Skip to main content
Log in

A Blueprint for Performance-Driven Operations Management

  • Published:
Mining, Metallurgy & Exploration Aims and scope Submit manuscript

Abstract

The growing availability of information and data analysis capabilities of recent years provides new opportunities for improving the performance of mining operations. By using real-time measurements and artificial intelligence, it is possible to respond faster to changing conditions, while accurate and timely information permits rapid evaluation of changes and fast business improvement decisions. This article presents a blueprint for alignment of systems, organizational design, and management practices to leverage these developments in performance-driven operations management in mining and mineral processing. The first component of the blueprint is a performance framework with a system of key performance indicators for production control that can be used across organizational levels. This system places improvement at the core of management activities, giving greater importance to improvement skills at lower organizational levels, so companies can leverage available information for improving operational control. Secondly, the blueprint defines an organizational structure that strengthens performance improvement with technological and change management capabilities. Finally, the blueprint proposes alignment of management practices, covering the optimization of short-interval controls, the application of an improvement project portfolio management system that determines the ownership of improvement projects, and the coordination of controls across the organization. This combination of systems, organizational design, and management alignment supports rapid decision-making at the right organizational level. Introduction of the presented blueprint for operations management enables mines to leverage the developments in information and analysis capabilities to improve the performance of operations.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  1. Hirt A (2010) Imperial mines and quarries in the Roman world: organizational aspects, 1st edition, Oxford University Press

  2. Gupta M, Galloway K (2003) Activity-based costing/management and its implications for operations management. Technovation 23(2):131–138

    Google Scholar 

  3. Whittle J (1988) Beyond Optimization in Open Pit Design. Proc First Can Conf Comp Appl Min Ind 331–337

  4. Copeland TE, Koller T, Murrin J (1990) Valuation: measuring and managing the value of companies. Wiley, New York

    Google Scholar 

  5. Hitomi K (2017) Manufacturing systems engineering, a unified approach to manufacturing technology, production management and industrial economics. 2nd edn, Taylor & Francis;

  6. McKinsey & Company (2015) How digital innovation can improve mining productivity. McKinsey Metals & Mining November 2015

  7. Busby JS, Williams GM (1993) The value and limitations of using process models to describe the manufacturing organizations. Int J Prod Res 9:2179–2194

    Google Scholar 

  8. Benndorf J, Buxton M (2016) Sensor-based real-time resource model reconciliation for improved mine production control – a conceptual framework. Min Technol 125(1):54–64

    Google Scholar 

  9. McKinsey & Company (2016) Transforming operations management for a digital world. McKinsey Operations October 2016

  10. Tank DM (2015) Enable better and timelier decision-making using real-time business intelligence system. IJ Inf Eng Electron Bus 1:46

    Google Scholar 

  11. Kang N, Cong Z et al (2016) A hierarchical structure of key performance indicators for operation management and continuous improvement in production systems. Int J Prod Res 54(21):6333–6350

    Google Scholar 

  12. Bititci U, Carrie A, McDevitt L (1997) Integrated performance measurement systems: a development guide. Int J Oper Prod Manag 17(5):522–534

    Google Scholar 

  13. Hayes RH (1981) Why Japanese factories work. Harv Bus Rev 1981:57–66

    Google Scholar 

  14. Deloitte Development LLC (2017) Tech trends 2018 – the symphonic enterprise. Deloitte Insights, www.deloitte.com/insights/us/en/focus/tech-trends/2018/tech-trends-introduction.html. Accessed 21 December 2018

  15. Jurisch C et al (2014) Which capabilities matter for successful business process change? Bus Process Manag J 20(1):47–67

    Google Scholar 

  16. Jones G, George J (1998) Essentials of contemporary management, 1st edn, McGraw-hill.

  17. Barr R, Cook RE (2009) Mining for operational excellence. Min Eng 2009(11):17–22

    Google Scholar 

  18. Huotari K, Hamari H (2017) A definition for gamification: anchoring gamification in the service marketing literature. Electr Mark 27:21–31

    Google Scholar 

  19. PriceWaterhouse Coopers LLC (2012) Strategic portfolio management – how governance and financial discipline can improve portfolio performance. PriceWaterhouseCoopers press.

  20. KPMG International (2013) Being the best: inside the intelligent finance function. KPMG Publication 130662

Download references

Acknowledgements

I thank Terry Briggs and Johan van Huyssteen for their insights and useful discussions on the topic of operations management.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to W. F. Visser.

Ethics declarations

Conflict of Interest

The authors declare that they have no conflict of interest.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Visser, W.F. A Blueprint for Performance-Driven Operations Management. Mining, Metallurgy & Exploration 37, 823–831 (2020). https://doi.org/10.1007/s42461-020-00199-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s42461-020-00199-5

Keywords

Navigation