Citation:

Muhammad Nuragustian Hidayat, Dermawan Wibisono. "Integrated Performance Management System for Material Replenishment in Mature Oil Field Operations: A Soft Systems and Balanced Scorecard Approach" International Research Journal of Economics and Management Studies, Vol. 4, No. 7, pp. 226-244, 2025.

Abstract:

Material stockouts in mature oil field operations significantly impact production efficiency and financial performance. This research develops an integrated Performance Management System using Soft Systems Methodology (SSM) enhanced with Analytical Hierarchy Process (AHP) within a Balanced Scorecard (BSC) framework to address material replenishment challenges. The study systematically identified five interconnected root causes: planning deficiencies with lack of structured forecasting; procurement inefficiencies including 3-12 month lead times and 20-30% staff vacancy rates; inventory management challenges evidenced by simultaneous stockouts and IDR 1.4 billion dead stock; coordination gaps between supply chain and operations; and performance monitoring limitations showing disconnect between reported service levels (99.84%) and actual production achievement (82.70%). A gap analysis revealed significant discrepancies across BSC perspectives, with daily production losses of USD 7,408.8 and ineffective service level measurement creating artificially inflated metrics. Stakeholder-driven AHP prioritization identified Learning & Growth initiatives as highest priority (34.1%), particularly employee fulfillment (22.4%), Availability of Planner in Every Function (19.3%), and MRP Application (18.5%), followed by Internal Process (26.9%), Customer Perspective (23.4%), and Financial Perspective (15.6%). The proposed Performance Management System provides specific indicators and a phased implementation strategy prioritizing foundational capability development before process optimization. The research demonstrates that integrating SSM with AHP effectively addresses both qualitative complexity and quantitative prioritization in supply chain contexts. This capability-focused approach contrasts with traditional process-only interventions, offering sustainable improvements for asset-intensive industries. The findings provide both theoretical contributions to performance management literature and practical guidance for mature oil field operations seeking comprehensive material availability optimization.

References:

[1] S. Alam, J. Zhang, M. Shehzad, N. Khan, and A. Ali, “Mediation approach of knowledge management process towards supply chain performance under green technology: an empirical analysis,” Business Process Management Journal, vol. 29, pp. 1466–1490, 2023, doi: 10.1108/bpmj-01-2023-0045.
[2] S. Al-Qubaisi dan M. Ajmal, “Determinants of operational efficiency in the oil and gas sector,” Benchmarking: An International Journal, 2018, doi: 10.1108/BIJ-04-2017-0079.
[3] M. Beheshtinia, P. Feizollahy, and M. Fathi, “Supply Chain Optimization Considering Sustainability Aspects,” Sustainability, 2021, doi: 10.3390/su132111873.
[4] R. S. Kaplan dan D. P. Norton, The Balanced Scorecard: Translating Strategy into Action, Harvard Business School Press, 1996.
[5] R. Bhagwat dan M. Sharma, “Performance measurement of supply chain management: A balanced scorecard approach,” Computers & Industrial Engineering, vol. 53, pp. 43–62, 2007.
[6] P. Panayides, O. Borch, and A. Henk, “Measurement challenges of supply chain performance in complex shipping environments,” Maritime Business Review, 2018.
[7] R. Rahmadhiputra dan D. Sushandoyo, “Improving Demand Management Performance using Knowledge Management Approach in an Oil and Gas Company,” International Journal of Current Science Research and Review, 2023.
[8] P. Ricardianto et al., “Supply chain management evaluation in the oil and natural gas industry using SCOR model,” Uncertain Supply Chain Management, 2022.
[9] A. Odunayo dan S. Idadokima, “Industry 4.0 and Supply Chain Performance in the Oil and Gas Industry,” International Journal of Scientific Research and Management, 2021.
[10] A. Attia, A. Ghaithan, and S. Duffuaa, “A multi-objective optimization model for tactical planning of upstream oil & gas supply chains,” Computers & Chemical Engineering, vol. 128, pp. 216–227, 2019.
[11] U. S. Bititci, P. Garengo, V. Dörfler, and S. Nudurupati, “Performance measurement: Challenges for tomorrow,” International Journal of Management Reviews, vol. 14, no. 3, pp. 305–327, 2012.
[12] A. Neely, C. Adams, and M. Kennerley, The Performance Prism: The Scorecard for Measuring and Managing Business Success, Prentice Hall, 2002.
[13] S. S. Nudurupati, U. S. Bititci, V. Kumar, dan F. T. Chan, “State of the art literature review on performance measurement,” Computers & Industrial Engineering, vol. 60, no. 2, pp. 279–290, 2011.
[14] M. Franco-Santos, L. Lucianetti, and M. Bourne, “Contemporary performance measurement systems: A review of their consequences and a framework for research,” Management Accounting Research, vol. 23, no. 2, pp. 79–119, 2012.
[15] H.-H. Chang, “An empirical study of evaluating supply chain management integration using the balanced scorecard in Taiwan,” Service Industries Journal, vol. 29, no. 11, pp. 1553–1570, 2009.
[16] G. Frederico, J. Garza‐Reyes, A. Kumar, and V. Kumar, “Performance measurement for supply chains in the Industry 4.0 era: a balanced scorecard approach,” International Journal of Productivity and Performance Management, 2020.
[17] J. W. Creswell dan J. D. Creswell, Research Design: Qualitative, Quantitative, and Mixed Methods Approaches, 5th ed., SAGE, 2018.
[18] P. Checkland, Systems Thinking, Systems Practice, Wiley, 1999.
[19] R. K. Yin, Case Study Research and Applications: Design and Methods, 6th ed., SAGE, 2018.
[20] P. Checkland dan J. Scholes, Soft Systems Methodology in Action, Wiley, 1990.
[21] M. Winter, “The relevance of soft systems thinking,” Human Resource Development International, vol. 3, pp. 377–383, 2000.
[22] P. Checkland dan J. Poulter, Learning for Action, Wiley, 2006.
[23] T. L. Saaty, “Decision making with the analytic hierarchy process,” International Journal of Services Sciences, vol. 1, no. 1, pp. 83–98, 2008.
[24] S. Holwell, “Soft Systems Methodology: Other Voices,” Systemic Practice and Action Research, vol. 13, pp. 773–797, 2000.
[25] D. Petkov, S. Alter, O. Petkova, D. T. Andrew, “On the Suitability of Soft Systems Methodology and the Work System Method in Some Software Project Contexts,” International Journal of Information Technologies and Systems Approach, vol. 6, pp. 22–34, 2013.
[26] S. K. Patil dan R. Kant, “Evaluating the impact of Knowledge Management adoption on Supply Chain performance by BSC-FANP approach: An empirical case study,” Tékhne, vol. 14, no. 1, pp. 52–74, 2016.
[27] Y. S. Lincoln dan E. G. Guba, Naturalistic Inquiry, SAGE, 1985.
[28] M. B. Miles, A. M. Huberman, and J. Saldaña, Qualitative Data Analysis: A Methods Sourcebook, 3rd ed., SAGE, 2014.
[29] H. Laihonen dan S. Pekkola, “Impacts of using a performance measurement system in supply chain management: a case study,” International Journal of Production Research, vol. 54, pp. 5607–5617, 2016.
[30] M. Christopher, Logistics and Supply Chain Management, Pearson, 2020.
[31] K. Zimmermann and S. Seuring, “Two case studies on developing, implementing and evaluating a balanced scorecard in distribution channel dyads,” International Journal of Logistics Research and Applications, vol. 12, no. 2, pp. 149–164, 2009.
[32] D. Mollov, “Strategic supply chain management with the balanced scorecard,” Economic Alternatives, vol. 4, pp. 675–689, 2020.
[33] M. Chlistalla dan T. Schaper, “Maintenance and continuous improvement of information systems,” dalam BPM Workshop, 2009.
[34] M. Sangari, R. Hosnavi, dan M. Zahedi, “The impact of knowledge management processes on supply chain performance: An empirical study,” The International Journal of Logistics Management, vol. 26, pp. 603–626, 2015.
[35] S. Patil dan R. Kant, “A fuzzy AHP-TOPSIS framework for ranking the solutions of Knowledge Management adoption in Supply Chain to overcome its barriers,” Expert Systems with Applications, vol. 41, pp. 679–693, 2014.
[36] S. Khan, A. Chaabane, and F. Dweiri, “A knowledge-based system for overall supply chain performance evaluation: a multi-criteria decision approach,” Supply Chain Management: An International Journal, 2019.
[37] S. Sangari, R. Hosnavi, and M. Zahedi, “The impact of knowledge management processes on supply chain performance: An empirical study,” International Journal of Logistics Management, vol. 26, no. 3, pp. 603-626, 2015.

Keywords:

Analytical Hierarchy Process, Balanced Scorecard, Material Replenishment, Performance Management System, Soft Systems Methodology, Oil and Gas Supply Chain.