dynamic decision management · m a r k e t t e a m s automotive industries financial institutions...

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Dynamic Decision Management –Strategische Entscheidungen bei Flexibilität undUnsicherheit

Gastvorlesung TU Berlin, Lehrstuhl für Finanzierung & Investition, Prof. Dr. Hirth

Berlin, 5. Juni 2012

A.T. Kearney 10/05.2012/43216d 2

Agenda

■ About A.T. Kearney

■ Dynamic Decision Management

• Methodology

• Long case: Rent a Power Plant

• Short case: Bidding Process

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About A.T. Kearney

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"Our success as consultants will depend upon theessential rightness of the advice we give and our

capacity to convince those in authority that it is good."

Andrew Thomas Kearney

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Our expertise spans a wide range of industries and servicesM

ark

et

Te

am

s

Automotive Industries

Financial Institutions

Utilities

Consumer & Retail

Pharmaceuticals &Health Care

Process Industries

Communications &High Tech

Transportation

Private Equity

Competence Teams

About A.T. Kearney

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Where we are

• Amsterdam• Berlin• Brussels• Bucharest• Copenhagen• Düsseldorf• Frankfurt• Helsinki• Istanbul

• Kiev• Lisbon• Ljubljana• London• Madrid• Milan• Moscow• Munich• Oslo

• Paris• Prague• Rome• Stockholm• Stuttgart• Vienna• Warsaw• Zurich

Europe

• Abu Dhabi• Dubai• Johannesburg• Manama• Riyadh

• Abu Dhabi• Dubai• Johannesburg• Manama• Riyadh

Middle East

• Bangkok• Beijing• Hong Kong• Jakarta• Kuala Lumpur• Melbourne• Mumbai

• Bangkok• Beijing• Hong Kong• Jakarta• Kuala Lumpur• Melbourne• Mumbai

Asia Pacific• Atlanta• Cambridge• Chicago• Dallas• Mexico City• New York

• Atlanta• Cambridge• Chicago• Dallas• Mexico City• New York

Americas

• San Francisco• São Paulo• Southfield• Toronto• Washington, DC

• New Delhi• Seoul• Shanghai• Singapore• Sydney• Tokyo

• Global footprint: 54 Offices in major business centers in 39 countries• Resources: More than 3,000 employees• Success: Consulting fees of more than US$1 bn in 2011• Recognition: Ranked 11th of 236 firms in "Best Firms to Work For 2009"

About A.T. Kearney

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• Methodology



Dynamic Decision Management

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The current economic challenges require fast and widestrategic decisions

Challenges

Business environment

• Scarce financial resources due to the crisis

• Reduction of investment volumes required

• Reprioritization of strategy or investmentdecisions respectively

• Highly volatile markets

• Uncertain future

Shortfalls of traditional decisionmaking approaches

• High planning complexity due to a wide rangeof dynamic parameters

• Often, modeling of selected scenarios donewithout explicit statement on probability

• No consideration of future decision alternativesin selected scenarios

• Value of entrepreneurial decision alternativescurrently not identified

Dynamic Decision Management: Methodology

Improved decision making and higher decision qualityfor strategic decisions

Objective

Source: A.T. Kearney

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Our Dynamic Decision Management methodology helps ourclients to answer four fundamental questions

Key client propositions: Dynamic Decision Management


Questions

Scenariodevelopmentand analysis

Strategic optionsdevelopment

Total valuecalculation

Trigger pointbased

strategy process

Which potentialfutures

are there?

What are strategicalternatives to

react?

Which set ofalternatives

provides highestvalue?

How can strategicoptions bemanaged

dynamically?

A DCB

Overview

Overallapproach


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Components of total value

• The DDM-Approach builds upon traditionalvaluation, i.e. the calculation of the NPV ofexpected cash flows

• Additionally, risks and uncertainties, e.g.external market conditions, are considered

• Furthermore, the value of decision alternativesis quantified

• As a next generation scenario approach,DDM evaluates the complete space ofpotential futures/scenarios

• A.T. Kearney approach successfully appliedin several cases with high uncertainty anddecision alternatives, e.g. energy deliverycontracts, power plant mothballing andinvestment decisions, high speed railwayinvestments, and M&A company valuation

Traditionalvaluation

The Dynamic Decision Management approach accounts foruncertainty and flexibility in strategic decision making

Unique selling proposition: DDM approach

Flexibility Total valueNPV ofexpectedcashflows

Risk

Riskvalue

Flexvalue

Totalvalue

Key considerations



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There are stages of excellence, on how to incorporate risk inyour decision making

• Higher risk meansproject-specific higherWACC

• Risk enhancement leadsto lower NPV

• Thus chancesdiscriminated versusrisks

• Diverse risks ofindividual cash flowelements not considered

WACC8%

WACC10%

risk

• Mapping of uncertainfuture cash flows usingdiscrete scenarios

• Completeness ofdecision alternativesresp. scenarios notprovided

• No statement onprobabilities

NPV

• Discrete scenarios withrespective risk aresubjectively/generallyallocated to probabilities

• Lack of fully analyticalderivation of probabilities

NPV

Probability (P)

Scenario 1

Scenario 2

Scenario 3

• Expected value andvolatilities mean: stabledistribution of cash flowsand their probabilities

• Completeness of allcash flow points throughanalytical methodologyinstead of intuition

• Risk considered throughprobabilities

NPV

Probability (P) Probability (P)

Total Value

• Consideration of activemanagement (flexibility)in the future

• Value optimizationthrough activemanagement = exerciseof decision alternatives

• NPV plus value offlexibility = Total Value

NPV with riskreduction

Scenario-basedNPV

NPV with lumpsum probabilities

NPV with specificprobabilities

Total value1 2 3 4 5

Scenariobundle 1

Scenariobundle 2

Scenariobundle 3

NPV

Risk Risk

Value enhancementthrough

investmentdecision

Probability toachieve project

value


Stages of Excellence in accounting for risk


Valuation approachincl. Risk

Valuation approach incl.Risk and Flexibility


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Different types of decision alternatives have to be differentiatedto model realistic business implications

Decisiontype

Description Example

Categorize types of decision alternatives


Abandon

Activate

Choose

Combine

Terminate a project or an ongoinginvestment

Carry out a project once a certaintrigger has been activated.

Choose the most valuable amongseveral projects

Choose the best combination ofpossible independent projects

A chemical company has started to commercializea new product. As it realizes that the business isnot profitable, it stops losses by terminating theproject

A reseller wins another sales contract if certainsales targets are met

A city plans to extend its public transportationsystem to a suburb. It can do so either by buildinga new tram line OR by buying new buses andbuilding the infrastructure for bus stops.

The investment plan to build a new marina com-plex includes an option to add several facilitiessuch as a supermarket AND/OR a fashion shopAND/OR a boat chandlery AND/OR a restaurant.

Switch Switch back and forth betweendifferent projects or operation modes

An automotive manufacturing line can switch toproduce different kinds of cars.


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• Identify macro drivers

• Determine most likely scenario & implications

• Estimate future cash flow of most likely scenario

• Derive probability distribution (risk value)• Derive value of flexibility (flex value)• Calculate total value

• Identify and prioritize strategic alternatives in „space ofpotential futures“ spanned by scenario analysis

• Implement trigger points and model decision paths

Based on a scenario analysis, relevant strategic decisionalternatives are identified, evaluated and managed by DDM


Methodology: Identification, valuation and management of strategic decisions

Methodology built on well-known cash flow models

Clear picture of strategy‘smost probable Total Value

Key elements Benefits

Demonstration thatmanagement will activelyinfluence value of strategy

C

A

• Identify trigger points with highest value impact• Develop trigger-point-based strategic radar• Implement dynamic strategy review process

Dynamic DecisionManagement fullyavailably

D

As a next generation scenario approach, DDM evaluates the complete space ofpotential futures/scenarios and allows for their quantification.

B


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Client examplePortfolio of strategic business topics for utilities

A matrix helps identify business issues with high un-certaintiesand a high degree of entrepreneurial flexibility

Business opportunities with high uncertainties AND a high business flexibilitycreate a substantial number of options with a potentially high real option value

"Classic"scenario-basedDCF assessment

External and internal“uncertainties"

Entrepreneurial "Flexibility"

low

high

low high

Gridstrategypower

Tradingstrategy

Waterstrategy

PHEVstrategy

Salesstrategy

M&A-Strategy

Smartmetering-strategy

"Total Value" approachbased on real optionsanalysis: additionalassessment of the value ofstrategic options

Gridstrategygas

Heatstrategy

Fossilgenerationstrategy

Renewablegenerationstrategy

Shared servicestrategy

Technical servicestrategy

Mothballingstrategy



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• Methodology




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Current situation and main questions

Source: Partner 1; A.T. Kearney

Long case: Rent a power plant

Current situation

• “Partner 2” and Partner 1 have acapacity utilization contract for “Powerplant” that will expire at the end of 2012

• When the contract expires, “Partner 2”has the exclusive right to extend thecontract

• The duration of the next contract issubject of negotiation between Partner 1and “Partner 2”

• Partner 1 can start negotiations withother companies only if “Partner 2”decides not to extend the contract

Main questions

• What value does the “Power plant”contract most probably have from“Partner 2’s” perspective ?

• How can uncertainties of the businesscase be considered in the evaluation?

• What value does “Partner 2’s” flexibilityto extend or terminate the contract atcertain points in the future have?

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The base and pessimistic case have been modeled based ondifferent price assumptions

• EEX base and peak prices have beenestimated based on the assumptionthat nuclear energy is not beingphased out

• It is assumed that “Power plant” isonline if forecasted price develop-ments result in a positive CDS; thisresults into a specific demandforecast

• CO2-price is assumed to remainconstant from 2013 onwards

• Dollar exchange rate is assumed tobe constant at 1.39 USD/€

• Installed capacity will increasegradually

2011 2012 2013 2014 2015 2016 2017 2018 2019 2020

Base price €/MWh 51.8 58.4 61.6 65.9 63.2 67.3 70.2 73.6 75.7 78.6

Peak price €/MWh 69.4 78.8 83.1 90.3 87.4 93.1 97.1 101.8 104.7 108.8

MWh Tsd.MWh

422 469 439 520 598 664 716 765 779 845

API#2 US$/t 99.9 104.5 107.0 109.0 110.0 112.2 114.4 116.7 119.1 121.4

CO2 €/EUA 16.8 20.5 25.0 25.0 25.0 25.0 25.0 25.0 25.0 25.0

Dollarexchangerate

US$/€ 1.39 1.39 1.39 1.39 1.39 1.39 1.39 1.39 1.39 1.39

Installedcapacity

MW 170.0 180.0 190.0 200.0 235.0 259.2 259.2 259.2 259.2 259.2

Main assumptions Partner 1


Example

For the pessimistic case, price levels and CO2-price levels are lower than in thebase case. All other assumptions remain equal.

Example: Base case


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Two NPV-scenarios have been calculated to determine thevalue of the “Power plant” contract

Base Case -2.0

PessimisticCase

-32.8

Basic NPV scenarios “Power plant” contract(in € mn)

• The two scenarios are based on specificsimulations of several cash flowcomponents from “Partner 2”-perspective

– Revenue

– Energy rate (CO2, coal, oil, operatingsupplies)

– Capacity charge

• Cash flows are highly uncertain due to thevolatility of their underlying price andquantity assumptions

Simple scenario calculations do not consider volatility of markets and“Partner 2’s” flexibility to extend the contract.



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Historic volatilities and correlations

Volatilities and correlations for the provided yearly cash flowshave been used as input factors for the model

Cashflow component Volatility

Revenue 34%

Cost of coal 32%

Cost of CO2 31%

Cost of oil and operatingsupplies

36%

Volatilities Correlations

Cashflowcomponent

Reve-nue

Cost ofcoal

Cost ofCO2

Cost ofoil & op.supply

Revenue 1.00 -1.00 -0.99 -1.00

Cost of coal 1.00 0.98 1.00

Cost of CO2 1.00 0.98

Cost of oil &op. supplies

1.00

Volatilities have been estimated based onyearly cashflows from “Partner 1’s” basecase scenario (2011-2020)

Correlations between revenue, cost of coal,cost of CO2, and cost of oil & operating sup-plies have been estimated based on yearlycashflows from “Partner 1’s” base casescenario (2011-2020)


Simplified


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We assume that “Partner 2” has the flexibility to extend thecontract in 2012 and 2015

Modeling of strategic decision alternatives

Valuation of flexibility: What is the value of “Partner 2’s” combined flexibility toextend the contract in 2012 and 2015?

2012 2015 2020


2011

End of currentcontractduration

Assumedend of

duration ofcontract 1

Current contract New contract 1 New contract 2

“Contractextension”

“Contracttermination”

“Activecontract”

“Contractextension”



Assumedend of

duration ofcontract 2

Assumption


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The value of the flexibility amounts to €31.2 mn, leading to aTotal Value of €29.3 mn compared to NPV of €-2.0 mn

• Result: Total Value amounts to €29.3 mn –compared to a NPV of €-2.0 mn

• The value of possibility to extend the contractin 2012 including the possibility to furtherextend in 2015 has a current value of€31.2 mn

Total value – base case

Components of Total Value

-2.0

Total Value

29.3

Flex Value

31.2

NPV


Probability Distribution

Contractextension

69%

• An extension in 2012 incl. the option to furtherextend from 2015 to 2020 shows a positivevalue in 69% of all scenarios.

• The value of the possibility to extend the con-tract in 2015 was calculated to be €23.0 mn

Example 2012


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• Methodology




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• Development of optimal sourcing strategy: closing of a fix-price long-term power supply contract is most attractive in terms of value (NPV) andrisk

• Value (NPV): long-term contract is equally attractive as sourcing at futuremarket prices as expected by client

• Risk: Lost market chances due to long-term fix-price log-in are smallerthan avoided market risks by securing the price via log-in by the contract.

For a major Swiss power off-taker, we organized a biddingprocess for power delivery

• Client analysis identified a 800 GWhwinter base load gap in its portfolio

• Client wants to source “green electricity”with delivery point in Germany orSwitzerland for 10 years

• Client is risk averse and has limited ex-perience in professional electricity trading

• Organize bidding process for long-termdelivery contract with fixed price; collectdata on EEX futures and asset dealopportunities

• Analyze value and risk profile of sourcingvia market (EEX) vs. full or partial closingof the gap via long-term delivery contract

Client situation

Project content

Approach and main results

Risk valuation: bidding process for 10 year energy delivery

Short case: Bidding Process


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The successful bidding process reduced cost and risksignificantly.

Source: Projektteam Analyse und Vergleich von Hedging-Alternativen

1300120011001000900700600500400

60 %

100%

90 %

80 %

70 %

50 %

800

40 %

30 %

20 %

10 %

0 %

NPV total cost in Mio. €

150014003000

EEX

50/50

Bidder A

Co

nfi

nd

en

ce

leve

l

Estimated risk through priceincrease in the market

Reduced Chance to potentiallysource energy at lower cost

€ 270 Mio.

€ 76 Mio.

Increasing costDecreasing cost

Short case: Bidding Process

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Questions?

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Americas AtlantaCalgary

ChicagoDallas

DetroitHouston

Mexico CityNew York

San FranciscoSão Paulo

TorontoWashington, D.C.

Asia Pacific BangkokBeijing

Hong KongJakarta

Kuala LumpurMelbourne

MumbaiNew Delhi

SeoulShanghai

SingaporeSydney

Tokyo

Europe AmsterdamBerlinBrusselsBucharest

BudapestCopenhagenDüsseldorfFrankfurt

HelsinkiIstanbulKievLisbon

LjubljanaLondonMadridMilan

MoscowMunichOsloParis

PragueRomeStockholmStuttgart

ViennaWarsawZurich

Middle Eastand Africa

Abu DhabiDubai

JohannesburgManama

Riyadh

A.T. Kearney is a global team of forward-thinking, collaborative partners that delivers immediate, meaningfulresults and long-term transformative advantage to clients.

Since 1926, we have been trusted advisors on CEO-agenda issues to the world’s leading organizations acrossall major industries and sectors. A.T. Kearney’s offices are located in major business centers in 39 countries.

dynamic decision management · m a r k e t t e a m s automotive industries financial institutions...

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