Enginring Analytics Opportunity Prviw Zinnov Rport August 2013
Enginring Analytics: Prviw Agnda Dfinition Markt Siz Summary 2
Enginring Analytics: Prviw Agnda Dfinition Markt Siz Summary 3
Agnda 1 Enginring Analytics Dfinition and Ovrviw 5 Minuts 2 Enginring Analytics Us Cass and Trnds 10 Minuts 3 Enginring Analytics Bnfits 5 Minuts 4 Markt Sizing 10 Minuts 4
Enginring Analytics: Prviw Agnda Dfinition Markt Siz Summary 5
Enginring Analytics has th potntial to transform businsss across all vrticals Dfinition: Driving maningful insights by procssing information providd by physical machins Across th glob aras such as Automotiv, Arospac, Halthcar, Enrgy and Industrial us svral complx physical machins 1 2 3 Ths machins ar continuously collcting data. Th data can b 1. Machin Data (Slf Monitoring Lifcycl Paramtrs) 2. Machin to Machin Data (Communication and xchangs) 3. Contxtual Data (Basd on th nvironmnt, usrs, traffic, t al) Th data is transfrrd ral-tim or loggd and this data can b transfrrd/stord by OEMs or srvic providrs Analytics: th data collctd can b procssd, xamind and intrprtd for bttr businss dcisions Sourc: Zinnov Enginring Analytics Rport 2013 6
For th purpos of this study Zinnov has considrd 5 vrticals Arospac Th arospac industry uss ngins, on ground, wathr, flight paramtrs, ful and othr data to optimiz th flight prformanc and product nginring Industrial Th Industrial vrtical uss prssur, tmpratur, lvl and flow masurmnt snsors combind with control rlatd instrumntation to optimiz output Halthcar Th halthcar industry includs mdical dvics, patint and rmot monitoring systms and hospital managmnt systms Automotiv Th automotiv industry includs cars, trucks, buss, smi-trailrs, tractors, and construction quipmnt Enrgy Th Enrgy industry includs smart grids rlatd quipmnt such as lctronic mtrs, grid infrastructur, powr lin communication tc. This vrtical also includs oil and gas quipmnt lik drilling snsors, rsrvoir snsors tc. Sourc: Zinnov Enginring Analytics Rport 2013 7
Us Cas Arospac: OEMs us Aircraft prformanc data to prdict failur of a componnt and plan a proactiv maintnanc schdul Th data capturd from Aircraft ngin is usd to build prdictiv modls and prdict th risk of failur and forcast quipmnt failurs. Thus allowing OEMs to dvlop an appropriat maintnanc schduls, nhanc safty & asst lif and rducd costs. Data captur Connctivity Enablmnt Backnd Analytics Connctivity Enablmnt Rspons Enablmnt Through snsor nablmnt, data on ngin prformanc indicators such as ful usag, missions, acoustic data, tmpratur lvls tc. is capturd and transmittd to th cntral intllignc systm Using prdictiv analytics on capturd data, various paramtrs ar calculatd: Probability of failur of dvic Tim to failur of dvic Ful usag forcasts Emrgncy warnings and maintnanc nds ar communicatd to th MROs Sourc: Zinnov Enginring Analytics Rport 2013 and Industry Rports 8
Enginring analytics can also b dployd in an unconvntional mannr in non traditional industris Accidnt rlatd xpnditurs account ~10% of a Canada basd lumbr a company s total rvnu. Th company dployd a combination of hardwar and softwar to hlp mitigat costs and stablish a saf working nvironmnt Data Captur Data Communication Ral Tim Data Analysis Rspons Communication Appropriat Rspons No Potntial Hazard Potntial Hazard Th data about workr location, tr hight and surfac ara, wind spd chainsaw proximity to a prson tc. is capturd through a multitud of snsors Th cntral systm intgrats and analyss th data and th risk for injury and dath is prdictd. Bas on this an appropriat rspons is communicatd Workr standing in th rang of falling tr Running chainsaw dangrously clos to any workr Th chainsaw is dactivatd if th thrat of an accidnt is dtctd Sourc: Zinnov Enginring Analytics Rport 2013 and Industry Rports 9
Th potntial application of nginring analytics is almost limitlss and will xpand as tchnology volvs Vhicls in th futur will communicat with ach othr and with traffic infrastructur to improv safty, traffic fficincy and provid a richr driving xprinc to th drivr V2V (Vhicl to Vhicl) communication V2I (Vhicl to Infrastructur) Communication q Through snsor and communication nablmnt vhicls will b abl to sns ach othr and xchang data with narby vhicls to track ach othr s actions and provid: V-2-V distanc proximity warning Intllignt cruis control Intllignt brak assist Suddn halt warnings Lan chang warnings V2I data form xtrnal traffic infrastructur can hlp th vhicls improv th driving xprinc for th usr by hlping thm : Finding parking spacs Avoiding congstd roads Avoid damagd roads Drivrlss Highways With intgration of V2V and V2I communication, th vhicl intllignc systm will on day b abl to autonomously driv th car to nsur: Bttr spac utilization on th road by optimizing th intr vhicl gap Safr and fastr travl by optimizing vhicl rout Improv nrgy fficincy by optimizing ful usag Sourc: Zinnov Enginring Analytics Rport 2013 and Industry Rports 10
Mga Trnds and Ky Tchnology driving Enginring Analytics Mga Trnds Incrasd Dmand: Th growing and aging population is putting a strain on utilitis providrs, hospitals and transport infrastructur du to th incrasd dmand Era of Prsonalization: Businsss ar moving from th on-siz-fits-all product approach to th prsonalization of products for individual customrs Analytics as a Diffrntiator: Th incrasd comptition has drivn businsss to look for diffrntiators and analytics is nabling thm to improv dcision making, minimiz risks, and driv quality & fficincy Enrgy Efficincy is Ky: Growing dmand and thinning rsourcs has ld to an nrgy conscious consumr forcing companis to focus on building lan and fficint products Ky Tchnology Trnds Incrasd Dploymnt of Snsors: Snsors ar incrasingly finding thir way into multipl systms and ar gnrating data that can b usd to gain actionabl insights Cloud Computing: Cloud computing has sn an incrasd adoption among organizations ovr th past fw yars, owing to lowr infrastructur costs, incrasing connctivity and nd for bttr scalability of storag Big Data: Th volum and vlocity of data capturd has grown xponntially ovr th last fw yars. Tchnological advancs hav allowd companis to lvrag big data platforms to mak informd dcisions. In Mmory Computing: On th chip procssing, with prformanc 10,000 tims fastr than standard disks, has nabld ral tim analysis of larg data strams Improvd Bandwidth: This has nabld ral tim transmission of larg volums of data across distant locations Sourc: Zinnov Enginring Analytics Rport 2013 and Industry Rports 11
Enginring Analytics: Prviw Agnda Dfinition Markt Siz Summary 12
Th bnfits of Enginring Analytics (EA) adoption broadly fall undr two catgoris viz. Incrasd Rvnu and Improvd Efficincy Bnfits of EA Adoption EA can hlp companis improv thir top lin in multipl ways: Improvd customr undrstanding Nw businss opportunitis Rducd tim to markt Othrs Incrasd Rvnu Sourc: Zinnov Enginring Analytics Rport 2013 Th largst impact of EA will b in th form of fficincy improvmnts across vrticals through: Stramlining of supply chain Improvd asst utilization Rducd maintnanc cost Othrs Improvd Efficincy 13
Improvd Rvnu: Thr ar numrous aspcts across which companis can bnfit through th adoption of nginring analytics (1/5) I n c r a s d R v n u Improvd Customr Exprinc Enginring analytics can hlp companis improv thir customr xprinc, lading to highr liftim valu of customr, improv markt shar and brand loyalty Individualizd Cars: Enginring analytics can nabl automobil companis to track and stor usr prfrncs and driving pattrns for vry individual customr and thus crat a usr profil rpository. Lowr Ful Economy: Companis can customiz cars basd on individual driving pattrns to achiv optimal ful consumption Prdicting customr nds: Companis can prdict customr nds basd on historic us pattrns and crat cars that bttr fit thir nds Crating a loyal bas: Companis offring individualizd cars will attract mor customrs and crat highr switching barrirs Gtting mor out of lss: Enginring analytics will nabl customr to gain mor utility out of fwr componnts. Mobil dvics will connct with homs and turn on lights and opn doors basd on GPS data Clothing could monitor customr s halth and xrcis trnds to nabl th warr to track thir prsonal fitnss milstons Cars could provid instant insuranc quots and warn mrgncy srvics in cas of accidnts Plans could warn passngrs of dlays du in ral tim without pilot intrvntion Sourc: Zinnov Enginring Analytics Rport 2013 and Industry Rports 14
Improvd Rvnu: Thr ar numrous aspcts across which companis can bnfit through th adoption of nginring analytics (2/5) I n c r a s d R v n u Nw Businss Modls & Opportunitis Enginring analytics will chang how companis do businss and additionally gnrat many nw opportunitis for rvnu nhancmnts: Nw Businss Modls: Snsor nablmnt allowd th aircraft ngin manufacturrs to com up with a Powr by th Hour businss modl whr airlins pay for th thrust thy usd pr flying hour. Similar nw businss modls ar xpctd to prolifrat with incrasing adoption of nginring analytics. As ral tim dtction of a potntial customr s propnsity to purchas bcoms rality, rtail businsss will hav to volv to tak this into account Insuranc companis ar alrady bginning to pric policis basd on drivr usag trnds basd on snsor data from cars. This modl will s adoption in ship / rail and vn prsonal insuranc Nw Opportunitis: Th scop of nginring analytics is almost limitlss and will xpand as tchnology improvs. This will opn doors to multipl opportunitis: Enabling citis to bcom smartr - from snsors that inform motorists of availabl parking slots to lctrical grids that adapt to dmand to bttr utilitis planning Mdical patchs/implants that can dtct vital signs, diagnos illnsss and administr mdicin autonomously Enabling cars to bcom safr through snsor and connctivity nablmnt Allowing insuranc companis and othr lgal ntitis to dtrmin at fault party for vhicl accidnts through a combination of vhicl to vhicl and vhicl to infrastructur data Sourc: Zinnov Enginring Analytics Rport 2013 and Industry Rports 15
Improvd Efficincy: Thr ar numrous aspcts across which companis can bnfit through th adoption of nginring analytics (3/5) I m p r o v d E f f i c i n c y Stramlining of Supply Chain Enginring analytics can hlp companis stramlin thir supply chain and logistics through improvd connctivity and smart dploymnt of snsors: Eliminating Wast: Wast in th supply chain rsulting from ordring rrors and communication brakdown can b significantly rducd through dploymnt of intllignt infrastructur/machins that continuously communicat with ach othr. Smart Manufacturing: Machins that manufactur componnts can track invntory lvls and automatically inform supplirs. Such machins can nabl Just in Tim invntory practics with littl to no human intrvntion. Smart Supplirs: Supply trucks can automatically communicat with th machins in th factory giving ral tim information about th dlivry tim. Supplirs with such infrastructur in plac will automatically b prfrrd ovr othrs. Complx Evnt Procssing(CEP): CEP is incrasingly bing utilizd by many B2B logistics companis to tackl procss infficincis. CEP systms ar bing usd for schduling and dlay calculations. Ths systms can calculat dlays causd by vnts such as missd flights to accuratly prdict th nw dlivry tim and communicat this to th dlivry location. Such systms tak into account complx chain of vnts to arriv at an accurat valu. With improvd M2M communication plans will b abl to communicat with such systms in ral tim thus making prdictions with pin point accuracy possibl Sourc: Zinnov Enginring Analytics Rport 2013 and Industry Rports 16
Improvd Efficincy: Thr ar numrous aspcts across which companis can bnfit through th adoption of nginring analytics (4/5) I m p r o v d E f f i c i n c y Improvd Asst Utilization Improvd asst utilization du to nginring analytics can significantly impact fficincy and bring costs down for companis and nd usrs: Smart Factoris: Enginring analytics can hav a significant impact on various aspcts of manufacturing through th dploymnt of snsors, analytics and connctivity. Machin Condition Monitoring: Snsor nablmnt of critical machins allows for logging of oprations and prformanc paramtrs. This data nabls oprators to undrstand th prcis condition of th machin and its componnts. Prdictiv analytics: Prformanc and oprations data loggd ovr tim across multipl machins of th sam typ along with prdictiv analytics can nabl oprators to anticipat componnt failurs and hlp significantly rducing machin downtim Across Vrticals: Similar bnfits can b drivd from th dploymnt of nginring analytics across othr vrticals. Halthcar: Mdical dvics, patints and hospital infrastructur can b linkd to stramlin hospital oprations to rduc wait tims and improv asst utilization Arospac: Conncting aircraft prdictiv maintain systms with part supplirs, MRO companis and transportation companis can significantly rduc aircraft s maintnanc ground tim Enrgy: Currntly th utilization of transformrs at distribution substations is only 40 prcnt. Smart grids will provid th control and information ndd by oprators to incras th loading of undr utilizd assts Sourc: Zinnov Enginring Analytics Rport 2013 and Industry Rports 17
Othrs: Thr ar numrous aspcts across which companis can bnfit through th adoption of nginring analytics (5/5) E f f i c i n c y Rducd Maintnanc Costs Enginring analytics has th potntial to significantly rduc maintnanc costs in th automotiv and th aviation industry through: Prdictiv maintnanc Connctd OEM supplir, MRO and flt can significantly rduc aircraft down tim Employ productivity can also b significantly impactd through th us of nginring analytics as: Automation can nabl a smallr workforc can handl mor work Improvd Productivity R v n u Improvd Tim to Markt Enginring analytics can hlp companis to incras markt shar and improv rvnus by: Lvraging historic product dvlopmnt knowldg combind with analytics to rduc tim to markt Sourc: Zinnov Enginring Analytics Rport 2013 and Industry Rports 18
EA rlatd bnfits ar currntly stimatd to b clos to 250 billion USD and ar xpctd to ris to narly 500 billion USD by 2017 Du to th natur of EA th valu of bnfits from improvd fficincy ar gratr than thos of incrasd rvnu ~501 Billion USD ~149 Billion USD ~247 Billion USD ~98 Billion USD Improvd Efficincy Incrasd Rvnu 2012 2017 Potntial Bnfits From Enginring Analytics (EA) Adoption (2012-2017) Sourc: Zinnov Enginring Analytics Rport 2013 and Industry Rports Enginring Analytics (EA) Markt Activity Split 19
Ths bnfits rprsnt a potntial opportunity for OEMs, Tir I Supplirs and Srvic Providrs Savings 247 billion USD rprsnts th currnt potntial savings for nd customrs lik Lufthansa, Shll, Pacific Gas & Elctric, Johns Hopkins Hospital tc. across 5 factors through EA adoption Ths savings ar calculatd basd on currnt adoption rat of nginring analytics which is assumd to b vry low Opportunity Ths saving rprsnts th potntial opportunity that can b addrssd by th various OEMs, Tir I supplirs and srvic providrs across th 5 vrticals This opportunity includs: Nw product and systms sals: Rvnu from sals of nw EA products and EA systms to nd customrs to hlp stramlin thir oprations Brownfild upgrads: Rvnus from th upgrads of xisting clint systms to mak thm EA compliant Outsourcing: Rvnu for srvic providrs from th outsourcing by OEMs and Tir 1 supplirs Projctions As th adoption rat incrass xponntially ovr th nxt 5 to 10 yars th saving ar xpctd to grow at a similar fast pac Th savings ar xpctd to rach mor than 500 billion USD by 2017 Sourc: Zinnov Enginring Analytics Rport 2013 20
To addrss this opportunity or rduc spnding OEMs, supplirs and nd customrs ar currntly spnding clos to 13 billion USD on EA rlatd products and srvics Systm Intgration Enginring Analytics Enginring spnding maks up for th majority of th EA markt ~27 Billion USD Enginring 7.1 Billion USD ~12.6 Billion USD Analytics Infrastructur 2.4 Billion USD Analytics Srvics 1.3 Billion USD Systm Intgration 1.8 Billion USD 2012 2017 EA Total Industry Spnding Projction (2012-2017) Sourc: Zinnov Enginring Analytics Rport 2013 Enginring Analytics (EA) Markt Activity Split 21
Enginring spnding maks up for narly 60 prcnt of th ovrall EA rlatd spnding 12.6 billion USD rprsnts th currnt spnding by OEMs, Tir I and End Customrs rlatd to EA products Spnding This spnding can b classifid into thr catgoris: Enginring spnding: This rprsnts th invstmnts* mad by OEMs and Tir I supplirs on trying to addrss th potntial opportunity w spok of bfor Analytics Spnding: This includs th total spnding on analytics including: Analytics infrastructur: Spnding by OEMs and End Customrs on Analytics infrastructur such as data warhousing,s/w licnsing, S/W maintnanc Analytics Srvics: Spnding by OEMs and End customrs on analytical srvics and consulting Systm Intgration Srvics: Spnding by End customrs on systm intgration srvics of EA componnts Projctions & Insights Total spnding is xpctd to incras to ~27 billion USD by 2017 drivn by an xpanding EA markt Enginring spnding forms th major componnt of th total spnding in 2012 and is xpctd to rmain high as OEMs and Tir I supplirs try to addrss a fast growing ovrall markt Not: *Spnding on activitis such as rsarch, NPD, product improvmnts tc. for EA spcific products Sourc: Zinnov Enginring Analytics Rport 2013 22
Industrial vrtical forms th largst part of th nginring analytics spnding du to larg nginring and SI spnding Total EA Spnding Across Vrtical Sizs Industrial CAGR # 17% ~3.9 Billion USD Enrgy CAGR # 23% ~3.2 Billion USD Automotiv CAGR # 14% ~2.1 Billion USD Halthcar CAGR # 21% ~1.8 Billion USD Arospac CAGR # 12% ~1.7 Billion USD CAGR # - Compound annual growth rat from 2012 to 2017 Sourc: Zinnov Enginring Analytics Rport 2013 23
Th biggst opportunity for Srvic Providrs lis in EA product nginring for th OEMs and Tir 1 supplirs EA Spnding Contribution End Customr OEMs Tir 1 Supplirs Enginring $7.1 Billion Analytics $3.7 Billion Systm Intgration $1.8 Billion Srvic providr EA addrssabl markt Enginring Analytics Analytics Srvics Analytics Infrastructur Systm Intgration Total Spnding $7.1 Billion $1.3 Billion $2.4 Billion $1.8 Billion 50.7% 99.2% ~0% 35.7% SP addrssability Addrssabl Markt $3.6 Billion $1.3 Billion Nil $0.5 Billion Sourc: Zinnov Enginring Analytics Rport 2013 Spnd Contribution Vry High High Mdium Low Vry Low 24
Narly 45 prcnt of th ovrall EA spnding by OEMs, supplirs and nd customrs is addrssabl by srvic providrs Systm Dvlopmnt maks up for th majority of th addrssabl EA markt Systm Dvlopmnt ~57 % Systm Intgration ~22 % Managd Srvics ~21 % ~14.8 Billion USD ~5.4 Billion USD Systm Dvlopmnt Systm Intgration Managd Srvics 2012 2017 EA Addrssabl Markt Siz Projction (2012-2017) Sourc: Zinnov Enginring Analytics Rport 2013 Addrssabl Enginring Analytics (EA) Markt Activity Split 25
PES rlatd activitis within systm dvlopmnt forms th largst part of th addrssabl markt Addrssabl Markt Opportunity Th addrssability of th spnding by OEMs, Tir I and End Customrs is calculatd with rspct to vry vrtical basd on an AHP basd approach and th total addrssabl markt siz is drivd Basd on Zinnov calculations narly 45 prcnt of th ovrall spnding is addrssabl by srvic providrs Th addrssabl markt is split into 3 componnts: Systm dvlopmnt: Rfrs to assisting OEMs and Tir I supplirs with PES activitis around nw EA products, EA product upgrads and nd of lif EA products Systm Intgration: Rfrs to assisting End Customrs with systm intgration of EA componnts within th Procss and Plant Enginring srvics Managd srvics: Rfrs to taking ovr complt rsponsibility of crtain activitis from EA OEMs and Tir I supplirs rlating to EA rlvant products Projctions Th addrssabl markt for srvic providrs is xpctd to almost tripl to 14.8 billion USD by 2017 This growth will b drivn prdominantly du to incrasd spnding by OEMs and Tir I supplirs as wll as incrasd adoption by nd customrs Sourc: Zinnov Enginring Analytics Rport 2013 26
Enrgy is th largst vrtical of th addrssabl EA markt du to highr addrssability of nginring spnding ovr that of Industrial vrtical Total Addrssabl Enginring Analytics Markt Vrtical Sizs Enrgy CAGR # 22.4% ~1.4 Billion USD Industrial CAGR # 18% ~1.4 Billion USD CAGR # 13.9% ~1.1 Billion USD Automotiv Halthcar CAGR # 21.8% ~0.8 Billion USD Arospac CAGR # 14.8% ~0.7 Billion USD CAGR # - Compound annual growth rat from 2012 to 2017 Sourc: Zinnov Enginring Analytics Rport 2013 27
Enginring Analytics: Prviw Agnda Dfinition Markt Siz Summary 28
Summary Enginring analytics is about driving maningful insights by procssing information providd by physical machins Enginring Analytics Th Enginring Analytics valu chain ncompasss th snsors that gnrat th information, ntworks that transmit it and softwar that procss it Th potntial applications of nginring analytics ar almost limitlss and will xpand as tchnology volvs. In th futur EA will affct consumrs in ways w cannot vn imagin. Th potntial bnfits to companis form Enginring Analytics ar currntly stimatd to b clos to 250 billion USD and ar xpctd to ris to narly 500 billion USD by 2017 OEMs, supplirs and nd customrs ar currntly spnding clos to 13 billion USD on EA product nginring, analytics and systm intgration Markt Siz Th addrssabl markt for srvic providrs is xpctd to almost tripl to 14.8 billion USD by 2017 from its currnt siz of 5.4 billion USD Th Industrial and th Enrgy vrticals witnss th largst EA rlatd spnding and also hav th largst addrssabl EA markt with rspct to srvic providrs Sourc: Zinnov Enginring Analytics Rport 2013 29
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