Project Portfolio Management Planning: A Method for Prioritizing Projects

Transcription

1 Portfolo Maagemet Plag: Meod for Prortzg s Mke Ross restmatg, LLC E. Eveg Glo Dr. Scottsdale, Z mke.ross@restmatg.com bstract IT departmets are caught betee a rock ad a hard place ese days. Budgets are shrkg hle e depedece o IT products ad servces s creasg. The pressure to demostrate at each e proect ll eer save moey, crease sales, or result eterprse-de effceces s greater a ever. d yet, e maorty of Global 000 compaes are stll choosg hch proects get fudg eer by e frst-come/frst served meod, e squeaky-heel gets e grease meod, or e most poerful sposor meod. Decdg hch IT proects get fudg should be based o more a ust subectve udgmet; raer, e proect should be aalyzed obectvely, lookg at a umber of factors cost of oershp, cycle tme, qualty, rsk, ad beeft(s) beg ust a fe. By aalyzg proects obectvely, ey ca be more effectvely prortzed. CIOs ad IT maagers ca e make ser ad more sghtful decsos about hch proects should get fudg ad hch should be eer postpoed or shelved. TBLE OF CONTENTS. INTRODUCTION.... TXONOMY FRMEWORK FOR PORTFOLIO MNGEMENT.... PORTFOLIO PLNNING PROCESS.... SUMMRY ND CONCLUSION... REFERENCES... BIOGRPHY... Purpose. INTRODUCTION The purpose of s paper s to establsh some basc taxoomy for e oto of portfolo maagemet ad e to descrbe a process for performg e portfolo plag part of portfolo maagemet. Scope The subect matter s paper, hle prmarly geared to large eterprse Iformato Techology (IT) fuctos s oeeless applcable to ay eterprse seekg to mprove e ay t attempts to make decsos about vestg softare developmet proects. Backgroud Back durg hgh-gro days of e "go-go '0s," fudg for Iformato Techology (IT) proects as't a bg deal at may compaes. If a proect shoed terestg potetal ad/or caught e eye of e rght decso maker, t ould lkely get e umbs-up. Tmes have certaly chaged, competto for resources to complete IT proects more tese a ever. To help em prortze multple proects, may CIOs ad IT maagers are applyg e prcples of vestmet portfolo maagemet to er portfolos of IT proects. Ths eables em to evaluate proects based o er cotrbutos to e hgh-level strategc ad facal obectves of e eterprse. 00 restmatg, LLC. ll rghts reserved. Ital, Jauary, 00 I oer ords, ey're attemptg to maage er proect portfolos ust lke portfolos of vestmets cotually trackg outlays, returs, potetal value ad e rsk of each proect order to maxmze retur o vestmet ad accomplsh corporate obectves. Just lke a vestmet portfolo, e goal s to fd e proper balace er proect portfolos order to make e best vestmets at ll maxmze returs ad mmze rsk. For example, a compay mght fud a fe hgh-rsk proects at have hgher potetal returs, but ould at to balace

2 s oer lo-rsk proects at offer more modest returs. Tradtoally, s kd of rsk-based decso makg has oly bee appled at e dvdual proect level e portfolo maagemet cocept expads s to collectos of proects. The process of maagg Iformato Techology (IT) proects usg a facal vestmet portfolo metaphor has attracted much terest from CIOs Fortue 000 compaes. Ths so-called IT portfolo maagemet process s expected to mprove returs o IT vestmets by esurg at resources are fueled to ose proects at ll cotrbute e most to e compay s overall success.. TXONOMY FRMEWORK FOR PORTFOLIO MNGEMENT Ths paper frst proposes a defto for Portfolo Maagemet at closely parallels e essece of Softare Maagemet as descrbed e Softare Egeerg Isttute s (SEI) Capablty Maturty Model Itegrato (CMMI). Ths essece cossts of key processes for Softare Plag ad Softare Motorg ad Cotrol. Cosequetly, e paper proposes at portfolo maagemet be decomposed to aalogous key elemets: oe called portfolo plag ad oe called portfolo motorg ad cotrol. The dea s to zoom out from a dvdual proect ve (characterstc of Level orgazatos) to oe at ecompasses a collecto of proects assocated a partcular busess eterprse (characterstc of Level ad hgher orgazatos). Portfolo Plag Ths paper proposes at portfolo plag s a key elemet of portfolo maagemet ad s aalogous to e CMMI Key Process called Softare Plag. Ths paper furer proposes at, coceptually, portfolo plag as t relates to IT proects meas makg IT proect vestmet (go o go) decsos as some fucto of potetal (estmated) Retur o Ivestmet (ROI). Hstorcally s has sometmes bee referred to as dog a cost-beeft aalyss or a trade study. Portfolo Motorg ad Cotrol Completg e aalogy e prevous paragraph, s paper proposes at portfolo motorg ad cotrol s a key elemet of portfolo maagemet ad s aalogous to e CMMI Key Process called Softare Motorg ad Cotrol. Ths paper furer proposes at, coceptually, portfolo motorg ad cotrol as t relates to IT proects meas usg e artfacts produced by e portfolo plag process as e bass for effectvely ad effcetly schedulg e tasks of ad allocatg resources to each proect e portfolo as some fucto of ter-task depedeces, resource avalablty, ad prorty. There are umerous tools o e market today at have specalzed performg s process at e proect level ad are o offerg ehacemets at make s possble at e portfolo level as ell.. PORTFOLIO PLNNING PROCESS Ths paper suggests at hat s bee mssg from most of e dscusso about e portfolo plag part of portfolo maagemet s some clear oto of quatfcato; out hch, obectve fact-based decsos are vrtually mpossble to make. Ths paper proposes a approach (summarzed Fgure ) at prortzes (rak-orders) e proects a gve portfolo by a calculated value called Rsk-dusted Retur o Ivestmet (RRROI). Calculato of RRROI requres koledge of to key estmated quattes, e proect's or to e eterprse (relatve retur) ad e proect's cost of oershp (rsk-adusted vestmet). Kog ese to estmated quattes allos e IT maager to make busess decsos e same ay a fud maager makes buy, sell, ad hold decsos. RISK-DJUSTED INVESTMENT VLUE-RELEVNT PROJECT INFORMTION Fgure : Portfolo Plag Process Data Flo Dagram Quatfyg e Rsk-dusted Ivestmet The rsk-adusted vestmet part of RRROI ca be estmated as a fucto of sze ad effcecy usg a structured process at s based o accepted statstcal meods ad real performace data. Structured estmatg meods ad tools, such as restmatg s restmator, employ ell-establshed solutos for s part of e problem. Structured estmatg begs by herarchcally decomposg e proposed softare product to maageable peces ad e descrbg each pece terms of ts expected effectve sze, (desty-adusted volume of e ad pre-exstg softare SLOC, Fucto Pots, Use Cases, etc.), ts expected specfc effcecy (based o relevat hstorcal data

3 ad/or a set of detaled evromet parameters), ad e assocated ucertates about each. Expected effectve sze ucertaty ad expected specfc effcecy ucertaty are maematcally combed to yeld calculated estmates for durato, effort, cost, staffg, ad delvered defects, as ell as e cofdece probablty dstrbutos assocated each. It s possble, erefore, to determe a proect soluto here e cost of oershp (rsk-adusted vestmet) value has, say, a 0% cofdece probablty;.e., ere s a 0% probablty at e actual outcome cost ll ot exceed s determed value. Note at 0% s merely a example; each dvdual eterprse must determe ts o rsk tolerace. Typcal reasoable cofdece probablty values rage from about 0% to 0%. Quatfyg e Retur ad ts ssocated Cofdece The retur, of course, ll vary tremedously from proect to proect as a fucto of e busess evromet. Retur s very dffcult to quatfy terms of some absolute uts lke dollars sce t teds to be flueced by multple factors such as value to e marketplace, fluece o customer satsfacto, fluece o eterprse productvty / qualty, etc. It s much more tractable to treat retur as a ormalzed relatve value. Ths relatve retur value ca be estmated straght aay or t ca perhaps be a eghted average of several retur parameters. Regardless of heer retur s estmated aggregate or parametrcally, sce relatoshps ad flueces vary from orgazato to orgazato, tryg to develop specfc algebrac estmato relatoshps (regressos) may ot be e best approach. Istead, s paper proposes establshg ormalzed relatve retur values usg e alytc Herarchy Process (HP) []. HP Step The frst step e HP elcts a herarchcal represetato of e decso crtera. The root ode of e herarchy represets e overall obectve. The leaf odes represet e set of decso alteratves. Itermedate levels e herarchy represet a decomposto of e relevat attrbutes of e decso process;.e., selecto crtera. HP Step The secod step e HP elcts relatoal data for comparg e alteratves. Ths s doe va a seres of parse comparsos betee each of e crtera at a gve level e herarchy respect to a crtero at e paret level (oe level up). The value of a comparso betee e crtero ( ) level q ad e crtero ( B ) level q respect to a level q (paret) crtero U s assged as follos: = for havg e same mportace as B respect to U. = for havg slghtly more mportace a B respect to U. = for havg more mportace a B respect to U. = for havg a lot more mportace as B respect to U. = for totally domatg B respect to U. = for havg slghtly less mportace a B respect to U. = for havg less mportace a B respect to U. = for havg a lot less mportace a B respect to U. = for totally domated by B respect to U.,,,,,,, = ca be used as termedate values. The results of e parse comparsos doe for level q respect a crtero at level q here level q cotas crtera ca be orgazed a postve parse comparso matrx as

4 here L L = M M O M L () := W := a colum vector, e elemets of hch are e ormalzed ro sums of repeat := + := - - a b = mportace of e a crtero over e b crtero here a, b,,...,. Note to mportat characterstcs about s type of matrx: a = (every value o e prcpal dagoal of s ) a a = (e values o oe sde of e prcpal dagoal are e mrror recprocals of e values o e oer sde of e prcpal dagoal). HP Step The rd step e HP determes e relatve eghts for each postve parse comparso matrx developed Step. Saaty [] troduced a meod for determg e relatve crtera eght vector W of a comparso matrx usg e rght egevector of. ( λ I) W = 0 () max utl W s suffcetly small for all elemets W W := a colum vector, e elemets of hch are e ormalzed ro sums of - HP appled to determg relatve retur frst determes e retur parameter mportace (eght) of each retur parameter ad e determes e relatve proect mportace for each retur parameter. The aggregate relatve retur for a gve proect s e sum of e eghted retur parameters for at proect. Note at e estmato process assocated e rskadusted vestmet must be doe before relatve proect mportace for each value parameter s determed (s cotrol depedecy dcated by e dashed arro Fgure ) sce relatve mportace ca chage as a fucto of e partcular durato, effort, cost, staffg, ad delvered defects assocated a gve soluto. For example, a certa value parameter could assume a greater mportace (eght) for a gve proect f e proect ca be delvered sooer. or here a = λmax () = = () = Calculatg Rsk-dusted Retur o Ivestmet (RRROI) Rsk-dusted Retur o Ivestmet (RRROI) s smply e rato of e relatve retur to e rsk-adusted vestmet as sho Equato (). RRROI P = = I RW C () The matrx algebra ecessary to solve for W ca be qute cumbersome. coveet umercal meod for approxmatg W s as follos: := here P RRROI = Rsk-dusted Retur o Ivestmet for proect P.

5 R W I C = Normalzed relatve proect mportace for e retur parameter. = Normalzed relatve parameter mportace (eght) for e rameter. retur pa- = Normalzed relatve vestmet (cost of oershp) cofdece percetage C here C represets e eterprse stadard rsk tolerace (desred probablty of success). Parse Comparso Matrx Retur s Customer Satsfacto Productvty Improvemet Normalzed Customer Satsfacto Productvty Improvemet Fgure : Parse Comparso Matrx ad Normalzed s for e Retur s RRROI-Based Ivestmet Decso Makg Oce Rsk-dusted Retur o Ivestmet (RRROI) has bee calculated for each proect, all at remas s to rak order e proects by descedg RRROI. ddg a colum for cumulatve estmated vestmet dollars provdes a quck meas of determg here e budget cut le should be dra. Example The follog s a seres of fgures at sho e sequece of e portfolo plag process steps for a portfolo of te proects here a proect s retur s determed by ts mportace to customer satsfacto ad productvty mprovemet ad here e eterprse s rsk tolerace has bee establshed at 0%. The eterprse s budget for s portfolo s $,000,000. Fgure : HP Decso Herarchy for e Portfolo s Retur Evaluato

6 Parse Comparso Matrx Customer Satsfacto 0 0 Normalzed Fgure : Parse Comparso Matrx ad Normalzed s for s vs-à-vs Customer Satsfacto Parse Comparso Matrx Productvty Improvemet 0 0 Normalzed Fgure : Parse Comparso Matrx ad Normalzed s for s vs-à-vs Productvty Improvemet

7 Name 0 Ivestmet 0% Cofdece Estmated Cost of Oershp Retur Customer Satsfacto Productvty Improvemet Value Value RRROI Cumulatve Ivestmet $, $,00.00 $, $,00.00 $ 0, $ 0, $, $,00.00 $, $,0,00.00 $ 0, $,0,00.00 $, $,,00.00 $ 0, $,, $ 00, $,0, $, $,0, Fgure : RRROI Calculatos Name 0 Ivestmet 0% Cofdece Estmated Cost of Oershp Retur Customer Satsfacto Productvty Improvemet Value Value RRROI Cumulatve Ivestmet $, $, $, $,00.00 $ 0, $ 0, $, $, $, $,00.00 $ 0, $, $, $,0, $ 00, $,, $, $,0, $ 0, $,0, Fgure : s Raked by Descedg RRROI Budget Cut Le at $,000,000. SUMMRY ND CONCLUSION Softare Iformato Techology (IT) proect portfolo maagemet ca be veed as cosstg of to key elemets: portfolo plag ad portfolo motorg ad cotrol. Tme-tested softare proect estmato meods ad tools are erefore a essetal part of effectve portfolo plag as ey represet e best practces for estmatg a proect's estmated relatve retur ad t s estmated rskadusted vestmet. These estmated values yeld a proect s Rsk-dusted Retur o Ivestmet (RRROI) hch, tur, ca be used as e bass for rakorderg ad ultmately selectg e proects to be fuded.

8 key byproduct of e vestmet (cost of oershp) estmato process s a basele pla, hch ca be used as a put to e portfolo motorg ad cotrol process. ddtoally, RRROI ca be used e portfolo motorg ad cotrol process as part of e bass for settg task prortes a pre-emptve prorty-based schedulg ad resource allocato scheme. Mke Ross has over 0 years of experece softare egeerg as a developer, maager, process champo, cosultat, structor, ad aard-g teratoal speaker. Mr. Ross s curretly e Presdet ad CEO of restmatg, LLC. Mr. Ross s prevous experece cludes ree years as Chef Egeer of Galora Ic. (makers of e SEER sute of estmato tools), seve years Quattatve Softare Maagemet, Ic. (makers of e SLIM sute of softare estmatg tools) here he as Vce Presdet of Educato Servces, ad years Hoeyell r Trasport Systems (formerly Sperry Flght Systems) ad years Tracor erospace here he developed or maaged e developmet of embedded softare for avocs systems stalled varous commercal arplaes ad for expedable coutermeasures systems stalled varous mltary arcraft. He also cofouded Hoeyell r Trasport Systems SEPG, served as ts focal for softare proect maagemet process mprovemet, ad served as a Hoeyell corporate SEI CMM assessor. Mr. Ross dd hs udergraduate ork at e Uted States r Force cademy ad rzoa State Uversty, recevg a Bachelor of Scece Computer Egeerg. Portfolo maagemet s a promsg cocept at eeds measuremet to be practcal. You ca t cotrol [maage] hat you ca t [do t] measure []. Ths paper provdes a reasoably smple calculato based o exstg meods ad tools at ca serve as a foudato for applyg measuremet to portfolo plag ad erefore help brg portfolo maagemet to e realm of obectve (.e., fact-based) decso makg. REFERENCES [] Che, Y.W., Implemetg a alytcal Herarchy Process by Fuzzy Itegral, Iteratoal Joural of Fuzzy Systems, Vol., No., pp. -0, 00. [] Demarco, T., Cotrollg Softare s: Maagemet, Measuremet, ad Estmato. Yourdo Press, Ne York, NY,. [] Saaty, T.L., Scalg Meod for Prortes Herarchcal Structures, Joural of Maematcal Psychology, Vol., No., pp.-,. [] Saaty, T.L., The alytc Herarchy Process: Plag, Prorty Settg, Resource llocato, McGra- Hll, Ne York, NY, 0. BIOGRPHY