© 2005. all rights reserved.1 strategic r&d value lifecycle management doug bodner, bill rouse...
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© 2005. All rights reserved. 1
Strategic R&D Value Lifecycle Management
Doug Bodner, Bill Rouse and Mike Pennock
Tennenbaum InstituteGeorgia Tech
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Outline
• R&D value and value lifecycle• Value levers• Simulation-based approach
– Process model and results– Product model and integration
• Future work
3
R&D Value Creation
• Value is derived from financial returns of deployed products or systems.
• Value is realized downstream.
• Upstream estimates of value are uncertain/dynamic.
• Multi-stage investment structure mitigates risk via flexibility.
Stage 1
Technical failure
Not Funded
Stage 2
Stage 3
Stage 4
$
$
$
$
Value realized
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R&D Value Lifecycle
Idea Concept Proposal Project Result
$ ?
Archive
DeployRetire
PatentMaintenanceObsolescence
ProductionLicensing
MaintenanceRevisions
DisposalOption Value
Cash Flow Value
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R&D in a PLM/SLM Context
Adapted from: IBM PLM definition slide at PDES Inc. Board Mtg. 2003-11
Portfolio Planning
Concept Developmen
t
Design
Portfolio Planning
Product/System Design Process
R&D
R&D Process
Results
Production& Test
Sales &Distribution
Market and technology feedback and forecasting
Addressing current and future needs
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Goals
• Identify value levers that can be manipulated to improve value creation
• Understand quantitative effects in relation to enterprise parameters
• Provide what-if analysis capability for strategic decision-making
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Value Levers
• Enterprise operation– How to valuate R&D products– How to allocate budget among
stages/programs– Portfolio management
• Enterprise design– How many R&D stages – Outsourcing R&D– Organizational structure
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Valuation Method
• Traditional project valuation approaches use discounted cash flow (DCF) analysis
• Real options analysis captures flexibility– Discontinue, defer,
expand, contract
• Analytic, recursive and simulation-based computationsDo nothing
– i.e., no exercise
Cost of future stage(s) – i.e., exercise price
Cash flow – i.e., asset price
Pay next stage – i.e., exercise
Pay this stage
Decision point
DCF
Real Options
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Budget Allocation
• Can be conceptualized as line-balancing– Allocate funds to meet
expected budget requests weighted by cumulative failure rates
• Is it better to– “Balance” the
allocation– Shift funds upstream– Shift funds downstream
Stage 1
Technical failure
Not Funded
Stage 2
Stage 3
Stage 4
R&DBudget
$
$
$
$
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Organizational Simulation• Modeling and data
gathering– Understand your
system
• Quantitative insight via controlled experiments– Attach numbers to
effects with statistics
• What-if analysis– Experiment and see
effect of changes without using the real enterprise
R&D Processes
Resources
Value
Computer Model• Dynamic behavior • Resources• Workflow• Output• People• Decisions• Uncertainty
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R&D World
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Model Description
• R&D process model (four stages)• R&D modeled as lines that traverse
through each stage• Budget requests per stage increase by
factor of 2• Technical failure rates decrease as stages
are traversed• Estimated deployed value varies
lognormally over time• Value realized after successful deployment
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Experimental DesignFactors– Valuation method (DCF vs. options)– Budget allocation (LB vs. UF)– Probability of initial NPV negativity (33% vs. 50%)– Volatility (20% vs. 60%)
Experiment- 10 replications- 25 years each- 5 year warm-up
Dependent Variables–Total value created (TVC)–Yield (Y) = TVC/Expenditures
Two 24 factorial experiments (one for each dependent variable).
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Results – Valuation
• Valuation using options outperforms DCF for total value created.– Especially when initial NPV negativity is
likely, and also when volatility is high.
• DCF outperforms for yield.• Options emphasize total value, while
DCF emphasizes ROI. DCF is more conservative than options
• Under DCF, lower percentages of R&D budget are expended.
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Results – Allocation
• Shifting funds upstream outperforms line-balancing for total value created.– Especially when volatility is high and when
initial NPV negativity is likely.
• Line-balancing outperforms for yield.– Especially with low volatility.
• This effect appears due to the upside potential of market risk.
• Line-balancing is more conservative.
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Thinking of R&D “Products”
• Different R&D product (RDP) types– Technologies, technical reports, prototype
systems or consumer products, patents
• Different status possibilities– Planned, proposed for funding, in progress,
available, retired
• Different generations• Precedence relationships• R&D value network
– Structure and dynamics
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RDP Value Network
Deployable(Market/applicationrisk)
Technologygenerations
AvailableProposed for fundingFuture (planned/possible)
Increasing R&D stage
Precedencerelationship
RDP
Failurepossibility
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Determining Value
$
$1
2
3
4
• V1 and V2 are functions of CA and CB
• V3 and V4 are functions of CB
A
B
• Both 1 and 2 are required for A and B• 1, 2 and 4 are required for B• 3 may not be required
V = valueC = cash flow
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Relational ModelRDP_Types
TypeDescriptionTechArea_Types
TypeDescription
Gate_Types
TypeDescription
Gates
IDType
RDPs
IDTypeTechAreaGenerationStatusCostPerYearDurationCurrentValueDeployedValueVolatilityStageProgram
Parent_Child
IDGateParentChild
Status_Types
TypeDescription
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Model Integration
Update RDP status
G ener at ion 1Value St r eam
St age1
1I nit ializat ion
Value St r eam
T r u e
F a ls e
St age 1Evaluat e NPV
B u d g e tC a s h F lo wC a s h F lo w P e r Y e a rC a s h F lo w P VD 1D 2E x e r c is e P r ic eN e t O p t io n V a lu eN P VN P V P e r P r ic eO p e r a t in g C o s tO p e r a t in g C o s t P e r Y e a rO p t io n V a lu eP u r c h a s e P r ic eS t a g eT e m pT y p eV o la t ilit y
At t r ibut es
Com put at ionNPV 1
O pt ionDispose
Dispose 2
Updat e 1Value St r eam
Com put at ionNPV 2 T r u e
F a ls e
St age 2Evaluat e NPV
St age2Updat e 2
Value St r eam
Com put at ionNPV 3 T r u e
F a ls e
St age 3Evaluat e NPV
Dispose 3
Updat e 3Value St r eam
Com put at ionNPV 4
T r u e
F a ls e
Deploym entEvaluat e
Dispose 4
Dispose 5
St age3T r u e
F a ls e
St age 3 Success
Dispose 6
G ener at ion 2Value St r eam
G ener at ion 3Value St r eam
2I nit ializat ion
Value St r eam
3I nit ializat ion
Value St r eam
T r u e
F a ls e
St age 2 Success
Dispose 7
St age 1 SuccessT r u e
F a ls e
Dispose 8
1Updat e St age
2Updat e St age
3Updat e St age
G ener at ionBudget I nit ializat ion
Budget
Cyc leBudget
Det er m iniat ionBudgetDiv is ion
Budget
O pt ionsSt age 1
G ener at ionSt age 1Allocat or Signal 1
T r u e
F a ls e
St age 1Fund Pr ojec t
Dispose 9
1Cyc le St age
Budget
G ener at ionSt age 2Allocat or
Signal 22
Cyc le St ageBudget
G ener at ionSt age 3Allocat or
Signal 33
Cyc le St ageBudget
O pt ionsSt age 2
T r u e
F a ls e
St age 2Fund Pr ojec t
Dispose 10
O pt ionsSt age 3
T r u e
F a ls e
St age 3Fund Pr ojec t
Dispose 11
G ener at ionSt age 4Allocat or
Signal 44
Cyc le St ageBudget
O pt ionsSt age 4
T r u e
F a ls e
St age 4Fund Pr ojec t
Dispose 12
Budget Cycle for Stages
Budget for Enterprise
Value Stream Creation
Stage 1 - Basic Research
Stage 2 - Exploratory Development
Stage 3 - Advanced Development
Stage 4 - Deployment
St age 1aAdjus t Value
St age 1bAdjus t Value St age 1c
Adjus t Value
4Updat e St age
St age 2aAdjus t Value
St age 2bAdjus t Value
St age 2cAdjus t Value
St age 3aAdjus t Value St age 3b
Adjus t Value
St age 3cAdjus t Value
St age 4aAdjus t Value
St age 4bAdjus t Value
T r u e
F a ls e
St age 4 Success
Dispose 13St age 4c
Adjus t Value
Deploym entUpdat e
0
0
0
0
0
0
0
0 0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0 0
0 0
0
0
0
0
0
0
0 0
0
0
0
0
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0
R&D Process Model
Initialize process model
R&D Product Model
Query parameters for value computation
Update current value
Query parameters for stage/programsubmission
ARENA® simulation
Microsoft® Access(Read/write via ADO)
Generate new RDPs
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Pull Dynamics
AvailableProposed for funding (could start work now)Future (prerequisites not fulfilled)
Desired RDP
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Future Research
• Model more complex decision logic in process model
• Specify computationally efficient valuation methods for RDPs in complex value networks
• Enhance knowledge management in product model
• Enhance and validate via case studies• Explore integration with strategic design
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Questions?
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Further Reading
• Bodner, Rouse and Pennock, 2005, Using simulation to analyze R&D value creation, Winter Simulation Conference, submitted.
• Hansen, Weiss and Kwak, 1999, Allocating R&D resources: a quantitative aid to management insight. Research Technology Management 42: 44-50.
• Rouse and Boff, 2003, Value streams in science & technology: a case study of value creation and intelligent tutoring systems, Systems Engineering 6: 76-91.
• Rouse and Boff, 2005, Organizational simulation. New York: Wiley-Interscience.
• Trigeorgis, 1996, Real options: managerial flexibility and strategy in resource allocation. Cambridge, MA: The MIT Press.