SavedAdd your journal

Journals / The Journal of International Scientific Researches / 2025 / Cilt: 10 Sayı: 3

Balanced Scorecard-Based Industry 4.0 Performance Evaluation: A Case Study in the Fast-Moving Consumer Goods Sector (FMCG)

Dengelenmiş Skor Kart Temelli Endüstri 4.0 Performans Değerlendirmesi: Hızlı Tüketim Ürünleri Sektöründe Bir Şirket Uygulaması

Ceren Dilbaz(İSTANBUL TEKNİK ÜNİVERSİTESİ)0009-0008-6823-0618
Hür Bersam Sidal(İSTANBUL TEKNİK ÜNİVERSİTESİ)0000-0002-3790-9897
Pages
322–339
Publication Date
2025-11-08
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The findings of this study reveal the impact of Industry 4.0 on the FMCG sector and provide an innovative contribution to performance management.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The fast-moving consumer goods (FMCG) sector is highly sensitive to performance evaluation processes due to the short lifecycle of products and intense market competition.
📊
Key Findings & Data:The innovative technologies offered by Industry 4.0 are crucial for optimizing production processes, responding more quickly to customer demands, and improving resource efficiency.
💡
Conclusion & Impact:The findings of this study reveal the impact of Industry 4.0 on the FMCG sector and provide an innovative contribution to performance management.
🔬Design:Review & Systematic Survey
📍Scope:Comprehensive Sample
⚙️Variables:Endüstri 4.0 · Dengelenmiş Skor Kart · Hızlı Tüketim Ürünleri

Abstract

The fast-moving consumer goods (FMCG) sector is highly sensitive to performance evaluation processes due to the short lifecycle of products and intense market competition. The innovative technologies offered by Industry 4.0 are crucial for optimizing production processes, responding more quickly to customer demands, and improving resource efficiency. Therefore, developing a suitable performance measurement model for the sector has become essential. This study adopts the Balanced Scorecard (BSC) model to evaluate the Industry 4.0 performance of companies in the FMCG sector. Sub-criteria for the four main dimensions of the BSC (Finance, Customer, Internal Processes, and Learning and Growth) were identified through a literature review. The importance weights of these criteria were calculated using the Analytic Hierarchy Process (AHP) based on insights obtained from in-depth interviews with industry managers. The results from these interviews formed the basis for determining the criteria weights and structuring the model. An application was conducted in a beverage company in the Aegean region, where the company’s Industry 4.0 performance was assessed, highlighting strengths and areas for improvement. The findings of this study reveal the impact of Industry 4.0 on the FMCG sector and provide an innovative contribution to performance management.

Özet

Hızlı tüketim ürünleri sektörü, kısa çevrim süresine sahip ürünlerin yoğun rekabet ortamında sunulması nedeniyle performans değerlendirme süreçlerine duyarlıdır. Endüstri 4.0'ın sunduğu yenilikçi teknolojiler, üretim süreçlerini optimize etmek, müşteri taleplerine daha hızlı yanıt vermek ve kaynak kullanımını daha verimli hale getirmek açısından önemlidir. Bu nedenle, sektöre uygun bir performans ölçüm modeli geliştirmek gereklilik haline gelmiştir. Bu makalede, hızlı tüketim ürünleri sektöründeki şirketlerin Endüstri 4.0 performanslarını değerlendirmek için Denge Skor Kartı (BSC) modeli temel alınmıştır. BSC’nin dört ana boyutuna (Finans, Müşteri, İçsel Süreçler, Öğrenme ve Gelişme) ait alt kriterler literatür taraması ile belirlenmiş, sektördeki yöneticilere yapılan derinlemesine mülakatlar sonucunda elde edilen görüşler doğrultusunda kriterlerin önem dereceleri Analitik Hiyerarşi Prosesi (AHP) yöntemi ile hesaplanmıştır. Bu mülakatlardaki sonuçlar, kriter ağırlıklarının belirlenmesinde ve modelin yapılandırılmasında temel alınmıştır. Ege bölgesindeki büyük ölçekli hızlı tüketim ürünleri sektöründe yer alan bir şirketin Endüstri 4.0 performansı değerlendirilmiş ve güçlü ile gelişime açık alanlar ortaya konulmuştur. Makalenin bulguları, Endüstri 4.0’ın hızlı tüketim ürünleri sektöründeki etkilerini ortaya koymuş ve performans yönetimine yenilikçi bir katkı sağlamıştır.

🔖

Cite This Article

Dilbaz, C., Sidal, H. B. (2025). Balanced Scorecard-Based Industry 4.0 Performance Evaluation: A Case Study in the Fast-Moving Consumer Goods Sector (FMCG). The Journal of International Scientific Researches, Cilt: 10 Sayı: 3, 322–339. https://doi.org/10.23834/isrjournal.1656832

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (16)

  1. Adeyemia, O. A., Pintob, P. M., Sunmolac, F., MusaAibinud, A., Okesolae, J., & Adeyemi, E. (2024). Towards the Adoption of Industry 4.0 Technologies in the Digitalization of Manufacturing Supply Chain. Procedia Computer Science, 337–347.
  2. Aka, D. Ç. (2022). Determination of Critical Success Factors in the Implementation of Industry 4.0 and Evaluation of the Situation of Firms Receiving Investment Incentives with the Interval Type-2 Fuzzy TOPSIS Method. Avrupa Bilim ve Teknoloji Dergisi(41), 36-47.
  3. Chen, C. P., & Zhang, C. Y. (2014). Data-intensive applications, challenges, techniques and technologies: A survey on Big Data. Information Sciences, 275, 314-347.
  4. Cihan, Ü., Sungur, C., ve Yıldırım, H. (2022). Application of the Maturity Model in Industrial Corporations. Sustainability.
  5. Clark, H. (2024, November 18). What Is the Weighted Scoring Model and How Does it Work? The Product Manager: https://theproductmanager.com/topics/weighted-scoring-model
  6. Çanakçıoğlu, M., ve Demirbaş, M. (2009). Performans Ölçüm Yöntemleri ile Kurumsal Karne Yaklaşımı. İstanbul Üniversitesi İktisat Fakültesi Mecmuası, 59, 213 - 238.
  7. Efimova, A., & Briš, P. (2021). Quality 4.0 for processes and customers. Quality Innovation Prosperity, 25.
  8. Entrepreneurship, C. (2020). Weighted Factor Model. Charity Entrepreneurship’s: https://www.charityentrepreneurship.com/weighted-factor-model
  9. Frederico, G. F., Garza-Reyes, J. A., Kumar, A., & Kumar, V. (2021). Performance measurement for supply chains in the Industry 4.0 era: a balanced scorecard approach. International Journal of Productivity and Performance Management, 70(4).
  10. Gebhardt, M., Spieske, A., Kopyto, M., & Birkel, H. (2022). Increasing global supply chains’ resilience after the COVID-19 pandemic: Empirical results from a Delphi study. Journal of Business Research, 150, 59-72.
  11. Gowland, M. (2024). What’s a weighted scoring model? An essential guide for beginners. Tempo Strategic Roadmaps: https://roadmunk.com/product-management-blog/weighted-scoring-model/
  12. Guidi, G., Goffo, G., & Violante, A. C. (2024, June). Application of the Analytic Hierarchy Process (AHP) method to identify the most suitable approach for managing irradiated graphite. Nuclear Engineering and Technology.
  13. Gümüş, H. G. (2023). İşletme Performansı ve Endüstri 4.0 Teknolojileri İlişkisi; Teorik Bir Analiz. İşletme ve Girişimcilik Araştırma Dergisi, 1-14.
  14. Jacob, K., Woschanka, M., & Nadine, O. (2024). Industry 4.0 Technologies and their Implications for Environmental Sustainability in the Manufacturing Industry. 5th International Conference on Industry 4.0 and Smart Manufacturing, (s. 2777–2789). Elsevier.
  15. Adeyemia, O. A., Pintob, P. M., Sunmolac, F., MusaAibinud, A., Okesolae, J., & Adeyemi, E. (2024). Towards the Adoption of Industry 4.0 Technologies in the Digitalization of Manufacturing Supply Chain. Procedia Computer Science, 337–347.
  16. Gowland, M. (2024). What’s a weighted scoring model? An essential guide for beginners. Tempo Strategic Roadmaps: https://roadmunk.com/product-management-blog/weighted-scoring-model/