Project Portfolio Management Planning

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1 Portfolo Maagemet Plag A Method for Prortzg s Mke Ross Galorath Icorporated 00 North Sepulveda Boulevard Sute 80 El Segudo, Calfora (480) (phoe) (480) (fax) mross@galorath.com Abstract. IT departmets are caught betee a rock ad a hard place these days. Budgets are shrkg hle the depedece o IT products ad servces s creasg. The pressure to demostrate that each e proect ll ether save moey, crease sales, or result eterprse-de effceces s greater tha ever. Ad yet, the maorty of Global 000 compaes are stll choosg hch proects get fudg ether by the frst-come/frst served method, the squeaky-heel gets the grease method, or the most poerful sposor method. Decdg hch IT proects get fudg should be based o more tha ust subectve udgmet; rather, the 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, they ca be more effectvely prortzed. CIOs ad IT maagers ca the make ser ad more sghtful decsos about hch proects should get fudg ad hch should be ether postpoed or shelved. Itroducto Purpose The purpose of ths paper s to establsh some basc taxoomy for the oto of portfolo maagemet ad the to descrbe a process for performg the portfolo plag part of portfolo maagemet. Scope The subect matter ths paper, hle prmarly geared to large eterprse Iformato Techology (IT) fuctos s oetheless applcable to ay eterprse seekg to mprove the ay t attempts to make decsos about vestg softare developmet proects.

2 Backgroud Back durg hgh-groth days of the "go-go '90s," fudg for Iformato Techology (IT) proects as't a bg deal at may compaes. If a proect shoed terestg potetal ad/or caught the eye of the rght decso maker, t ould lkely get the thumbs-up. Tmes have certaly chaged, th competto for resources to complete IT proects more tese tha ever. To help them prortze multple proects, may CIOs ad IT maagers are applyg the prcples of vestmet portfolo maagemet to ther portfolos of IT proects. Ths eables them to evaluate proects based o ther cotrbutos to the hghlevel strategc ad facal obectves of the eterprse. I other ords, they're attemptg to maage ther proect portfolos ust lke portfolos of vestmets cotually trackg outlays, returs, potetal value ad the rsk of each proect order to maxmze retur o vestmet ad accomplsh corporate obectves. Just lke a vestmet portfolo, the goal s to fd the proper balace ther proect portfolos order to make the best vestmets that ll maxmze returs ad mmze rsk. For example, a compay mght fud a fe hgh-rsk proects that have hgher potetal returs, but ould at to balace ths th other lo-rsk proects that offer more modest returs. Tradtoally, ths kd of rsk-based decso makg has oly bee appled at the dvdual proect level the portfolo maagemet cocept expads ths 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 that resources are fueled to those proects that ll cotrbute the most to the compay s overall success. A Taxoomy Frameork for Portfolo Maagemet Ths paper frst proposes a defto for Portfolo Maagemet that closely parallels the essece of Softare Maagemet as descrbed the Softare Egeerg Isttute s (SEI) Capablty Maturty Model (CMM). Ths essece cossts of key process areas for Softare Plag ad Softare Trackg ad Oversght [Paulk et. al., 993]. Cosequetly, the paper proposes that portfolo maagemet be decomposed to aalogous key elemets: oe called portfolo plag ad oe called portfolo trackg ad oversght. The dea s to zoom out from a dvdual proect ve (characterstc of Level 2 orgazatos) to oe that ecompasses a collecto of proects assocated th a partcular busess eterprse (characterstc of Level 3 ad hgher orgazatos). To facltate ths aalogy e frst reve the CMM deftos for Softare Plag ad Softare Trackg ad Oversght.

3 Softare Plag The purpose of Softare Plag as a key process area s to establsh achevable plas for performg ad maagg softare developmet [3]. Softare Plag volves developg estmates for the ork to be performed, establshg the ecessary commtmets, ad defg the pla to perform the ork [4]. Softare Plag begs th a statemet of the ork to be performed ad the goals ad costrats that defe ad boud the softare proect (those establshed by the practces of Requremets Maagemet). The softare plag process cludes steps to estmate the maagemet measures (sze, techology, tme, cost/effort/staffg, ad relablty), detfy ad descrbe the actvtes to be performed, detfy ad assess rsks ad opportutes, ad egotate commtmets. Iteratg through these steps may be ecessary to establsh a basele pla [4]. Softare Trackg ad Oversght The purpose of Softare Trackg ad Oversght s to provde adequate vsblty to actual progress so that maagemet ca take effectve actos he the softare proect s performace devates sgfcatly from the softare plas [3]. Softare Trackg ad Oversght volves trackg ad reveg the softare accomplshmets ad results agast documeted estmates, commtmets, ad plas, ad adustg these plas based o the actual accomplshmets ad results [4]. The basele pla (the prmary product of the Softare Plag process) s used as the bass for trackg progress, commucatg status, ad revsg plas. Softare maagemet measures, actvtes, rsks/opportutes, ad commtmets are perodcally tracked ad compared to ther correspodg plaed values. Whe t s determed that the softare proect s plas are ot beg met, correctve actos are take. Ths may clude revsg the basele pla to reflect the actual accomplshmets ad replag the remag ork or takg actos to mprove performace [4]. Portfolo Plag Ths paper proposes that portfolo plag s a key elemet of portfolo maagemet ad s aalogous to the CMM Key Process Area (KPA) called Softare Plag. Ths paper further proposes that, 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 ths has sometmes bee referred to as dog a cost-beeft aalyss or a trade study. Portfolo Trackg ad Oversght Completg the aalogy the prevous paragraph, ths paper proposes that portfolo trackg ad oversght s a key elemet of portfolo maagemet ad s aalogous to the

4 CMM KPA called Softare Trackg ad Oversght. Ths paper further proposes that, coceptually, portfolo trackg ad oversght as t relates to IT proects meas usg the artfacts produced by the portfolo plag process as the bass for effectvely ad effcetly schedulg the tasks of ad allocatg resources to each proect the portfolo as some fucto of ter-task depedeces, resource avalablty, ad prorty. There are umerous tools o the market today that have specalzed performg ths process at the proect level ad are o offerg ehacemets that make ths possble at the portfolo level as ell. Portfolo Plag Process Ths paper suggests that hat s bee mssg from most of the dscusso about the portfolo plag part of portfolo maagemet s some clear oto of quatfcato; thout hch, obectve fact-based decsos are vrtually mpossble to make. Ths paper proposes a approach (summarzed Fgure ) that prortzes (rak-orders) the proects a gve portfolo by a calculated value called Rsk-Adusted Retur o Ivestmet (RARROI). Calculato of RARROI requres koledge of to key estmated quattes, the proect's orth to the eterprse (relatve retur) ad the proect's cost of oershp (rsk-adusted vestmet). Kog these to estmated quattes allos the IT maager to make busess decsos the same ay a fud maager makes buy, sell, ad hold decsos.

5 Fgure : Portfolo Plag Process Data Flo Dagram Quatfyg the Rsk-Adusted Ivestmet The rsk-adusted vestmet part of RARROI ca be estmated as a fucto of sze ad techology usg a structured process that s based o accepted statstcal methods ad real performace data. Structured estmatg methods ad tools, such as Galorath's SEER- SEM, are ell establshed solutos for ths part of the problem (see Fgure 2).

6 Fgure 2: Structured Estmato Process as Implemeted Galorath s SEER-SEM Structured estmatg begs by herarchcally decomposg the proposed softare product to maageable peces ad the descrbg each pece terms of ts expected effectve sze, (volume of e ad pre-exstg softare), ts expected effectve techology (based o a set of detaled techology parameters), ad the assocated ucertates about each. Varous estmato-tool-supported szg techques; e.g., by drect measure (SLOC, Fucto Pots, Use Cases, etc.), by parse comparso, ad by aalogy, ad the IT maager

7 descrbg expected effectve sze ad ts ucertaty. Koledge bases (a complato ad stratfcato of the data from thousads of real completed proects) ad descrbg the detaled techology parameters ad ther ucertaty as a fucto of a proect/product s geeral characterstcs (Platform, Applcato, Acqusto Method, Developmet Method, ad Developmet Stadard). Expected effectve sze th ucertaty ad expected effectve techology th ucertaty are mathematcally combed to yeld calculated estmates for durato, effort, cost, staffg, ad delvered defects, as ell as the cofdece probablty desty fuctos assocated th each. It s possble, therefore, to determe a proect soluto here the cost of oershp (rsk-adusted vestmet) value has, say, a 80% cofdece;.e., there s a 80% probablty that the actual outcome cost ll ot exceed ths determed value. Note that 80% s merely a example; each dvdual eterprse must determe ts o rsk tolerace. Typcal reasoable cofdece percetage values rage from about 70% to 90%. Icdetally, as a byproduct of ths structured estmatg process, a actvty-artfact-skll dstrbuto over caledar tme ca be geerated that, essece, represets the basele pla; the key artfact requred as put to the Softare Trackg process. Quatfyg the Retur ad ts Assocated Cofdece The retur, of course, ll vary tremedously from proect to proect as a fucto of the 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 the 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 hether 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 the best approach. Istead, ths paper proposes establshg ormalzed relatve retur values usg the Aalytc Herarchy Process (AHP) [6]. Tools, such as Galorath's SEER-AccuScope, ad the mplemetato of ths process. AHP Step The frst step the AHP elcts a herarchcal represetato of the decso crtera. The root ode of the herarchy represets the overall obectve. The leaf odes represet the set of decso alteratves. Itermedate levels the herarchy represet a decomposto of the relevat attrbutes of the decso process;.e., selecto crtera.

8 AHP Step 2 The secod step the AHP elcts relatoal data for comparg the alteratves. Ths s doe va a seres of parse comparsos betee each of the crtera at a gve level the herarchy th respect to a crtero at the paret level (oe level up). The value of a comparso betee the th th crtero ( A ) level q ad the crtero ( B ) level q th respect to a level q (paret) crtero U s assged as follos: = for A havg the same mportace as B th respect to U. = 3 for A havg slghtly more mportace tha B th respect to U. = 5 for A havg more mportace tha B th respect to U. = 7 for A havg a lot more mportace as B th respect to U. = 9 for A totally domatg B th respect to U. = for A havg slghtly less mportace tha B th respect to U. 3 = for A havg less mportace tha B th respect to U. 5 = for A havg a lot less mportace tha B th respect to U. 7 = for A totally domated by B th respect to U. 9 = 2, 4,6,8,,,, ca be used as termedate values The results of the parse comparsos doe for level q th respect a crtero at level q here level q cotas crtera ca be orgazed a postve parse comparso matrx A as follos:

9 A Where: L 2 L = a b M M O M L 2 Represets the relatve mportace of the crtero here ab,,2,...,. th a crtero over the th b Eq. Note to mportat characterstcs about ths type of matrx: a = (every value o the prcpal dagoal of A s ). a = (the values o oe sde of the prcpal dagoal are the mrror recprocals a of the values o the other sde of the prcpal dagoal). AHP Step 3 The thrd step the AHP determes the relatve eghts for each postve parse comparso matrx developed Step 2. Saaty [5] troduced a method for determg the relatve crtera eght vector W of a comparso matrx A usg the rght egevector of A. or ( ) A λmaxi W= 0 Eq. 2 = a = λ max Eq. 3 here = = Eq. 4 The matrx algebra ecessary to solve for W ca be qute cumbersome. A coveet umercal method for approxmatg W s as follos: :=

10 A := A W := a colum vector, the elemets of hch are the ormalzed ro sums of repeat utl W := + A := A- A - W := a colum vector, the elemets of hch are the ormalzed ro sums of A W s suffcetly small for all elemets - AHP appled to determg relatve retur frst determes the retur parameter mportace (eght) of each retur parameter ad the determes the relatve proect mportace for each retur parameter. The aggregate relatve retur for a gve proect s the sum of the eghted retur parameters for that proect. Note that the estmato process assocated th the rsk-adusted vestmet must be doe before relatve proect mportace for each value parameter s determed sce ths relatve mportace ca chage as a fucto of the partcular durato, effort, cost, staffg, ad delvered defects assocated th a gve soluto. For example, a certa value parameter could assume a greater mportace (eght) for a gve proect f the proect ca be delvered sooer. Calculatg Rsk-Adusted Retur o Ivestmet (RARROI) Rsk-Adusted Retur o Ivestmet (RARROI) s smply the rato of the relatve retur to the rsk-adusted vestmet as sho belo. A RARROI P = = I RW C Eq. 5 Where: RARROI Rsk-Adusted Retur o Ivestmet for proect P. P R Normalzed relatve proect mportace for the th retur parameter. W I C Normalzed relatve parameter mportace (eght) for the th retur parameter. Normalzed relatve vestmet (cost of oershp) th cofdece percetage C here C represets the eterprse stadard rsk tolerace (desred probablty of success).

11 RARROI-Based Ivestmet Decso Makg Oce Rsk-Adusted Retur o Ivestmet (RARROI) has bee calculated for each proect, all that remas s to rak order the proects by descedg RARROI. Addg a colum for cumulatve estmated vestmet dollars provdes a quck meas of determg here the budget cut le should be dra. A Example The follog s a seres of fgures that sho the sequece of the 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 the eterprse s rsk tolerace has bee establshed at 80%. The eterprse s budget for ths portfolo s $,000,000. Fgure 3: AHP Decso Herarchy for the Portfolo s Retur Evaluato Parse Comparso Matrx Retur s Customer Satsfacto Productvty Improvemet Customer Satsfacto Productvty Improvemet Normalzed Fgure 4: Parse Comparso Matrx ad Normalzed s for the Retur s

12 Parse Comparso Matrx Customer Satsfacto Normalzed Fgure 5: Parse Comparso Matrx ad Normalzed s for s vs-à-vs Customer Satsfacto Parse Comparso Matrx Productvty Improvemet Normalzed Fgure 6: Parse Comparso Matrx ad Normalzed s for s vs-à-vs Productvty Improvemet

13 Name Ivestmet 80% Cofdece Estmated Cost of Oershp Retur Customer Satsfacto Productvty Improvemet Value Value RARROI Cumulatve Ivestmet $ 28, $ 28, $ 237, $ 265, $ 304, $ 570, $ 73, $ 743, $ 283, $,026, $ 680, $,706, $ 68, $,774, $ 08, $,883, $ 200, $ 2,083, $ 87, $ 2,70, Fgure 7: RARROI Calculatos Name Ivestmet 80% Cofdece Estmated Cost of Oershp Retur Customer Satsfacto Productvty Improvemet Value Value RARROI Cumulatve Ivestmet $ 68, $ 68, $ 28, $ 96, $ 08, $ 205, $ 283, $ 488, $ 73, $ 66, $ 304, $ 966, $ 87, $,053, $ 200, $,253, $ 237, $,490, $ 680, $ 2,70, Fgure 8: s Raked by Descedg RARROI th Budget Cut Le at $,000,000 Summary ad Cocluso Softare Iformato Techology (IT) proect portfolo maagemet ca be veed as cosstg of to key elemets: portfolo plag ad portfolo trackg ad oversght. Tme-tested softare proect estmato methods ad tools are therefore a essetal part of effectve portfolo plag as they represet the best practces for estmatg a proect's estmated relatve retur ad t s estmated rsk-adusted vestmet. These estmated values

14 yeld a proect s Rsk-Adusted Retur o Ivestmet (RARROI) hch, tur, ca be used as the bass for rak-orderg ad ultmately selectg the proects to be fuded. A key byproduct of the vestmet (cost of oershp) estmato process s a basele pla, hch ca be used as a put to the portfolo trackg ad oversght process. Addtoally, RARROI ca be used the portfolo trackg ad oversght process as part of the bass for settg task prortes a pre-emptve prorty-based schedulg ad resource allocato scheme. Portfolo maagemet s a promsg cocept that 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 methods ad tools that ca serve as a foudato for applyg measuremet to portfolo plag ad therefore help brg portfolo maagemet to the realm of obectve (.e., fact-based) decso makg. Refereces [] Che, Y.W., Implemetg a Aalytcal Herarchy Process by Fuzzy Itegral, Iteratoal Joural of Fuzzy Systems, Vol. 3, No. 3, pp , 200. [2] Demarco, T., Cotrollg Softare s: Maagemet, Measuremet, ad Estmato. Yourdo Press, Ne York, NY, 982. [3] Paulk, M.C., Curts, B., Chrsss, M.B., Weber, C.V., Capablty Maturty Model for Softare, Verso.. Pttsburgh, PA: Softare Egeerg Isttute, Carege Mello Uversty, 993. [4] Paulk, M.C., Weber, C.V., Garca, S.M., Chrsss, M.B., Bush, M., Key Practces of the Capablty Maturty Model, Verso.. Pttsburgh, PA: Softare Egeerg Isttute, Carege Mello Uversty, 993. [5] Saaty, T.L., A Scalg Method for Prortes Herarchcal Structures, Joural of Mathematcal Psychology, Vol. 5, No. 3, pp , 977. [6] Saaty, T.L., The Aalytc Herarchy Process: Plag, Prorty Settg, Resource Allocato, McGra-Hll, Ne York, NY, 980.

15 Bography Mchael A. Ross has over 28 years of practcal experece softare egeerg as a developer, maager, process champo, cosultat, structor, ad teratoal speaker. Mr. Ross s curretly the Chef Egeer of Galorath Icorporated, makers of the SEER sute of estmato tools, here he s resposble for the advacemet ad realzato of the techology aspects of Galorath s msso ad vso. Pror to og Galorath, Mr. Ross as Vce Presdet of Educato Servces for aother softare proect maagemet frm here, durg hs seve-year teure, he as resposble for the developmet ad delvery of all trag ad served as oe of the compay s prmary cosultats ad aalysts orkg th Fortue 500 compaes ad govermet ageces the areas of softare measuremet, szg, estmatg, trackg, forecastg, ad bechmarkg. Mr. Ross, durg 7 years th Hoeyell Ar Trasport Systems (formerly Sperry Flght Systems), developed or maaged the developmet of embedded softare for avocs systems stalled varous commercal arplaes cludg the Lockheed L0-500, Boeg 757/767, Arbus A320, Douglas MD-, Brtsh Aerospace BAe-46, ad the Boeg 777. He also co-fouded the dvso s process mprovemet team (later to become ts SEPG), served as a corporate SEI CMM assessor, ad served as the dvso s focal for softare proect maagemet process mprovemet. Mr. Ross dd hs udergraduate ork at the Uted States Ar Force Academy ad Arzoa State Uversty, recevg a Bachelor of Scece Computer Egeerg. He s a member of the Maagemet Isttute (PMI), IEEE, the Iteratoal Fucto Pots Users Group, the Iteratoal Socety of Parametrc Aalysts, the Arzoa Softare Assocato, ad the Phoex area Softare Process Improvemet Netork.