4. • Constant arrival and service time
• Customers will arrive 30 seconds apart
• Each one will be served a standard product
– (Pretty) constant serving time
– 25 seconds
Waiting Line Situation One
0 30 60 90 120
1st customer 2nd customer 3rd customer 4th customer
1st customer 2nd customer 3rd customer 4th customer
There is no waiting!
5. • Constant service and random arrival time
• Average arrival rate is still the same
Waiting Line Situation Two
0 30 60 90 120
1st customer
2nd customer
enters
1st customer
2nd customer
3rd
customer
4th customer
wait
wa
it
3rd customer
enters
4th customer
enters
There is some waiting!
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The flaw of averages
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The flaw of averages
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What is simulation?
Simulation is the imitation of the operation of a
real-world process or system over time. The act
of simulating something first requires that a model
be developed; this model represents the key
characteristics or behaviors/functions of the
selected physical or abstract system or process.
The model represents the system itself, whereas
the simulation represents the operation of the
system over time.
10. Variability: Where It Comes From
ProcessingBuffer
Input
Random arrivals
(randomness is the rule,
not the exception)
Incoming quality
Product mix
Processing times
Inherent variation
Lack of procedures
Quality (scrap/rework)
Resources
Breakdowns/Maintenance
Operator absence
Setup times
Routing
Variable routing
Dedicated resources
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When to Use Simulation
Looking
Back Looking
Forward
It is desirable to understand the impact of a change to a policy, a
business process, or a space layout – before you implement.
Simulation enhances your existing decision making process.
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Situations For Simulation
• Average is not enough
• Complex process
• Many possible input variables
• Dependent relationships between variables
• Need a “Sand Box” test environment
• Risky (potential danger)
• Expensive (moving equipment, building walls)
• Time & Resource (running many tests to find the optimum)
• Rare occurrence (extremely high demand, disaster response)
• Data constraints (estimational, not available, or “dirty”)
• Stakeholder engagement (visualize the future in order to gain buy-in)
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The benefits of simulation
Risk- Free
Uses data
intelligently
Increases
confidence in
decision
making
Test and
compares
potential
solutions
More
accurate
than a
spreadsheet
Models
variability
Simulates
the passing
of time
Visual-
Engages
Stakeholders
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Applications
Simulation is used to answer “What If” questions
about processes in many areas, including:
Revenue Cycle
Capacity
Lean & Six
Sigma
Supply Chain
Staffing
Operations
Throughput
Scheduling
Patient Delays &
Wait Lists
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Strategic Planning
Make sure you have enough
capacity before you build.
Visualize how processes will
flow in a new floor plan.
AND
Test everyone’s ideas in a
virtual environment.
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Essentials in a simulation project
• Problem statement
• Process details
– Process maps
– Data
– Rules
• Measures of success/failure
• (List of scenarios to test)
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These questions need to be answered before you
can begin to build a simulation.
1. What is the question you want to answer?
2. How will you measure performance?
3. What are your levers (variables)?
Scope Definition
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Data Accuracy Requirements
How much data do you need in order to build a reasonable simulation?
Approximation is often beneficial
for the first phase of a project:
• Minimal need for data
collection and analysis.
• Can be provided by
stakeholders.
• Easy to understand and
communicate.
• Represents a typical
day/patient/event, rather
than uncommon events.
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Requirements for Process Simulation
• Accurate & agreed process definition
• Accurate process times (especially bottlenecks)
• Accurate resource definition (who does what)
• Availability (people) and Downtime (equipment)
• Undisclosed quality issues (rework)
• Understanding of causes and magnitude of delays
• Key process and outcome metrics
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CASE STUDIES
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Call center case study
• Project delivered for a Top 3 US bank
• Very large call center
– 400,000 calls per day
– 20,000 agents on staff
• Agents have different proficiencies for
different call types
• Objective: reduce staffing levels without
sacrificing customer service
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Call center case study
40%
50%
60%
70%
80%
90%
100%
-4% -3% -2% -1% Current 1% 2%
Staffing Levels
ServiceLevelsandOccupancyRates
Service Levels
Occupancy Rates
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Call center case study
• Results:
– Model development uncovered a wealth of
information about internal systems/processes
– Identified savings of over $20M annually
• Additional capabilities:
– Staffing strategies
– Customer prioritization
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London Gatwick Airport case study
• Gatwick Airport was acquired by Global
Infrastructure Partners several years ago
• GIP are looking to improve the airport in
order to sell it at a profit
• Second largest airport in London
– 38M passengers (it would be the 13th largest
airport in the US, right behind Miami)
– Single runway
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London Gatwick Airport case study
• Objective: increase passenger dwell time
in the departure lounge
– Reduce time at check-in
– Reduce time at security
– Increase time in departure lounge
• 3 interlinked models were developed, one
for each area
• Today we are showing the security model
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London Gatwick Airport case study
• Results:
– Comprehensive set of tools to test a wide
range of scenarios
– Tool used to communicate changes to the
terminal to airlines
– A single metal detector per 2 security lanes
will not impact waiting times significantly
– Reduction in staff supervising the e-gates
– Lessons learned applied to Edinburgh Airport
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SIMUL8: HANDS-ON (INTRO)
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SIMUL8: HANDS-ON
Kristen’s Cookie Company
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Kristen’s cookie company - processes
Process Process time Resource
Wash and mix 6 minutes You
Spoon 2 minutes You
Set temperature 1 minute Roommate, oven
Bake 9 minutes Oven
Pack 2 minute Roommate
Payment 1 minute Roommate
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Kristen’s cookie company - processes
• Let’s build the baseline model together
• Add the following results to the Results
Manager
– Utilization (all resources)
– Total number orders delivered
– % of orders completed within 60 minutes
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Kristen’s cookie company - processes
• Add variability in process times / arrivals
• What happens when you add another
oven?
• Should we add any financial information?
• Can you think of any other improvements?
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Wrap-up
• What are your thoughts on simulation?
• Can you think of areas of application in
your organization?