Business Process Simulation: How to get value out of itDenis Gagné,www.BusinessProcessIncubator.comChair BPMN MIWG at OMGB...
AbstractBusiness Process Simulation can be an effective tool when looking for optimal performancefrom a Business Process M...
Poor Performing Processes      May lead to:        Delays        Back log        Refund Claims        Angry customers     ...
Simulation for Process Analysis     Provides a priori Insight     Can be Effective Process Analysis tool for:       Altern...
Benefits of Simulation     Advantages of simulation over testing on the     real world include:        Lower relative cost...
Simulation for Business Processes   Visual Depiction (Visualization & Animation)     User is presented with a (sometime in...
Types of Process Analysisusing Simulation      Structural Analysis        The structural aspects (configuration) of a proc...
When is Numeric Simulationmost Appropriate  Capacity analysis of processes that potentially are    Highly Variable       V...
When is Numeric SimulationLess (Not) Appropriate    When an expedited analysis indicates a negligible problem    When ther...
Process Simulation Other Uses   Training & Learning     Although very popular in support of operations, limited use in oth...
Process Simulation not yetCommon Practice: Why?    Potential Reasons:      Availability      Limitation of existing BPMS T...
Optimization Selection of a best scenario (with regard to some criteria) from some set of available alternatives    Almost...
Process Improvement ProjectBest Practices Defining Success       “Can’t get there if you do not know where you are going” ...
Process Improvement Projectusing Simulation  Get the Goal Right       Clearly define the goal or problem to be investigate...
Clearly Define the Goal     Intentions Examples           Reduce headcounts or expenses           Improve process predicta...
Clearly Define the Objectives    Provide SMART Objectives       Specific          Usually answer the five "W" questions   ...
Optimization Conundrum                  Quality    Time                    Satisfaction           Lean                  Cost
Expertise vs Experimentation           Expert     Verify Process                    Structure and logic                   ...
Model Granularity Pick the right level of process model abstraction    e.g. What is an atomic task For example a certain l...
Model Input Parameterization Setting Input parameters for process model elements to reflect external stimulation    e.g. A...
Select Candidate Probability Based on the external observed behavior Is it Constant or Random Select a distribution that b...
Assess Fidelity Check how well your input parameterization reflect the observed behavior    Model behave as desired or exp...
Simulation is often a process of discovery      Examine output results      Unexpected result are not necessarily a proble...
When Examining Results When randomness is introduced replications should be used   Replication = same scenario but with di...
Demo Randomness and likelihood
Business Process Simulation Working Group               BPSWG             www.BPSim.org
Why BPSim     Encourage wider adoption of simulation within BPM     community through a standards led approach     Process...
BPSim Scope Complements existing process modeling standards                 “Not Reinvent the Wheel”
BPSim Element Parameters Each element parameter of a scenario references a specific element of a process within the busine...
Demo
Business Process SimulationBest Practices The Right Model for the Right Goal   Align Modeling Objectives with Simulation O...
Business Process SimulationCaveats Unrealistic User Expectations    Simple Press-Button Simulation    Deterministic behavi...
Discussions & Questions            www.BPSim.org               dgagne@trisotech.com
Upcoming SlideShare
Loading in …5
×

Business process simulation how to get value out of it (no magic 2013)

2,384 views

Published on

Persentation to NoMagic World 2013

Published in: Business
0 Comments
4 Likes
Statistics
Notes
  • Be the first to comment

No Downloads
Views
Total views
2,384
On SlideShare
0
From Embeds
0
Number of Embeds
145
Actions
Shares
0
Downloads
0
Comments
0
Likes
4
Embeds 0
No embeds

No notes for slide
  • Ludic : playful in an aimless way
  • Business process simulation how to get value out of it (no magic 2013)

    1. 1. Business Process Simulation: How to get value out of itDenis Gagné,www.BusinessProcessIncubator.comChair BPMN MIWG at OMGBPMN 2.0 FTF Member at OMGBPMN 2.1 RTF Member at OMGCMMN Submission at OMGChair BPSWG at WfMCXPDL Co-Editor at WfMC
    2. 2. AbstractBusiness Process Simulation can be an effective tool when looking for optimal performancefrom a Business Process Model. Although considered quite relevant and applicable in thecontext of Business Process Management (BPM), Business Process Simulation is not currentpractice for -and even seldom used by- Business Analyst in the course of process analysis.In this presentation we will explore why this may be the case and will discuss how to useBusiness Process Simulation efficiently while identifying some of the pitfalls along the way.Various Business Process Simulation approaches, their benefits and applicability will beintroduced. The session will conclude with a quick overview of a new Business ProcessSimulation standard that is emerging within the industry.
    3. 3. 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
    4. 4. Simulation for Process Analysis Provides a priori Insight Can be Effective Process Analysis tool for: Alternative Evaluation Decision Support Performance Prediction Optimization
    5. 5. 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
    6. 6. Simulation for Business Processes Visual Depiction (Visualization & Animation) User is presented with a (sometime interactive) animated depiction of the business process model Numeric Simulation (Discreet Events) User asked to provide values for input and decision parameters of a simulated business model Role Play (Serious Gaming) User asked to take actions and make decisions within a simulated business environment
    7. 7. Types of Process Analysisusing 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)
    8. 8. When is Numeric Simulationmost 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)
    9. 9. When is Numeric SimulationLess (Not) Appropriate When an expedited analysis indicates a negligible problem When there is little or no variability or uncertainty When the consequences of poor estimates are acceptable When the cost of intervention is less than the cost of the analysis experiment
    10. 10. Process Simulation Other Uses Training & Learning Although very popular in support of operations, limited use in other Business disciplines Persuasion & Selling Simulating results of a proposed solution Cause and Effect simulation Verification & Validation Validation: Are we doing the right “thing”? Verification: Are we doing “it” right?
    11. 11. Process Simulation not yetCommon Practice: Why? Potential Reasons: Availability Limitation of existing BPMS Tooling Lack of Training or Expertise Lack of Standards
    12. 12. Optimization Selection of a best scenario (with regard to some criteria) from some set of available alternatives Almost impossible without tool support Sub optimization caveat Optimizing the outcome for a subsystem will in general not optimize the outcome for the system as a whole.
    13. 13. Process Improvement ProjectBest Practices Defining Success “Can’t get there if you do not know where you are going” Why are we conducting this project and what are the objectives Stakeholder Analysis “When it comes to assessing success your own opinion while interesting is irrelevant” How do your stakeholders define success While it is obvious that satisfying the most important stakeholder is necessary, it is rarely sufficient. Do not ignore other stakeholders
    14. 14. Process Improvement Projectusing 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
    15. 15. Clearly Define the Goal Intentions Examples Reduce headcounts or expenses Improve process predictability or reliability Increase throughput Increase output Ensure SLA Design the Experiment 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
    16. 16. Clearly Define the Objectives Provide SMART Objectives Specific Usually answer the five "W" questions Measurable Aiming for quantifiable, concrete results Achievable While an attainable goal may stretch a team in order to achieve it, the goal is not extreme Relevant To your boss, your organization, your stakeholders Time Bound Within a time frame, with a target date Be mindful of the Optimization Conundrum
    17. 17. Optimization Conundrum Quality Time Satisfaction Lean Cost
    18. 18. Expertise vs Experimentation Expert Verify Process Structure and logic OptimizationProcess Modeling Novice Learning via Quantitative Experimentations Analysis Novice Expert Simulation
    19. 19. 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
    20. 20. Model Input Parameterization Setting Input parameters for process model elements to reflect external stimulation e.g. Arrival Patterns Opportunity to introduce event variability into the process model Select Candidate Probability Assess Fidelity Can easily be the cause of misleading results “Garbage in garbage out”
    21. 21. Select Candidate Probability Based on the external observed behavior Is it Constant or Random Select a distribution that best captures characteristics, observations, or available data Some distribution are better fits to specific situations (e.g. Poisson for mutually independent arrivals) Using available historical or event log data as reference may require data cleansing e.g. minimum task time =8 mins Mode task time = 32 mins Maximum task time = 9.5 hours May not notice that maximum task time includes an 8 hour off shift
    22. 22. Assess Fidelity Check how well your input parameterization reflect the observed behavior Model behave as desired or expected, or Model behavior reflects “As Is” situation Carry out Sensitivity Testing Determine how sensitive your model is to different input parameters Check sensitivity in magnitude (e.g. mean) and variability (e.g. range)
    23. 23. Simulation is often a process of discovery Examine output 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
    24. 24. When Examining Results 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
    25. 25. Demo Randomness and likelihood
    26. 26. Business Process Simulation Working Group BPSWG www.BPSim.org
    27. 27. 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
    28. 28. BPSim Scope Complements existing process modeling standards “Not Reinvent the Wheel”
    29. 29. 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 Perspectives  TimeParameters  ControlParameters P  ResourceParameters  CostParameters  InstanceParameters  PriorityParameters
    30. 30. Demo
    31. 31. Business Process SimulationBest 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)
    32. 32. Business Process SimulationCaveats Unrealistic User Expectations Simple Press-Button Simulation Deterministic behavior assumptions A Business Process Model is a Simulation Model (not necessarily) Their goals (purposes) may be misaligned Be Mindful of Misleading Results (Garbage in Garbage Out) A simulation model that is fidel &valid with uncharacteristic data can lead to incorrect conclusions or predictions, Negative Training, … Sub-Optimization Partial or sub-model optimization can lead you astray
    33. 33. Discussions & Questions www.BPSim.org dgagne@trisotech.com

    ×