven business partner that supports strategic decision-making and scalable growth.

• Automation of the monthly accounting and reporting processes (?fast close?) through vba driven excel modelling.
• Digitalization and restructuring of the planning and budgeting process by implementing a software solution that allows multidimensional data cubes.
• Transformation of the static management reporting into a BI driven process.

• Lead advisory in the acquisition and integration of a leading animal health company (deal value approx. EUR 11 bn).
• Tax-purchase price allocation (PPA) and S-1 valuation report for a chemicals company with a deal value of approx. EUR 200m.
• Valuation of a chemicals company with a deal value of approx. EUR 800m.
• Buy-side financial due diligence in the industrial segment with a deal value of approx. EUR 50m.
• Trainee program in ?Transaction Due Diligence?, ?Valuation, Business Modelling & Economics?, ?Commercial Advisory?, and ?Audit?.