The Lighthouse Operating System 2025
Page 13 of 33 · WEF_The_Lighthouse_Operating_System_2025.pdf
Codified maturity levels for an exemplary capability within the Lighthouse OS FIGURE 3
Ecosystem-leading5
Business-shaping4
Technology-enabled3
Process-optimized2
Standarized1Five-step maturity model
Connected and transparent flows: Assessment criteria and scoring levels for the capability of synchronized material flow Example:Cutting-edge sustainability,
digitalization and operational
efficiency
Traditional/pre-lean
Standarized1
Process-optimized2
Technology-enabled3
Business-shaping4
Ecosystem-leading5
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/work-
stations – 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)
Source: World Economic Forum
The Lighthouse Operating System: Driving Responsible Transformation
13
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