MONITORING AND EVALUATION OF ENTERPRISE PERFORMANCE MANAGEMENT INDICATORS IN THE CONTEXT OF ENSURING COMPETITIVENESS

The article explores the theoretical and practical aspects of monitoring and evaluating enterprise management indicators within the VUCA environment. The VUCA environment is characterised by volatility, uncertainty, complexity, and ambiguity, and is a defining feature of modern business operations. The acronym VUCA was first coined in the post-Cold War era, yet its components are applicable to both business conditions and the broader global context. The significance of this research lies in its contribution to the enhancement of enterprise adaptability to market challenges through the implementation of effective monitoring systems, controlling practices, and strategic analysis tools. The primary objective of this study is to develop a scientifically grounded methodology for assessing managerial indicators influencing enterprise competitiveness. In order to achieve this, the role of human capital, tax flexibility, and digital transformations will be taken into account. The research employs a range of methodological approaches, including dialectical methodology, comparative analysis, tabular techniques, systems approach, and modelling. The proposed model integrates indicators that appear to be incompatible, thereby bridging the gap between real-time analytics and forward-looking strategic forecasting. This enables a proactive evaluation of enterprise performance. This approach enables businesses to transition from a focus on retrospective analysis to a more proactive stance by integrating operational metrics with strategic foresight. This, in turn, serves to mitigate the impact of uncertainty and preserve competitive advantages. The model was tested on a hypothetical company X (distinct from the former Twitter entity), incorporating financial, organisational, and behavioural performance indicators. The scientific novelty lies in the consistent combination of traditional and digital management tools with predictive analytics based on knowledge of personnel abilities and creativity, optimisation of tax flexibility, which allows for risk prediction and development of an adaptive strategy. The practical significance of the article lies in the proposal of a universal real-time competitiveness assessment system suitable for the effective development of enterprises of various scales.

Authors

Institutions

Publication Details

Journal
Економіка розвитку систем
Published
2025-08-13
DOI
https://doi.org/10.32782/2707-8019/2025-2-1
Primary Topic
Economic and Business Development Strategies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

MONITORING AND EVALUATION OF ENTERPRISE PERFORMANCE MANAGEMENT INDICATORS IN THE CONTEXT OF ENSURING COMPETITIVENESS

Тетяна Костишина, Serhii Zhyliakov
1 links
Економіка розвитку систем
Economic and Business Development Strategies
article

MONITORING AND EVALUATION OF ENTERPRISE PERFORMANCE MANAGEMENT INDICATORS IN THE CONTEXT OF ENSURING COMPETITIVENESS

Тетяна Костишина, Serhii Zhyliakov
article en

Abstract

The article explores the theoretical and practical aspects of monitoring and evaluating enterprise management indicators within the VUCA environment. The VUCA environment is characterised by volatility, uncertainty, complexity, and ambiguity, and is a defining feature of modern business operations. The acronym VUCA was first coined in the post-Cold War era, yet its components are applicable to both business conditions and the broader global context. The significance of this research lies in its contribution to the enhancement of enterprise adaptability to market challenges through the implementation of effective monitoring systems, controlling practices, and strategic analysis tools. The primary objective of this study is to develop a scientifically grounded methodology for assessing managerial indicators influencing enterprise competitiveness. In order to achieve this, the role of human capital, tax flexibility, and digital transformations will be taken into account. The research employs a range of methodological approaches, including dialectical methodology, comparative analysis, tabular techniques, systems approach, and modelling. The proposed model integrates indicators that appear to be incompatible, thereby bridging the gap between real-time analytics and forward-looking strategic forecasting. This enables a proactive evaluation of enterprise performance. This approach enables businesses to transition from a focus on retrospective analysis to a more proactive stance by integrating operational metrics with strategic foresight. This, in turn, serves to mitigate the impact of uncertainty and preserve competitive advantages. The model was tested on a hypothetical company X (distinct from the former Twitter entity), incorporating financial, organisational, and behavioural performance indicators. The scientific novelty lies in the consistent combination of traditional and digital management tools with predictive analytics based on knowledge of personnel abilities and creativity, optimisation of tax flexibility, which allows for risk prediction and development of an adaptive strategy. The practical significance of the article lies in the proposal of a universal real-time competitiveness assessment system suitable for the effective development of enterprises of various scales.

Економіка розвитку системVol. 7(2)
Poltava University of Economics and Trade (UA)
Openalex Percentile: Top 67%
Economic and Business Development Strategies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.