Supply Chain Management

Case Study Assignment on

Mckinsey - Improving
warehouse operations digitally

PRESENTED BY:
GAURAV TANDEL - 1912040
VAISHAK GOKUL - 1912026
SYED MUHAMMAD HUSSEIN - 1912053
Case Objective

Tackling a structural change without

affecting day to day operation of a
company by taking advantage of
technology in order to increase its
operating efficiency.
• Creating a digital twin of warehouse
in order to increase efficiency by 20-
25% without effecting day to day
operations of a company
 Industry operated : Management
consultancy

Founder : James O. Mckinsey

About the
Company Total revenue - $10+ billion

•McKinsey & Company provides strategy and

management consulting services, such as
providing advice on an acquisition, developing
a plan to restructure a sales force, creating a
new business strategy or providing advice on
downsizing.

•McKinsey's cliente includes 80% of the world's

largest corporations, and an extensive list of
governments and non-profit organisations.
Acquisitions Investments
Competitors
 KEY ISSUE
SKU mix Order and Seasonal demand FACED IN
Shipment profiles spikes
WAREHOUS
E
OPERATION
Productivity Automation Warehouse S
Initiatives options layouts
ISSUES IDENTIFIED IN THE CASE

A North American Manufacturer

• Decided to consolidated several regional manufacturing and warehouse locations into a single
campus with separate buildings dedicated to manufacturing and warehousing.
• Faced challenges such as capital constraints, insufficient warehouse space and a need to move fast.
SOLUTION
• The company used a digital warehouse-design approach to simulate various options across
warehousing.
OUTCOME
• The digital tools allowed the company to develop detailed OPEX and CAPEX estimates for both
manual and automated solutions.
• The company reduced planned capex by approximately 10 percent and operating expenses by more
than 30 percent.
ISSUES IDENTIFIED IN THE CASE
Company Rethinking Existing Facility
• Company deployed digital warehouse-design and simulation tools to optimize and revamp its operations in a
warehouse currently in operation.
• It built models to test various layouts, material handling-flow scenarios, picking methods, and targeted
automation solutions.
SOLUTION
• The company used a digital warehouse-design approach to simulate various options across warehousing.
• Starting from an optimized slotting design, the digital twin analyzed historical orders to estimate the exact labor
and equipment requirements by day of the week and by hour of the day.
OUTCOME
• With accurate labor-staffing models, the company was able to choose the most optimal, modular design to
implement during the transition.
• The company defined precise, engineered standards for each operation of the warehouse, and it could monitor
daily labor and equipment performance once the new system was in place.
• This enabled the company to reduce annual operating expenses by 18 percent.
ISSUES IDENTIFIED IN THE CASE

Business with several millions of annual costs

• A business company with a central regional warehouse in Eastern Europe with several millions of
annual costs.
SOLUTION
• The company used a digital warehouse-design approach to simulate various options across
warehousing.
• By constructing a digital twin, the company analyzed the potential improvements from a proposed
layout change (specifically, a picking zone that enabled one-step picking).
OUTCOME
• Looking at both high-season and low-season volume, the company determined that it could reduce
input costs by more than 25 percent.
Foundational Capabilities

• Unlike most technologies, DIGITAL TWIN in not the turnkey solution.

• To capture its full potential, companies must understand their strategy not only for
today and tomorrow, but also well into the future.
• Success requires new capabilities in warehouse design—typically engineers who
understand the range of variations and permutations for a space.
• As a practical matter, the simulation process must involve operations and
warehouse managers those with the deep day-to-day knowledge and real-world
insights that can only come from direct experience.
• Companies need to plan for repeated changes over time. Optimizing warehouse
performance is a process without a finish line—it must happen again and again, as
market forces, technology, and consumer preferences continue to evolve.
• Companies face a growing need to improve their warehouse operations. Digital
warehouse design is one clear means to help them do so.
• The process may be virtual, but the results generate a real impact on performance,
providing an edge in an ever-more-complex warehousing landscape.
 The keys to success
McKinsey & Company made the technology-supported changes that lead them to success due to digital
transformations and following are those that best explain the success of an organization:
Culture and Change

• McKinsey have distinctive knowledge, tools and expertise to help

large organizations design and implement major change programs,
where business results are dependent on people shifting their day-
to-day behaviours and mindsets to drive value. Their experience
and attentive approach help clients to shape its success programs
and build cultures of continuous improvement. Specifically, when
they work closely with clients to:

• Strengthen organizational health:

• Shape and deliver transformational change
• Shift behaviour to shape organizational culture
• Help leaders become models for change
• Convene leaders and share insights
 Challenge
• A retail company needed to improve the
overall flow of products in one of its fresh
food warehouses, which operates in a 24/7
schedule, whilst leveraging its global
efficiency and maintaining the freshness of
its products. For this purpose they were
provided two alternative layouts, McKinsey
main goals were:
• To understand each layouts strong points
and limitations
• To assure a high service level and the
flexibility of the operation
• To follow the different performance
indicators for the current and the alternative
layouts.
Solution
• Aiming to tackle the retailer's problem, a
digital twin technology was used to accurately
to simulate the current operation.
Subsequently, modifications were made in the
model to evaluate the two proposed
alternative layouts. Each layout was tested for
distinct levels of affluence and for various
scenarios, in order to better understand the
warehouses congestion levels and how each
layout impacts the company's key performance
indicators.
• All the main indicators obtained from the
simulation models were gathered and
delivered to the retailer, therefore leveraging a
more accurate, data-driven decision regarding
the distinct layouts.
 Results
• Through the digital twin technology, the retailer obtained
a bird's eye view and a detailed-view of the warehouse
operation.
• The project not only conveyed a new perspective on the
current functioning of the warehouse, but it also allowed
a thorough analysis of the main performance indicators
for the three layouts.
• The project demonstrated that digital twin's technology
may help developing risk-free approaches for testing in
an agile way, different layouts and scenarios.
• Hence, instead of time-consuming and costly real-life
experiments, a model was created to aid decision making,
while allowing a better perception on the future
evolution of the company.
 Conclusion
• When Digital Twin technology in simulating warehouse design and
operation is implemented, companies can design, simulate and test new
warehouse operations and product movements virtually, without
making any changes to existing sites, which are becoming increasingly
complex. The technology is also proving to be success for businesses in
opening new warehouses or making any changes in existing ones and as
new automation systems is applied companies can virtually see what
kind of impact they can generate on workflows and which can be easily
optimized without any shutdowns
• McKinsey Digital twins in simulating warehouse design and operation
can lead to efficiency gains of 20 to 25 percent, before any money has
even been spent. But in some cases, incorrect or inappropriate
automation can create more problems than it solves.
• Digital modelling lets companies see what is possible from a range of
technologies and applications before they make any investment
decisions
THANK YOU