550 5. CONCLUSIONS AND RECOMMENDATIONS When a mining company begins its digital transformation journey, investing in technology must be supported by a data analytics tool that measures unit process performance and identifies the most critical bottlenecks. The methodology presented proved highly effective, allowing the company to move away from local optimization and prioritize innovation efforts based on actual systemic constraints. By digitizing the principles of Value Stream Mapping and the Theory of Constraints, this modernization of work presents a valuable, replicable model for other mining companies looking to drive similar and highly effective transformations. ACKNOWLEDGEMENTS The authors express their appreciation to the operational and technology teams at the mining company for their support in the development, deployment, and validation of the value chain productivity monitoring platform. REFERENCES American Psychological Association. (2009). Publication Manual of the American Psychological Association (6th ed.). Washington, DC: Author. Goldratt, E. M., & Cox, J. (2004). The Goal: A Process of Ongoing Improvement (3rd Revised ed.). Great Barrington, MA: North River Press. Martin, K., & Osterling, M. (2013). Value Stream Mapping: How to Visualize Work and Align Leadership for Organizational Transformation. New York, NY: McGraw-Hill Education. Thomson, W. (1883). Electrical Units of Measurement. In Popular Lectures and Addresses (Vol. 1, pp. 73-74). London: Macmillan and Co.
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