THE IMPACT OF DIGITAL MONITORING AND KPI TRANSPARENCY ON THE OPERATIONAL EFFICIENCY OF INDUSTRIAL ENTERPRISES
This article analytically examines the impact of digital monitoring technologies and key performance indicator (KPI) transparency on the operational efficiency of industrial enterprises, using empirical evidence from manufacturing plants in the Kashkadarya region of Uzbekistan. It proves that collecting operational data alone does not automatically guarantee production performance growth. Practical results require transforming raw operational data into standardized KPIs based on international standards (ISO 22400), identifying systematic deviations from normatives, and establishing structured management workflows. The research utilizes a system-oriented approach, process modeling, comparative analysis, before-and-after assessment, and empirical case studies on "Sultan Tex" LLC and "Asia Golden Oil" LLC. The findings demonstrate that integrating digital monitoring, KPI transparency, and Lean management tools (TPM, SMED) leads to significant improvements in Overall Equipment Effectiveness (OEE), reductions in Mean Time to Repair (MTTR) and changeover duration, and optimization of Inventory Days Outstanding (DIO). A structured operational decision-making framework is proposed.
1. O‘zbekiston Respublikasi Prezidentining 2020-yil 5-oktabrdagi “Raqamli O‘zbekiston – 2030” strategiyasini tasdiqlash va uni samarali amalga oshirish chora-tadbirlari to‘g‘risidagi PF-6079-son Farmoni. Qonunchilik ma’lumotlari milliy bazasi. URL: https://lex.uz/docs/-5030957
2. International Organization for Standardization. ISO 22400-1:2014. Automation systems and integration — Key performance indicators for manufacturing operations management — Part 1: Overview, concepts and terminology. Geneva: ISO, 2014. URL: https://www.iso.org/standard/56847.html
3. International Organization for Standardization. ISO 22400-2:2014. Automation systems and integration — Key performance indicators for manufacturing operations management — Part 2: Definitions and descriptions. Geneva: ISO, 2014. URL: https://www.iso.org/standard/54497.html
4. Kaplan R.S., Norton D.P. The Balanced Scorecard: Measures that Drive Performance // Harvard Business Review. 1992. Vol. 70, No. 1. P. 71–79. URL: https://hbr.org/1992/01/the-balanced-scorecard-measures-that-drive-performance-2 5. Ohno T. Toyota Production System: Beyond Large-Scale Production. Portland: Productivity Press, 1988. 176 p
6. Womack J.P., Jones D.T. Lean Thinking: Banish Waste and Create Wealth in Your Corporation. 2nd ed. New York: Free Press, 2003. 396 p.
7. Shah R., Ward P.T. Lean manufacturing: context, practice bundles, and performance // Journal of Operations Management. 2003. Vol. 21, No. 2. P. 129–149. DOI: https://doi.org/10.1016/S0272-6963(02)00108-0 8. Shah R., Ward P.T. Defining and developing measures of lean production // Journal of Operations Management. 2007. Vol. 25, No. 4. P. 785–805. DOI: https://doi.org/10.1016/j.jom.2007.01.019 9. Buer S.V., Strandhagen J.O., Chan F.T.S. The link between Industry 4.0 and lean manufacturing: mapping current research and establishing a research agenda // International Journal of Production Research. 2018. Vol. 56, No. 8. P. 2924–2940. DOI: https://doi.org/10.1080/00207543.2018.1442945 10. Kolberg D., Zühlke D. Lean Automation enabled by Industry 4.0 technologies // IFAC-PapersOnLine. 2015. Vol. 48, No. 3. P. 1870–1875. DOI: https://doi.org/10.1016/j.ifacol.2015.06.359
Copyright (c) 2026 «ACTA NUUz»
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
.jpg)
1.png)
