Graduate Program in
Business Information Systems
BIS 581
Business Process Management
Lecture-3
Aslı Sencer
Department of Management Information Systems
1
Business Process Management – 3
Process Improvement / Reengineering
Process Analysis
2
Process Improvement (BPI)
Process improvement is to reorganize the business processes so
as to improve their effectiveness, efficiency and flexibility. The
objectives of BPI are to improve:
Effectiveness: Does the process produce the desired results and
meet the customer’s needs? Does the process produce what
the customers want?
Efficiency: Does the process minimize the use of resources and
eliminate bureaucracy? Can the responsible employees use the
process easily?
Adaptability: Is the process flexible in the face of changing needs?
Can the process be easily modified on the basis of changing
business requirements?
3
An Improved Process Provides...
The new process design is supposed to provide a process
 with less number of errors
 with less waiting times
 that is easier to implement
 with more focus on changing needs of the customer
 with more competitive power.
4
Choosing the Process to be Improved
The processes to be improved initially are
identified by considering the followings:
 Changes in the competitive environment
 Complaints of the external/internal customer
 Advances in new technologies
 Existence of relatively long and costly processes
 Low performance processes as compared to
benchmarks
 Existence of processes with a high gap.
5
Process Improvement Techniques
•Process improvement starts by identifying a KPI to be
improved and/or optimized.
•From a systemic and analytical approach, these KPI’s are
improved either by
–changing the process model, or by
–changing the level of a set of decision (or control) variables.
•Most common KPI’s are related to
 Duration
 Cost
 Quantity
6
BPI Techniques (cont’d.)
• The purpose of process modeling is to assess the behavior of a
business process before it is actually developed and deployed.
• First the model is executed. If the model behaves as expected,
the project can proceed with development and deployment.
• Otherwise, there are three choices:
1. Change the process model to eliminate the bottlenecks or
other factors that do not measure up to expectations.
2. Add more resources (change of decision variable) to
improve the performance and eliminate the bottlenecks.
3. Reset the expectations of the customers served by the
process so that the expectations are consistent with what
the model predicts.
7
Inputs, Outputs, Decision Variables
From the modelling perspective
• Inputs are the predefined parameters of the system. These
parameters may be introduced by the customers, or obtained
from the internal system.
• Decision variables are the inputs that are controlled by the
decision maker. Their levels may or may not be set optimally
depending on the decision maker’s management concerns.
• Outputs are in the form of goods, services that leads to a
value creation. Quality of the outputs are directly related to
the quality of the process that is measured by KPI’s.
If the value of the decision variables are determined optimally,
the performance of the modelled work flow is optimized in
terms of the chosen KPI’s. But this does not ensure that the
workflow itself is optimal!
8
Systemic Approach to Business Process
Modeling
INPUTS
OUTPUTS
Uncontrollable inputs:
Parameters
Probability distributions
Controllable inputs:
Performance Measures
BUSINESS PROCESS
MODEL
KPI’s OR Objectives
OR Goals
Decision variables OR
Control variables
9
Process Improvement Techniques:
Elimination
Activity 2
Activity 1
Pro’s:
 Savings in time and cost
 Decreased complexity
Activity 3
Activity 4
Activity 5
Activity 6
Attention!
 Output quality should not be lower
 Output should be the same
10
Process Improvement Techniques:
Outsourcing
Activity 2
Activity 2
Activity 1
Pro’s:
 Focus on core competencies
 Lower fixed costs
 Higher quality
Activity 3
Activity 4
Activity 5
Activity 6
Attention!
 Difficulties in control and management
 Risk of lower quality
 Outsource might quit the aggreement
 Risk of information sharing
11
Process Improvement Techniques:
Merging
Activity
2
Activity
2+3Activity 3
Activity 1
Pro’s:
Savings in time and cost
Inceased motivation
Activity 4
Activity 5
Activity 6
Attention!
Difficulties in control and management
12
Process Improvement Techniques:
Parallel activities
Activity 2 ActivityActivity
2
3
Activity 1
Activity 3
Activity 5
Activity 6
Activity 4
Pro’s
 Shorter process durations
 Shorter waiting times
Attention!
Need for extra personnel
Need for extra location
13
Process Improvement Techniques:
Change of Decision Variables
Initial solution
Choose a decision
variable to be
optimized
Identify its
possible values
Find the optimal
solution
Is the solution
satisfactory?
yes
Deploy the solution
no
Choose a different
decision variable
Business Process Analysis
• After the current system and the improved
system are modeled, their performances are
evaluated and analyzed.
• Simulation and statistical analysis are the basic
methodologies used in BPA.
15
BPMA Software
• A Business Process Management and Analysis (BPMA)
software can perform workload and throughput analysis on a
process prior to development of a deployable solution.
• BPMA can run or execute a large number of process incidents
in a simulation environment and produce statistical data on
resource utilizations, process durations, waiting times, etc.
• These are used by the process owner or analyst to change the
process or the resources with the goal of optimizing its
performance.
16
Statistical Analysis
• Statistical analysis needs data that comes from instances, so
it is applicable processes that have high volumes and resource
constraints such as requirements processing, order
processing, and call centers.
• Processes that are not resource constrained or involve
creativity by knowledge workers, can not be optimized by
statistical modeling. Creativity should not be constrained by
strict time limitations. Creative processes have their own
dynamics that may not follow predefined paths and
assumptions. Similarly, a managerial processes that is carried
out only a few times in a year will not benefit from statistical
analysis.
17
Assumptions for Modeling Scenarios
A scenario is a set of assumptions about the resources
used in a business process and the probabilities of
various events that might occur during the course of a
process.
– The business rules of the company
– Assumptions about the resources
– Time used at various steps in the process
– Probabilities of various events that might happen at
specific points in the process.
18
Inputs of the Generated Models
• Rate of arrivals: Number of times the trigger condition occurs
per unit time. Ex: # order receivals per day, # customer arrivals
per hour
• The incident count setting: Length of the simulation run
defined by number of incidents required to reach a steady
state. Ex: Simulate for 100 customer requests. Yet some
processes might never reach a steady state.
• Preload incidents : Warm up period that is specified by the
number of incidents that might occur through the model in
order to reach a stabilized system. Ex: If the incident count set
is 100 and the preload set is 10, the simulation is run for 110
insidents and the 11th-110th incidents are used for analysis.
19
Inputs of the Generated Models
• Day calendar: Specification of the working schedules
including the breaktimes of the resources.
• Task priority: Queueing rules of incidents waiting for
a process that should be completed by a resource.
Ex: existence of high priority customers.
• Generating random time durations: Activity
durations may be random. In BPMA softwares
random durations are either uniform, normal or
exponential. Very restrictive!
20
Uniform Distribution
• Every value is equally likely to occur between the parameters
for maximum, b and minimum, a.
21
Normal Distribution
• Normal distribution has two paramaters: mean, µ
and standard deviation, σ.
22
Exponential Distribution
• Exponential distribution has one paramater: Rate, .
23
Step Level Assumptions
• Lag time: Time between the completion of a task and
beginning of the next task. Ex: After call work in a call center.
• Number of resources: Number staff available to perform a
task
• Task rate: Rate of the users assigned to complete a task. By
multiplying the overhead rate with the task time, the software
can calculate the cost of performing a task.
• % returned: % tasks returned due to lack of information and
other factors. Ex: Abondonment rates in a call center
• % Resubmitted and Resubmit duration: After the task has
been completed, it may be necessary to open and resubmit
the same task again. Ex: Change of mind of the customer
during the ordering process
24
Executing the Model
• After the assumptions/inputs are set, the BPMA software uses
the information about the model and the scenarios to run a
large number of imaginary incidents and collect statistical
data. The BPM system has 3 roles:
• Role of individuals or applications performing tasks at each
step of the process: Determine how fast each step is
completed.
• Role of the engine or BPM server: Uses the process map to
decide in which order the steps are executed.
• Role of time manager: It maintains the internal modeling clock
(IMC), so that the model can be completed much faster than it
would be in real life.
25
Approaches for Implementing Statistical Modeling:
Time Driven Modeling
IMC: Internal Modeling clock
or the simulation clock
26
Approaches for Implementing Statistical Modeling:
Event Driven Modeling
27
Results of Modeling
The performance of the model is measured in terms of the KPI’s that
include some standard statistical measures such as:
Incident Elapsed Time: Time spent in the system by an incidence. Ex:
Average/max/min/deviation of time it takes to complete an order request.
Incident cost: Cost of processing an incident. Ex: If most of the costs are
found to be associated by the tasks performed by a senior executive, the
process might be redesigned to lower the costs.
Step task time: Time it takes to perform a process. Used to check if the
actual values in the model, fits well with the theoretical inputs. Ex: Check,
min/max/average/deviation.
Step lag time: The lag time is a combination of lag time specified in the
scenario plus the unproductive time a user spents waiting for new tasks. In
an unbalanced process some steps have high, others have low workloads.
Step elapsed time: Combination of task time and lag time. It measures the
throughput of the system. Ex: Task time =4min, Lag time=1min, then
throughput=1/5min*60 min=12 items/hr.
28
Results of Modeling (cont’d.)
• Step cost: Cost of a step in business process=Task time*rate cost. How
much eax-ch step contributes to the total cost.
• Step utilization: Distribution of the time for a step that was consumed in
performing the task (task time), waiting for tasks (wait time), or spent in
other activities (lag time).
• Process utilization: How time is utilized across all steps in the process, by
all the resources in every step.
• Under utilization report: A pie chart display of the wait time for all steps in
a process.
• Balance report: Plot of the incident number versus the total elapsed time
for the incident. Provides a graphical view of the change in the total
elapsed time to complete each successive incident.
29