Abstract

Continuous improvement practices don’t directly drive organizational improvement. The effect is fully mediated by learning. The organizations that improve the fastest aren’t the ones with the most sophisticated tools, but those that create structures for learning from new experiences and new data. ML is the technological extension of that same principle. Where your quality management system learns from audits, corrective actions and management reviews at the organizational level, ML algorithms learn from operations data at the level of individual process steps. When you connect these learning loops (human insight informing machine models, coupled with machine discoveries informing human decisions) you create something more powerful than either alone.