The Lighthouse Operating System 2025

OS maturity levels used to identify capability gaps and drive continuous improvement FIGURE 12 1. Use Lighthouse OS framework principles and capability areas to identify key improvement needs 2. Use Lighthouse OS maturity levels to identify current state and capability gaps to develop for the next step Adaptable and robust processes Connected and transparent flows End-to-end synchronization Embedded sustainability Learning organization Accelerated digital and data Standarized Process-optimized Technology-enabled Business-shaping Ecosystem-leading Criteria from level 1 Criteria from level 2 Criteria from level 3 Criteria from level 4 Basic pull system or first-in-first-out (FIFO) lanes for main components implemented through Kanban loop/cards and/or supermarket Defined inventory levels between processes (incl. safety stocks) – based on experience Production plan with standardized slots for A types Milk runs with standardized schedules in place across entire plant (e.g. every hour) – supported by adaptive material-handling carts (e.g. shelf/tube/kit carts) Standardized boxes and pallets Standardized storage routines in place and material stored close to production cells/worksta- tions – minimizing walking distances for shop floor staffAdvanced pull system enabled by electronic Kanban/supermarket for material flow control established (e.g. via barcodes) Inventory levels between processes regularly reviewed and optimized – inventory drivers fully understood Production plan considering A and B types of products – allowing for minimization of work in progress (WIP) Milk run schedules dynamically aligned with production speed (takt) Material supply via circular transportation containers – allowing for waste reduction Material stored seamlessly within production cells/workstations (i.e. walking distance fully eliminated)Digital Kanban/ supermarket established through identification tag system (e.g. via radio-frequency identification [RFID] or Bluetooth Low Energy [BLE]) allowing for traceability Material flow parameters (e.g. inventory levels, FIFO lengths) automatically optimized through digital tools Production plan further optimized for all product types (A, B and C) through digital tools (e.g. long-term customer demand analysis) Material supply largely through automated guided vehicles (AGVs) – operated by AGV control centre Smart material management in place leveraging machine learning (ML) tech to automatically derive suggestions for improvement (e.g. automatic optimization of Kanban/supermarket) Material flow parameters measured in real time via smart devices (e.g. sensors) and connected to manufacturing execution system (MES) – artificial intelligence (AI)-driven algorithm to optimize synchronization with production flow and overall supply chain AGVs able to automatically prioritize material transports via smart inventory management based on insights from MESEntire material supply (intra- and inter-plant as well as beyond/from and to suppliers) run, synchronized, and optimized completely autonomously by self-sufficient and IoT -driven flow planning agent (e.g. AI robot), able to steer multitude of autonomous subagents (e.g. drones) 3 4 5 2Adaptable and robust processes Connected and transparent flows End-to-end synchronization Embedded sustainability Learning organization Accelerated digital and data 1 Source: World Economic Forum The Lighthouse Operating System: Driving Responsible Transformation 25