klastorin_parte1_2.ppt

8/16/2019 klastorin_parte1_2.ppt

1/38

Criticisms of NPV/DCF1) Assumes that cash flow forecasts are accurate; ignores

the “human bias” effect

2) Fails to include effects of inflation in long term

projects3) Ignores interaction with other proposed and ongoing

projects minimi!e ris" through di#ersification)

$) %se of a single discount rate for the entire project ris"is t&picall& reduced as the project e#ol#es)


2/38

Expected Commercial Value (ECV)

Develop NewProduct

Technical Failure

Technical Success

Probability = p t

Probability = 1 - p t

Launch NewProduct

CommercialFailure (with net

enefit ! ")

Commercial Success(with net enefit !

NPV)

Probability = p c

Probability = 1 - pc

'is" class 1 'is" class 2


3/38

DCF Example #e$isited

(iscount rate r 1 (iscount rate r 2

Research &Product

Development

De$elopment

Succeeds

Probability = p t

De$elopment Fails

Probability = 1 - p t

MarketDevelopment

Product Demand%i&h

0.3

Product Demand'edium

Product Demandow

0.5

0.2

Drop pro ect


4/38

#an*in&/Scorin& 'odelsProfitability/value1) Increase in profitability?2) Increase in market share?3) Will add knowledge to organization that can be leveraged by other projects?4) Estimated NPV, ECV, etc.

Or

ganization's Strate

g

y1) Consistent with organization's mission statement?2) Impact on customers?

Risk1) Probability of research being successful?2) Probability of development being successful?3) Probability of process success?4) Probability of commercial success?5) Overall risk of project6) Adequate market demand?7) Competitors in market

Or

ganization Costs1) Is new facility needed?2) Can use current personnel?3) External consultants needed?4) New hires needed?

Miscellaneous Factors1) Impact on environmental standards?2) Impact on workforce safety?3) Impact on quality?4) Social/political implications


5/38

Scorin& +ttri utes

vi xi =1 - exp L - x i1 - exp L - U

.

To con$ert $arious measurement scales to a (", -) ran&e.

I*+A' ,-A +. #alue of attribute i is

+/0 *+* IA ,-A +. #alue of attribute i is

vi xi =xi - LU - L

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1.00

1 2 3 4 5 6 7

Response

Linear Scale

Exponential Scale


6/38

#an*in&/Scorin& Example


7/38

+ttri ute 0- 01 02 03 04Pro ect

Score (V )

Pro ect + $ &es li"el& $ 1Pro ect 5 2 no unsure 3 $

inear ScalePro ect + 456 426 456 0.413Pro ect 5 426 456 46 46 456 0.525

Exponential ScalePro ect + 475 48$ 4 475 4 0.581Pro ect 5 48$ 475 499 499 475 0.845

Ranking/Scoring Example (cont’d)


8/38

+nal67in& Pro ect Portfolios8 5u le Dia&ram

Expected NPV

Prob of Commercial Success

High Zero

Low

High


9/38

+nal67in& Pro ect Portfolios8 Product $s Process

ExtentofProdu

ctChange

Extent of Process Change

Source: Clark and Wheelwright, 1992


10/38

9e6 Elements of Pro ect Portfolio Selection Pro lem

14 :ulti period in#estment problem

24 op management t&picall& allocates funds to different product lines e4g4< compact cars< high end sedans)

34 0roduct lines sell in separate but not necessaril&independent) mar"et segments

$4 0roduct line allocations are changed fre=uentl&

64 -onditions in each mar"et segment are uncertain from period to period due to competition and changingcustomer preferences


11/38

:Sta&e; ?udget-ontingenc& 0lan0roduct >0erformance 'e#iews

>nitiation Define Desi&n Control>mpro$e

@or" ,tatement'is" Assessment0urchasing 0lan-hange :gt

Initiation0roject 'e#iew-harter

Source: PACCAR Information Technology DivisionRenton, WA

0roduction close out

essons learned

0ost project audit


12/38

Pro ect Selection Example

Y e a r (t)1 2 3 4

Project A ($40) $10 $20 $20

Project B ($65) ($25) $50 $50Bu !et

"i#it (B t ) $120 $20 $40 $55


13/38

Phases of Pro ect 'ana&ementn

0roject formulation and selectionn 0roject planningu ,ummar& statementu @or" brea"down structureu rgani!ation planu ris" managementu ,ubcontracting and bidding process

n 0roject schedulingu ime and scheduleu 0roject budgetu 'esource allocationu

+=uipment and material purchasesn :onitoring and control

u -ost control metricsu -hange ordersu :ilestone reports


14/38

Pro ect Plannin&n ,ummar& ,tatement

u + ecuti#e summar&. mission and goals< constraintsu (escription and specifications of deli#erablesu Bualit& standards used e4g4< I, )u 'ole of main contractor and subcontractorsu -omposition and responsibilities of project team

n rgani!ation 0lanu :anagerial responsibilities assigned; signature authorit&u -ross impact matri who wor"s on what)

u 'elationship with functional departmentsu 0roject administrationu 'ole of consultantsu -ommunication procedures with organi!ation< client< etc4


15/38

>mportance of Pro ect Plannin&

The ?P #ule of Pro ect 'ana&ement8

P rior P lanning P re#ents Poor P rojectP erformance

:>f 6ou fail to plan, 6ou will plan to fail=

+non6mous


16/38

@or* 5rea*down Structure (@5S)

1) ,pecif& the end item “deli#erables”

2) ,ubdi#ide the wor"< reducing the dollars andcomple it& with each additional subdi#ision

3) ,top di#iding when the tas"s are manageable “wor" pac"ages” based on the following.

C ,"ill group s) in#ol#ed

C :anagerial responsibilit&

C ength of time

C Dalue of tas"


17/38

@or* Pac*a&es/Tas* Definition

he wor" pac"ages tas"s or acti#ities) that are defined b& the @?, must be.

C 'ana&ea le

C >ndependent

C >nte&rata le

C 'easura le


18/38

Desi&n of a @5S

“ he usual mista"e 0:s ma"e is to la& out too man& tas"s;subdi#iding the major achie#ements into smaller andsmaller subtas"s until the wor" brea"down structure

@?,) is a Eto do list of one hour chores4 It s eas& to get

caught up in the idea that a project plan should detaile#er&thing e#er&bod& is going to do on the project4 hissprings from the screw& logic that a project manager s jobis to wal" around with a chec"list of 15


19/38

Two; e$el @5S

1. Charity Auction

1.1 EventPlanning

1.2 ItemProcurement

1.3 Marketing 1.4. CorporateSponsorships

@?, le#el 1

@?, le#el 2


20/38

Three; e$el @5S

1.1 EventPlanning

1.2 ItemProcurement

1.3 Marketing

1. Charity Auction

1.4 CorporateSponsorships

1.1.1 Hire Auctioneer

1.1.2. Rent space

1.1.3 Arrange fordecorations

1.2.1 Silentauction items

1.2.2 Live auctionitems

1.2.3 Raffle items

1.3.1 Individualticket sales

1.3.2 Advertising

1.1.4 Print catalog

@?, le#el 1

@?, le#el 2

@?, le#el 3


21/38

Estimatin& Tas* Durations (contAd)

B 5enchmar*in&

B 'odular approach

B Parametric techni ues

B earnin& effects


22/38

5eta Distri ution

Completion time of task j

Optimistic Time t jo Pessimistic Time t j

pTime

Probability densityfunction

Expected duration = µMost Likely Time = t m


23/38

5eta Distri utionFor each tas" j< we must ma"e three estimates.

most optimistic time

most pessimistic time

most li"el& time

t jo

t jp

t jm

Expected duration µ j =t jo + t j

p + 4t jm

6

Variance of task j = σ j2 = t jp - t jo 2

36


24/38

Estimatin& Tas* Durations8 Paintin& a #oomTas* . 0aint $ rooms< each is appro imatel& 1 2 4 %se flat paint on walls<semi gloss paint on trim and woodwor"4 +ach room has two doors and fourwindows4 Hou must appl& mas"ing tape before painting woodwor" around thedoors and windows4 0reparation consists of washing all walls and woodwor"

some sanding and other prep wor" will be needed)4 nl& one coat of paint isnecessar& to co#er e isting paint4 All supplies will be pro#ided at the start of thetas"4 0re#ious times on similar painting jobs are indicated in the table below4

%ours #in %ours #in

27 25 31 5238 25 19 1533 12 26 2717 44 30 2726 7 25 2122 1 24 2814 2 32 5830 27 32 128 30 13 4321 13 42 45

23 59 22 5727 44 32 1523 15 32 3137 6 27 1517 54 26 1117 13 21 52

@hat is &our estimate of the a#erage time &ou willneed @hat is &our estimate of the #ariance


25/38

Estimatin& Tas* Durations with >ncenti$es

Tas*8 Consider the paintin& o that 6ou ha$e ust estimated Now, howe$er, there areexplicit incenti$es for meetin& 6our estimated

times >f 6ou finish paintin& the room efore6our specified time, 6ou will recei$e a -"onus pa6ment % @EVE#, if 6ou finish

the paintin& o after 6our specified time, 6ou

will e fined -"""#e$ised estimated time !


26/38

Estimatin& Tas* Durations with >ncenti$es

Tas*8 Consider the paintin& o that 6ou ha$e ust estimated Now, howe$er, there areexplicit incenti$es for meetin& 6our estimated

times >f 6ou finish paintin& the room efore6our specified time, 6ou will recei$e a -"onus pa6ment >f 6ou finish the paintin& o

after 6our specified time, there is no penalt6

#e$ised estimated time !


27/38

#ole of Pro ect 'ana&er/Team

0roject :anager

-lient

,ubcontractors

'egulating

rgani!ations

0roject eam

Functional:anagers

op:anagement


28/38

#esponsi ilities of a Pro ect 'ana&er

To the or&ani7ation and top mana&ement C :eet budget and resource constraints C +ngage functional managers

To the pro ect team C 0ro#ide timel& and accurate feedbac" C Jeep focus on project goals C :anage personnel changes

To the client C -ommunicate in timel& and accurate manner

C 0ro#ide information and control on changesKmodifications C :aintain =ualit& standards

To the su contractors C 0ro#ide information on o#erall project status


29/38

Pro ect Team

@hat is a pro ect teamA group of people committed to achie#e acommon set of goals for which the& hold

themsel#es mutuall& accountableCharacteristics of a pro ect team

C (i#erse bac"groundsKs"illsC Able to wor" together effecti#el&Kde#elop s&nerg&C %suall& small number of peopleC La#e sense of accountabilit& as a unit


30/38

“I design user interfaces to please an audience of one.I write them for me. If I’m happy, I know some coolpeople will like it. Designing user interfaces by

committee does not work very well; they need to becoherent. As for schedule, I’m not interested inschedules; did anyone care when War and Peace cameout?”

Developer, Microsoft Corporation As reported by MacCormack and Herman, HBR Case 9-600-097:

Microsoft Office 2000

“I design user interfaces to please an audience of one.I write them for me. If I’m happy, I know some coolpeople will like it. Designing user interfaces by

committee does not work very well; they need to becoherent. As for schedule, I’m not interested inschedules; did anyone care when War and Peace cameout?”

Developer, Microsoft Corporation As reported by MacCormack and Herman, HBR Case 9-600-097:

Microsoft Office 2000


31/38

>ntra;team Communication

' ! Num er of pro ect team mem ers ! Num er of lin*s etween pairs of team mem ers

If : M2< then M 1

If : M3< then M 3


32/38

Num er of >ntra;team in*s

0

50

100

150

200

250

300

350

400

450

1 3 5 7 9 1 1

1 3

1 5

1 7

1 9

2 1

2 3

2 5

2 7

2 9

& ' &o. o ea# *e#bers

L = Number of Intra-team Links = N2

= N(N-1)2


33/38

>mportance of Communication

n the occasion of a mi&ration from the east, men disco$ered aplain in the land of Shinar, and . said to one another, :Come, letus uild oursel$es a cit6 with a tower whose top shall reach thehea$ens. = The ord said, .:Come, let us &o down, and therema*e such a a le of their lan&ua&e that the6 will not

understand one anotherAs speech = Thus, the ord dispersedthem from there all o$er the earth, so that the6 had to stop

uildin& the cit6

Genesis 11: 1-8


34/38

Pro ect Performance and


35/38

Pro ect Performance and


36/38


37/38

Extent of >ndi$idual Contri ution8 %i&h $s owPerformin&


38/38

Decision 'a*in& Effecti$eness8 %i&h $s owPerformin&

klastorin_parte1_2.ppt

Documents