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Value-driven
warehouse
automation
A new approach to warehouse
operations that maximizes returns
from digital investments
Between 2015 and 2019:
Investment in warehouse
automation is now essential
In 2020
+
Rapid growth of
ecommerce
‘lot size one’ production
demands
= $11 billion
average investment annually into
warehouse automation
34%
Addressing new and changed business requirements
Labor availability
constraints 61%
Source: Accenture’s 2020 Supply Chain Survey
Increasing velocity, volume and throughput of work
55%
COVID-19 amplified both labor shortages and the pressure
on global logistics networks, spurring even more
investment into warehouse automation
Top three drivers for automation and robotics in warehouses
The right level of automation and autonomy
will not only enable faster, safer, and more
efficient day-to day warehouse operations.
It will also cut costs and improve delivery
times, creating a faster, leaner, more scalable,
and sustainable operation, ultimately
providing the end-consumer with loyalty-
driving level of service expected in this on-
demand economy.
Autonomous warehouse
systems are on the rise
Conveyor
belts
Autonomous
mobile robots
Shuttle
systems
Fully-
autonomous
robots
Mobile
manipulation
robots
&
Drone-based
surveying
systems
Goods-to-person
picking systems
Robotic
product-handling
Advanced
robotic
imaging
Forklift
trucks
Sortation
system
Pallet cranes/
automated
high-bay
1920’s
1950’s
1970’s
Laser-
guided
AGVs
1990’s
2000’s
2004
2005
2020+
2018
2015
2010’s
1910’s
The rate of innovation
in warehouse automation
technologies
Distracted by the latest shiny
objects, companies choose
technologies irrespective of the
needs of their warehouses or the
types of operations at play,
resulting in point solutions.
Into the Mousetrap:
Companies are struggling to build the right solutions
To justify returns, they apply
technologies that are
familiar and deliver quick
wins but fail to achieve the
scalability required to drive
strategic returns. As a result,
the full potential of human
and machine collaboration
remains untapped.
Copyright © 2021 Accenture. All rights reserved.
A new path forward
for warehouse automation
5
1. Align around a broader vision
Re-evaluate the relevance and role warehouses are expected to
play in overall supply chain strategies.
2. Avoid one-size-fits-all solutions
Categorize warehouses based on the complexity of operations
and labor intensity requirements to identify the right technology
solutions.
3. Measure all that matters
Identify and include the less obvious but vital returns when
calculating ROI.
4. Build digital architecture for end-to-end
connectivity
Integrate and combine technologies to facilitate impactful
automation and autonomy.
Do I need as-a-
service or buy
options when it
comes to my
technology
choices?
Is the set-up
scalable?
Have I
evaluated the
warehouse
processes and
flows to
eliminate
unnecessary
movements?
Have I
evaluated the
rent vs buy vs
lease options?
Is the
warehouse
strategically
located?
Does our
warehouse
strategy align to
the value our
business aims
to deliver?
Re-evaluate the relevance and role
warehouses are expected to play in
overall supply chain strategies
Step 1:
Align around a broader vision
Fundamental Questions:
Step 2:
Avoid one-size- fits-all
solutions
Workforce intensity
Warehouse
operations
High
complexity
Low
complexity
Low-labor intensive High-labor intensive
Low scale operations
that have standardized
processes which are not
highly labor intensive
E.g.: Micro-fulfilment center
• Lower number of SKUs and low
complexity
• Manual or mechanized processes
• Resource engaged in mundane and
repetitive tasks
• Low space availability requires just in
time inventory management
Medium to large sized
operations that have
standardized processes
but require more labor to
handle the operations
E.g.: Distribution center
• Processes are standardized but require
high dependency on labor
• Size of the workforce is difficult to
manage
• Labor is engaged for cleaning and
maintenance tasks
• Resource engaged in mundane and
repetitive tasks
Large scale operations
with less complex
assortment of SKUs to be
sorted, compiled and
shipped in time
E.g.: Centralized distribution
center/ production warehouse
• Complex assortments lead to high
error rate
• Large size of operations could result in
fatigue and lower productivity
• Low-labor results in longer lead time
• Finding the right skills to match the
complexity a challenge
Mammoth scale
operations and highly
differentiated
assortment of SKUs that
needs to be handled in
time and at speed
E.g.: Mega fulfilment center
• Maintaining end-to-end visibility on
operations can be a task
• Tracking SKUs and labor both becomes
an effort
• Peak season labor requirements
become difficult to arrange for quickly
II
I
IV
III
Categorize warehouses based on the
complexity of operations and labor
intensity requirements to identify the
right technology solutions
Step 3:
Measure all that matters
Identify and include the less obvious
but vital returns when calculating ROI.
Executives must include less obvious,
non-traditional metrics when
calculating ROI to deliver a more
‘balanced’ view of value.
Warehouse Executive, multinational medical
device manu
facturer
Integrate and combine
technologies to facilitate
impactful automation and
autonomy
To generate desired returns
from warehouse automation
investments, companies
must design the right the
digital architecture for their
warehouses.
Step 4:
Build digital architecture for end-to-end connectivity
Generate
intelligence
with data on
the Cloud
Enable
autonomy in
processes
and systems
Create
collaborative
harmony
between
humans and
machines
Build the foundation with data on the cloud
Old approaches towards deploying new technology solutions will not deliver the desired
levels of return. It’s time for a greater strategic shift. The value is clearly already there to
be unlocked. Follow the new approach to warehouse automation to unlock untapped,
unprecedented gains.
Painting a bigger picture
• Deploy robotic technologies as
a solution to elevate the human
workforce to more value-
added tasks
• Build a responsible, cleaner,
safer, healthier workplace
using robotic technologies
• Upskill the workforce to create
more meaningful and fulfilling
warehousing careers
• Invest in technologies that
converge to create the right
digital architecture
• Have a clear plan to integrate
legacy infrastructure with new
technologies
• Identify the right platform to
enable greater autonomy
• Hidden, non-traditional
metrics must be considered
while calculating returns
• Significant weightage should
be given to the not-so-obvious
gains when making digital
investment decisions
• Due diligence around the
size, scale and purpose of
operations must be done.
• Warehouses must be
categorized based on our
warehouse classification
model.
• The role and function of
the warehouse must be
re-evaluated, considering
changing business models and
customer expectations
• Fundamental questions around
warehouse size, scale, location,
and scalability need to be
addressed in advance
Visualize
Broader business
alignment
Strategize
Solutions based on
warehouse category
Analyze
The not-so-obvious
returns
Integrate
The right digital
architecture
Execute
Human-machine
collaborative harmony
• Deploy robotic technologies
as a solution to elevate the
human workforce to more
value- added tasks
• Build a responsible,
cleaner, safer, healthier
workplace using robotic
technologies
• Upskill the workforce to
create more meaningful and
fulfilling warehousing careers
• Invest in technologies that
converge to create the right
digital architecture
• Have a clear plan to integrate
legacy infrastructure with
new technologies
• Identify the right platform
to enable greater autonomy
• Hidden, non-traditional
metrics must be considered
while calculating returns
• Significant weightage should
be given to the not-so-
obvious gains when making
digital investment decisions
• Due diligence around the size,
scale and purpose of
operations must be done.
• Warehouses must be
categorized based on our
warehouse classification
model.
• The role and function of
the warehouse must be
re-evaluated, considering
changing business models
and customer expectations
• Fundamental questions around
warehouse size, scale,
location, and scalability need
to be addressed in advance
A framework to maximize value from warehouse automation
Visualize
Broader business
alignment
Strategize
Solutions based on
warehouse category
Analyze
The not-so-obvious
returns
Integrate
The right digital
architecture
Execute
Human-machine
collaborative harmony
Authors
Antoine Martin
Managing Director – Autonomous
Robotic Systems Global Lead, Industry X
antoine.martin@accenture.com
Key Contributors
Prabhakar R. Katta
Pierre J. Mawet
Acknowledgements
Prashant Bhamidipati
Steven Osburn
Lyes Ould Hamouda
Gregory P. Spata
Rajesh A. Rangaswamy
Vinicius Mascarenhas
Mohammed Hajibashi
Ashwani Tripathi
Zubair Ahmed
Ignacio González de la Vega
Maria Rey-Marston
Rushda Afzal
Manager– Digital Transformation Research and
Detroit InnovationCenter Research Lead,
Industry X
rushda.s.afzal@accenture.com
Ida Nair Sharma
Research Specialist – Digital Manufacturing and
Operations,Industry X
ida.nair.sharma@accenture.com
Umesh Inamdar
Associate Director – Digital Transformations and
Detroit InnovationCenter Lead, Industry X
umesh.j.inamdar@accenture.com
Martin Brickell
Principal Director – Physical Logistics &
Fulfillment Practice Lead, SupplyChain and
Operations
martin.brickell@accenture.com
Raghav Narsalay
Managing Director – Global Research Lead,
Industry X
raghav.narsalay@accenture.com

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Value-driven Warehouse Automation | Accenture

  • 1. Copyright © 2021 Accenture. All rights reserved. 1 Value-driven warehouse automation A new approach to warehouse operations that maximizes returns from digital investments
  • 2. Between 2015 and 2019: Investment in warehouse automation is now essential In 2020 + Rapid growth of ecommerce ‘lot size one’ production demands = $11 billion average investment annually into warehouse automation 34% Addressing new and changed business requirements Labor availability constraints 61% Source: Accenture’s 2020 Supply Chain Survey Increasing velocity, volume and throughput of work 55% COVID-19 amplified both labor shortages and the pressure on global logistics networks, spurring even more investment into warehouse automation Top three drivers for automation and robotics in warehouses
  • 3. The right level of automation and autonomy will not only enable faster, safer, and more efficient day-to day warehouse operations. It will also cut costs and improve delivery times, creating a faster, leaner, more scalable, and sustainable operation, ultimately providing the end-consumer with loyalty- driving level of service expected in this on- demand economy. Autonomous warehouse systems are on the rise Conveyor belts Autonomous mobile robots Shuttle systems Fully- autonomous robots Mobile manipulation robots & Drone-based surveying systems Goods-to-person picking systems Robotic product-handling Advanced robotic imaging Forklift trucks Sortation system Pallet cranes/ automated high-bay 1920’s 1950’s 1970’s Laser- guided AGVs 1990’s 2000’s 2004 2005 2020+ 2018 2015 2010’s 1910’s The rate of innovation in warehouse automation technologies
  • 4. Distracted by the latest shiny objects, companies choose technologies irrespective of the needs of their warehouses or the types of operations at play, resulting in point solutions. Into the Mousetrap: Companies are struggling to build the right solutions To justify returns, they apply technologies that are familiar and deliver quick wins but fail to achieve the scalability required to drive strategic returns. As a result, the full potential of human and machine collaboration remains untapped.
  • 5. Copyright © 2021 Accenture. All rights reserved. A new path forward for warehouse automation 5 1. Align around a broader vision Re-evaluate the relevance and role warehouses are expected to play in overall supply chain strategies. 2. Avoid one-size-fits-all solutions Categorize warehouses based on the complexity of operations and labor intensity requirements to identify the right technology solutions. 3. Measure all that matters Identify and include the less obvious but vital returns when calculating ROI. 4. Build digital architecture for end-to-end connectivity Integrate and combine technologies to facilitate impactful automation and autonomy.
  • 6. Do I need as-a- service or buy options when it comes to my technology choices? Is the set-up scalable? Have I evaluated the warehouse processes and flows to eliminate unnecessary movements? Have I evaluated the rent vs buy vs lease options? Is the warehouse strategically located? Does our warehouse strategy align to the value our business aims to deliver? Re-evaluate the relevance and role warehouses are expected to play in overall supply chain strategies Step 1: Align around a broader vision Fundamental Questions:
  • 7. Step 2: Avoid one-size- fits-all solutions Workforce intensity Warehouse operations High complexity Low complexity Low-labor intensive High-labor intensive Low scale operations that have standardized processes which are not highly labor intensive E.g.: Micro-fulfilment center • Lower number of SKUs and low complexity • Manual or mechanized processes • Resource engaged in mundane and repetitive tasks • Low space availability requires just in time inventory management Medium to large sized operations that have standardized processes but require more labor to handle the operations E.g.: Distribution center • Processes are standardized but require high dependency on labor • Size of the workforce is difficult to manage • Labor is engaged for cleaning and maintenance tasks • Resource engaged in mundane and repetitive tasks Large scale operations with less complex assortment of SKUs to be sorted, compiled and shipped in time E.g.: Centralized distribution center/ production warehouse • Complex assortments lead to high error rate • Large size of operations could result in fatigue and lower productivity • Low-labor results in longer lead time • Finding the right skills to match the complexity a challenge Mammoth scale operations and highly differentiated assortment of SKUs that needs to be handled in time and at speed E.g.: Mega fulfilment center • Maintaining end-to-end visibility on operations can be a task • Tracking SKUs and labor both becomes an effort • Peak season labor requirements become difficult to arrange for quickly II I IV III Categorize warehouses based on the complexity of operations and labor intensity requirements to identify the right technology solutions
  • 8. Step 3: Measure all that matters Identify and include the less obvious but vital returns when calculating ROI. Executives must include less obvious, non-traditional metrics when calculating ROI to deliver a more ‘balanced’ view of value. Warehouse Executive, multinational medical device manu facturer
  • 9. Integrate and combine technologies to facilitate impactful automation and autonomy To generate desired returns from warehouse automation investments, companies must design the right the digital architecture for their warehouses. Step 4: Build digital architecture for end-to-end connectivity Generate intelligence with data on the Cloud Enable autonomy in processes and systems Create collaborative harmony between humans and machines Build the foundation with data on the cloud
  • 10. Old approaches towards deploying new technology solutions will not deliver the desired levels of return. It’s time for a greater strategic shift. The value is clearly already there to be unlocked. Follow the new approach to warehouse automation to unlock untapped, unprecedented gains. Painting a bigger picture • Deploy robotic technologies as a solution to elevate the human workforce to more value- added tasks • Build a responsible, cleaner, safer, healthier workplace using robotic technologies • Upskill the workforce to create more meaningful and fulfilling warehousing careers • Invest in technologies that converge to create the right digital architecture • Have a clear plan to integrate legacy infrastructure with new technologies • Identify the right platform to enable greater autonomy • Hidden, non-traditional metrics must be considered while calculating returns • Significant weightage should be given to the not-so-obvious gains when making digital investment decisions • Due diligence around the size, scale and purpose of operations must be done. • Warehouses must be categorized based on our warehouse classification model. • The role and function of the warehouse must be re-evaluated, considering changing business models and customer expectations • Fundamental questions around warehouse size, scale, location, and scalability need to be addressed in advance Visualize Broader business alignment Strategize Solutions based on warehouse category Analyze The not-so-obvious returns Integrate The right digital architecture Execute Human-machine collaborative harmony • Deploy robotic technologies as a solution to elevate the human workforce to more value- added tasks • Build a responsible, cleaner, safer, healthier workplace using robotic technologies • Upskill the workforce to create more meaningful and fulfilling warehousing careers • Invest in technologies that converge to create the right digital architecture • Have a clear plan to integrate legacy infrastructure with new technologies • Identify the right platform to enable greater autonomy • Hidden, non-traditional metrics must be considered while calculating returns • Significant weightage should be given to the not-so- obvious gains when making digital investment decisions • Due diligence around the size, scale and purpose of operations must be done. • Warehouses must be categorized based on our warehouse classification model. • The role and function of the warehouse must be re-evaluated, considering changing business models and customer expectations • Fundamental questions around warehouse size, scale, location, and scalability need to be addressed in advance A framework to maximize value from warehouse automation Visualize Broader business alignment Strategize Solutions based on warehouse category Analyze The not-so-obvious returns Integrate The right digital architecture Execute Human-machine collaborative harmony
  • 11. Authors Antoine Martin Managing Director – Autonomous Robotic Systems Global Lead, Industry X antoine.martin@accenture.com Key Contributors Prabhakar R. Katta Pierre J. Mawet Acknowledgements Prashant Bhamidipati Steven Osburn Lyes Ould Hamouda Gregory P. Spata Rajesh A. Rangaswamy Vinicius Mascarenhas Mohammed Hajibashi Ashwani Tripathi Zubair Ahmed Ignacio González de la Vega Maria Rey-Marston Rushda Afzal Manager– Digital Transformation Research and Detroit InnovationCenter Research Lead, Industry X rushda.s.afzal@accenture.com Ida Nair Sharma Research Specialist – Digital Manufacturing and Operations,Industry X ida.nair.sharma@accenture.com Umesh Inamdar Associate Director – Digital Transformations and Detroit InnovationCenter Lead, Industry X umesh.j.inamdar@accenture.com Martin Brickell Principal Director – Physical Logistics & Fulfillment Practice Lead, SupplyChain and Operations martin.brickell@accenture.com Raghav Narsalay Managing Director – Global Research Lead, Industry X raghav.narsalay@accenture.com