This document proposes a capability-based method for selecting and evolving software-service bundles to meet client needs. It involves: 1. Defining a capability model and support matrix to map which bundle configurations suit different client contexts and performance levels. 2. An initial bundle is selected for a new client based on their context. Performance is monitored and contexts tracked for changes. 3. If goals are not met or contexts change, bundles are evolved by selecting a new configuration, updating the support matrix, or developing a specialized bundle. 4. An example of evolving a business information exchange process is simulated as demand and volatility change over time.

1. Selection and Evolutionary
Development of Software-Service
Bundles: a Capability Based Method
Jānis Grabis1, Kurt Sandkuhl2
1Institute of Information Technology, Riga Technical University,
Kalku 1, Riga, Latvia
2 Chair of Business Information Systems , University of Rostock,
Albert-Einstein-Straße 22, Rostock, Germany
grabis@rtu.lv, kurt.sandkuhl@uni-rostock.de

2. Outline
• Motivation
• Objectives and problem statement
• Method elaboration
• Application example
• Conclusion

3. Software-Service Bundle
• Software is available
in different versions
• Software is made
available with a
number of additional
services
• Support
• Domain expertise
• Outsourcing

4. State of the Art
• Product-line development
– Pohl et al. (2005)
• Packaged software selection
– Jadhav and Sonar (2009)
• Evidence based software engineering
– Olsson and Bosch (2015)

5. CDD Approach
• Assumptions
– Suitability of software-service bundles is context
dependent
– A bundle optimizing performance is desirable
– Clients share software usage data
• Capability driven development (CDD) is an
approach for delivering services in different
contexts at the desired level of performance
– Bērziša et al. (2015)

6. Objectives
• To elaborate a method allowing
collaboration between vendor and client
in selection of the right configuration of
software-service bundles and continuous
improvement of the selected
configuration
– Based on the CDD approach

7. Problem Statement
Software-
service bundle
O1 O2
O3 O4
O5 O6
Performance and
context data
Vendor
Client A
Context
Performance
O5
Client B
Context
Performance
O4
Client C
Context
?
?

8. Evolutionary development process
Create capability
support matrix
Define capability
model
Engage new
client
Select appropriate
configuration
Deploy solution
Monitor delivery
Goals not achieved
Context has changed
• Capability model
• What factors affect service delivery and
which solutions could be used
• Capability support matrix
• Which configuration is suitable in a
specific context situation
• Continuous improvement
• Development of new configurations

9. Evolutionary Development Stages
Design stage
Delivery stage
Evolution

10. Design Stage
• Initial configuration of the software-service
bundle is selected and deployed for a new
client
• Relevant parameter for the selection:
– Context elements: have a context range
– Context situations: combinations of context
element values from the context range
– Most plausible context situation Cnew for a new
client
– Configurations Oj derived from
Capability Support Matrix
• Client also sets KPI
• Least cost configuration Oj appropriate for
context situation faced by the new client
1
1
1
1 N2 …
1
H
2
…
Configurations
ContextSituations
CSM
),...,( 1 iiTii crcrCR 
 
N
H
CRCR
CSCS
 ...
,...,
1
1
)1|min( i
new
ij CSCSaj 

11. Delivery Stage
• Software-service bundle is in use by the client
• Context situations and delivery performance are monitored
• Delivery performance:
– Monitoring is based on real-time values of KPI
– Actual values are compared to target values
– On underperformance, recommendation to revise solution is
issued
• Context monitoring
– Comparison of observed context situation with context
situations supported by current configuration
– If current configuration no longer fits, warning is issued
• Context monitoring serves as an advanced warning system to
potential performance deterioration

12. Evolution
• Adjustment of software-service bundle to
changing circumstances
• Violations of performance objectives or
unsupported context situations suggest an
upgrade of the current configuration
• Alternative ways
– Selection of a more suitable configuration from
CSM
– Reevaluate CSM for the software product
– Special software-service bundle needs to be
developed

13. Application Example
• Business information exchange process
– Manual processing
– Automated processing
– Outsourcing

14. Capability Model

15. Capability support matrix
Processing load
level
Load volatility O1 O2 O3
Low Low 1
Low Medium 1 1
Low High 1
Medium Low 1
Medium Medium 1 1
Medium High 1
High Low 1
High Medium 1
High High 1

16. Simulated Evolution
• Demand for data processing services is
simulated
– Changing demand level
– Changing demand volatility
• EXP1
– Is manual processing appropriate for low
demand situation?
• EXP2
– Is outsourcing needed for high volatility
situations?
low,if 100
medium,if 00 1000
high,if 1000
PLC





   
 

17. Simulation Results (EXP1)
O1 O2

18. Simulation Results (EXP2)
O2 O3

19. Conclusion
• Incentives for data sharing
• Limitations of simulation based
evaluation
• Cost of evolutionary development