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WhitE papEr Big VisiBility

turnn “B Daa” ino

“B Vb”leadn compane are bennn o everae her

daa o an vauabe neence and auomae

procee acro her end-o-end upp chan

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Mos ms ve ledy nvesed n busness nellgence,

suly cn mngemen (SCM), nd modelng ools

clm o mke ossble o dll deee no e suly cnd n sec of svngs. tese ools e oen mkeed w

vgue omses ey wll ness e ognzon’s “bg

d” nd/o ovde “end-o-end” (e2e) vsbly.

Ye dese e fc ey ve undegone numbe of

comlex nd exensve ecnology mlemenons, mos

C-level nd suly cn execuves dm ey sll ve

lle de of w s enng ougou e exended

suly cn unl long e evens ve ken lce. i s

nely mossble fo e ognzon o sense n ssue nd

modfy o omze s esonse n mely mnne.

as esul, ody’s execuves e fused—ey know

e comnes e sng on exemely vluble nfomon

sses nd ye ey e unble o levege fo e bene

of e ognzon. Wle ey wok d evey dy unnng

oeons o yng o gue ou ow o bes lloce e

lmed cl, e oug s lwys n e bck of e

mnds ee s o be bee wy. te oblem

oweve s s vey cllengng o know w ools o

nves n nd ow o me nvesmen.

ts we e exloes ow comnes cn successfully

levege e bg d o gn unecedened levels of

vsbly nd conol coss e suly cn. i wlldemonse w e g ecnology oc,

comnes e mkng sgncn ss n e use of d

o nclude dvnced nlycs nsfom socl

nd el me d cued n e own SCM nd Erp

sysems (nd ose of e dng nes) no edcve

nd escve nsgs. tese comnes e usng

dvnced nlycs o ovde el me vsbly coss e

suly cn nd move foecsng, demnd lnnng,

elensmen, soucng, elensmen, oducon,

nsoon nd logscs, nd dsbuon ocesses.

Noe wle no ll ognzons e edy o ness

e bg d nd mlemen dvnced nlycs, mny

dvnges cn sll be gned fom nlycs wou e

lcon becomng ovely sosced o comlex. Fo

some, smly gnng moe ccue wndow no w

s enng coss e end-o-end suly cn s

wowle nvesmen. in e end, ee cn be lle doub

wee o no you ledy ve d wng o be

used, nvesng n new nlycl ools wll lkely be n you

ognzon’s fuue.

advnced nlycs cn genee dee nd exnsve vlue by ovdng el me vsbly cosse suly cn nd movng foecsng, demnd lnnng, soucng, elensmen, oducon,

nsoon nd logscs, nd dsbuon ocesses.

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supp chan’ be buzzword: “B Daa” and“end-o-end vb”

Evey we e, webn, nd cle bou suly cns

ese dys seems o nclude some menon of bg d, end-

o-end (“e2e”) vsbly, o dvnced nlycs. as w mos

buzzwods, e denons e vgue nd s uncle ow, f

ll, ey e eled o ec oe.

Wen lkng bou bg d, mos souces emsze e

see scle of e d ses now exs, w nyng ove

1 ebye usully geng e bg d lbel.1  a ebye of

1. “Bg d: e we mkng bg mske?”, Fnncl tmes, 2014.

d s 1024 ebyes, nd ebye of d s 1024 ggbyes.

to ovde some sense of scle (nd ow f we’ve come),

20 ebyes s e ol moun of d dsk dve scemnufcued n 1995. tody s e moun Google

ocesses on dly bss. Fo 15 ecen of mnufcues n

ecen suvey, 20 ebyes lso eesens e cuen sze

of e Erp dbses.2 

Fndng consensus fo w suly cn vsbly mens s

muc de, bu by ny denon ’s vey ssve execse.

Essenlly, comnes e execung nscons, song e

2. “5 Ses Suly Cn Execuves Cn tke o hness Bg D”,Suly Cn insgs, 2013.

20 petabytes is the total amount of hard disk drive spacemanufactured in 1995. Today it is the amount that Google

 processes on a daily basis.

Ke Fac

• a ecen suvey of 400 execuves (moe n lf n C-sue oles) found 51% of

esondens beleved edcve nlycs wll ovde moe ecse sk ssessmen

of sules, bu only 31% e cuenly usng edcve nlycs n s mnne

(te Economs).

• 58% of comnes n e suly cn ndusy ve nvesed o ln o nves n bg

d ecnology dung nex wo yes (Gne resec 2013).

• a ecen suvey of 127 comnes n suly cn nduses, mjoy ndced

e bgges cllenge w bg d ws o undesnd ow o exc vlue

(Gne resec 2013).

• By 2017, 30% of comnes wll do sm mcnes fo no-umn decson-

mkng n one o moe suly cn ocesses (Gne pedcs 2014).

• By 2017, e convegence of sucued nd unsucued d wll fundmenlly

cnge e wy Cp suly cns delve vlue (Gne pedcs 2014).

30%

Using predictiveanalytics, 51% sayuseful but notusing

31%

will adopt smartmachines by2017

58%Invested or planto invest in bigdata in next 2 yrs

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esuls n d weouse, usng e d o ols nd/

o busness nellgence ools, unnng nlycs on w s

ened, nd jus yng o do bee nex me. and wlee “end-o-end” lbel s oen used, e u s mos

ecnology sysems sll oe smlsc fom of vsbly no

one of e suly cn e exense of e oe. a

bes (nd s s e), s mens vsbly coss e nenl

demens of e ognzon w nonl sles nd

ucsng vsbly no s mmede dng nes.

Gven ese lmons, s no wonde Gne resec

ecenly eveled vully no comnes e ble o o

wll be ble o ovde end-o-end suly cn vsbly n

e ne fuue; n fc, by 2016, ey esme less n 20%of comnes wll be ble o ovde end-o-end suly cn

vsbly.3  te u s mos comnes e essenlly

yng blnd.

Wy s end-o-end vsbly so d o obn? te my

eson (nd one s been ovelooked by mos oe

commenos), s suly cn vsbly s mly bg

d oblem.

3. Gne “pedcs 2013: Collboon, Cloud nd EvolvngSeges wll Dve Globl Logscs”, vlble (ged):://www. gne.com

the ouourced upp chan’ b daa probem

Smly u, o obn end-o-end vsbly you need o solve

numbe of bg d oblems. te eson wy ee s been

so lle ogess on e vsbly fon s ody’s suly

cns e oo swlng, oo ousouced, nd oo comlex

fo donlly ceced sysems o ndle. Comnes

ve bndoned vecl negon, nsed ousoucng

lge mjoy of e suly cn funcons ey once

mnged n-ouse. te esul s suly cns ve

become ncedbly comlex globl webs of dng nes

sceed ll ove e wold, ec focusng on now slce

of e fulllmen o mnufcung ocess. tey e lled

w 1000s of sules, SKUs, nd comonens.

Execuves undesnd e donl enese

mngemen sysems e no desgned o mnge cvy

beyond e fou wlls of e enese, nd e cenly

no equed o del w e bg d oblem. as suly

cns become moe ngled, w gee numbe of f

ung sules, cusomes, nd logscs ovdes, mnges

e fced w sks cn co u n dozens of counes.

No wonde ecen Deloe suvey of 600 execuves

mnufcung nd el comnes found 63% wee

gly concened bou sks wn e exended suly

cn comsng vendos nd cusomes, nkng mong

e o-wo concens.4 

4. Deloe Consulng, “te rle Eec”, 2013, vlble : ://www.deloe.com/vew/en_US/us/Sevces/consulng/Segy-Oeons/09e44390e17c310VgnVCM1000003256f70rCrD.m

Gartner Research recently revealed that virtually no companiesare able to or will be able to provide end-to-end supply chain

visibility in the near future.

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Wh B Vb you Can...

• Model suly cn d w muc moe ecson.

• Cue nd neconnec d n mul-ne, mul-

ecelon envonmen o cee nellgence.

• ale decsons n el me (wn nsconl

ocess wokow).

• Ulze edcve nd escve nlycs o solve

oblems befoe ey occu nd ulze omzon

o move oucomes n evenue, nvenoy, nd

nsoon exenses.

in esonse, comnes ve long used comlex d

ses o ln mnufcung o mee cusome demnd e

now lookng o combne d fom exenl souces o beeedc fuue sks. te oblem s, f sngle mnufcue

lone cn ouse 20 ebyes of d (s we ledy lened),

ow muc moe d mus e es of e suly cn

conn?

inroducn “b vb” (upp chan’advanced nh)

Fowd-nkng comnes undesnd elnce on

nlycs esens e only sclble oc o nlyzng

nd gnng nsgs fom deluge of bg d. Muc lke

gndmse n cess, ey mus become exe n lookng

deen ens wn e suly cn. a cess

gndmse emloys se of conble seges o wn

mces, wc djus el-me deendng on e moves

seleced by e oonens. in sml fson comnes

mus esbls se of oocol seges wc cn be

eecvely deloyed on el-me bss s e eces on ou

bod cnge on dly nd weekly bss s esul of suly

condons, consume decsons, vlble deos, o some

elevn combnon of fcos.

te gndmse does no mke d oc decsons n e

momen. re e o se deloys move wn muc

lge conex. Smlly, s comnes seek o undesnd

ow e oucomes e eled o ll e cons nd

decsons of e dng nes nd consumes, ey mus

consde oocol seges ele o e ene end-o-

end connuum. One Newok s cllng s cbly “bg

vsbly”.

Combining human insights with stascal/mathemacalapproaches yields beer predicons than either is capable of

 producing on their own.

an mon on o emembe s elyng on umn

nuon o mnul nlyss cnno suo e knd of

fc-bsed, fs, oble decson mkng s equedby bg vsbly. advnced nsgs of s ye e dven

by combnon of bo umn nd mcne necon.

Combnng umn nsgs w sscl/memcl

oces yelds bee edcons n ee s cble of

oducng on e own. a good exmle of s s wee

foecsng wee e moun of d nd comue owe

boug o be on e oblem s uge, ye e umn

elemen sll dds vlue. 5

5 ts exmle ken fom Ne Slve’s “te sgnl nd e nose”,2013.

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inroducn he b vb road map

recng e oly gl of bg vsbly wll no be esy. i

eques wde nge of d fom coss e nenl suly

cn, e dng ne newok, nd fom mcoecomomccondons. Cuen suly cn nlycs ools e nowee

close o delveng ese knds of dvnced nlycs.6 tey

suggle w cung, ousng, nd nlyzng d, muc

less ecognzng demnd nd suly ens.

Even moe dscougng, Gne edced mny of

e nlycs-bsed suly cn decson suo ools wll

lkely become obsolee due o e nbly o del w bg

d, conduc nlyss wn e equed me cycle fo e

decson, nd uome decson mkng.7 

So ow cn comnes ceve bg vsbly? W follows

s 5 ae maur mode  ognzons cn use

s odm. Ec sge of muy oes s own

6. Gne resec ecenly eoed e sclbly, dgovennce, nd ovell soluon muy e no s dvnced sn moe esblsed ecnology ools. Gne resec, “MkeGude fo Suly Cn anlycs tecnology”, 2014

7. Gne resec, “pedcs”, 2014.

unque cllenges (nd benes f ceved). te ve

sges (llused bove) e eesenon, ccessbly,

nellgence, decson mngemen, nd oucome-bsed

efomnce. to fue lluse ec sge, One Newok

s ovded el exmles fom cul One Newok

cusomes.

1. Repreenaon (Daa)

te s se owd bg vsbly s meely eesenng

e suly cn’s d. W e dven of bg d,

eesenon s cnged foeve. i s no longe necessy

o lm eesenve d n e suly cn bsed on

donl sysem o ecnology consns. advnces

suc s hdoo bsed cecue nd ozonl gd

comung enble ognzons o eesen d w nunecedened moun of exbly nd sclbly.

Cae sud: Wlm, fo exmle, mkes on of sle

(pOS) d vlble evey 15 mnues. ts d s vluble

sse nd sould be used o move evenue nd mgn

e sque foo e soe self. W cuen ecnology

cecues would ve been mossble (o nfesble) o

BIG VISIBILITY ROADMAP

www.onenetwork.com

2. ACCESSIBILITY (PROCESS& PERMISSION)

Is my data useful at

the process and decision-layers?

Has my data has beenconverted into actionable

information through

interactive processdesigns?

(e.g. improving a processmid transaction)

1. REPRESENTATION (DATA)

Does my technology

support precision datamodeling?

(e.g. millions ofitem/location

combinations)

3. INTELLIGENCE(PREDICTIVE ANALYTICS)

Am I meeting expectations

(both current and future)?

Do I have full visibility to all

performance gaps across myvalue chain?

4. DECISION MANAGEMENT

Is my system capable of

taking action, both auto-mated and interactive,

against all performance

gaps and exceptions?

 (e.g. prescriptive analyt-

ics, trade-off analysis)

5. OUTCOME-BASEDMETRICS PERFORMANCE

How can big visibility and

real time collaborationimprove my organization

and underlying processes?

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oely model, ln nd execue s level of del. One

Newok s oven o be ble o eesen mllons of em/

self/soe combnons, ude d evey 15 mnues,

un nscons gns d, nd solve fo exceons

on connuous bss wle ovdng vsbly coss mulle

dng nes nd suly cn ecelons.

2. Acceb (Proce and Permon)

te second sge of bg vsbly s ccessbly, nd ee el

me ocess uomon nd mngemen ve cnged e

gme. in donl cecues, ccessbly s somew

synonymous w negon, unvesl objec denons,

nd longevy. howeve new cecues ovde el me

busness ocess mngemen lye wc n un ovdes

full conol nd necon wle execung nscon

 – oug se cnge nd ckng even lnkges. and

no only s e d ccessble, bu oug dvnced

ocess cbles ncludng olcy nd emsson conol,

ccessbly o bg d now genees uge vlue e

ocess nd decson-mkng lyes.

Cae sud: a e 1 uomove mnufcue (nd cuen

One Newok cusome) d mde good movemen n

nvenoy ove e s ye, bu d eced on of

One Network has proven to be able to represent millions of item/ shelf/store combinaons, update that data every 15 minutes,

run transacons against that data, and solve for excepons on a

connuous basis while providing visibility across mulple trading

 partners and supply chain echelons.

lack of acceb w pca reu n hefoown commenar…

• DC Manaer - “i kes sue use o gue ou ow

o ck nd ce.”

• Buer – “i cn ck Wip by pO#, bu os fcoy ive o use conne #’s, BOL #’s, cse #’s ec.”

• Accounan – “Smens fom 2012 ve cul

feg coss, bu 2013 only sow ssumed pO feg

fco – cn’ come.”

lack of repreenaon w pca reu nhe foown commenar…

• DC Manaer – “We cn’ see nbound delvees

coss mos of ou md sze o smlle sules.”

• Buer – “My pO’s don’ sow s ‘n-ns’ unl

week e ey s.”

• Accounan – “Ec que close s ngme

becuse we don’ know bou goods delveed FOB

mon end.”

• sore – “Smens ve n esmed Eta, bu sow

u 2 o 3 dys le.”

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dmnsng euns. te consn ws n ode o

connue dvng down nvenoy, ey needed o mnge

new sule olces wn nscon, e n eo meod of yng o move e olcy os nscon

(wen ws usully oo le). in s cse, sules wee

sng ely, bsed on n dvnced sng noce (aSN),

nd nng e mnufcue’s nvenoy osons. Sml

o e Wlm exmle, e only wy o solve s oblem

ws o ncese eesenon o nclude evey numbe

evey locon wn e ocess ws execung

beween e mnufcue nd s sules, ncludng 3d

y nsoon ovdes nd dsbuon nes.

Ye gong beyond eesenon, ccessbly needed o beovded oug new nsconl ocess llowed

e mnufcue o goven e new nvenoy olcy wle

lso conollng nsconl se eled o e aSN’s.

Fnlly, e new ocess needed o nege o e Erp

sysems n ode o comlee e nscon nd “ove

o y”. Ely esuls sow sgncn decese n nvenoy

usng e new ccessbly/ocess/olcy/nscon.

3. ineence (Predcve Anac)

Becuse cevng bg vsbly’s eesenon nd

ccessbly sges ve swned new nd moe esonsve

se of ocesses nd olces, comnes now ve e

oouny o genee ge level of nellgence by

comng e ncomng ocess d o e execons of

bo e ocess’ efomnce self s well s e ocess’

oucomes. inellgence s ll bou knowng wee comny

s vesus wee wns o be. pedcve nlycs ly key

ole s sge.

Cae sud: One Newok need w to 3 globl oy

mnufcue ws losng sles dung mjo oldy

sesons becuse dd no ve e eesenon o

ccessbly n ode o cee e g nellgence eled o

eles’ evenue ges, n soe/n sock levels, o dys of

suly. W One Newok’s dvnced eesenon ws

ble o model s mos mon ele’s pOS d nd un

foecs n connuous mode o undesnd wee ey

wee meeng execons bo cuen nd fuue.

lack of neence w pca reu nfoown commenar…

• DC Manaer – “inbound volume foecss e only

sen once e mon. te sysem sould genee

new foecs nfomon weneve ee s

sgncn cnge o even.”

• Buer – “i nk lnded cos s sng, bu i ve o

us lge d ses o excel o clcule ollng

wndow mecs.”

• Accounan – “Lnded cos s sown on weekly

execuve dsbod, bu e clculon gnoes DC

byss smens.”

• sore – “i ve o un fou see eos o

clcule wen ou of sock ems wll be

vlble gn.”

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4. Decon Manaemen (Precrpve Anac)

Ulmely, bg vsbly nellgence s useless unless

comny cn neu busness decson on n

ocess nd cee mesubly deen oucome. i’s

mzng ow mny mlemenons so e nellgence

sge nd jus us d no d weouse o

busness nellgence ol. te eson of couse s e

cecue sn’ desgned fo e bg vsbly ccessbly

o ocess uomon ws descbed ele. W s

decson mngemen cbly, comnes cn ke e

newly dscoveed nellgence nd neu nscons nd/

o ocesses ee se nsons o by ggng ckng

evens. Once e nellgence sows n exceon o e

execed efomnce exss, ey cn en nvoke numbe

of meods o mnge s exceon, bo w uomed

ounes nd umn nevenon nd/o collboon. tese

meods nclude escve nlycs, omzon, nd

de-o nlyss.

Cae sud: anoe One Newok cusome ( mjo CpG

mnufcue) d moved gely on s foecs eo

usng bg vsbly nellgence, bu of couse (gven no

foecs wll eve be 100% ccue) sll exeenced some

eo n ls mnue sles e self o o elensmen

smens fom e DC. One Newok gve e bly o un

ls mnue llocon omzon edsbued e

mx bsed on el me vew of soe/n sock fo evey em

on evey self, wc ws ugely benecl.

5. Oucome-Baed Merc and Performance

acevng eesenon, ccessbly, nellgence, nd

decson mngemen enbles e ges fom of bg

vsbly—oucome-bsed mecs nd efomnce. a

necessy oucome of ou evolvng suly cn newoks wll

be o mke sue we lce e g sses n e g lce

e g me n e g mouns, ll bound by el me

collboon nd bg d vsbly. included n s evoluon

wll be smulneous eos focused on ognzonl

cnge, ocess eengneeng, nd len/sx sgm ogm

mngemen.

lack of decon manaemen w pca

reu n he foown commenar…• DC Manaer – “i eceve n uomed eo wen

soe eceves con s dmged n e nvenoy

sysem. W m i suosed o do w s le?”

• Buer – “i would ke lo of me nd eo o

lwys consde cgebck ends wen ssung new

pO’s, so i only evew em befoe sesonl pO’s.”

• Accounan – “i un eo on ll cgebcks

e endng, nd en ve o eml ec sule/

buye ndvdully. i would be bee f e

les wee sysem geneed decly o e eced

es.”

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as Mcel poe oved n s wok on mke comeon,

e coce fo ny comny o emn on e fence n ems

of djusng segy bsed on foeseeble mke ss wllesul n ulme busness flue.8 tnk bou e ycl

suly cn nfsucue. Sucued negon nd

communcon vecles lke EDi en’ gong wy, bu e

bly fo e donl suly cn desgn o ec nd

esond, gven ll e nfomon nd led me delys bo

usem nd downsem, s smly no comeve. te

fequency nd dely of vlble d coss ou demnd/

suly ecosysem s gowng geomec e. ts d s

n ncedble sse nd One Newok s seen w s clens

wen s d s leveged gns n dvnced suly

cn newok deloymen s e oenl o dve u o 4% ncese n sles, 10% educon n oeng exense,

nd 30% educon n nvenoy.

Demng oned ou long go no only s von e

enemy of ocess movemen, bu you mus lso be ble o

eecvely mesue ocess o move .9 a ycl mul-

ecelon, mul-ne globl suly cn deloymen s fe

w von n cce, mesuemen nd decson mkng.

Descve nlycs s well s moe dvnced edcve nd

escve nlycs cn el o denfy oo cuse eled

o ocess von. a oely desgned wokbenc wllllow uses vous levels wn n ognzon o gn

vsbly o bo ocess efomnce nd ocess oucomes,

8. Mcel poe, “Comeve Segy: tecnques fo anlyznginduses nd Comeos”, Fee pess.

9 W. Edwds Demng, “Quly poducvy nd Comeveposon”, Mit.

s well s execue cons o move bo e ocess desgn

self nd e oucomes genees.

Von s mos lkely e bgges cuse fo oo

efomnce n ny suly cn. all ou clculons

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