an optimization model for valuating process flexibility
DESCRIPTION
Although flexible processes are deemed critical for many companies and constitute a key concern of business process management, there is a lack of approaches for valuating process flexibility from an economic perspective and for determining an appropriate level of process flexibility. Today, companies do not know how flexible their processes should be. While generally advocating balanced investments, scholars provide concrete recommendations for very specific settings only. What is missing is a more general guidance and a deeper investigation of the positive economic effects of flexible processes, which are hard-to-measure and beset with risks. Against this backdrop, we propose an optimization model that enables determining the optimal level of process flexibility in line with the principles of value-based business process management. We also report on the insights gained from applying the optimization model to the production processes of an international company from the semi-conductor industry.TRANSCRIPT
II/2010-1
01007
An optimization model for
valuating process flexibility
Presentation at the International Conference
on Information Systems (ICIS), Milan
December 17th 2013
University of Augsburg
Patrick Afflerbach, Gregor Kastner,
Felix Krause, Maximilian Röglinger
Research Center
Finance & Information Management
Fraunhofer Project Group
Business & Information Systems Engineering
Department of Information Systems Engineering
& Financial Management
Elite Graduate Program
Finance & Information Management
www.fim-rc.de/en
www.fit.fraunhofer.de/bise
2 • M. Röglinger and P. Afflerbach • An optimization model for valuating process flexibility © FIM Research Center
Motivation
Challenges derived from the literature
Challenge 1: Provide more
general guidance for decisions
on process flexibility!
Challenge 2: Focus on
positive economic effects of
process flexibility!
Challenge 3: Explore the
benefits of treating flexibility
as a multi-process concept!
3 • M. Röglinger and P. Afflerbach • An optimization model for valuating process flexibility © FIM Research Center
Theoretical background
Defining process flexibility
Functional flexibility refers to
the readiness with which tasks
can be changed in response to
varying business demands.
(Sethi and Sethi 1990)
Volume flexibility enables
to increase or decrease
production above or below
the installed capacity.
(Goyal and Netessine 2011)
Process flexibility is the ability to
create multiple outputs on the same
capacity, and to reallocate capacity
between processes in response to
realized demand.(inspired by Goyal and Netessine 2011)
A CB
A DB‘
4 • M. Röglinger and P. Afflerbach • An optimization model for valuating process flexibility © FIM Research Center
Optimization model
General setting
A CB A DB‘
Providing process:
Inferior output
Lower profit margin
Provides flexible capacity
Implements flexibility projects
Receiving process:
Superior output
Higher profit margin
Receives flexible capacity
General setting:
Assumptions and definitions:
Process flexibility is the percentage of the
capacity of the providing process that can be
reallocated to create the superior output.
Selling the superior output is such profitable
that capacity is always reallocated if needed.
The demand for both process outputs is risky.
It is uniformly distributed and scatters symmetrically
around the respective capacity.
Decision makers aim to identify the level of
flexibility potential that maximizes the risk-adjusted
expected present value of the process cash flow.
5 • M. Röglinger and P. Afflerbach • An optimization model for valuating process flexibility © FIM Research Center
Optimization model
Basic idea – An example case
Capacity Capacity
Characteristics:
Investment phase: Flexibility potential is
established by implementing flexibility projects.
Operations phase: Flexible capacity is used to
create superior output in response to the realized
demand.
Demand
Needed
flexibility
Provided
flexibility
Flexibility
potential
Flexibility
potential
Demand
Remaining
capacity
Cash flow effects:
Investment phase: Cash outflows for
implementing flexibility projects.
Operations phase (per period): (a) Increased
cash inflows from the superior output, (b) no
decreased cash inflows from the inferior output.
Providing process: Receiving process:
Maximum
Demand
Minimum
Demand
Maximum
Demand
Minimum
Demand
6 • M. Röglinger and P. Afflerbach • An optimization model for valuating process flexibility © FIM Research Center
Optimization model
Cash inflows: Case analysis to cope with risky demand
(Periodic) Cash inflows
Case 2: Increased
cash inflows from
superior output.
Case 1: No increased
cash inflows from
superior output.
Case 2.1: Reduced cash
inflows from inferior
output are certain.
Probability = 0.5 Probability = 0.5
Probability = 0.5 Probability = 0.5
Case 2.2: Reduced cash
inflows from inferior output
are possible.
DemandDemand
DemandDemand
Receiv
ing p
rocess
Pro
vid
ing p
rocess
7 • M. Röglinger and P. Afflerbach • An optimization model for valuating process flexibility © FIM Research Center
Optimization model
Cash outflows: Important drivers
Cash
outflows
Flexibility
potential
Overhead
factor
Worst-case
cash
outflows
Process
character-
istics
Critical
steps
Similarity
of critical
steps
Idea:
1. Start with the full replication of the
receiving process as a worst-case
scenario.
2. Use process characteristics to reduce
the worst-case cash outflows (e.g.,
criticality, similarity, variability).
3. Adjust cash outflows to the desired
level of flexibility potential considering
an overhead factor for administration
and coordination.
A CB A DB‘
Providing process: Receiving process:
Example:
A DB‘ Step D is uncritical because it does
not cause a capacity shortage.
8 • M. Röglinger and P. Afflerbach • An optimization model for valuating process flexibility © FIM Research Center
Optimization model
Integrating cash inflows and cash outflows
Properties of the cash inflows:
Present value based on risk-adjusted
interest rate
Strictly monotonically increasing
Strictly concave
Properties of the cash outflows:
Strictly monotonically increasing
Strictly convex
Properties of the cash flow:
Difference of inflows and outflows
Strictly concave
Maximum as single extreme point
Maximum can be determined analyticallyRisk-adjusted expected present-value cash flow
Cash outflows
Risk-adjusted expected present-value cash inflows
0,0 0,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8 0,9 1,0𝐹
𝐹∗
9 • M. Röglinger and P. Afflerbach • An optimization model for valuating process flexibility © FIM Research Center
Real-world application in the semi-conductor industry
Metal Layer
production
Photo
Layer
production
Providing process:
2 x 12 x
Metal Layer
production
Photo
Layer
production
3 x 24 x
Special Photo
Layer
production
3 x
Providing process Receiving process
Output
super junction metal-
oxide-semiconductor
field-effect transistor
(SMOSFET)
SMOSFET + bipolar
junction transistor
(SM-BJT)
Profit
margin
326 EUR
per wafer
896 EUR
per wafer
Expected
demand
1,000 wafer
per week
200 wafer
per week
Demand
deviation
336 wafer
per week
200 wafer
per week
Capacity1,000 wafer
per week
0 wafer
per week
Receiving process:
Case context:
Investment case from one of the company’s
semi-conductor factories in South Asia
Industry: high output variety, short
lifecycles, highly fluctuating demand, huge
investments
Contact: Management of the strategic
production planning department
Approach:
First interview: Discussion of the model
and adaptation of distinct model components
Second interview: Data collection and
application of the model
10 • M. Röglinger and P. Afflerbach • An optimization model for valuating process flexibility © FIM Research Center
Real-world application in the semi-conductor industry
Question: Was the company’s last investment in a flexible photolithography
machine as well as the corresponding training measures and IT support reasonable?
Further input and calculations: Cash flow effects:
Value
Cash outflows 3 Mio. EUR
Enabling effect
+200 SM-BJT
(-300 SMOSFET)
wafer per week
Flexibility potential 30 %
Exchange rate 0.67
Interest rate 0.0018 per week
Combined process
and scaling factor33,333 EUR
Value
Expected cash inflows per week 29,000 EUR
Expected present-value cash inflows 16.2 Mio. EUR
Insights:
Investment in process flexibility was reasonable!
An investment of about 2.4 Mio. EUR would have
been optimal (F* = 27 %).
Data to calculate the case could be gathered easily.
Optimization model could be adapted to the setting
of the case at hand!
11 • M. Röglinger and P. Afflerbach • An optimization model for valuating process flexibility © FIM Research Center
Discussion and Outlook
Challenge 1: Provide more general guidance for decisions on process flexibility!
Challenge 2: Focus on positive economic effects of process flexibility!
Challenge 3: Explore the benefits of treating flexibility as a multi-process concept!
Optimal level of flexibility can be calculated.
The model can be solved analytically.
Data can be collected easily.
Focus on a distinct variant of flexibility.
The model should be applied to processes
from other domains (e.g., services).
Risky demand
Multi-period planning horizon
Increased inflows from superior outputs,
decreased inflows from inferior outputs.
Cash outflows were estimated in a rather
straightforward manner.
It has to be critically assessed which of the
simplifying assumptions can be relaxed.
Process flexibility refers to two processes.
One process with a superior output
One process with an inferior output
The providing process might benefit from
process flexibility as well.
Process flexibility could be extended to
more than two processes.
12 • M. Röglinger and P. Afflerbach • An optimization model for valuating process flexibility © FIM Research Center
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