NoEstimates Scrum En - Speaker Deck

Slide 1

Slide 1 text

/P&TUJNBUFT4DSVN 3FHJPOBM4DSVN(BUIFSJOH5PLZP34(5 CZ*LVP4VZBNB

Slide 2

Slide 2 text

*LVP4VZBNB !NBSUJO@MPWFS@TF "QQSFOUJDFl"HJMF%FWFMPQFSz *MPWF.PC1SPHSBNNJOH $ZCFS"HFOU "*5FDI4UVEJP -0%&0

Slide 3

Slide 3 text

5PEBZ *NHPOOBUBMLJOHBCPVU &TUJNBUF BOE4DSVN

Slide 4

Slide 4 text

&TUJNBUJPOJTNFBOJOHGVMBOEVTFGVMJOUIFTPGUXBSFEFWFMPQNFOU *BHSFFUPUIBU %JTDMBJNFS 5IJTTFTTJPOJT/05BDMBJNUIBU 8FTIPVMETUPQFTUJNBUJOH CFDBVTFJUTXBTUF 8IZEPOUXFSFDPOTJEFSBCPVUFTUJNBUJPO GSPN/P&TUJNBUFTUPHFUIFS

Slide 5

Slide 5 text

8IZ 8F4UPQ &TUJNBUJOH

Slide 6

Slide 6 text

w 5IFNBOBHFSBTTJHOTUBTLT w 5IFQFSTPOXIPJTBTTJHOFEFTUJNBUFTUIFUBTL w 5IFQFSTPOJOQVUUIFQSPHSFTTPOUIF(BOUUDIBSU w 5IFNBOBHFSBOECVTJOFTTTIBSFUIFQSPHSFTTJOXFFLMZ.5( w 8FIBWFEFBEMJOFTCVUXFVTVBMMZNJTTJU .FNCFSTFYUFOEUIFEFBEMJOFCZUIFJSJOUVJUJPO 0VS%FWFMPQNFOUXJUI&TUJNBUFT

Slide 7

Slide 7 text

BMNPTUpOJTIFE XFDBOEFMJWFSJU OFYUXFFL 0, 1MFBTF *OB8FFLMZ1SPHSFTT.FFUJOH 0VS%FWFMPQNFOUXJUI&TUJNBUJPO

Slide 8

Slide 8 text

BMNPTUpOJTIFE XFDBOEFMJWFSJU OFYUXFFL 0, 1MFBTF /FYU8FFL 0VS%FWFMPQNFOUXJUI&TUJNBUJPO

Slide 9

Slide 9 text

0, 1MFBTF 5IFXFFL"GUFS/FYU 6I *U`T &TUJNBUFT :PVTBJE OFYUXFFL 'PSFWFS1SPHSFTT BMNPTUpOJTIFE XFDBOEFMJWFSJU OFYUXFFL 0VS%FWFMPQNFOUXJUI&TUJNBUJPO

Slide 10

Slide 10 text

4PNFUIJOHT8SPOH ʢ*U`TUPUBMMZNFBOJOHMFTT SJHIU ʣ

Slide 11

Slide 11 text

34(5,FZ/PUF CZ$ISJT-VDJBO /P &TUJNBUFT $PTU PG&TUJNBUFT

Slide 12

Slide 12 text

0.( 5IBU`T*5

Slide 13

Slide 13 text

5IFO 8F4501&TUJNBUJOH

Slide 14

Slide 14 text

w 4FMGPSHBOJ[FEEFWFMPQNFOUUFBN 8FIBWFDPOpEFODFJO8IBUXFDBOEPJOUIJTXFFL XFDBOLFFQUIBUQSPNJTF w "TBSFTVMU XFCVJMEUSVTUXJUIUIFCVTJOFTT 8FDBOEPSFMJBCMFQMBOOJOHUPHFUIFS &WFSTJODF4UBSUJOH 8FBSFOFWFSBTLFEGPSFTUJNBUFT 0VS%FWFMPQNFOUXJUI/P&TUJNBUFT

Slide 15

Slide 15 text

5IF/FHBUJWF"TQFDUTBOE7BMVFPG&TUJNBUJPO 4DSVNBOE&TUJNBUJPO 0VS/P&TUJNBUFT4DSVN 3FBMJUJFTPG/P&TUJNBUFT "HFOEB 0VS1SBDUJDFBOE4V⒎FSJOH TJODF34(5

Slide 16

Slide 16 text

5IF/FHBUJWF"TQFDUTBOE7BMVFPG&TUJNBUJPO 4DSVNBOE&TUJNBUJPO 0VS/P&TUJNBUFT4DSVN 3FBMJUJFTPG/P&TUJNBUFT

Slide 17

Slide 17 text

5IF/FHBUJWF"TQFDUTPG&TUJNBUJPO

Slide 18

Slide 18 text

8IZJT5IJT)BQQFO 0, 1MFBTF 6I *U`T &TUJNBUFT :PVTBJE OFYUXFFL 'PSFWFS1SPHSFTT BMNPTUpOJTIFE XFDBOEFMJWFSJU OFYUXFFL

Slide 19

Slide 19 text

5IF)JEEFO$PTUPG&TUJNBUFTCZ$ISJT-VDJBO $03$0%%5&$51-ɹ w $PTUPGUIF3VMF PGGFBUVSFTJTGPSSFRVFTUTGSPNPGUIFVTFST w $PTUPG%FMBZ 5IFWBMVFOPUSFBMJ[FEGPSUIFEVSBUJPOUIBUBGFBUVSFEPFTOPUFYJTU 1SPCMFNTCZ 1SJPSJUJ[JOH 1SPCMFNTCZ 2VBOUJGZJOH w %FTJHO5SBEFP⒎T 4BDSJpDFTNBEFUPUIFRVBMJUZJOGBWPSPGTQFFEUPNBSLFU w &TUJNBUJPO$SFBUJPO5JNF 5IFUJNFTQFOUCZUIFQFPQMFNBLJOHUIFFTUJNBUFT w 5IF$PTUPG1BSLJOTPOT-BX 8PSLFYQBOETTPBTUPpMMUIFUJNFBWBJMBCMFGPSJUTDPNQMFUJPO

Slide 20

Slide 20 text

%FTJHO5SBEFP⒎T1SFTTVSFUP$PNNJU 1BSLJOTPOT-BX.BYJNJ[JOH8PSL &TUJNBUJPO$SFBUJPO5JNF*MMVTJPOPG"DDVSBDZ 1SPCMFNT$BVTFECZ2VBOUJGZJOH

Slide 21

Slide 21 text

1SPCMFNT$BVTFECZ2VBOUJGZJOH 8IFO&TUJNBUFT/ 4UPSZ1PJOUPS%BZ EFDJEFE / BDUVBMWBMVFBMXBZTWBSJFT XIFOXFEPJU "DDVSBDZEPFTOUJNQSPWFFWFOPWFSUJNF .63" VOFWFOOFTT PG"DDVSBDZ JUJTUSFBUFEBTEFBEMJOF BOENBLFTTUSPOHQSFTTVSFUPDPNNJU &TUJNBUJPOBTB$PNNJUNFOU .63* 0WFSCVSEFO PG%FBEMJOF 8PSLFYQBOETBTJUpMM UIFUJNF 1BSLJOTPOT-BX .6%" XBTUF PG8PSL *UDBVTFT. .63*.6%".63"

Slide 22

Slide 22 text

5IF1PTJUJWF"TQFDUTPG&TUJNBUJPO

Slide 23

Slide 23 text

/PUPOMZFTUJNBUFT #VUBMTPQMBOOJOHJTOFFEFE GPSNBLJOHEFDJTJPOT Estimating and planning are not just about determining an appropriate deadline or schedule. Planning— especially an ongoing iterative approach to planning—is a quest for value. A good plan is one that stakeholders ﬁnd sufﬁciently reliable that they can use it as the basis for making decisions. 8IZ%P8F/FFE&TUJNBUJPO —Agile Estimating and Planning

Slide 24

Slide 24 text

$POWFSUJOHUIF&TUJNBUJPOJOUP4DIFEVMF 1MBOOJOHJTDPOUJOVPVTQSPDFTTPGUIJTDPOWFSTJPO %FTJSFE 'FBUVSFT &TUJNBUF TJ[F &TUJNBUF EVSBUJPO 4DIFEVMF GSPN"HJMF&TUJNBUJOHBOE1MBOOJOH w 3FMBUJWF4UPSZ1PJOUT w *EFBM5JNF w $BMDVMBUJOHUIFEVSBUJPO GSPNWFMPDJUZ

Slide 25

Slide 25 text

Slide 26

Slide 26 text

*O%FUBJM %FTJSFE 'FBUVSFT &TUJNBUF TJ[F &TUJNBUF EVSBUJPO 4DIFEVMF 4J[F %VSBUJPO &TUJNBUF WBMVF 7BMVF 1SJPSJUJ[F H Y 1SJPSJUZ G Y $PTU *OGP w 3JTLT w &YQFSUT0QJOJPO %FMQIJ.FUIPE w 4UPSZ1PJOUT w *EFBM5JNF w )PXWBMVBCMFJTJU w 0SEFS %FpOJUJPOPG&TUJNBUJPO *OUIJTTFTTJPO 2VBOUJGZ$BVTFPG. w )PXNVDIEPFTJUDPTUUPEFWFMPQ

Slide 27

Slide 27 text

Slide 28

Slide 28 text

8IBU8F/FFE %FTJSFE 'FBUVSFT &TUJNBUF TJ[F &TUJNBUF EVSBUJPO 4DIFEVMF 4J[F %VSBUJPO &TUJNBUF WBMVF 7BMVF 1SJPSJUJ[F H Y 1SJPSJUZ G Y $PTU *OGP w 3JTLT w &YQFSUT0QJOJPO %FMQIJ.FUIPE w 4UPSZ1PJOUT w *EFBM5JNF w )PXWBMVBCMFJTJU w 0SEFS #VU5IJT 2VBOUJGZ$BVTFPG. /PU5IJT w )PXNVDIEPFTJUDPTUUPEFWFMPQ

Slide 29

Slide 29 text

8IBU8F/FFE %FTJSFE 'FBUVSFT &TUJNBUF TJ[F &TUJNBUF EVSBUJPO 4DIFEVMF 4J[F %VSBUJPO &TUJNBUF WBMVF 7BMVF 1SJPSJUJ[F H Y 1SJPSJUZ G Y $PTU *OGP w 4UPSZ1PJOUT w *EFBM5JNF w 0SEFS #VU5IJT w 3JTLT w &YQFSUT0QJOJPO %FMQIJ.FUIPE w )PXWBMVBCMFJTJU 2VBOUJGZ$BVTFPG. 8F/FFE 7BMVF $PTU *OGP UPNBLFEFDJTJPOT /PU5IJT w )PXNVDIEPFTJUDPTUUPEFWFMPQ

Slide 30

Slide 30 text

Slide 31

Slide 31 text

0VS/P&TUJNBUFT %FTJSFE 'FBUVSFT &TUJNBUF TJ[F &TUJNBUF EVSBUJPO 4DIFEVMF 4J[F %VSBUJPO &TUJNBUF WBMVF 7BMVF 1SJPSJUJ[F 1SJPSJUZ $PTU *OGP w 4UPSZ1PJOUT w *EFBM5JNF w 0SEFS w 3JTLT w &YQFSUT0QJOJPO %FMQIJ.FUIPE w )PXWBMVBCMFJTJU 2VBOUJGZ$BVTFPG. H Y G Y "OE(FUUJOH UIFN 4UPQQJOHUIJT w )PXNVDIEPFTJUDPTUUPEFWFMPQ *OTUFBEPGDPOWFSUJOH UIFEFTJSFEGFBUVSFTJOUP 4J[F%VSBUJPO .BOBHFUPHFUPOMZXIBUJTSFRVJSFEGPS EFDJTJPONBLJOHBOEQSPKFDUQMBOOJOH $PTU *OGPSNBUJPO 7BMVF

Slide 32

Slide 32 text

3BUIFSJUJTUPBQQSPBDI %FDJTJPONBLJOHJOBEJ⒎FSFOUXBZ XIJMFBWPJEJOHPSNJOJNJ[JOH UIFOFHBUJWFBTQFDUTPGUIFFTUJNBUJPO . .VSJ .VEB .VSB (PBMJTOPUUP4UPQ&TUJNBUJOH

Slide 33

Slide 33 text

It is signiﬁcant to me that much of why we do estimates is that we need to make decisions: To decide something. In other words, it looks to me that what we need are decisions , not estimates. 8PPEZ;VJMM8IZEPXFOFFEFTUJNBUFT

Slide 34

Slide 34 text

5IF/FHBUJWF"TQFDUTBOE7BMVFPG&TUJNBUJPO 4DSVNBOE&TUJNBUJPO 0VS/P&TUJNBUFT4DSVN 3FBMJUJFTPG/P&TUJNBUFT

Slide 35

Slide 35 text

2)PXNBOZUJNFTEPFTUIFXPSE FTUJNBUFBQQFBSJO5IF4DSVN(VJEF

Slide 36

Slide 36 text

"̕UJNFT

Slide 37

Slide 37 text

✓ Product Backlog items have the attributes of a description, order, estimate, and value. ✓ Product Backlog reﬁnement is the act of adding detail, estimates, and order to items in the Product Backlog. 4DSVN"SUJGBDUT1SPEVDU#BDLMPH 1#*"UUSJCVUF 8IBUXFOFFE GSPNFTUJNBUJPO ✓All incomplete Product Backlog Items are re-estimated and put back on the Product Backlog. The work done on them depreciates quickly and must be frequently re- estimated. 4DSVN&WFOUT$BODFMMJOHB4QSJOU 1#*FTUJNBUFTTIPVMECFVQEBUFEGSFRVFOUMZ BMXBZTVQUPEBUF *OPSEFSUPQSJPSJUJ[F

Slide 38

Slide 38 text

✓The input to this meeting is the Product Backlog, the latest product Increment, projected capacity of the Development Team during the Sprint, and past performance of the Development Team. The number of items selected from the Product Backlog for the Sprint is solely up to the Development Team. 4DSVN&WFOUT4QSJOU1MBOOJOH5PQJD0OF XFTIPVMEEFUFSNJOFDBQBDJUZ CZQBTUQFSGPSNBODF 1FPQMFXIPBDUVBMMZXPSLEPFTUJNBUJPO BOEDPNNJUUPJU ✓ More precise estimates are made based on the greater clarity and increased detail; ✓ The Development Team is responsible for all estimates. The Product Owner may inﬂuence the Development Team by helping it understand and select trade-offs, but the people who will perform the work make the ﬁnal estimate. 5IBUTUSVF 4DSVN"SUJGBDUT1SPEVDU#BDLMPH

Slide 39

Slide 39 text

✓As new work is required, the Development Team adds it to the Sprint Backlog. As work is performed or completed, the estimated remaining work is updated. ✓At any point in time in a Sprint, the total work remaining in the Sprint Backlog can be summed. *OPSEFSUPNPOJUPSQSPHSFTT 4DSVN"SUJGBDUT4QSJOU#BDLMPH 4DSVN"SUJGBDUT4QSJOU#BDLMPH.POJUPSJOH4QSJOU1SPHSFTT ✓The Development Team usually starts by designing the system and the work needed to convert the Product Backlog into a working product Increment. Work may be of varying size, or estimated effort. 4DSVN&WFOUT4QSJOU1MBOOJOH 4#*BMTPOFFETFTUJNBUFT

Slide 40

Slide 40 text

w 'PS3FMFBTF1MBOOJOH1SJPSJUJ[BUJPO ✓ Product Backlog items have the attributes of a description, order, estimate, and value. ✓ Adding detail, estimates, and order to items in the Product Backlog w 'PS4QSJOU1MBOOJOH$BQBDJUZ $PNNJUNFOU ✓ The number of items selected from the Product Backlog for the Sprint is solely up to the Development Team. ✓ The Development Team is responsible for all estimates. w 'PS.POJUPSJOH1SPHSFTT ✓At any point in time in a Sprint, the total work remaining in the Sprint Backlog can be summed. 4VNNBSZ&TUJNBUJPOJO4DSVN *UEPFTOUTBZ2VBOUJGZ

Slide 41

Slide 41 text

5IF/FHBUJWF"TQFDUTBOE7BMVFPG&TUJNBUJPO 4DSVNBOE&TUJNBUJPO 0VS/P&TUJNBUFT4DSVN 3FBMJUJFTPG/P&TUJNBUFT

Slide 42

Slide 42 text

0VS/P&TUJNBUFT4DSVN

Slide 43

Slide 43 text

No content

Slide 44

Slide 44 text

5IF7BMVFPG&TUJNBUJPOJO4DSVN(VJEF "MUFSOBUFPG&TUJNBUFT $PSF1SBDUJDF

Slide 45

Slide 45 text

#BDLMPH3FpOFNFOU 1SJPSJUJ[F

Slide 46

Slide 46 text

#BDLMPH 3FBEZ 5PEP %PJOH %POF 'FBUVSF" 1#*ɹ̍XFFL 1#* 1#* ɿ 1#*" 1#*# 1#*ɹ̍XFFL 1#* 1#* 'FBUVSF# 1#* 1#*̐ #BDLMPH3FpOFNFOU ɿ ̍%JWJEFUIF1#* w 5PXJUIJO4QSJOU XFFL w %FpOJUJPOPG3FBEZ

Slide 47

Slide 47 text

#BDLMPH 3FBEZ 5PEP %PJOH %POF 'FBUVSF" 1#* 1#* ɿ 1#*ສX 1#*#ສX ̎ɽ0SEFSCZ$%%FTD w &TUJNBUJOH$PTUPG%FMBZ &TUJNBUFWBMVF w "MMEVSBUJPOJTUSFBUFEBTX *HOPSJOHBOFSSPSMFTTUIBOX 1#* 1#* 'FBUVSF# 1#*"ສX 1#*̐ສX ɿ #BDLMPH3FpOFNFOU

Slide 48

Slide 48 text

5IFEFTDFOEJOHPSEFSPG$%JTUIFPQUJNBMTPMVUJPOGPS NJOJNJ[JOHMPTTFT NBYJNJ[JOHQSPpU JOBQFSJPE 1SJPSJUJ[F $%$PTUPG%FMBZ%JWJEFECZ%VSBUJPO $PTUPG%FMBZ %VSBUJPO 8JUIUIFEFMJWFSZPGUIJTGFBUVSFJTEFMBZFE IPXNVDIEPFTJUDPTUQFSVOJUQFSJPE ʹ&TUJNBUFWBMVF 5IFEVSBUJPOOFFEFEGPSUIFEFMJWFSZ ʹ&TUJNBUFEVSBUJPO GPSUIFEFUBJMTQMFBTFSFGFSUP-&"/&/5&313*4&Q

Slide 49

Slide 49 text

w 5IFTJ[FPGUIF1#*JTXJUIJOTQSJOU XFFLGPSVT %FpOJUJPOPG3FBEZ"QQMZJOHUPBMM1#*UIBUQSPCBCMZCFTFMFDUFEXJUIJOUIFMBTUTQMJOU 5IF10BOEUIFEFWFMPQNFOUUFBNBHSFFUPUIBUUIFTJ[FJTMFTTUIBOPSFRVBMUP4QSJOU -BSHFFOPVHIGPSMFBSOJOHTPNFUIJOHBOETNBMMFOPVHIGPSSFEVDJOHEBNBHFJGJUTXSPOH w 8FUSFBUBMM1#*TTFMFDUFEGPSUIFTQSJOUBTXFFLEVSBUJPO *HOPSJOHBOFSSPSMFTTUIBOTQSJOU w 8FQSJPSJUJ[FNBLJOHTNBMMFSUIFTJ[FPWFSBWPJEJOHEFQFOEFODZ )PXFWFS XFVTFBWFSUJDBMGFBUVSFTMJDFJOPSEFSUPMFBSOTFQBSBUFMZ FHCFGPSFUIFDPNQMFUFJNQMFNFOUBUJPOPGOFXGFBUVSFT BEFNPGPSTQFDJpDJOEVTUSJFT 5IJTJTUIFNPTUEJ⒏DVMUQPJOU %VSBUJPO1#*4J[JOH"MUFSOBUFPG&TUJNBUFT #ZDPOUSPMMJOHUIFTJ[F UBLFPVUUIFEVSBUJPOXJUIPVUFTUJNBUJPO DPOWFSUJOHUIFOVNCFS

Slide 50

Slide 50 text

8F%0&TUJNBUF7BMVF 8FOFFEJU $PTUPG%FMBZ&TUJNBUFWBMVF

Slide 51

Slide 51 text

w 5IJTGFBUVSFJT999TFMMJOUIFNPTUSFDFOURVBSUFS QMBOOFE 999 8FFL.POUI MPTTGPS8EFMBZ w 5IJTGFBUVSFTBWFTO)PVS%BZBUJNFPGCVTJOFTT &YQFDUFETBMFTPG:::8FFLJGCVTJOFTTVTFUIFUJNFUPTBMFTBDUJWJUJFT :::MPTTGPS8EFMBZ 8JUIUIFEFMJWFSZPGUIJTGFBUVSFJTEFMBZFE IPXNVDIEPFTJUDPTUQFSVOJUQFSJPE $POTJEFSUIFMBUFTUWBMVFGSPNUIFEFMJWFSZ $PTUPG%FMBZ&TUJNBUFWBMVF

Slide 52

Slide 52 text

4QSJOU1MBOOJOH $BQBDJUZ $PNNJUNFOU

Slide 53

Slide 53 text

#BDLMPH 3FBEZ 5PEP %PJOH %POF 'FBUVSF" 1#* 1#* ɿ 1#*ສX 1#*#ສX 1#* 1#* 'FBUVSF# 1#*"ສX 1#*̐ສX 4QSJOU1MBOOJOH5PQJD ɿ 1#*̑ສX ɿ ̏ɽ4FMFDU1#*CZQBTUSFTVMUT w $BQBDJUZJTEFUFSNJOFECZ"WHJUFNDPVOU w $PNNJUUP4QSJOU(PBM 8FXJMMEFMJWFSGFBUVSF"JOUIJT4QSJOU 1#*ສX 1#*#ສX 1#*"ສX 1#*̐ສX 4QSJOU(PBM

Slide 54

Slide 54 text

4QSJOU1MBOOJOH5PQJD$BQBDJUZ $BMDVMBUJOH$BQBDJUZ1#*5ISPVHIQVU w 8FKVEHFUIFDBQBDJUZGSPNUIFUISPVHIQVUPGQSFWJPVT4QSJOUT 5IF/VNCFSPG1#*XFEJEJOB4QSJOU *OPVSDBTF 3PVHIMZd w 5IFEFWFMPQNFOUUFBNEFUFSNJOFXIFUIFSJUJTQPTTJCMFUPQVU JOUPBTQSJOU 5IFEFWUFBNDPOpSNUIFEJ⒏DVMUZPGFBDI1#*XJUIUIF10

Slide 55

Slide 55 text

w 8FDPNNJUUPUIF4QSJOU(PBM OPU1#* FHXFXBOUUPCFBCMFUPEFMJWFSUIFOFX999GPSNBUUIJTXFFL w 5IFOVNCFSPG1#*JTTFMFDUFECZBWFSBHFDIBMMFOHJOH $IBMMFOHJOHUBSHFU %POUTUJDLUPDPNQMFUFBMMTFMFDUFE1#*T "TTVNJOHUIBUUIFEJTUSJCVUJPOPGUIFUISPVHIQVUGPMMPXTOPSNBMEJTUSJCVUJPO XF NJTTUIFBWFSBHFJOQSPCBCJMJUZ 4QSJOU1MBOOJOH5PQJD$PNNJUNFOU 4QSJOU(PBM

Slide 56

Slide 56 text

#BDLMPH 3FBEZ 5PEP %PJOH %POF 'FBUVSF" 1#* 1#* ɿ 1#* 1#* 'FBUVSF# 4QSJOU1MBOOJOH5PQJD ɿ 1#*̑ສX ɿ 1#*ສX 1#*#ສX 1#*"ສX 1#*̐ສX 5BTL#PBSE 4#* 4#* 4#* 4#* 4#* 4#* 4#* 4#* ̐ɽ*EFOUJGZUIFUBTLT w %POU&TUJNBUF4#* w %JWJEFXJUIJOEBZ JHOPSFFSSPS w .BLFSPVHIBHSFFNFOU UIFO.PC 1SPHSBNNJOH 4#*

Slide 57

Slide 57 text

w 5IFEFWFMPQNFOUUFBNJEFOUJGZUIFUBTLTPGTFMFDUFE1#* w "TXJUI1#* 5IFZBSFDPOUSPMMFECZTJ[JOHXJUIPVUFTUJNBUJOH w UIFEFWFMPQNFOUUFBNBHSFFUPUIBUUIFTJ[FPGUIFUBTLJTMFTTUIBOPOFEBZ w *HOPSJOHUIFFSSPSMFTTUIBOPOFEBZ w *OUIFMJTUFEUBTL XFNBLFBSPVHIBHSFFNFOUBCPVUIPXUPEPUIBU w "GUFSUIBU XFDPMMFDUUIFPQJOJPOXIJMFEPJOHUIFUBTLXJUI.PC 1SPHSBNNJOH XFBMXBZTEPUIF%FMQIJNFUIPE TPXFEPOUOFFEHBUIFSJOHJOGPSNBUJPOUISPVHI UIF1MBOOJOH1PLFS 4QSJOU1MBOOJOH5PQJD$BQBDJUZ $BMDVMBUJOH$BQBDJUZ4#*5ISPVHIQVU 4J[JOH"MUFSOBUFPG&TUJNBUFT

Slide 58

Slide 58 text

%BJMZ4DSVN 1SPHSFTT.BOBHFNFOU

Slide 59

Slide 59 text

#BDLMPH 3FBEZ 5PEP %PJOH %POF 'FBUVSF" 1#* 1#* ɿ 1#* 1#* 'FBUVSF# %BJMZ4DSVN ɿ 1#*̑ສX ɿ 1#* 1#*# 1#*" 1#*̐ 5BTL#PBSE 4#* 4#* 4#* 4#* 4#* 4#* 4#* 4#* 4#* ̑ɽ.POJUPS1SPHSFTT w $POpSNUIFOVNCFSPGUBTLTBOE SFNBJOJOHEBUFPG4QSJOU

Slide 60

Slide 60 text

w 6TFUIFSFNBJOJOHOVNCFSPGUBTLTUPDPOpSNQSPHSFTT 8FpHVSFUIBUXFDBOpOJTIPSOPUGSPNUIFSFNBJOJOHEBZTPGUIF4QSJOU w 8FEJWJEFBEEEFMFUFUBTLTJGOFFEFEXIFOpOJTIJOHUIFUBTL *OTUFBEPGSFFTUJNBUJOH 4#*5ISPVHIQVU

Slide 61

Slide 61 text

Monte Carlo methods, or Monte Carlo experiments, are a broad class of computational algorithms that rely on repeated random sampling to obtain numerical results. &YQFSJNFOUBM.POUF$BSMP.FUIPE 4JNVMBUJOHXIBUXJMMIBQQFO GSPNUIFQBTUUSFOE %POUUSZUPTFDPOEHVFTT.FBTVSF .POUF$BSMPNFUIPE8JLJQFEJB

Slide 62

Slide 62 text

5IFGVODUJPOPG,BOCBOJ[FXIJDIXFVTF *UUFMMTVTUIBU 5IFSFJT/DIBODFUIBUXFDBOpOJTI.UBTLTJOUIFSFNBJOJOHEBZTPGUIF4QSJOU 5IFTNBMMFSUIFTUBOEBSEEFWJBUJPOJT UIFNPSFSFMJBCMFUIFQMBOJT / &YQFSJNFOUBM.POUF$BSMP.FUIPE

Slide 63

Slide 63 text

5PUSVTU1#*UIF4#*UISPVHIQVU 8FOFFEDPOpEFODFUIBU XFDBOHPXJUIBCPVUUIJTTQFFE XFOFFE$PVSBHF

Slide 64

Slide 64 text

$PSFQSPDFTTFTTVQQPSUJOH$PVSBHF .PC1SPHSBNNJOH

Slide 65

Slide 65 text

4QSJOU 5IF%FWFMPQNFOU8PSL 1SFEJDUBCJMJUZ

Slide 66

Slide 66 text

On the same thing... At the same time... In the same place... On the same computer... —Mob Programming A Whole Team Approach" / Agile 2014, Woody Zuill .PC1SPHSBNNJOH

Slide 67

Slide 67 text

"DDPSEJOHUP6OEFSTUBOEJOH$ZDMF5JNF%JTUSJCVUJPO4IBQFT5SPZ.BHFOOJT w 5IFSFJTBIZQPUIFTJTUIBUUIFDZDMFUJNFEJTUSJCVUJPOTIBQFJTEJ⒎FSFOUEFQFOEJOHPOUIF EFQFOEFODZ w 5IFEJTUSJCVUJPOQFBLTIJGUTMFGUJGUIFUFBNIBTGFXPSOPEFQFOEFODJFT .PC1SPHSBNNJOHBOE-FBEUJNF4UBCJMJUZ Teams with few (or no) external dependencies Tams who limit WIP (eg. kanban teams) Teams who do batch iterations (eg. Scrum teams) Teams who do large batches (waterfall)

Slide 68

Slide 68 text

5IFBDUVBMNFBTVSFEWBMVFPGPVSUFBN w 8FBDIJFWF8*1 $SPTTGVODUJPOBM /PFYUFSOBMJOUFSOBMEFQFOEFODJFTUFBNCZ.PC 1SPHSBNNJOH w 5IFQFBLPGUIFDZDMFUJNFJTUIFMFGUTJEF .PC1SPHSBNNJOHBOE-FBEUJNF4UBCJMJUZ

Slide 69

Slide 69 text

w *UJTJNQPSUBOUUIBU5IFDZDMFUJNFJTTUBCMF TUBOEBSEEFWJBUJPOJTTNBMM XFDBOpOEUIBUXIFODBOXFpOJTIGSPNUBTLDPVOU .PC1SPHSBNNJOHBOE-FBEUJNF4UBCJMJUZ

Slide 70

Slide 70 text

w "MXBZTUBLFUIFCFTUDPOEJUJPOPGUIFUFBN w UIFUISPVHIQVUJTOUB⒎FDUFECZQFSTPOBM FTQFDJBMMZ"DF DPOEJUJPO PSTPNFPOFMFBWJOHUFBN .PC5FTUJOH"O*OUSPEVDUJPO&YQFSJFODF3FQPSU .PC1SPHSBNNJOHBOE5ISPVHIQVU4UBCJMJUZ

Slide 71

Slide 71 text

*OGPSNBUJPOJTPOFPGUIFWBMVFFYUSBDUFEGSPN&TUJNBUFTJ[F *OUIFFTUJNBUJPOQSBDUJDFTMJLF1MBOOJOH1PLFS /FDFTTBSZJOGPSNBUJPOJTDPMMFDUFEGSBOLMZGSPNUIFFYQFSUT JTNPSFJNQPSUBOUUIBO UIFOVNCFSJTHJWFO %FMQIJNFUIPE w *O.PC1SPHSBNNJOH XFQSPDFFEXIJMFBHHSFHBUJOHUIFPQJOJPO PGUIFXIPMFUFBN w .BLJOHBSPVHIBHSFFNFOUBCPVUUIFQSPDFEVSF UIFOXFDBO EFUFSNJOFXIJMFEPJOHUIFUBTL XIJMFEPJOHUIFUBTLJTVTVBMMZUIFCFTUTPMVUJPOCZNBYSFTPMVUJPO .PC1SPHSBNNJOHBOE%FMQIJ.FUIPE

Slide 72

Slide 72 text

w 5IFXIPMFUFBNBHSFFUP1SPDFFEXJUIBNJOJNVNPGXPSLSFRVJSFEGPSUIJTUBTL w "MTPBHSFFUPUIFOFDFTTBSZFMFNFOUTUPNBJOUBJOUIFRVBMJUZPGUIFDPEF 65 SFGBDUPSJOH OBNJOHDPOWFOUJPOTFUD w &BDINFNCFSTIBWFEJ⒎FSFOUXIBUDPNNJUUFEUPUIBUpMMUIFUJNF FHGVODUJPOBMQSPHSBNNJOHTIPVMECFXSJUUFOJOUIJTXBZ FHUIJTNFUIPETIPVMECFJOUIJTDMBTT w 8JUIPVUIFTJUBUJPOCFDBVTFUIFXIPMFUFBNQSPDFFECZUIFBHSFFNFOU :"(/*CZNVMUJBOHMF .PCBMXBZTB⒎FDUUPNJOJNJ[FUIFTJ[FPGUIFUBTL .PC1SPHSBNNJOHBOE1BSLJOTPOT-BX

Slide 73

Slide 73 text

.PC1SPHSBNNJOHBOE4DSVN7BMVFT 4VQQPSUJOH/P&TUJNBUFT

Slide 74

Slide 74 text

'PDVTCZ.PC .VMUJ"OHMF:"(/* 0QFOOFTTPG 3FMJBCMF4DIFEVMF ,FFQB1SPNJTF 3FTQFDU 1BSLJOTPOT-BX .6%" XBTUF PG8PSL "DDVSBDZEPFTOUJNQSPWFFWFOPWFSUJNF .63" VOFWFOOFTT PG"DDVSBDZ 4UBCJMJUZ61 1SFEJDUBCJMJUZ6Q 3FMJBCMF.FBTVSFNFOU $PVSBHF $PNNJUNFOU

Slide 75

Slide 75 text

3FTQFDU UIF4DIFEVMF 3FDUBOHMFPG5SVTU &TUJNBUJPOBTB$PNNJUNFOU .63* 0WFSCVSEFO PG%FBEMJOF

Slide 76

Slide 76 text

8IBU8F/FFE %FTJSFE 'FBUVSFT &TUJNBUF TJ[F &TUJNBUF EVSBUJPO 4DIFEVMF 4J[F %VSBUJPO &TUJNBUF WBMVF 7BMVF 1SJPSJUJ[F H Y 1SJPSJUZ G Y $PTU *OGP w 4UPSZ1PJOUT w *EFBM5JNF 2VBOUJGZ$BVTFPG. &TUJNBUFCZ $PTUPG%FMBZ %JWJEJOH BOEUSFBUBTTBNF EVSBUJPO (BUIFSXIJMF EPJOH.PC

Slide 77

Slide 77 text

5IF/FHBUJWF"TQFDUTBOE7BMVFPG&TUJNBUJPO 4DSVNBOE&TUJNBUJPO 0VS/P&TUJNBUFT4DSVN 3FBMJUJFTPG/P&TUJNBUFT

Slide 78

Slide 78 text

)PXEJEXFTUBSU/P&TUJNBUFT 4VJUBCMF6OTVJUBCMFUFBNGPS/P&TUJNBUFT 5SPVCMFTJO/P&TUJNBUFT )PXDBOXFLFFQBEFBEMJOF

Slide 79

Slide 79 text

+645%0*5

Slide 80

Slide 80 text

#FGPSF/P&TUJNBUFT w 5IFNBOBHFSBTTJHOTUBTLT w 5IFQFSTPOXIPJTBTTJHOFEFTUJNBUFTUIFUBTL w 5IFQFSTPOJOQVUUIFQSPHSFTTPOUIF(BOUUDIBSU w 5IFNBOBHFSBOECVTJOFTTTIBSFUIFQSPHSFTTJOXFFLMZ.5( w 8FIBWFEFBEMJOFTCVUXFVTVBMMZNJTTJU .FNCFSTFYUFOEUIFEFBEMJOFCZUIFJSJOUVJUJPO

Slide 81

Slide 81 text

w 8FTUPQFEFTUJNBUJOHTJODFXFVTFPOMZ,BOCBO &WFSZPOFOPUJDFEUIBUUIFFTUJNBUFXBTOPUXPSLJOH w *OTUFBE CFHBOUPEJWJEFUIF1#*BTTNBMMBTQPTTJCMF w &WFSZPOFLOPXT8IFOUIJTGFBUVSFJTEFMJWFSFE JOSFBM UJNF 5IFPSEFSPGUIFOFYUUPEP BMJTUPGEPJOHOPXIBTCFFOPQFOFE 5IJTXBTXIBUXFOFFEFEGPS *OWPMWJOHUIF#PTT4UBSU,BOCBO &WFSTJODF4UBSUJOH 8FBSFOFWFSBTLFEGPSFTUJNBUFT

Slide 82

Slide 82 text

"SPVOEUIF4BNF5JNF4UBSU.PCCJOH w #ZMJNJUJOH8*1 EFMJWFSZPG1#*CFDBNFGBTU w 8IFODBOXFEFMJWFSJU CFDBNFNPSFSFMJBCMFUIBO (BOUU$IBSU w &WFSZPOFDBOEJWJEFUIFUBTL BOETBZGPSDFSUBJOIPXUP EPJU

Slide 83

Slide 83 text

w 3FUSPTQFDUJWFT 8FTUBSUGSPNUIJTUPJOWPMWFUIFXIPMFUFBN w 4QSJOU1MBOOJOH *UXBTOFDFTTBSZTZODISPOJ[JOHUIFJOGPSNBUJPOUIBU8IBUEPXFOFFE 8IBUDBOXFpOJTI w #BDLMPH3FpOFNFOU *UXBTOFDFTTBSZUSBOTQBSFODZUPQSJPSJUJ[BUJPO w %BJMZ4DSVN 4JODFXFTUBSUFE.PCCJOH JUCFHBOOBUVSBMMZUPNBLFUIFTUSBUFHZPGUIF EBZ w 3FWJFX *UCFHBOOBUVSBMMZUPHBUIFSUIFGFFECBDL *OWPMWJOHUIF#VTJOFTTSFBDIJOH4DSVN 5PBEBQUDIBMMFOHFT XFJNQMFNFOUFEUIFTDSVNFWFOUTTUFQCZTUFQ

Slide 84

Slide 84 text

)PXEJEXFTUBSU/P&TUJNBUFT 4VJUBCMF6OTVJUBCMFUFBNGPS /P&TUJNBUFT 5SPVCMFTJO/P&TUJNBUFT )PXDBOXFLFFQBEFBEMJOF

Slide 85

Slide 85 text

5IF%FWFMPQNFOU5FBN w 5IFUFBNJTNBUVSFUPTPNFFYUFOU "DSPTTGVODUJPOBM BOEIBTBTLJMMSFRVJSFEUPCVJMEUIFJODSFNFOUT 4FMGPSHBOJ[FE BOEFOBCMFTUPEFUFSNJOFUIF1#*4#*DBQBDJUZJOUIF4QSJOUCZ UIFJSPXO w 5IFUFBNIBTUIFSFTVMUPGUIFWFMPDJUZ BOE*UJTTUBCMF w 5IFUFBNIBTBCJMJUZUPEJWJEFUIF1#*4#* 7FSUJDBM4MJDF w 5IFCPTTUSVTUUIFUFBNBOEEFMFHBUFUIFBVUIPSJUZ 5IJTJTQSPCBCMZNPTUJNQPSUBOU -POHUFSNUFBNNBZCFBCMFUPTUBSUTNPPUIMZ

Slide 86

Slide 86 text

w /PU%FBEMJOF%SJWFO CVU'FBUVSF%FMJWFSZ%SJWFO w *O%FBEMJOF%SJWFO JUNBZCFQPTTJCMFJGUIFSFJTBOVOEFSTUBOEJOHPG DIBOHJOHUIFTDPQF w #VJMEBSFMBUJPOTIJQCFUXFFOCVTJOFTTBOEEFWFMPQNFOU w /PUCFBTLFEUPDPNNJUUPUJHIUEFBEMJOFTGSPNEPVCUUPUIFUFBN w HFUUIFDPPQFSBUJPOJOUIFSFRVJSFEFWFOUT *OJUJBM4UBSUVQ1IBTF0QFSBUJPO(SPXUI1IBTF 1SPEVDU3FMBUJPOTIJQ#FUXFFO#VTJOFTT

Slide 87

Slide 87 text

*GPOFPSUXPBSFNFU PUIFSTXJMMCFNFUXIJMFEPJOH 5IF,FZJT %PFTUIFUFBNIBWFBVUIPSJUZ %PFTUIFUFBNHJWFUSBOTQBSFODZUPUIFQMBO #VU *UTTV⒏DJFOU OPUOFDFTTBSZ .PC1SPHSBNNJOHJTHPPEQMBDFUPTUBSU

Slide 88

Slide 88 text

)PXEJEXFTUBSU/P&TUJNBUFT 4VJUBCMF6OTVJUBCMFUFBNGPS/P&TUJNBUFT 5SPVCMFTJO/P&TUJNBUFT )PXDBOXFLFFQBEFBEMJOF

Slide 89

Slide 89 text

5FOEUP#F4IPSUTJHIUFE

Slide 90

Slide 90 text

w UIFMPOHUFSN1#*JTIBSEUPCFTFMFDUFE w FHUFDIOJDBMEFCU JNQSPWFNFOUPGUIFJODPOWFOJFOUQPJOU SFTFBSDIBOEEFWFMPQNF w 5IF1#*UIBUTFFNTUPCFQSPpUBCMFUFOEUPCFTFMFDUFE w GFFMTMJLFUIFCPJMJOHGSPH XIFOXFJOUSPEVDFEUIF$% XFUIPVHIUMJLF 5IJTJTUIFCFTU XFDBODPNQBSFUPBMMPG1#*JOpOBODJBMWBMVF 5IJTJTUIFNPTUWBMVBCMFPSEFS#65 -BDLPGNFEJVNMPOHUFSNWJFX "EWFSTFF⒎FDUTPGTUPQQJOHUIF30* *UEPFTOPUNBUUFSCZ/P&TUJNBUFT

Slide 91

Slide 91 text

w "EPQUUIFQSPEVDUQPSUGPMJP FH/FXGFBUVSF9 JNQSPWFNFOU: UFDIEFCU; w 1MBONFEJVNBOEMPOHUFSN*UFNTCZ0,3 8IBUJTUIFQPJOUPGUIFOFYURVBSUFS )BSEUPTBZUIBUJTXPSLJOHXFMM -BDLPGNFEJVNMPOHUFSNWJFX.FBTVSFT

Slide 92

Slide 92 text

.JTTFE UIF EFBEMJOF

Slide 93

Slide 93 text

5ZQJDBM.JTDPNNVOJDBUJPO /P&TUJNBUFTEPFTO`UNBUUFS -BTU"VHVTU 8FNJTTFEUIFEFBEMJOFESJWFOEFMJWFSZEFUFSNJOFECZUIFDPOUSBDU #J[VOUJMUIF / EBZTDBOCFBEKVTUFEXJUIUIFDMJFOU CVU*XBOUUPTUBSUJOUIF/EBZT %FW8FXJMMCFBCMFUPpOJTIJO/EBZT #VU/EBZTJT0, SJHIU d"GUFS/EBZTd #J[6I $PVMEXFTUBSUUPEBZ %FW6I XFXJMMTUBSUJUJOUIFEBZBGUFSUPNPSSPX

Slide 94

Slide 94 text

$PODMVTJPO /PUJOUSPVCMF

Slide 95

Slide 95 text

)PXEJEXFTUBSU/P&TUJNBUFT 4VJUBCMF6OTVJUBCMFUFBNGPS/P&TUJNBUFT 5SPVCMFTJO/P&TUJNBUFT )PXDBOXFLFFQBEFBEMJOF

Slide 96

Slide 96 text

w 8IZUIFEFBEMJOFJTOFFEFE XIFUIFSUIFSFJTBSFBTPO JGUIFZDBOOPUFYQMBJO UIFEFBEMJOFJTQSPCBCMZOPUOFDFTTBSZ w *ODMVEJOHUIFBEKVTUNFOU IPXMPOHDBOXFEFMBZ w 8IBUIBQQFOTJGNJTTJU IPXNVDIEPFTJUDPTU w 5IFDMPTFSUIFEFBEMJOF UPTIBSFUIFTJUVBUJPOJOSFBMUJNF $POpSNUIF3&"-%FBEMJOF 5BLFUIFOFDFTTBSZDPNNVOJDBUJPO &TUJNBUJPOEPFTOUNBUUFS

Slide 97

Slide 97 text

#1 Reason we miss deadlines We START too late 4UBSU&BSMZ 5SPZ.BHFOOJT

Slide 98

Slide 98 text

w #BTJD*EFB$% $%JTOPUBCPVU8IBUUPCFHJO CVU8IBUUPEFMBZ ,FFQUIFTUBUF&WFSZUIJOHJTPLCZ$%EFTD w 4UBSUFBSMZ XJUIBNBSHJOPGBUMFBTU4QSJOU $BMDVMBUFUIFUIFMBTUQPJOUXFNVTUTUBSUXJUIUIFNBSHJO 5P4UBSU&BSMZ%FDJEF8IBUUP%FMBZ

Slide 99

Slide 99 text

&WFO/P&TUJNBUFT 8F$BO,FFQUIF %FBEMJOF

Slide 100

Slide 100 text

5IF/FHBUJWF"TQFDUTBOE7BMVFPG&TUJNBUJPO w/FHBUJWF"TQFDUT.63* .6%" .63"CZ2VBOUJGZJOH w5IF7BMVF$PTU *OGPSNBUJPO 7BMVFGPS1MBOOJOH 4DSVNBOE&TUJNBUJPO w1SJPSJUJ[BUJPO $BQBDJUZ $PNNJUNFOU 1SPHSFTT 0VS/P&TUJNBUFT4DSVN w4J[JOH .POJUPSJOH5ISPVHIQVU 4DSVN7BMVFT 5SVTU w.PC1SPHSBNNJOH 3FBMJUJFTPG/P&TUJNBUFT w&BTZUPTUBSUJOUIFMPOHUFSNUFBN w/PUJOUSPVCMFXJUI/P&TUJNBUFT w5PQSPUFDUUIFEFBEMJOF TUBSUFBSMZ 4VNNBSZ

Slide 101

Slide 101 text

&TUJNBUJPO -FUT .PC1SPHSBNNJOH

Slide 102

Slide 102 text

Thank You for Your Kind Attention! UXJUUFS!NBSUJO@MPWFS@TF Thank you for English proof reading! Arnab Gupta, Hideaki Oshima,ɹ Cherifa Mansoura Thank you for meaningful feedback! Koichi Yoshida, Nobuaki Miura, Hiroki Konishi, Minoru Yokomichi

Slide 103

Slide 103 text

• "HJMF&TUJNBUJOHBOE1MBOOJOH 3PCFSU$.BSUJO4FSJFT .JLF$PIO • -FBO&OUFSQSJTF)PX)JHI1FSGPSNBODF0SHBOJ[BUJPOT*OOPWBUFBU4DBMF#BSSZ0`3FJMMZ +PBOOF.PMFTLZ +F[)VNCMF • 4DSVN5IF"SUPG%PJOH5XJDFUIF8PSLJO)BMGUIF5JNF+F⒎4VUIFSMBOE • 5IF4DSVN(VJEF,FO4DIXBCFS +F⒎4VUIFSMBOE • 6OEFSTUBOEJOH$ZDMF5JNF%JTUSJCVUJPO4IBQFT5SPZ.BHFOOJT • 8IBU`TUIFTUPSZBCPVU"HJMF%BUB5SPZ.BHFOOJT • .PC1SPHSBNNJOH"8IPMF5FBN"QQSPBDI"HJMF 8PPEZ;VJMM • #FZPOE&TUJNBUFT-JGF -JCFSUZ BOEUIF1VSTVJUPG"HJMJUZ8PPEZ;VJMM ◦ /P&TUJNBUF1SPHSBNNJOH4FSJFTr*OUSP1PTU ◦ $BO8F$PEF8JUIPVU&TUJNBUFT ◦ 8IZEPXFOFFEFTUJNBUFT • 5IF)JEEFO$PTUPG&TUJNBUFT$ISJT-VDJBO • 4PGUXBSF&TUJNBUJPO1BSBEPY$ISJT-VDJBO • 8IBU4DSVN4BZT"CPVU&TUJNBUFT4DSVNPSH4MBWB.PTLBMFOLP • 5IFMPHJDPG/P&TUJNBUFT/P&TUJNBUFTGPMMPXTJOUIFGPPUTUFQTPG"HJMFBOE4DSVN8JMMFN+BO"HFMJOH • /P&TUJNBUFT1BSU %PJOH4DSVN8JUIPVU&TUJNBUFT • .PC5FTUJOH"O*OUSPEVDUJPO&YQFSJFODF3FQPSU 3FGFSFODF