Uncovering Key Features for Model-Driven Engineering of Complex Performance Indicators: A Scoping Review
Benito Giunta, Corentin Burnay
TL;DR
This scoping review surveys how Model-Driven Engineering (MDE) can support the design and management of Complex Performance Indicators (CPIs), which combine multiple indicators to measure latent business factors. By collecting 36 papers across 18 frameworks from 2003–2024 and analyzing them with a structured feature-mbased approach, the study derives 31 features categorized into Language Expressiveness, BU Empowerment, and Capabilities/Support for MDE, and presents a Framework-Feature Matrix to benchmark coverage. The results show that no single framework fully covers all identified features, though several features are widely shared, indicating partial convergence and clear gaps. The authors discuss the practical implications for building a comprehensive CPI modeling framework, and outline future work to incorporate empirical features, validate with practitioners, and develop an SSBI-oriented MDE framework with a CPI modeling language and graphical notations. This work provides a structured, objective basis for evaluating CPI frameworks and guiding future research toward more accessible, transparent, and adoptable CPI solutions in organizations.
Abstract
This paper addresses challenges of designing and managing Complex Performance Indicators (CPI), which amalgamate individual indicators to measure latent, yet crucial business factors like customer satisfaction or sustainability indices. Despite their significant value, designing and managing CPI is intricate; they evolve with rapidly changing business contexts and present comprehension and explanation challenges for end-users. Model-Driven Engineering (MDE) emerges as a potent solution to overcome these hurdles and ensure CPI adoption, though its application to CPI remains an understudied research area. While prior efforts targeted specific CPI modeling objectives, a comprehensive overview of literature advancements is lacking. This study addresses this gap by conducting a scoping review yielding dual outcomes: (1) a comprehensive mapping of modeling features in the literature and (2) a comparative analysis of the coverage offered by the modeling frameworks. These outcomes enhance CPI understanding in academic and practitioner circles and offer insights for future MDE CPI advancements.