Alexei A. Gaivoronski IIASA, Workshop on Coping with Uncertainty, 10-12.12.20071
Stochastic optimization and modeling of network risk and uncertainty:
the case of telecommunication services
Alexei A. GaivoronskiAlexei A. GaivoronskiNorwegian University of Science and Norwegian University of Science and
TechnologyTechnology
Joint work with Josip Zoric, Denis Becker, Adrian Werner, Joint work with Josip Zoric, Denis Becker, Adrian Werner, Paolo PisciellaPaolo Pisciella
Alexei A. Gaivoronski IIASA, Workshop on Coping with Uncertainty, 10-12.12.2007 2
Risk adapted performance networksRisk adapted performance networks
Electric power generation and distributionElectric power generation and distribution Gas production, transportation, dirstributionGas production, transportation, dirstribution Telecommunications and internetTelecommunications and internet TransportationTransportation1.1. Hierarchical networks with nodes of different levels of Hierarchical networks with nodes of different levels of
complexity: from equipment to enterprisescomplexity: from equipment to enterprises
2.2. Nodes designed to meet local risk adjusted performance Nodes designed to meet local risk adjusted performance targets targets locallylocally
3.3. Network should satisfy risk/performance tradeoff Network should satisfy risk/performance tradeoff globallyglobally
4.4. Inherent uncertaintyInherent uncertainty
Alexei A. Gaivoronski IIASA, Workshop on Coping with Uncertainty, 10-12.12.2007 3
Quantitative evaluation of business models for Quantitative evaluation of business models for collaborative service provisioncollaborative service provision
Work directionsWork directions
Getting qualitative understanding of business models, Getting qualitative understanding of business models, input from qualitative part, SPICE scenarios, surveysinput from qualitative part, SPICE scenarios, surveys
Development of quantitative modelsDevelopment of quantitative models Implementation in a prototype of decision support systemImplementation in a prototype of decision support system Testing on SPICE scenarios, casesTesting on SPICE scenarios, cases Deliverable on quantitative evaluationDeliverable on quantitative evaluation
Alexei A. Gaivoronski IIASA, Workshop on Coping with Uncertainty, 10-12.12.2007 4
Status Task 1.4, quantitative analysis of business modelsStatus Task 1.4, quantitative analysis of business models
The Edition 1 of the set of models for investment business The Edition 1 of the set of models for investment business analysis of collaborative service provision has been analysis of collaborative service provision has been developed: top static viewdeveloped: top static view
Architecture of the prototype of decision support system Architecture of the prototype of decision support system for analysis of business models is selectedfor analysis of business models is selected
Parts of this prototype is under implementationParts of this prototype is under implementation
Alexei A. Gaivoronski IIASA, Workshop on Coping with Uncertainty, 10-12.12.2007 5
Work in progressWork in progress
Edition 2 of the model set: service lifetime, different Edition 2 of the model set: service lifetime, different constellations of actorsconstellations of actors
Build up of the prototype of decision support system for Build up of the prototype of decision support system for business analysisbusiness analysis
Analysis of SPICE scenarios using the model setAnalysis of SPICE scenarios using the model set Analysis of possible business models using qualitative Analysis of possible business models using qualitative
input from other participantsinput from other participants Further dissemination effortFurther dissemination effort
Alexei A. Gaivoronski IIASA, Workshop on Coping with Uncertainty, 10-12.12.2007 6
Quantitative business modelsQuantitative business models
What is it?What is it? Well understood in theory of corporate finance and in Well understood in theory of corporate finance and in
business practicebusiness practice BUT focus is on one single enerprise who selects industrial BUT focus is on one single enerprise who selects industrial
project or project portfolioproject or project portfolio Identify and measure and commeasure all cash flows Identify and measure and commeasure all cash flows
related to a given business activityrelated to a given business activity Give integrated assessment of cash flow/profit performance Give integrated assessment of cash flow/profit performance
based on different business principlesbased on different business principles Return on investment NPV Risk/performance tradeoff
Decision about business activityDecision about business activity Recent emphasis on risk controlRecent emphasis on risk control
Alexei A. Gaivoronski IIASA, Workshop on Coping with Uncertainty, 10-12.12.2007 7
Challenges to this viewChallenges to this view
Networked industrial environmentNetworked industrial environmentDifferent independent agents are contributing to Different independent agents are contributing to
the common goal being in complex relations of the common goal being in complex relations of competition and collaborationcompetition and collaboration
How all this functions in such networked How all this functions in such networked environment?environment?
Corporate finance theory needs further Corporate finance theory needs further development for this casedevelopment for this case
Risk control issuesRisk control issuesGood example: evaluation of business models in Good example: evaluation of business models in
context of SPICEcontext of SPICE
Alexei A. Gaivoronski IIASA, Workshop on Coping with Uncertainty, 10-12.12.2007 8
ObjectiveObjective
Starting from theory of corporate finance and Starting from theory of corporate finance and optimal decisions under uncertainty and risk optimal decisions under uncertainty and risk develop methods and tools for quantitative develop methods and tools for quantitative evaluation of business models in networked evaluation of business models in networked environmentenvironment
Utilize this methodology in SPICE context for Utilize this methodology in SPICE context for evaluation of collaborative service provision on evaluation of collaborative service provision on SPICE platformSPICE platform
Alexei A. Gaivoronski IIASA, Workshop on Coping with Uncertainty, 10-12.12.2007 9
Risk/performance networksRisk/performance networks
State of the art: different attempts but no State of the art: different attempts but no universally accepted answersuniversally accepted answers
Growing importance in different fieldsGrowing importance in different fields Telecommunications Supply chain management Energy
Alexei A. Gaivoronski IIASA, Workshop on Coping with Uncertainty, 10-12.12.2007 10
Example of structural description of service provision
Alexei A. Gaivoronski IIASA, Workshop on Coping with Uncertainty, 10-12.12.2007 11
Different constellations of rolesDifferent constellations of roles
Alexei A. Gaivoronski IIASA, Workshop on Coping with Uncertainty, 10-12.12.2007 12
Service architectureService architecture
risk
return
feasible set
R
x
efficient frontier
x0x1
x2
risk
return
feasible set
R
x
efficient frontier
x0x1
x2
risk
return
feasible set
R
x
efficient frontier
x0x1
x2
risk
return
feasible set
R
x
efficient frontier
x0x1
x2
risk
return
feasible set
R
x
efficient frontier
x0x1
x2
risk
return
feasible set
R
x
efficient frontier
x0x1
x2
risk
return
feasible set
R
x
efficient frontier
x0x1
x2
risk
return
feasible set
R
x
efficient frontier
x0x1
x2
risk
return
feasible set
R
x
efficient frontier
x0x1
x2
risk
return
feasible set
R
x
efficient frontier
x0x1
x2
Alexei A. Gaivoronski IIASA, Workshop on Coping with Uncertainty, 10-12.12.2007 13
Services, roles and actorsServices, roles and actors
users services Components, enablers, roles
SPICE
actors
Alexei A. Gaivoronski IIASA, Workshop on Coping with Uncertainty, 10-12.12.2007 14
Economic requirementsEconomic requirements
Platform should be attractive for all actorsPlatform should be attractive for all actorsActors should feel incentive to join service Actors should feel incentive to join service
provision, that is they should want to join provision, that is they should want to join cooperative effort because they will benefit from itcooperative effort because they will benefit from it
Services should provide to actors a competitive Services should provide to actors a competitive source of profitsource of profit
Risk/return considerations: risk that users will not Risk/return considerations: risk that users will not accept the service as expected, cannibalizing, etcaccept the service as expected, cannibalizing, etc
Alexei A. Gaivoronski IIASA, Workshop on Coping with Uncertainty, 10-12.12.2007 15
Approach of modern financial theoryApproach of modern financial theory
Actors participate in service(s) provision assuming roles Actors participate in service(s) provision assuming roles and providing components for servicesand providing components for services
Quantify cash flow, profits and risksQuantify cash flow, profits and risks Each actor will select tradeoff between profit and risk Each actor will select tradeoff between profit and risk
exposure according to its preferencesexposure according to its preferences This will result in This will result in service portfolioservice portfolio for each actor for each actor Coordination tools should assure that the actors will select Coordination tools should assure that the actors will select
on their own accord participation in service provision in on their own accord participation in service provision in required proportionrequired proportion
Alexei A. Gaivoronski IIASA, Workshop on Coping with Uncertainty, 10-12.12.2007 16
Risk/return tradeoffRisk/return tradeoffNobel prise winning conceptNobel prise winning concept
risk
return
feasible set
R
x
efficient frontier
x0x1
x2
Alexei A. Gaivoronski IIASA, Workshop on Coping with Uncertainty, 10-12.12.2007 17
Quantitative modelQuantitative modelDescription of serviceDescription of service
Services consist of components which my be provided by Services consist of components which my be provided by different actorsdifferent actorsN components indexed by i and M services indexed by j
ij - share of component i in service j.
Description of service through components:
Service generate revenue Service generate revenue vvjj
Revenue sharing coefficients
Actor who contribures with component i recieves revenue
j 1j , . . , Nj
j 1j , . . , Nj
ijv i
Alexei A. Gaivoronski IIASA, Workshop on Coping with Uncertainty, 10-12.12.2007 18
Description of actorsDescription of actors
Actors assume roles by providing service componentsActors assume roles by providing service components This incurs costs and brings revenueThis incurs costs and brings revenue
K actors indexed by k
cik – unit provision costs for actor k providing component i
Wik – provision capability of component i by actor k
xijk – the portion of provision capability for component i of actor k dedicated to participation in provision of service j.
Profit model for actor k
xijkWik - the volume of provision of component i dedicated by actor k to service j
Alexei A. Gaivoronski IIASA, Workshop on Coping with Uncertainty, 10-12.12.2007 19
Profit model for actor Profit model for actor kk
xijkWik/λij- volume of service j in which the actor k participates
vjxijkWki/λij - the total revenue from this service
vjxijkWkiγij/λij - the part of the revenue which goes to actor k
Profit of actor k:
k j 1
M
v jx ijkWik ij ij
x ijkc ikW ik j 1
M
x ijkWikc ikv j ijcik ij
1
Alexei A. Gaivoronski IIASA, Workshop on Coping with Uncertainty, 10-12.12.2007 20
Profit model for actor Profit model for actor kk
Basic case: an actor provides only one Basic case: an actor provides only one componentcomponent Profit
Return
Portfolio viewpoint: an actor chooses portfolio of services to which contribute
i Wic i j 1
M
x ijv j ijci ij
1
r i j 1
M
x ijv j ijci ij
1
x i x i1, . . . ,x iM
Alexei A. Gaivoronski IIASA, Workshop on Coping with Uncertainty, 10-12.12.2007 21
Portfolio viewpointPortfolio viewpoint
Return coefficients associated with participation in each service
expected return coefficients
expected return
Risk that actual return will be different from Risk that actual return will be different from expected return or even become lossexpected return or even become loss
r ij v j ijci ij
1
ij ijEv jci ij
1
r i j 1
M
ijx ij j 1
M
x ij ijEv jci ij
1
Alexei A. Gaivoronski IIASA, Workshop on Coping with Uncertainty, 10-12.12.2007 22
Efficient service portfoliosEfficient service portfolios
Problem to solve for computing eficient frontierProblem to solve for computing eficient frontier
minx StDev2 j 1
M
x ijv j ijci ij
1
j 1
M
x ij ijEv jci ij
1
j 1
M
x ij 1, x ij 0
Alexei A. Gaivoronski IIASA, Workshop on Coping with Uncertainty, 10-12.12.2007 23
Next level: quantitative coordinationNext level: quantitative coordination
What is necessary is that the whole service What is necessary is that the whole service provision platform functions properlyprovision platform functions properly
And this means that different actors should And this means that different actors should independently make decisions to participate in independently make decisions to participate in different services which nevetherless will provide different services which nevetherless will provide coordinated result.coordinated result.
Revenue sharing coefficients should be chosen in Revenue sharing coefficients should be chosen in order to achieve thisorder to achieve this
Alexei A. Gaivoronski IIASA, Workshop on Coping with Uncertainty, 10-12.12.2007 24
Coordinator (service provider) Coordinator (service provider) problemproblem
Paper is available on Edition 1 of the model set
Alexei A. Gaivoronski IIASA, Workshop on Coping with Uncertainty, 10-12.12.2007 25
Architecture of the DSS prototypeArchitecture of the DSS prototype
Mathematicalmodel
Top level algorithmsScenario generation
Postprocessing
Problem solvers
Data and userinterface
Data User interaction
Results presentation
Excel MATLAB
XPRESS
SQG
CPLEX
results
data
User intervention
Service modelDetailed service
structure, resources
Service description
Alexei A. Gaivoronski IIASA, Workshop on Coping with Uncertainty, 10-12.12.2007 26
Screenshot 1 of demo of DSS prototypeScreenshot 1 of demo of DSS prototype
Alexei A. Gaivoronski IIASA, Workshop on Coping with Uncertainty, 10-12.12.2007 27
Screenshot 2 of demo of DSS prototypeScreenshot 2 of demo of DSS prototype
Alexei A. Gaivoronski IIASA, Workshop on Coping with Uncertainty, 10-12.12.2007 28
Example: business person on the Example: business person on the movemove
Alexei A. Gaivoronski IIASA, Workshop on Coping with Uncertainty, 10-12.12.2007 29
Risk/performance preferencesRisk/performance preferences
0.05
0.1
0.15
0.2
0.25
0.3
0 0.2 0.4 0.6 0.8
risk
pro
fit
Alexei A. Gaivoronski IIASA, Workshop on Coping with Uncertainty, 10-12.12.2007 30
Market sharesMarket shares
0
0.2
0.4
0.6
0.8
1
0 0.2 0.4 0.6 0.8
risk
pla
tfo
rm s
erv
ices
Alexei A. Gaivoronski IIASA, Workshop on Coping with Uncertainty, 10-12.12.2007 31
Price competitionPrice competition
0
0.2
0.4
0.6
0.8
1
0.18 0.2 0.22 0.24 0.26 0.28 0.3 0.32 0.34
risk
pla
tfo
rm s
ervi
ces
-10%
-5%
+5
10
Alexei A. Gaivoronski IIASA, Workshop on Coping with Uncertainty, 10-12.12.2007 32
SummarySummary
Modern theory of corporate finance and risk Modern theory of corporate finance and risk management together with optimization under management together with optimization under uncertainty provides a foundation for quantitative uncertainty provides a foundation for quantitative analysis of risk/performance networks in the analysis of risk/performance networks in the context of collaborative service provisioncontext of collaborative service provision
Alexei A. Gaivoronski IIASA, Workshop on Coping with Uncertainty, 10-12.12.2007 33
ConclusionsConclusions
Traditional risk management paradigm should be augmented and Traditional risk management paradigm should be augmented and developed further: noncommeasurable risksdeveloped further: noncommeasurable risks
Modern theory of corporate finance and risk management provides a Modern theory of corporate finance and risk management provides a foundation for quantitative analysis of risk/performance networks but foundation for quantitative analysis of risk/performance networks but much more work is neededmuch more work is needed
Many possibilities for stochastic programming approachesMany possibilities for stochastic programming approaches Three components: Modern computing technology, off-shelf Three components: Modern computing technology, off-shelf
optimization software, custom algorithm designoptimization software, custom algorithm design It is possible to solve highly nonlinear and nonconvex problems in It is possible to solve highly nonlinear and nonconvex problems in
industrial quantitiesindustrial quantities