Operational Excellence Through Historical Data: A Generic Framework with Predictive Algorithms
Accurate predictions are crucial for informed decisions, even when only historical data is available and traditional time series models like ARIMA are not applicable. This work aims to develop a generic forecasting model that delivers robust predictions through feature engineering and prediction algorithms. Enhanced by time series data, diagnostic and autocorrelation analysis, the model's explainability is improved. The goal is to ensure data and model quality, promote operational excellence and create sustainable value.
Target Audience: Data scientists, analysts, and decision-makers interested in predictive analytics and operational insights. Professionals from industries such as logistics, manufacturing, or supply chain management who rely on data-driven decisions
Prerequisites: Fundamental knowledge of machine learning (ML)
Level: Basic
Dr. Ana Moya is an experienced data scientist and analytics expert. She studied statistics and data science and received her doctorate in statistics at the Technical University of Dortmund. With over 15 years of professional experience in the publishing industry, at FUNKE Mediengruppe and Handelsblatt Media Group, she has led and implemented numerous innovative projects – from data integration to the development of data and text mining algorithms to the application of advanced statistical and AI models.
Since 2018, Dr. Moya also brings her expertise into the academic world: She teaches data science and business intelligence at the International School of Management and has been an honorary professor since 2024. She is currently working as a Data Scientist and Green AI Researcher at Infomotion, a leading data performance company.
Marius Paganetti is a consultant at INFOMOTION GmbH, specializing in Business Information Systems with a focus on business intelligence and data-driven decision-making. Currently pursuing his master's degree, he helps organizations transform data into actionable insights. With a strong foundation in both IT and business, Marius bridges the gap between technical solutions and real business value, ensuring that data and analytics lead to meaningful improvements.
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