estimating projects (pmp)

8/9/2019 Estimating Projects (PMP)

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Project Estimation and

scheduling Outline:

– Estimation overview

– Cocomo: concepts, process and tool.

– Detailed schedule/planning terminology and processes

– Planning ools !"# Project$


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Estimation

%he single most important tas& o' a project: setting realistic e(pectations.

)nrealistic e(pectations *ased on

inaccurate estimates are the single largest

cause o' so'tware 'ailure.+utrell, #ha'er and #ha'er, %-uality #o'tware Project "anagement+


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Why its important to you!

Program development o' large so'tware systems

normally e(perience 012

cost overruns and a 32 schedule slip

342 o' large projects deliver56O7869

;ey reasons5poor management and inaccurate

estimations o' development cost and schedule

8' not meeting schedules, developers o'ten pay

the price


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he Pro*lems

Predicting so'tware cost

Predicting so'tware schedule

Controlling so'tware ris&

"anaging/trac&ing project as it progresses


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undamental estimation


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Costing and pricing

Estimates are made to discover the cost, to thedeveloper, o' producing a so'tware system.

here is not a simple relationship *etween the

development cost and the price charged to thecustomer.

@roader organisational, economic, political and

*usiness considerations in'luence the pricecharged.


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#o'tware pricing 'actors


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6ature o' Estimates

"an "onths !or Person "onths$, de'ined as 34man0hours o' direct0charged la*or

#chedule in months !reell0managed program


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A Common !su*jective$

estimation models

E(pert Budgment nalogy

Par&insons law

Price to win


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E(pert judgment

One or more e(perts in *oth so'twaredevelopment and the application domain use their

e(perience to predict so'tware costs. Processiterates until some consensus is reached.

dvantages: elatively cheap estimation method.Can *e accurate i' e(perts have direct e(perienceo' similar systems

Disadvantages: Fery inaccurate i' there are noe(perts


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Estimation *y analogy

he cost o' a project is computed *y comparing

the project to a similar project in the same

application domain dvantages: "ay *e accurate i' project data

availa*le and people/tools the same

Disadvantages: 8mpossi*le i' no compara*le project has *een tac&led. 6eeds systematically

maintained cost data*ase


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Par&insonGs Haw

he project costs whatever resources are

availa*le

dvantages: 6o overspend

Disadvantages: #ystem is usually un'inished


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op0down and *ottom0up estimation

ny o' these approaches may *e used top0downor *ottom0up.

op0down

– #tart at the system level and assess the overallsystem 'unctionality and how this is deliveredthrough su*0systems.

@ottom0up

– #tart at the component level and estimate the e''ortre


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op0down estimation

)sa*le without &nowledge o' the systemarchitecture and the components that might *e

part o' the system.

a&es into account costs such as integration,con'iguration management and documentation.

Can underestimate the cost o' solving di''icult

low0level technical pro*lems.


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@ottom0up estimation

)sa*le when the architecture o' the system is&nown and components identi'ied.

his can *e an accurate method i' the system has

*een designed in detail. 8t may underestimate the costs o' system level

activities such as integration and documentation.


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Estimation methods

Each method has strengths and wea&nesses. Estimation should *e *ased on several methods.

8' these do not return appro(imately the same

result, then you have insu''icient in'ormationavaila*le to ma&e an estimate.

#ome action should *e ta&en to 'ind out more in

order to ma&e more accurate estimates.

Pricing to win is sometimes the only applica*le

method.


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Pricing to win

his approach may seem unethical and un0 *usinessli&e.

7owever, when detailed in'ormation is lac&ing it

may *e the only appropriate strategy. he project cost is agreed on the *asis o' an

outline proposal and the development isconstrained *y that cost.

detailed speci'ication may *e negotiated or anevolutionary approach used 'or systemdevelopment.


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lgorithmic cost modeling

Cost is estimated as a mathematical 'unction o' product, project and process attri*utes whose

values are estimated *y project managers

he 'unction is derived 'rom a study o' historicalcosting data

"ost commonly used product attri*ute 'or cost

estimation is HOC !code siJe$ "ost models are *asically similar *ut with

di''erent attri*ute values


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Criteria 'or a 9ood "odel

De'inedKclear what is estimated ccurate

O*jectiveKavoids su*jective 'actors

esults understanda*le Detailed

#ta*leKsecond order relationships

ight #cope

Easy to )se

CausalK'uture data not re


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measure o' the rate at which individualengineers involved in so'tware development

produce so'tware and associated

documentation. 6ot


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#iJe related measures *ased on some output 'romthe so'tware process. his may *e lines o'

delivered source code, o*ject code instructions,

etc. unction0related measures *ased on an estimate

o' the 'unctionality o' the delivered so'tware.

unction0points are the *est &nown o' this type o'measure.

Productivity measures


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Estimating the siJe o' the measure !e.g. how many'unction points$.

Estimating the total num*er o' programmer

months that have elapsed. Estimating contractor productivity !e.g.

documentation team$ and incorporating this

estimate in overall estimate.

"easurement pro*lems


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>hatGs a line o' code= – he measure was 'irst proposed when programs were typed

on cards with one line per card?

– 7ow does this correspond to statements as in Bava which can

span several lines or where there can *e several statementson one line.

>hat programs should *e counted as part o' the system=

his model assumes that there is a linear relationship

*etween system siJe and volume o' documentation. &ey thing to understand a*out early estimates is that

the uncertainty is more important than the initial line –dont see one estimate, see& justi'ia*le *ounds.

Hines o' code


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he lower level the language, the more productive the programmer – he same 'unctionality ta&es more code to

implement in a lower0level language than in a high0level language.

he more ver*ose the programmer, the higherthe productivity

– "easures o' productivity *ased on lines o' codesuggest that programmers who write ver*ose codeare more productive than programmers who writecompact code.

Productivity comparisons


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#ystem development times


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Empirical Model (COCOMO)

Provide computational means 'or deriving #/> costestimates as 'unctions o' varia*les !major cost drivers$

unctions used contain constants derived 'rom

statistical analysis o' data 'rom past projects: – can only *e used i' data 'rom past projects is availa*le

– must *e calibrated to re'lect local environment

– relies on initial siJe and cost 'actor estimates which

themselves are


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COCOMO

COCO"O !CO 6#)C8FE CO# "ODEH$

0irst pu*lished *y Dr. @arry @oehm, 3LM3

8nteractive cost estimation so'tware pac&age thatmodels the cost, e''ort and schedule 'or a new

so'tware development activity. – Can *e used on new systems or upgrades

Derived 'rom statistical regression o' data 'rom a

*ase o' N1 past projects ! 0 43, D#8s$


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>here to ind CoCo"o

http://sunset.usc.ede Or do a 9oogle search on @arry @oehm.


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Productivity Hevels

ends to *e constant 'or a given programmingshop developing a speci'ic product.

3 #HOC/"" 'or li'e0critical code

1 #HOC/"" 'or )# 9overnment


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6ominal Project Pro'iles

#iJe #HOC

M#HOC

1#HOC

3M#HOC

"" 4 3 L3 1L

#chedule"onths

4 M 3A A

#ta'' 3.3 . N.4 3N

#HOC/""

A 1N 14 1


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8nput Data

Delivered ; source lines o' code!;#HOC$ Farious scale 'actors:

– E(perience

– Process maturity

– e


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COCOMO

)ses @asic E''ort E


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COCOMO Mode & Model

hree development environments !modes$ – Organic "ode

– #emidetached "ode

– Em*edded "ode

hree increasingly comple( models

– @asic "odel – 8ntermediate "odel

– Detailed "odel


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COCOMO Modes

Organic "ode – Developed in 'amiliar, sta*le environment

– Product similar to previously developed product

– T4, D#8s !e(: accounting system$

#emidetached "ode – somewhere *etween Organic and Em*edded

Em*edded "ode

– new product re


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COCOMO Models

@asic "odel – )sed 'or early rough, estimates o' project cost, per'ormance,

and schedule

– ccuracy: within a 'actor o' o' actuals N2 o' time

8ntermediate "odel – )ses E''ort djustment actor !E$ 'm 34 cost drivers

– Doesnt account 'or 3 0 2 o' cost !trng, maint, D, etc$

– ccuracy: within 2 o' actuals NM2 o' time

Detailed "odel – )ses di''erent E''ort "ultipliers 'or each phase o' project

!every*ody uses intermediate model$

B i M d l


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Basic Model

Effort Equation (COCOMO 8)

E''ortQ!siJe$e(ponent

– is a constant *ased on the developmental mode

S organic Q .A

S semi Q 1.

S em*edded Q 1.N

– #iJe Q 3s #ource Hines o' Code !;#HOC$

– E(ponent is constant given mode

S organic Q 3.4

S semi Q 3.3

S em*edded Q 3.

B i M d l


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Basic Model

chedule Equation (COCOMO 8)

"DEF !"inimum time to develop$ Q.4R!E''ort$e(ponent

.4 is constant 'or all modes

E(ponent *ased on mode – organic Q .1M

– semi Q .14

– em*edded Q .1

6ote that "DEF does not depend on num*er o'

people assigned.


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Counting;#HOC


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#till how to estimate ;#HOC

9et %e(perts+ to provide estimates. – @etter i' estimates are *ased on so'tware re


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#ome *eginners guidelines

S good estimate is de'enda*le i' the siJe o' the product is identi'ied inreasona*le terms that ma&e sense 'or the application. >ithout seriouse(perience, estimating Hines o' Code 'or a su*stantial application can *e meaningless, so stic& to what ma&es sense. @ottom up is *etter 'or *eginners.

S n estimate is de'enda*le i' it is clear how it was achieved. 8' the

estimate simply came 'rom #>9, or whatever sugar0coated term youwould li&e to give 'or an unde'enda*le num*er$, that in'ormation itsel'gives us an understanding o' the legitimacy we can apply to thenum*ers, and we should e(pect a large uncertainty.

S 8' it was achieved *y ta&ing the *usiness targets and simply suggestingwe can 'it all the wor& into the availa*le time, we can send the

estimator *ac& to the drawing *oard.S good estimate allows all the sta&eholders to understand what went

into the estimate, and agree on the uncertainty associated with thatestimate. >ith that, realistic decisions can *e made. 8' there is any *lac& magic along the way, or i' there is a suggestion that you canaccurately predict, you are in 'or trou*le.


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@asic COCO"O assumptions

8mplicit productivity estimate Organic mode Q 3N HOC/day

Em*edded mode Q A HOC/day

ime re


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8ntermediate COCO"O

a&es *asic COCO"O as starting point 8denti'ies personnel, product, computer and

project attri*utes which a''ect cost and

development time. "ultiplies *asic cost *y attri*ute multipliers

which may increase or decrease costs


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ttri*utes

Personnel attri*utes nalyst capa*ility

Firtual machine e(perience

Programmer capa*ility

Programming language e(perience pplication e(perience

Product attri*utes elia*ility re


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"ore ttri*utes

Computer attri*utes E(ecution time constraints

#torage constraints

Firtual machine volatility

Computer turnaround time

Project attri*utes

"odern programming practices

#o'tware tools

e


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"ntermediate Model

Effort Equation !COCOMO 8)

E''ortQER!siJe$e(ponent

– E !e''ort adjustment 'actor$ is the product o' e''ortmultipliers corresponding to each cost driver rating

– is a constant *ased on the developmental modeS organic Q 1.

S semi Q 1.

Sem*edded Q .M

– #iJe Q 3s Delivered #ource 8nstruction !;D#8$

– E(ponent is constant given mode


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COCOMO COST DRIVERSRatings range: VL, L, N, H, VH, XH

RELY Reliability PCAP Programmer Capability

DATA Database Size AEXP Applications Experience

CPLX Complexity PEXP Platform Experience

RUSE Required Reusability LTEX Language and Tool Experience

DOCU Documentation PCON Personnel ContinuityTIME Execution Time Constant TOOL se of Soft!are Tools

STOR "ain Storage Constraint SITE "ultisite De#elopment

PVOL Platform $olatility SCED Required Sc%edule

ACAP Analyst Capability

Gone:VIRT,TURN,MDDP,VEXP New: RUSE, DOCU, PVOL, PCON

E l COCOMO


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E#ample COCOMO$%' and $OO d*ustments

COCO"O M3 ating H 6 7 F7

COCO"O "ultiplier:

CPHV 3. 3.34 3.1 3.1

COCO" "ultiplier:

OOH 3.A 3.3 3.


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"ntermediate Model E#ample

+i,hly comple# intermediate or,anic pro*ect-ith hi,h tool use.

Estimate 1 D#8s

CPHV Q 3.1 !F7$OOH Q 3.3 !H$

E Q 3.1R3.3 Q 3.A1

E''ort Q 3.A1 R 1. R 13./4 Q 3A.4 man months"DEF Q .4 R 3A.4/.1M Q N.L months

#ta'' re


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E(ample with %options+

Em*edded so'tware system on microcomputer hardware. @asic COCO"O predicts a A4 person0month e''ort

re


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Option: 7ardware 8nvestment

Processor capacity and store dou*led 8"E and #O multipliers Q 3

E(tra investment o' W1, re


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Cocomo in practice !ML projects$ Canned Hanguage "ultipliers were accurate – can

*e tuned/cali*rated 'or a company.

"odeling personnel 'actors, and creatingoptions/scenarios can *e a valua*le tool.

ssumptions and is&s should *e 'actored into the

model

ool Demonstration


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ool Demonstration!we* *ased version$

http://sunset.usc.edu/research/COCO"O88/e(pertXcocomo/e(pertXcocomo.html

http://sunset.usc.edu/research/COCO"O88/e(pertXcocomo/e(pertXcocomo.html

8ts ree and easy to use. #o )se it

Iou can also get a standalone win1 version


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ree CoCo"o ools

COCO"O 88 0 his program is an implementation o' the 3LM3 COCO"O 8ntermediate"odel. 8t predicts so'tware development e''ort, schedule and e''ort distri*ution. 8t is availa*le'or #unO# or "# >indows and can *e downloaded 'or 'ree. he COCO"O 88 model is anupdate o' COCO"O 3LM3 to address so'tware development practiceGs in the 3LLGs and Gs.

evised 8ntermediate COCO"O !EF8C$ is availa*le 'or downloading 'rom the )#ir orce Cost nalysis gency !C$.

") COCO"O is an on0line version o' COCO"O 'rom e(as Y" )niversity. gile COCO"O 0 he Center continues to do research on gile COCO"O 88 a cost

estimation tool that is *ased on COCO"O 88. 8t uses analogy *ased estimation to generateaccurate results while *eing very simple to use and easy to learn.

COCO# 0 he )#C Center is actively conducting research in the area o' o''0the0shel'so'tware integration cost modelling. Our new cost model COCO# !COnstructive CO#$,

'ocuses on estimating the cost, e''ort, and schedule associated with using commercial o''0the0shel' !CO#$ components in a so'tware development project. hough still e(perimental,COCO# is a model complementary to COCO"O 88, capturing costs that traditionally have *een outside the scope o' COCO"O. 8deally, once 'ully 'ormulated and validated, COCO#will *e used in concert with COCO"O to provide a complete so'tware development cost

estimation solution.


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esources

#o'tware Cost Estimating >ith COCO"O 88 – @oehm,*ts, @rown, Chulani, Clar&, 7orowitJ, "adachy, ei'er, #teece 8#@6:0310NNL0

COCO"O 88 0 http://sunset.usc.edu/research/COCO"O88/

6# Cost Estimating >e* #ite 0 http://www3.jsc.nasa.gov/*u/COCO"O.html

Hongstreet Consulting 0 http://www.i'pug.com/'reemanual.htm

@arry @oehm @io 0 http://sunset.usc.edu/esearchX9roup/*arry.html


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Conclusions

E(perience shows that seat0o'0the0pants estimates o' costand schedule are 420 42 o' the actual time/cost. hisamount o' error is enough to get a manager 'ired in manycompanies.

Hac& o' hands0on e(perience is associated with massivecost overruns.

echnical ris&s are associated with massive costoverruns.

Do your estimates care'ully ;eep them up0to0date

"anage to them


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Project #cheduling/Planning

COCO"O his high0level resource estimation. oactually do project need more re'ined plan.


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Estimation

7istory is your *est ally – Especially when using HOC, 'unction points, etc.

)se multiple methods i' possi*le

– his reduces your ris& – 8' using %e(perts+, use two

9et *uy0in

emem*er: its an iterative process

;now your %presentation+ techni


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Estimation

@ottom0up

S "ore wor& to create *ut more accurate

S O'ten with E(pert Budgment at the tas& level

op0downS

)sed in the earliest phasesS )sually with/as nalogy or E(pert Budgment

nalogyS Comparison with previous project: 'ormal or in'ormal

E(pert BudgmentS Fia sta'' mem*ers who will do the wor& S "ost common techni


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Estimation

Parametric "ethods – ;now the trade0o''s o': HOC Y unction Points

unction Points – @ene'it: relatively independent o' the technology used to

develop the system – >e will re0visit this *rie'ly later in semester !when discussing

%so'tware metrics+$

– Fariants: >E@"O !no need to &now this 'or e(am$

e0)se Estimation – #ee -#P" outline

) Calgary


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Iour Early Phase Processes

8nitial Planning:

S >hy – #O>, Charter

S >hat/7ow !partial/3st pass$ – >@#

– Other planning documents[ #o'tware Development Plan, is& "gmt., C'g. "gmt.

EstimatingS #iJe !


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i l


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erminology

Precedence:S tas& that must occur *e'ore another is said to have

precedence o' the other

Concurrence:S Concurrent tas&s are those that can occur at the same time

!in parallel$

Heads Y Hag ime

S Delays *etween activitiesS ime re


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erminology

"ilestones – 7ave a duration o' Jero

– 8denti'y critical points in your schedule

– #hown as inverted triangle or a diamond – O'ten used at %review+ or %delivery+ times

S Or at end or *eginning o' phases

S E(: #o'tware e


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erminology

E(ample"ilestones

i l


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erminology

#lac& Y loat – loat Y #lac&: synonymous terms

– ree #lac& – #lac& an activity has *e'ore it delays ne(t tas&

– otal #lac& – #lac& an activity has *e'ore delaying whole project

– #lac& ime # Q H – E

S E Q earliest time an event can ta&e place

S H Q latest date it can occur w/o e(tending projects

completion date

# h d li h i


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#cheduling echni


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6etwor& Diagrams

Developed in the 3L4s graphical representation o' the tas&s necessary

to complete a project

FisualiJes the 'low o' tas&s Y relationships

" th ti l l i


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"athematical nalysis

PE – Program Evaluation and eview echni


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"#0Project E(ample

6 t & Di


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6etwor& Diagrams

wo classic 'ormats – O: ctivity on rrow

– O6: ctivity on 6ode

Each tas& la*eled withS 8denti'ier !usually a letter/code$

S Duration !in std. unit li&e days$

here are other variations o' la*eling here is 3 start Y 3 end event

ime goes 'rom le't to right

6 d t


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6ode ormats

6 t & Di


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6etwor& Diagrams

O consists o' S Circles representing Events

– #uch as Zstart or Zend o' a given tas&

S Hines representing as&s

– hing *eing done Z@uild )8S a.&.a. rrow Diagramming "ethod !D"$

O6S as&s on 6odes

– 6odes can *e circles or rectangles !usually latter$ – as& in'ormation written on node

S rrows are dependencies *etween tas&s

S a.&.a. Precedence Diagramming "ethod !PD"$

C iti l P th

http://sunset.usc.edu/research/COCOMOII/expert_cocomo/expert_cocomo2000.html


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Critical Path

%he speci'ic set o' se


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Critical Path E(ample

CP"


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CP"

Critical Path "ethod – he process 'or determining and optimiJing the

critical path

6on0CP tas&s can start earlier or later w/oimpacting completion date

6ote: Critical Path may change to another as you

shorten the current #hould *e done in conjunction with the you Y the

'unctional manager

A as& Dependency ypes


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Mandatory Dependencies

S %7ard logic+ dependencies

S 6ature o' the wor& dictates an ordering

S E(: Coding has to precede testing

S E(: )8 design precedes )8 implementation

/iscretionary DependenciesS %#o't logic+ dependencies

S Determined *y the project management teamS Process0driven

S E(: Discretionary order o' creating certain modules



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E#ternal Dependencies

S Outside o' the project itsel'

S E(: elease o' 1rd party product? contract signo''

S E(: sta&eholders, suppliers, I;, year end

esource DependenciesS wo tas& rely on the same resource

S E(: Iou have only one D@ *ut multiple D@ tas&s

as& Dependency elationships


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as& Dependency elationships

inish0to0#tart !#$ – @ cannot start till 'inishes

– : Construct 'ence? @: Paint ence

#tart0to0#tart !##$ – @ cannot start till starts

– : Pour 'oundation? @: Hevel concrete

inish0to0inish !$ – @ cannot 'inish till 'inishes

– : dd wiring? @: 8nspect electrical

#tart0to0inish !#$ – @ cannot 'inish till starts !rare$

E(ample #tep 3


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E(ample #tep 3

"ilestone Chart


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"ilestone Chart

#ometimes called a %*ar charts+

#imple 9antt chart

– Either showing just highest summary *ars

– Or milestones only

@ar Chart


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@ar Chart

9antt Chart

http://pages.cpsc.ucalgary.ca/~hongd/SENG/621/report2.htmlhttp://misc/QSPM/Chapter_10.ppt#COCOMO%2081%20%20II%20Converting%20Size%20Estimateshttp://www.stsc.hill.af.mil/crosstalk/2002/jun/reifer.asphttp://fpex.doc/


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9antt Chart

9antt Chart


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9antt Chart

Disadvantages – Does not show interdependencies well

– Does not uncertainty o' a given activity !as does PE$

dvantages

– Easily understood

– Easily created and maintained

6ote: #o'tware now shows dependencies among tas&s in

9antt charts – 8n the %old+ days 9antt charts did not show these dependencies,

*ar charts typically do not. "odern 9antt charts do show them.

educing Project Duration


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educing Project Duration

7ow can you shorten the schedule=

Fia

– educing scope !or


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Compression echni


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"ythical "an "onth


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"ythical "an0"onth

%Cost varies as product o' men and months, progress does not.+

%7ence the man0month as a unit 'or measuring the

siJe o' jo* is a dangerous and deceptive myth+ eliance on hunches and guesses

– >hat is Zgutless estimating=

he myth o' additional manpower – @roo&s Haw

– % Adding manpower to a late project makes it later +

"ythical "an0"onth


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"ythical "an0"onth

Optimism – %ll programmers are optimists+

– 3st 'alse assumption: %all will go well+ or %each tas& ta&es only

as long as it Zought to ta&e+

– he i(: Consider the larger pro*a*ilities Cost !overhead$ o' communication !and training$

S 7is 'ormula: n!n03$/

– 7ow long does a 3 month project ta&e=

– 3 person: 3 month

– persons Q months ! man0months e(tra$

– 1 persons Q 4 months !e man0months e(tra$

– i(: dont assume adding people will solve the pro*lem


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"ythical "an0"onth


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"ythical "an0"onth

-: %7ow does a project get to *e a year late+= – : %One day at a time+

#tudies

– Each tas&: twice as long as estimated – Only 42 o' wor& wee& was programming

i(es

– 6o %'uJJy+ milestones !get the %true+ status$ – educe the role o' con'lict

– 8denti'y the %true status+

Planning and #cheduling ools


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Planning and #cheduling ools

@ig variety o' products, 'rom simple/single project toenterprise resource management

#ee 'or instance: – http://www.colum*ia.edu/jm3/\Other#o'tware

– http://www.startwright.com/project3.htm #ome 'ree tools to play with:

– 9anttproject !java *ased$

– #ome tools on linu(

ree evaluation – 8ntellysis project des&top

– astrac& #chedule

"#0Project


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"# Project

"id0mar&et leader 7as appro(. 42 overall mar&et share

0M2 "#0Project users never used automated project

trac&ing prior !a %'irst+ tool$

6ot a mid/high0end tool 'or EP" !Enterprise Project

"gmt.$

>hile in this class you can get a 'ree copy though "#

cademic lliance – email me i' interested.

Project Pros


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Project Pros

Easy outlining o' tas&s including support 'or hierarchical>or& *rea&down structures !>@#$

esource management

ccuracy: *aseline vs. actual? various calculations

Easy charting and graphics

Cost management

Capture historical data


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he "#0Project Process


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he "# Project Process

"ove >@# into a Project outline !in as& #heet$

dd resources !team mem*ers or roles$

dd costs 'or resources

ssign resources to tas&s Esta*lish dependencies

e'ine and optimiJe

Create baseline

Track progress (enter actuals, etc.)

Create Iour Project


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Create Iour Project

ile/6ew #etup start date

#etup calendar

– "enu: Project/Project 8n'ormation

– O'ten le't with de'ault settings

– 7ours, holidays

Enter >@#


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Enter >@#

Outlining

#u*0tas&s and summary tas&s

Do not enter start/end dates 'or each

Bust start with as& 6ame and Duration 'or each )se 8ndent/Outdent *uttons to de'ine summary

tas&s and su*tas&s

Iou can enter speci'ic #tart/End dates *ut dontmost o' the time

Esta*lish Durations


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Esta*lish Durations

;now the a**reviations – h/d/w/m

– D is de'ault

Can use partial

– .4d is a hal'0day tas&

Elapsed durations

Estimated durations

– Put a Z= a'ter duration

D)8O6 Q >O; !*ut initial de'ault is that it is$

dd esources


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dd esources

>or& esources – People

S !can *e 2 o' a person. ll resources split e


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esource #heet

Can add new resources here – Or directly in the tas& entry sheetS @eware o' mis0spellings !Project will create near0duplicates$

#etup costs

– #uch as annual salary !put Zyr a'ter Z#td. ate$

E''ort0Driven #cheduling


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o t ve #c edu g

"#0Project de'ault Duration R )nits Q >or&

S Duration Q >or& / )nits !D Q >/)$

S >or& Q Duration R )nits !> Q DR)$

S )nits Q >or& / Duration !) Q >/D$ dding more resources to a tas& shortens duration

Can *e changed on a per0tas& *asisS 8n the advanced ta* o' as& 8n'ormation dialog *o(

S as& ype setting

@eware the "ythical "an0monthS 9ood 'or laying *ric&s, not always so 'or so'tware development

Hin& as&s


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On tool*ar: Hin& Y )nlin& *uttons – 9ood 'or many at once

Or via 9antt chart

– Drag 'rom one tas& to another

"ilestones


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_ero duration tas&s 8nsert tas& Znormally *ut put in duration

Common 'or reports, unctional module/test

completions, etc.

– 9ood #E practice says milestones ")# *e

measura*le and well spread through the project.

"a&e ssignments


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g

pproach 3. )sing as& #heet – )sing esource 6ames column – Iou can create new ones *y just typing0in here

. )sing ssign esources dialog *o(

– 9ood 'or multiple resources – 7ighlight tas&, ools/esources or tool*ar *utton

1. )sing as& 8n'ormation dialog – esources ta*

A. as& Entry view – Fiew/"ore Fiews/as& Entry

– Or as& Entry view on esource "gmt. tool*ar

#ave @aseline


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#aves all current in'ormation a*out your project – Dates, resource assignments, durations, costs


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Project


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j

1 Editions: #tandard, Pro'essional, #erver "# Project #erver

– !@s never used server or newer$ @ased on docs.

S )pgrade o' old %Project Central+

S 8ncludes %Project >e* ccess+, we*0*ased )8 !partial$S >or&group and resource noti'ication 'eatures

S e


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j

"#0Project Pro'essional – %@uild eam+ 'eatureS #&ills0*ased resource matching

– esource Pools: with s&ill set trac&ing

– esource #u*stitution >iJard %Project 9uide+ 'eature

– CustomiJa*le %process component+

estimating projects (pmp)

Documents