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Lukas Reese

Sr. Power BI Developer

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About Lukas

Lukas began his career in data analysis, specializing in transforming complex data into actionable business insights. As a Senior Data Analyst focusing on Power BI, he has consistently demonstrated his ability to simplify intricate datasets into clear, strategic intelligence that drives critical business decisions. He was pivotal in managing projects that significantly enhanced various companies’ operational efficiency and strategic direction.

Lukas then honed his business intelligence and advanced analytics skills, focusing on Revenue Growth Management, Operations, and Supply Chain. His approach combines statistical and econometric methods with advanced machine learning techniques. He has expertise in using Power BI, SQL, Alteryx, and Python to analyze and interpret data effectively.

Lukas holds a Master’s degree in International Business and Management, specializing in Logistics & Supply Chain Management, from the University of Applied Sciences Osnabrück. Luka’s unique combination of skills and experience delivers exceptional value to clients and stakeholders, ensuring that all data solutions are aligned with business needs and effectively implemented.

Recent Articles

Pricing Intelligence Engine

Rebuilding Pricing and Promotion Analytics for a Global Data-Storage OEM

April 21, 2026

A Fortune 500 global data-storage OEM was bleeding margin in its $200M U.S. B2C hard-drive business. One flagship family had taken a substantial net-pricing hit year-over-year, and roughly 45% of historical promos were returning only 0 to 20% ROI. Revology rebuilt the pricing and promotion analytics from the ground up using causal Double Machine Learning, a retailer-math ROI model, and a three-archetype segmentation framework. The target: $3M to $6M of incremental EBITDA (a 10x to 20x return on the engagement) within 12 months.

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Project APEX Pricing Power

Unlocking Pricing Power for a Global Pharmaceutical Manufacturer in Emerging Markets

April 21, 2026

A Fortune 500 global pharmaceutical manufacturer was making emerging-market pricing decisions by feel. We built a repeatable Pricing Quick Wins engine across four pilot markets, grounded in causal elasticity modeling, automated competitive equivalence mapping, and price-pack architecture and inflation-aware simulators. The pilots identified around $8M of median revenue opportunity, with a best-case of ~$12M. Local teams now own the engine and can repeat the analysis annually as inflation and the competitive set shift.

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Automated RGM Engine

Operationalizing Revenue Growth Management Analytics for a Leading Plant-Based Creamer Brand

April 21, 2026

A leading plant-based creamer brand wanted real visibility into more than $13 million of annual trade spend and a credible way to forecast promo ROI before writing checks. We built the Revenue Growth Management analytics engine for them in Python and Power BI, running on their existing stack. The team now refreshes pricing, promo, and revenue/gross profit performance deep dive models in 10 to 20 minutes and catches variance the old process missed by weeks.

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