1 Big Data " A Dwsing Rd t Lcate Innvatins?! Markus Breunig & Gdehard Gerling! Hchschule Rsenheim und g3cnsulting PartG!
2 Mdern Dwsing Rds pure High-Tech!! Ft:%augsburger-allgemeine.de%
3 Big Data is...!...like teenage sex: everyne talks abut it, nbdy really knws hw t d it, everyne thinks everyne else is ding it, s everyne claims they are ding it. (Dan Ariely n his facebk page)! Ft:%telegraph.c.uk%
4 Agenda! Recap - Big Data! Three Hrizns f Innvatin & Big Data! Methdical Appraches fr the Individual Hrizns! Incremental! Adjacent! Disruptive! Cnclusins!
5 Vlume' GB,'TB'r'PB' Recrds/Transac<ns' Tables/Files' Velcity' Batch' NearA/RealA<me' Streaming' 3'Vs'' f'' Big'Data' Structured' SemiAStructured' Unstructured' Variety'
6 Big Data & Business Mdel Innvatin! Impact% Type'f' Innva<n:' Management' Objec<ve:' Tls'&' Methds:' Incremental% Adjacent% Radical%-%Disrup=ve% Efficiency,% DDD% Scre%Cards,% Cckpits% Op=miza=n% Canvas%Mdeling,% 10-Types% Innva=n% Business%Transfrma=n% Ethngraphic,%Explratry,% Agile%Prject%Management%
7 Big Data & Business Mdel Innvatin:" Incremental Innvatin! Impact% Type'f' Innva<n:' Management' Objec<ve:' Tls'&' Methds:' Incremental% Adjacent% Radical%-%Disrup=ve% Efficiency,% DDD% Scre%Cards,% Cckpits% Op=miza=n% Canvas%Mdeling,% 10-Types% Innva=n% Business%Transfrma=n% Ethngraphic,%Explratry,% Agile%Prject%Management%
8 Incremental Innvatin: " Optimizing the existing Business! Phase%1% Imprving' the' Reprts' Phase%2% Bs<ng' the' Insights' Phase%3% Advancing' the' Gals' Which%reprts%are% currently%used%t%mnitr% the%business?% (Hw)%can%Big%Data% imprve%the%accuracy%f% the%numbers%in%these% reprts?% Which%ques=ns%d%the% recipients%f%the%reprts% answer%based%n%these% reprts?% (Hw)%can%these%ques=ns% be%answered%bexer%using% Big%Data?% Which%gals%d%the%reprt% recipients%pursue%by% asking%these%ques=ns?% (Hw)%can%these%gals%be% supprted%bexer%using%big% Data?%
9 Big Data & Business Mdel Innvatin:" Adjacent Innvatin! Impact% Type'f' Innva<n:' Management' Objec<ve:' Tls'&' Methds:' Incremental% Adjacent% Radical%-%Disrup=ve% Efficiency,% DDD% Scre%Cards,% Cckpits% Op=miza=n% Canvas%Mdeling,% 10-Types% Innva=n% Business%Transfrma=n% Ethngraphic,%Explratry,% Agile%Prject%Management%
10 Wh are ur Key Partners? Wh are ur key suppliers? Which Key Resurces are we acquairing frm partners? Which Key Activities d partners perfrm? mtivatins fr partnerships Optimizatin and ecnmy Reductin f risk and uncertainty Acquisitin f particular resurces and activities What are the mst imprtant csts inherent in ur business mdel? Which Key Resurces are mst expensive? Which Key Activities are mst expensive? is yur business mre Cst Driven (leanest cst structure, lw price value prpsitin, maximum autmatin, extensive utsurcing) Value Driven (fcused n value creatin, premium value prpsitin) sample characteristics Fixed Csts (salaries, rents, utilities) Variable csts Ecnmies f scale Ecnmies f scpe The makers f Business Mdel Generatin and Strategyzer What Key Activities d ur Value Prpsitins require? Our Distributin Channels? Custmer Relatinships? Revenue streams? catergries Prductin Prblem Slving Platfrm/Netwrk What Key Resurces d ur Value Prpsitins require? Our Distributin Channels? Custmer Relatinships? Revenue Streams? types f resurces Physical Intellectual (brand patents, cpyrights, data) Human Financial This wrk is licensed under the Creative Cmmns Attributin-Share Alike 3.0 Unprted License. T view a cpy f this license, visit: r send a letter t Creative Cmmns, 171 Secnd Street, Suite 300, San Francisc, Califrnia, 94105, USA. What value d we deliver t the custmer? Which ne f ur custmer s prblems are we helping t slve? What bundles f prducts and services are we ffering t each Custmer Segment? Which custmer needs are we satisfying? characteristics Newness Perfrmance Custmizatin Getting the Jb Dne Design Brand/Status Price Cst Reductin Risk Reductin Accessibility Cnvenience/Usability What type f relatinship des each f ur Custmer Segments expect us t establish and maintain with them? Which nes have we established? Hw are they integrated with the rest f ur business mdel? Hw cstly are they? examples Persnal assistance Dedicated Persnal Assistance Self-Service Autmated Services Cmmunities C-creatin Thrugh which Channels d ur Custmer Segments want t be reached? Hw are we reaching them nw? Hw are ur Channels integrated? Which nes wrk best? Which nes are mst cst-efficient? Hw are we integrating them with custmer rutines? channel phases 1. Awareness Hw d we raise awareness abut ur cmpany s prducts and services? 2. Evaluatin Hw d we help custmers evaluate ur rganizatin s Value Prpsitin? 3. Purchase Hw d we allw custmers t purchase specific prducts and services? 4. Delivery Hw d we deliver a Value Prpsitin t custmers? 5. After sales Hw d we prvide pst-purchase custmer supprt? Fr what value are ur custmers really willing t pay? Fr what d they currently pay? Hw are they currently paying? Hw wuld they prefer t pay? Hw much des each Revenue Stream cntribute t verall revenues? types Asset sale Usage fee Subscriptin Fees Lending/Renting/Leasing Licensing Brkerage fees Advertising fixed pricing List Price Prduct feature dependent Custmer segment dependent Vlume dependent dynamic pricing Negtiatin (bargaining) Yield Management Real-time-Market Fr whm are we creating value? Wh are ur mst imprtant custmers? Mass Market Niche Market Segmented Diversified Multi-sided Platfrm Adjacent Innvatin: " Optimizing the business mdel! The Business Mdel Canvas Designed fr: Designed by: Date: Versin: Key Partners Key Activities Value Prpsitins Custmer Relatinships Custmer Segments Key Resurces Channels Cst Structure Revenue Streams! Business%Mdel%Canvas%! Itera=ve%&%Incremental% designed by: Business Mdel Fundry AG strategyzer.cm Business% Mdel%! Dblin s%10-types%
11 Alexander Osterwalder: " Business Mdels can be Described in 9 Key Aspects! Surce:businessmdelgenera=n.cm%
12 Keely s 10 Types f Innvatin can be Matched t Key Aspects f Business Mdels! Result f investigating > 3000 innvatins! Cmbinatins f types may be present in any innvatin! Successful & sustainable innvatins " cmbine > 3.5 innvatin types! cf.%keely,%l.%et%al.%ten%types%f%innva=n.%new%yrk:%wiley;%2013.!
13 Each Innvatin Type is Cmprised f " Multiple Innvatin Tactics (112 in Ttal)! cf.%keely,%l.%et%al.%ten%types%f%innva=n.%new%yrk:%wiley;%2013.!
14 We have Identified the Data-Driven Innvatin Tactics! (Example: 1 st Fur Types f Innvatin)! Prfit Mdel" " Netwrk" Structure" Prcess" AdASupprted' Auc=n% Bundled'Pricing' Cst%Leadership% Disaggregated'Pricing' Financing% Flexible'Pricing' Flat% Frced'Scarcity' Freemium' Installed%Base% Licensing% Membership' Metered'Use' Micrtransac=ns% Premium% Risk%Sharing% Scaled%Transac=ns% Subscrip<ns' Switchbard' UserADefined' Alliances% Cllabra=n% Cmplementary% Partnering% Cnslida=n% Cpera=n% Franchising' Merger/Acquisi=n% Open%Innva=n% Secndary%Markets% Supply'Chain'Integra<n Asset%Standardiza=n% Cmpetency%Center% Crprate%University% Decentralized% Management% Incen<ve'Systems' IT%Integra=n% Knwledge%Management% Organiza=nal%Design% Outsurcing% Crwdsurcing% Flexible'Manufacturing' Intellectual%Prperty% Lean%Prduc=n% Lcaliza=n% Lgis=cs%Systems% OnADemand'Prduc<n' Predic<ve'Analy<cs' Prcess%Autma=n% Prcess%Efficiency% Prcess%Standardiza=n% Strategic%Design% User-Generated% Surce:%dblin.cm%
15 Data-Driven Innvatin Tactics Examples! Prfit Mdel" Bundled Pricing! Sell$in$a$single$transac-n$ tw$r$mre$items$that$ culd$be$sld$as$standalne$ fferings.$ Iden<fy'items't'bundle' based'n'data'analysis.' Predict'the'resul<ng' changes'in'revenue.' Analyze'the'resul<ng' changes'in'revenue.'' Prduct Perfrmance" Feature Aggregatin! Cmbine$a$number$f$ exis-ng$features$frm$ disparate$surces$int$a$ single$ffering.$ Analyze'which'features'are' mstly'used'tgether'in'the' disparate'surces.'predict' changes'in'usage.'analyze' changes'in'feature'usage/ revenue/prfit.' Service" Lyalty Prgrams! Prvide$benefits$and/r$ discunts$t$frequent$and$ Cmpute'the'frequent/ highavalue'custmers.' Analyze'usage'f'the' prduct'by'these' custmers.'decide'which' incen<ves't'ffer.'mdel' cst/prfit'changes.'
16 Big Data & Business Mdel Innvatin:" Radical - Disruptive! Impact% Type'f' Innva<n:' Management' Objec<ve:' Tls'&' Methds:' Incremental% Adjacent% Radical%-%Disrup=ve% Efficiency,% DDD% Scre%Cards,% Cckpits% Op=miza=n% Canvas%Mdeling,% 10-Types% Innva=n% Business%Transfrma=n% Ethngraphic,%Explratry,% Agile%Prject%Management%
17 Disruptive Innvatin: Develp new Business Mdels centered n Custmers and their Behaviur! Prttyping is Part f a Design Prcess 3 Stages f Prttyping! Design%Thinking% EMPATHIZE EMPATHIZE INSPIRE IDEATE IDEATE DEFINE DEFINE EVOLVE PROTOTYPE PROTOTYPE # f Prttypes TEST TEST! X-Func=nal%Team% Embrace failure Build culd t think What be Lw reslutin Expect changes Experiment What shuld be Targeted mdels VALIDATE Manage Changes Whattwill be Build spec. Integrated Mdels Stanfrd Innvatin Masters Series 10 (frm Mggridge) Stanfrd Innvatin Masters Series Custmer%The Exercise Nt Just fr Prducts The Task: Get the ball frm the tp f! the Itera=ve%&%Incremental% table int the basket as many times as pssible in 45 secnds, subject t the rules! Custmer%Jurney% Interactins Rll up yur sleeves and Prttype! Spaces Experiences 11
18 Custmer/User Jurneys " Serve as the Fundatin fr New Insights! Persna% Observable%Behaviurs% Surce%1% Surce%2% %Surce...% % Data% Surces% Data%
19 Design Thinking Prvides a Structured Discvery and Imprvement Prttyping is Part Prcess! f a Design Prcess EMPATHIZE IDEATE DEFINE PROTOTYPE TEST # f Prttypes The current brader use f the term Design Thinking dentes an interdisciplinary apprach t prblem slving based n radical cllabratin. It prmtes hands-n research (bservatins, enquiries, interviews, self-experiments), ethnlgical (v. statistical) methds, varius ideatin techniques (brainstrming, sketching, prttyping), and repeated user and reality feedback by way f prttypes t iteratively refine an apprach r a slutin. Design Thinking is biased twards actin. It wrks under Stanfrd the Innvatin assumptin Masters Series that all 10design activities (frm M are ultimately scial in nature and that making ideas and cncepts tangible will imprve the discussin en rute t slving a prblem.! Nt Just fr Prducts
20 X-Functinal Team - Cmpetence Prfiles"! Business'!%Scre%Cards%!%Canvas%Mdeling% %%%%%10-Types%!%Design%Thinking% Hw%t%use%which% data%mst%beneficial% t%further%my% business%mdel?%! Hadp%Ecsystem%! Clud%Strage%! Sta=s=cs%! Data%Mining% What%can%be% inferred%frm% the%data%using% which% algrithm?% Hw%and%where% will%the%data%be% cllected,%stred% and%prcessed?% % Data'Scien<sts' IT/Infrastructure'
21 Big Data & Business Mdel Innvatin! Impact% Type'f' Innva<n:' Management' Objec<ve:' Tls'&' Methds:' Incremental% Adjacent% Radical%-%Disrup=ve% Efficiency,% DDD% Scre%Cards,% Cckpits% Op=miza=n% Canvas%Mdeling,% 10-Types% Innva=n% Business%Transfrma=n% Ethngraphic,%Explratry,% Agile%Prject%Management%
22 Cnclusins!!! Innvatin can be mdeled in 3 hrizns Big Data can be instrumental in all 3 f them! " DDD Adjacent Innvatin Structured Disruptin! Each hrizn requires a specific apprach! Success results frm a structured cmbinatin f well-established innvatin methds and Big Data!!
23 Thank yu fr yur attentin!! Prf. Dr. Markus Breunig! " Gdehard Gerling! "