GLOBAL LIGHTHOUSE NETWORK - INSIGHTS FROM THE FOREFRONT OF THE 4TH INDUSTRIAL REVOLUTION - MCKINSEY
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Global Lighthouse Network Insights from the forefront of the 4th Industrial Revolution January 2020 CONFIDENTIAL AND PROPRIETARY Any use of this material without specific permission of McKinsey & Company is strictly prohibited
Executive summary
The latest findings from the Global Lighthouse Network, an ongoing research collaboration
between McKinsey & Co. and the World Economic Forum, show that industrial leaders in
applying Fourth Industrial Revolution (4IR) digital technologies are benefiting from a head start
to generate even more value across the entire enterprise, and not just within factories
This brief summary examines what the 44 Lighthouse manufacturers do differently; crucial
insights for the vast majority of manufacturers that aren’t yet competitive with the leaders
At least 70 percent of manufacturers are languishing in “pilot purgatory,” unable to bring
manufacturing innovation to scale; they’re at higher and higher risk of falling permanently
behind the leaders
A detailed look at Lighthouse success cases reveals organizations that are driving outsized
improvement in productivity, sustainability, operating cost, and speed to market
A common thread across Lighthouses is that the digital journey begins with the transformation
of the plant’s system of operations and is then propelled through 6 key scale-up enablers
End-to-End (E2E) Lighthouses in particular are using technology to drive value for the
enterprise in three ways: customer-centered design, seamless connectivity across functions,
and continuous connectivity beyond organizations
Transforming manufacturing from sourcing to delivery increases complexity and shifts
stakeholder incentives as digital connectivity expands; addressing these changes requires
breaking down internal divisions, sharing data externally, and building new capabilities,
demonstrating the importance of the human element in successful technology application.
Adoption of 4IR technologies affect tasks performed and the ways in which people work
together. Lighthouses are preparing their workforce through 6 common actions to maximize the
potential of workers.
McKinsey & Company 2
The Global Lighthouse Network includes 44 sites where 4IR
technology is successfully deployed at scale
1 Zymergen 13 AGCO
Biotechnology, US Agricultural equipment, 37 Johnson & Johnson
DePuy Synthes
DE
19
2 Fast Radius with UPS Medical devices, CN
Additive manufacturing, 14 Rold
18
US Electrical components, IT 38 Bosch
3 Johnson & Johnson Automotive, CN
vision care 15 Bayer
41
Division pharmaceuticals, 6 10 12 32
Medical devices, US 7 11
IT 9 13 17
33 44 39 Procter & Gamble
8 16 34
4 Groupe Renault 36 42 43 Consumer goods, CN
16 BMW Group 14 15 20
Automotive, BR
Automotive, DE 26
40
MODEC 2 22 39 40 Boashan Iron & Steel
5 21
38
17 Procter & Gamble
1 35 37 Steel products, CN
Oil and gas, BR
Consumer goods, CZ 3 31
6 Johnson & Johnson 23 24
DePuy Synthes 41 Haier
18 Sanvik Coromant 25 Appliances, CN
Medical devices, IR Industrial tools, SE
7 GSK 27 29
19 Nokia 28
42 POSCO
Pharmaceuticals, UK 30
Electronics, FI Steel products, KOR
8 Schneider Electric
20 Arcelik A.S.
Electrical components, 43 GE Healthcare
FR Home appliances, RO 5
4 Healthcare, JP
9 Groupe Renault 21 Petkim
Automotive, FR Chemicals, TR 44 Hitachi
Industrial equipment, JP
10 Tata Steel 22 Ford Otosan
Steel products, NL Automotive, TR
11 Henkel
23 Saudi Aramco 25 Tata Steel 26 Siemens 27 Infineon 28 Schneider Electric 29 Micron 30 Petrosea
Consumer goods, DE
Gas treatment, SA Steel products, IN Semiconductors, SG Electrical components, ID
Industrial automation Semiconductors, SG Mining, ID
12 Phoenix Contact products, CN
24 Unilever
Industrial automation, DE
Consumer goods, UAE 31 Foxconn Industrial Internet 32 FOTON Cummins 33 Danfoss 34 Weichai 35 SAIC Maxus 36 Haier
Electronics, CN Automotive, CN Industrial equipment, CN Industrial machinery, CN Automotive, CN Home appliances, CN
McKinsey & Company 3
Lighthouses demonstrate what’s possible with measurable
improvements in operations
E2E Lighthouses Factory Lighthouses
KPIs improvements Impact range observed Lighthouse example
Factory output increase 4-200%
Productivity increase 5-160%
Produc- OEE increase 3-90%
tivity Product cost reduction 5-40%
Operating cost reduction 2-45%
Quality cost reduction 5-90%
Waste reduction 5-45%
Sustain-
Water consumption reduction 10-30%
ability
Energy Efficiency 1-50%
Inventory reduction 10-90%
Agility Lead time reduction 7-90%
Change-over shortening 30-70%
Speed to Speed to market reduction 30-90%
market Design iteration time reduction 15-40%
Configuration accuracy increased 15-20%
Customi-
zation Lot size reduction 55%-90%
Source: McKinsey & Company Lighthouse Analysis McKinsey & Company 4
Lighthouses are deploying 92 use cases with some focusing within the
manufacturing site and others on connecting the E2E value chain (1/2)
Manufacturing
Digital assembly & machines Digital maintenance Digital performance management Digital quality management Digitally enabled sustainability
Real-time locating system (RTLS) for Cost optimization Of heavy operations Analytics platform for remote Scanning to replace and improve Energy optimization by
key manufacturing components through sensor analysis production optimization performance for high cost CMM (scans) predictive analytics
Cycle time optimization through big- Machine alarm aggregation, Digital dashboards to monitor OEE Automated in-line optical inspection to IIoT real-time energy data aggregation
data analytics on lines PLCs prioritization and analytics enabled performance replace end-product manual and reporting dashboard
Light-guided assembly sequence problem solving Digital twin for remote production inspections Sensor-based data collection for energy
Mixed reality to enable digital standard Predictive maintenance aggregating optimization Digital work instructions & quality management
work/trainings data based on historical and Enterprise Manufacturing Intelligence functions
sensor data system to upgrade operations Digitized standard procedures for line
Advanced IIoT applied to process
optimization Real-time pipeline cost optimization management operations with integrated workflow
based on edge sensors Integration platform to connect Mixed reality glasses to guide operators
Artificial Intelligence-powered process
control Remote assistance using machine-level data with enterprise- in the end-of-line inspection
augmented reality software Field quality failures aggregation,
Digital lean tools
(e.g., eKanban, eAndon, eSpaghetti) Analytics platform for deviation root- Real-time asset performance prioritization and advanced analytics
cause identification monitoring enabled problem solving
Artificial intelligence guided machine
and visualization IoT enabled manufacturing quality
performance optimization
Sensor-based manufacture KPI management
Digitally enabled variable takt time
reporting Digital quality audit
Digitally enabled modular production
Digital tools to enhance a connected Quality improvement by
configuration
workforce predictive analytics
Digital recruitment platform tailored to
shop floor
Digital twin of sustainability
Digitally enabled man-machine
matching
McKinsey & Company 5
Lighthouses are deploying 92 use cases with some focusing within the
manufacturing site and others on connecting the E2E value chain (2/2)
End-to-end value chain
Supply network connectivity E2E product development E2E planning E2E delivery Customer connectivity
Aggregate demand across end-to-end 3D printing for rapid design prototyping Predictive demand forecasting Dynamic delivery optimization Connected devices to track and
supplier network 3D simulations / digital twin for product Real-time S&OP Robotics enabled logistics execution measure consumer behaviors
Should-cost modeling to support make design and testing Real-time inventory management Digital track and trace Mass customization and B2C
versus Testing automation (internal / extremal) online ordering
Asset utilization and yard management
buy decisions Delivering to customers wherever they
Advanced analytics for performance Dynamic production scheduling with for logistics
Analytics driven procurement supported management across the idea digital twin are through new delivery solutions
No touch order management
by spend intelligence & automated to market Customer end-user interface to
Dynamic network optimization Digital enabled picking and transport
spend cube configure and order a product, and
Product development using robotics Predictive inventory replenishment
End-to-end real-time supply chain Predictive maintenance in fleet assets track delivery
Big-data / Al enabled product design Analytics for dynamic warehouse
visibility platform "Uberization' Of transport Smart / intelligent packaging
and testing resource planning and scheduling
Supplier and materials quality tracking ATP based on real-time constraints Customer analytics enabled by RFID
Virtual reality supported prototyping Dynamic simulation for warehousing
Part traceability from unique digital tag Digital logistics control tower Online communities for customer
Digital thread implementation through design
based on surface scanning insights
product development lifecycles No-touch master planning (allocation to
Digital supplier performance GPS based map and customer location
Rapid outsourced prototyping the plants)
management
Crowd-sourcing & competitions to Digital integrated business planning 3D printing
Artificial Intelligence to accelerate
develop digital solutions Closed loop planning Connected devices to track and
scaling of digital applications
measure product performance
across sites End-to-end real-time supply chain
visibility platform Digital Twin of Customer System
Joint data analytics with equipment
OEM for process optimization Advanced analytics to optimize
manufacturing and distribution footprint
Production planning optimized by
advanced analytics
McKinsey & Company 6
The gap between the frontrunners and the
majority continues to grow
~50
WEF lighthouses1
expected for 2020, first
Only a handful
lighthouses with impact
across the e2e network
vanguards went from
pilot to lighthouse and
are starting to scale
71% network-wide
of manufacturers stuck
2017 2018 2019 2020 in pilot purgatory
Manufacturers Initial 16 WEF 26 WEF Light-houses, several
experimenting Lighthouses, starting to scale, e.g.,…
with several e.g.,... Secret formula for
pilots
scaling business
Emergence of E2E connected WEF impact decoded
Lighthouses
1. Estimated based on pipeline of applications to the WEF
Source: World Economic Forum and McKinsey & Company McKinsey & Company 7To escape pilot purgatory, Lighthouses become the scale-up vehicle
for the entire company
Scale-up architecture Scale-up Unit
Lighthouses as scale-up vehicles Lighthouses create an MVP1 of the company wide IIoT operating system
One Company operating system
New way of working across value
IIoT/Data
systems Modernized IIoT stack & data model
Augmented-reality operators, allow cyber connection between reality
chains, people, assets and sites robotics, and leaned-out, (eg, shop-floor sensors) and IT
automated processes are systems, and agility to add use cases
simulated and optimized using in matter of weeks (technology
Few Lighthouses digital twin methodology Business Management democratization)
Integrated 20+ use cases that process systems
together innovate a value chain or
factory and allow to build the Upskilled workforce with FoW 2 Digital performance management—
ready profiles via an IIoT with AI-powered, personalized
infrastructure to scale dashboards and alerts—creates one
academy. Agile operating model People
fostered through agile digital source of truth and eliminates waste in
systems
50+ Use cases studio decision making
Digital innovations that change how
business/process is conducted
Scale-up enablers
500+ Deployments
Local transformations that innovate
Lighthouses build the infrastructure to scale
the way we work across the Agile approach IIoT stack IIoT academy
organization
Agile digital studio Tech ecosystem Transformation office
1. Minimum viable product
2. Future of work
McKinsey & Company 8Key enablers are the secret sauce to scaling fast
Scale-up enablers
Lighthouses build the infrastructure to scale
Lighthouses iterate quickly, fail fast, and learn continuously. Create minimum viable products (MVPs) in two-week sprints, and bundle
Agile approach
use-cases for fast transformations This agile approach stands in stark contrast to year-long pilots that are designed for perfection
Agile digital To be agile, co-location of translators, data engineers, ERP systems engineers, IIoT architects, and Data Scientists is key, as is
studio direction by product managers and an agile coach, who make sure that results are delivered in sprints and iterated fast
Lighthouses are preparing existing IT systems to design & modernize the next generation of technology capabilities, ensuring that
IIoT stack
selected IIoT architecture is sufficiently adaptable and future proof
Relationships supported by mutual exchange of large amounts of data and collaboration on technology platforms to facilitate the
Tech
exchange and consumption. This is a notable shift from the age-old idea of safeguarding technology solutions and data as a
ecosystem
competitive advantage
Given the need to reskill and upskill the workforce at scale, the development of effective learning methods focused on technology
IIoT academy becomes critical. Examples include gamification, digital learning pathways, VR/AR learning, and AR and digital custom real-time work
instructions
Transformation Lighthouses that achieve scale have established governance models to support best practice exchange and prioritization with a focus
office on impact and solutions, as opposed to focusing principally on technology
McKinsey & Company 9Though Lighthouses have a common set of value drivers - E2E
leaders deliver value in 3 distinct ways
Value drivers across both areas Value drivers in E2E Lighthouses Lighthouses
Technology democratization and Customer centricity
augmenting the operator By placing customers at the center of process design
Technology on the shop floor is transforming and operations, organizations are improving the initial
ways of working, as operators develop their purchase experience as well as use over the product
own apps and solutions to facilitate and lifetime
automate their tasks.
Seamless connectivity across functions
Big data decision-making
Seamless data exchange and transparency across
Decisions are not hypothesis-driven, but functions reduces friction, allowing for more efficient
rather are based on big data deciphered by decisions and reduction of redundant communications
pattern recognition – and not by humans.
Process and business model innovation
Continuous connectivity across organizations
Fourth Industrial Revolution technologies
enable the lighthouses to develop new 4IR technologies enable unprecedented data collection,
business models that complement and/or exchange, and processing; this allows organizations to
disrupt the traditional business and value create new ecosystems in the manufacturing space
chain.
Source: Fourth Industrial Revolution: Beacons of Technology and Innovation in Manufacturing McKinsey & Company 10Lighthouses are taking common actions to prepare their workforce
for change
Transforming the ways in which Lighthouses are successfully navigating these changes through 6
people work together as part of the common actions to maximize the potential of workers.
4IR transformation is essential
Lighthouses have invested in people
Keeping people at the center, empowering Empowering the front line to innovate, using technology and data
them to realize their full potential alongside
that of digital technology, demonstrates that
Proactively building capabilities, both technical and soft, and managing talent
true 4IR innovation is directly entwined with
people and that the Fourth Industrial
Revolution is, after all, a human enterprise
Adjusting the organizational structure to enable Fourth Industrial Revolution
transformation
Implementing new ways of working such as agile and increased transparency
Improving day-to-day assembly and operating tasks through automation and
technology
Increasing levels of problem solving and collaboration on the front line
McKinsey & Company 11“From-To” illustrates these common actions impacting front-line
workers’ daily work and engagement (1/2)
Example
lighthouses From To
Empowering the Innovation in my production line is generated from the I own innovation in my production line—we all come up with ideas
front line to top
innovate, using
I always see scorecards measuring the same KPI—but All our scorecards are based on data from a single source that now
technology and with different numbers we all use to make decisions
data
I spend my time confirming data accuracy and My data is tracked automatically from hundreds of sources and feeds
inputting it into multiple report templates real-time into scorecards
Proactively building I learn the basics to perform my job, but have limited I have a customized reskilling program, adjusted for my abilities with
capabilities, both opportunities to develop other skills digital technologies and accelerated multiskilling
technical and soft,
My company relies on our internal knowledge and My company uses innovative external methodologies for training,
and managing talent experience to train our team, and it is limited to the first blending on-the-job coaching, rotations, augmented reality, and
week on the job virtual stations or a digital learning center
The talent-management system is one-size-fits-all, Partnerships with universities and other companies offer new
relying on expertise learning opportunities to learn from others, as part of an online
platform with an individual training journey
Adjusting the I see many silos between IT functions and operations We have new cross-functional team focusing on digital deployment
organizational
structure to enable My team is production only—we only focus on running My team merges production and maintenance, with technicians and
equipment operators running automated operations
4IR transformation
McKinsey & Company“From-To” illustrates these common actions impacting front-line
workers’ daily work and engagement (2/2)
Example
lighthouses From To
Implementing new Solution development is finished outside of our To develop a fit-for-purpose product, the agile team involves us early
ways of working operations before being tested in minimum viable product (MVP) development, though sprint review
such as agile and
increased My discussion with my supervisor is based on the last My discussion with my supervisor uses real-time and relevant data
transparency hour or day with limited data that does not help us for the losses we are having, so we can diagnose root causes and
problem solve—so its mostly just a review make decisions quickly
Improving day-to- More than 90% of my shift tasks are repetitive and For basic tasks, I have help from automation and cobots
day assembly and manual
operating tasks
through automation I rely on few support tools, mostly paper standard I have digital tools for real-time help (electronic SOPs, augmented
and technology operating procedures (SOPs) reality)
I can only manage a few machines since they have My machines are self-learning with automated centerlining and other
frequent breakdowns, and I have to make adjustments settings, which eliminates most breakdowns and allows me to track
based on my experience more machines in parallel
Increasing levels of I spend most of my time gathering data, yet most I have relevant data available in a centralized source to use when
problem solving sessions lack all relevant data needed
and collaboration
on the front line Decisions in my line typically are based on experience, My team relies on self-diagnosing machine-based data to make
not data decisions
McKinsey & CompanyScale-Up enablers Value Drivers
Technology democratization and
Agile digital studio
augmenting the operator
Agile approach Big data decision-making
Appendix – Process and business model
IIoT stack
Case studies innovation
Tech ecosystem Customer centricity
Seamless connectivity across
IIoT academy
functions
Continuous connectivity across
Transformation office
organizations
McKinsey & Company 14Schneider electric case example for Continuous
Digital technology improves connectivity Connectivity across organizations
throughout the value chain allowing organizations
to minimize the effects of deviations in production
Schneider Electric in Batam has created a platform for stakeholders to monitor and
adjust to anomalies within its manufacturing processes
One Communication Portal
used by all suppliers to communicate
Key Impacts
operational capabilities enabling better +70% Supplier service rate
supply chain planning
-85% Administration time
+40% On-time delivery
IIOT Platform Supplier Portal QR Code
Monitors and transfers Communicates demand Aids company and
real-time data to supplier forecasts to suppliers facilitating suppliers to effectively track and
informing any variations in more efficient inventory trace inventory throughout the
production planning at the suppliers’ value chain
locations
Source: https://www.computerweekly.com/news/252451662/Inside-Schneider-Electrics-Batam-smart-factory; Site Visit Report McKinsey & Company 15The right portfolio of interconnected Nokia Case example for agile working mode
technologies enables operational agility
while minimizing efficiency costs
Automated Ex. Impact on KPIs
VR Flexible Robotics
Internal Logistics Produc-
Virtualization of R&D Rapid line changes to Standardized point of tion lead-
-80%
speed up NPI achieved use stock replenishment time
Lessens time to market
and helps identify through modularity through automation
quality issues early Multi-skill robotics to No touch material
ensure flexibility in use handling
Standard
unit per +90%
Wireless network & cloud infrastructure FTE
Robust private cellular network infrastructure allows for all machines to be upload and
download data seamlessly
Enables plug and play of machines without rewiring LAN
Process
Data from the cloud is inputted into analytics platforms to identify inefficiencies and -50%
quality
correct those through planning
(PPM)
2016 17 18 2019
McKinsey & Company 16Fast Radius case Example for Integrated
Digital planning overcomes inefficiencies by data backbone
leveraging total data transparency across
functions to make holistically efficient decisions
Design Testing Production Shipment
Key Impacts
Analytics platform captures data throughout the process -36% inventory reduction
Analytics platform utilizes multiple machine learning algorithms to provide -90% time to market
Digital Twin
specific feedback to all segments of the value chain
for Remote
Production Empowers root cause problem solving across all functions by utilizing
the feedback to work on the deficient areas
Production can be The platform is enabled by an open communication protocol between all of
viewed across all sites the factory’s sensors in the line and the central cloud data storage
Allocates job to the site Reduced amount of quality issues and rework based on improved design
while solving for from data feedback loop
logistics and capacity
of the sites
McKinsey & Company 17Organizations place customer experience at the
Haier Case Example for customer centricity
core of their strategy and utilize technology to
establish a link with performance management
Haier’s air conditioning unit is achieving its transformational goal of moving from a one-time
customer mindset to a lifetime user mentality by utilizing digital technology to connect customer
experience with daily operations
Key Impacts
Real-time +21% quality improvement
Data Monitor
+63% in labor productivity
Customer PM analyzes
unit performance data -50% customer PM FTE
and any deterioration in
Product Purchase performance is Team/Dept. Issue Solved Lessons Applied -33% lead time
reported
Using interactive With the data provided from the system, the root cause of the customer’s
platform, customer issue can be addressed
customizes and places
If production worker error caused the fault, the appropriate individual’s
order
Customer Complaint record will be updated in the shop floor bonus system accordingly
If part error, parts will be examined to determine appropriate course
Customer calls with any issues and the of action
data engine retrieves the performance
data from unit serial number
McKinsey & Company 18SAIC Maxus case Example for customer centricity
E2E Lighthouses continue to generate value outside
the four walls by creating solutions that enable a
differentiated customer centric experience
SAIC Maxus is utilizing digital solutions to revolutionize the mass production of mass customized
vehicles to provide unprecedented service to the customers
Key Impacts
-35% Time to market
Online Digital Supply Smart Quality
-20% Production lead time
Platform Digital Twin Chain Engineering Assurance
99.8% Configuration
Customer uses 3D simulation to Car configuration Automated AI tool accuracy
web app to configure car as and production system continuously
customize, order, per customer queue are differentiates checks build -30% Tooling and
and track status order transmitted to thousands of progress to changeover
supplier to initiate configurations to identify errors
Just-in-Sequence confirm correct
shipment build
McKinsey & Company 19Schneider Electric Case Example for Seamless
As organizations foster cross function connectivity across functions
collaboration, they are able to achieve impact at
scale rapidly
Integrated cross-
Siloed Teams Enabled by “transformation group leader”
functional teams
Transformation group was composed
IT
of participants from every function ensuring Key Impacts
collaboration throughout the transformation
PRODUCTION
+12% operational efficiency
Collaboration is enabled by a universal technology
platform, EcoStruxure, with custom app development
-44% machine downtime
PRODUCT
DESIGN that can be plugged-in to the ecosystem PRODUCT
DESIGN
Change management program effectively leveraged
PRODUCTION the collaboration to establish IT
Quick pilot to scale-up cadence MAINTENANCE
MAINTENANCE
McKinsey & Company 20Phoenix Contact Case Example for Seamless
Digital connectivity enables an integrated and trans-
connectivity across functions
parent operating model that results in value creation
greater than the sum of each step in the value chain
Phoenix Contacts uses RFID tags that carry information ensuring transparency and accessibility of
data to all steps of the process
Key Impacts
24/7 running of the line
Product Testing Production Delivery +40% performance
Design
Up to -30% production time
Unique products at cost of
mass production
Machine building department acts as R&D All the testing data is Customer information and delivery
facility for rapid introduction of new solutions recorded and passed details are known by production
Digital twin contains all testing specifications along to the team and conveyed to the
production team customer for real-time order status
McKinsey & Company 21Zymergen case Example for Seamless connectivity
When utilizing a single repository of data, analytics
across functions
and big data can effectively plan across functions
and contribute to connectivity
Zymergen is employing advanced analytics and automation to digitize the traditional method of
performing lab works
Key Impacts
+46% labor efficiency
Sensor Central Data Digital Work Digital Work Modular
-42% operating cost
Network Lake Scheduling Instructions Automation
-50% lead time
Sensors at all All data stored in System analyzes Cloud held data In-house
processes collect one location and capacity, machine used to generate developed robots +40% line yield
data and verify effectively used breakdown times, work instructions capable of using
that the process across processes and inventory to for operators and standard work
parameters are to improve schedule work machines to tools are reliable
being met connectivity centers and avoid greatly improve operators and
costly errors throughput rate significantly cut
costs
McKinsey & Company 22The Global Lighthouse Network is a community of production sites and other
facilities that are world leaders in the adoption and integration of the cutting-
edge technologies of the Fourth Industrial Revolution (4IR).
Lighthouses apply 4IR technologies such as artificial intelligence, 3D-printing
The Global and big data analytics to maximize efficiency and competitiveness at scale,
Lighthouse transform business models and drive economic growth, while augmenting the
workforce, protecting the environment and contributing to a learning journey
Network for all-sized manufacturers across all geographies and industries.
The Global Lighthouse Network is a World Economic Forum project in
collaboration with McKinsey & Co, and the factories are chosen by an
independent panel.
Find out more: https://www.weforum.org/projects/technology-and-innovation-
for-the-future-of-production
McKinsey & Company 23Want to
learn more?
Read the summary report at
https://mckinsey.com/business- Enno de Boer Yves Giraud Ingrid Millan
functions/operations/our- Lead Partner Expert Associate Partner
insights/industrys-fast-mover-
advantage-enterprise-value-
from-digital-factories
Read the full report at
weforum.org/whitepapers/fourth
-industrial-revolution-beacons-
of-technology-and-innovation-
in-manufacturing
Julian Salguero James Hoch Katy George
Partner Engagement Manager Senior Partner
McKinsey & Company 24You can also read
