D1 – Problem Definition
(I) Formulation of verifiable research questions
(II) Translation of research questions into statistical modeling frameworks

D2 – Research Design
(I) Operationalization of variables into measurable items, survey questions
(II) Development of measurement and structural models
(III) Sample size calculation and sampling strategy design

D3 – Data Acquisition
(I) Development of data pipelines and survey instruments
(II) Conducting expert interviews, application of the Delphi methodology
(III) Web scraping and database extraction

D4 – Data Analytics (R, Python, SPSS, Mplus)
(I) Extract–Transform–Load (ETL) procedures
(II) Exploratory scaling and dimensionality techniques
(III) Generalized linear modeling
(IV) Latent variable modeling (see: statmodel.com)
(V) Multiple imputation for missing data (see: amices.org)
(VI) Machine learning applications

D5 – Documentation and Reporting
(I) Dynamic report generation
(II) Monitoring and playback of key performance indicators
(III) Development of impactful presentations and visualizations

D6 – Strategic Discussion and Decision Support