Thursday 05 June 2025
The quest for better business intelligence has led researchers down a winding path, exploring various approaches to modeling and measuring key performance indicators (KPIs). A recent study takes a comprehensive look at the existing literature on this topic, compiling features from multiple frameworks and identifying areas where current methods fall short.
The authors begin by defining KPIs as measurable values that organizations use to evaluate their performance. They then delve into the challenges of designing effective KPI models, citing issues such as data quality concerns, lack of standardization, and difficulties in linking KPIs to strategic objectives.
To address these challenges, researchers have developed various frameworks for modeling and measuring KPIs. These frameworks often rely on a combination of conceptual, logical, and operational elements to define and calculate KPI values. However, the authors note that existing frameworks tend to focus on specific aspects of KPI modeling, such as data quality or performance measurement, without providing a comprehensive view of the entire process.
The study’s authors set out to change this by conducting a scoping review of the literature on KPI modeling and measurement. They analyzed 64 articles from various fields, including business intelligence, information systems, and operations research, identifying key features and challenges in each framework.
One notable finding is that current KPI models often prioritize technical aspects over user needs and organizational goals. The authors suggest that this imbalance can lead to ineffective KPIs that fail to support decision-making or drive business improvement.
Another significant issue is the lack of standardization in KPI modeling and measurement. Different frameworks and organizations may define and calculate KPIs using different methods, making it difficult to compare results across borders or industries.
The study’s authors propose a more holistic approach to KPI modeling and measurement, emphasizing the importance of aligning KPIs with organizational goals and involving stakeholders throughout the design process. They also recommend developing standardized frameworks that can be adapted to various industries and contexts.
In terms of practical applications, the findings of this study have implications for business intelligence professionals, who must navigate complex landscapes of data and performance indicators to support decision-making. By adopting a more comprehensive approach to KPI modeling and measurement, organizations may be able to develop more effective metrics that drive meaningful improvements in their operations.
Ultimately, this study serves as a valuable reminder of the importance of integrating technical expertise with business needs and stakeholder perspectives when designing and implementing KPI models.
Cite this article: “Assessing Key Performance Indicators: A Holistic Approach to Modeling and Measurement”, The Science Archive, 2025.
Business Intelligence, Key Performance Indicators, Kpi Modeling, Measurement, Data Quality, Standardization, Organizational Goals, Stakeholder Engagement, Decision-Making, Performance Metrics
