The concept of diagnostic analytics

Purpose: The goal of the paper is to analyze the main features, benefits and problems with the diagnostic analytics usage. Design/methodology/approach: Critical literature analysis. Analysis of international literature from main databases and polish literature and legal acts connecting with researched topic. Findings: The paper discusses the concept of diagnostic analytics, which is a powerful tool for organizations to understand the underlying factors and reasons behind specific outcomes or events. By analyzing historical data and applying statistical techniques, organizations can identify root causes, patterns, and correlations that explain past events. This understanding enables informed decision-making, performance improvement, risk mitigation, enhanced customer insights, process optimization, resource allocation, and continuous improvement. Nevertheless, there are several challenges associated with diagnostic analytics. Firstly, the analysis process can be time-consuming due to the need for thorough examination and interpretation of data. Additionally, real-time insights may be limited as diagnostic analytics primarily focuses on historical data. Issues related to data quality and availability may also arise, impacting the accuracy and reliability of the analysis. Furthermore, diagnostic analytics lacks predictive capabilities, making it more challenging to anticipate future outcomes. The complexity of analysis, data privacy and security concerns, risks of bias and misinterpretation, and difficulties in identifying causal relationships further add to the challenges organizations face. Originality/value: Detailed analysis of all subjects related to the problems connected with the diagnostic analytics.