Presentation to the BPM Portugal 2013 Conference

1. Business Process Simulation:
How to get value out of it
Denis Gagné,
www.BusinessProcessIncubator.com
Chair BPMN MIWG at OMG
BPMN 2.0 FTF Member at OMG
BPMN 2.1 RTF Member at OMG
CMMN Submission at OMG
Chair BPSWG at WfMC
XPDL Co-Editor at WfMC

2. Marketing Poster of BPM
• “Doing things right” Do more with less
Business Efficiency
• Quickly adapt to changing Business Conditions
Business Agility
• Current status, outcome, compliance
Business Insight

3. Improvement vs. Management
Process Improvement
Is project based
Is discontinuous improvement
Addresses particular process problems
Process Management
Is not project based but a management philosophy
Is a continuous improvement culture
Is about process-based management
Will require some culture change

4. Poor Performing Processes
May lead to:
Delays
Back log
Refund Claims
Angry customers
Lost of goodwill (Mission Critical)
Lost of lives (Life Critical)
Gain Insight: Thoroughly analyse business
process in a safe isolated environment prior to
Deploying

5. BPMN Process Diagram
www.BPMNVisioModeler.com www.BPMNWebModeler.com

6. Simulation for Process Analysis
Provides a priori Insight
Can be Effective Process Analysis tool for:
Alternative Evaluation
Decision Support
Performance Prediction
Optimization

7. Benefits of Simulation
Advantages of simulation over testing on the
real world include:
Lower relative cost of business
transformation explorations
Speed of validation of potential scenarios
No disturbance to current operations

8. Types of Process Analysis
using Simulation
Structural Analysis
The structural aspects (configuration) of a process model
Usually Statistical Analysis (using static methods)
Capacity Analysis
The capacity aspects of a process model
Usually Dynamic Analysis (using discreet simulation
methods)

9. When is Numeric Simulation
most Appropriate
Capacity analysis of processes that potentially are
Highly Variable
Variability makes outcomes difficult if not impossible to predict
Interdependent
Changes in one process affect other processes
Complex
Complex structure or complex behavior
Capacity Constraints
Hard resources constraints (as independent variables)

10. Process Improvement Project
using Simulation
Get the Goal Right
Clearly define the goal or problem to be investigated using
simulation
Clearly state the objectives of the simulation investigation
Match Expertise to Desired Experimentation
Different levels of Investigation Complexity
Get the Model Right
Model Granularity
Model Parameterization

11. Clearly Define the Goal
Intentions Examples
Reduce headcounts or expenses
Improve process predictability or reliability
Increase throughput
Increase output
Ensure SLA
Design the Experiment Accordingly
Independent vs dependent variables
Same process model under different parameterisations
Different process models under same parameterization
Number of distinct model settings to be run
The experiment should provide insight
The experiment should help inform a decision
The experiment should be in response to clearly defined objectives
that are relevant to a decision

12. Expertise vs Experimentation
Verify Process
Structure and logic
Optimization
Learning via
Experimentations
Quantitative
Analysis
Novice
Expert
Expert
Novice
Process Modeling
Simulation

13. Model Granularity
Pick the right level of process model abstraction
e.g. What is an atomic task
For example a certain level of details may suitable to
compare relative throughput of alternative process designs
while not be detailed enough to provide reliable prediction
of actual throughput

14. Model Input Parameterization
Setting Input parameters for process model elements to reflect external
stimulation
e.g. Arrival Patterns
When randomness is introduced replications should be used
Replication = same scenario but with different sequences of random
variables
e.g. repeated coin toss
Warm up periods may be required
Reflect the notion of work in progress (WIP)
Time during which results are either not collected, or which can be
separated off from the main results collection period
e.g. A bank (opens empty and idle each day) model does not require warm-up (and indeed should not have warm-
up). Common examples of situations requiring warm-up are manufacturing in general, hospital emergency rooms,
24-hour telephone exchanges, etc

15. Demo
Randomness and likelihood

16. When Examining Results
Unexpected result are not necessarily a problem
Primary reason for your simulation experimentation
Need to find an explanation
Will provide enlightenment of actual process behavior
vs assumed process behavior
Unexplainable results are a problem
Simulation is often a process of discovery

17. BPSim Scope
Complements existing process modeling standards
“Not Reinvent the Wheel”

18. Why BPSim
Encourage wider adoption of simulation within BPM
community through a standards led approach
Process simulation is a valuable technique to support process
design, reduce risk of change and improve efficiency in the
organisation
Provide a framework for the specification of simulation
scenario data and results as a firm foundation for
implementation
Open interchange of simulation scenario data between
modeling tool, simulator, results analysis/presentation tool

19. BPSim Element Parameters
Each element parameter of a scenario references a specific element of
a process within the business process model
Each element of the business process model may be parameterized
with zero or multiple element parameters
P
Perspectives
 TimeParameters
 ControlParameters
 ResourceParameters
 CostParameters
 InstanceParameters
 PriorityParameters

20. Demo

21. Business Process Simulation
Best Practices
The Right Model for the Right Goal
Align Modeling Objectives with Simulation Objectives
Abstraction
Fidelity
Validity (soundness and completeness)
The Right Answer to the Right Question
Make sure to instrument your business process model with parameters that
are actual indicators (influencers) of what you wish to explore
The Right Expert for the Right Task
Although conceptually simple to grasp, successfully (meaningfully) using
numerical simulation for business modeling still requires some expertise
(Advanced Mathematical Skills)

22. Discussions & Questions
www.BPSim.org
dgagne@trisotech.com