Bringing automated supply chain decisions to production - Lecture 7.2

00:00 Introduction
03:39 Automation has always been the goal
06:28 Exception management and alerts
10:27 The story so far
14:33 Our production rollout today
15:59 Recap: deliverable, scope and roles
19:01 Uncovering the form of the decision
23:00 Legacy-driven response
27:20 Iterating to zero percent insanity
32:30 Aspirational metrics
36:27 Dual run: manual + mechanical
39:19 Analysis paralysis
43:21 Gradual automation take-over
46:08 Process sedimentation
48:57 From planner to network manager
52:46 The KPI tourist
54:58 Leadership: from coach to product owner
58:46 The analogic supply chain boss
01:02:25 Conclusion
01:04:44 7.2 Bringing automated decisions to production - Questions ?


We seek a numerical recipe to drive an entire class of mundane decisions, such as stock replenishments. Automation is essential to make supply chain a capitalistic endeavor. However, it carries substantial risks of doing damage at scale if the numerical recipe is defective. Fail fast and break things is not the proper mindset to green-light a numerical recipe for production. However, many alternatives, such as the waterfall model, are even worse as they usually give an illusion of rationality and control. A highly iterative process is the key to design the numerical recipe that proves to be production grade.