Presentation_PAO Briefing 03-14-13 v5

Smarter Analytics: Predictive Asset Optimization BriefingBig Data. Real Solutions. Big Results.

Improving Operational and Financial Results through Predictive Maintenance

2013 IBM Corporation

Introductions

Jerry KurtzVice President - Industrial Sector Business Analytics and Optimization

Rollin Lovell IIIVice President IBM Client Center for Advanced Analytics

Lester McHargueBusiness Solutions - Industrial Sector Business Analytics and Optimization

Paul Hoy, CPIMGlobal Industrial Sector Executive IBM Business Analytics

Dan BarrettIndustrial Sector Solutions Leader Business Analytics

2


AgendaTopic Welcome and Kick Off IBM Center for Advanced Analytics Preventative Asset Optimization Break Predictive Asset Optimization Case Studies Predictive Asset Optimization Demonstration Lunch Predictive Asset Optimization Roadmap Discussion and Break Out Sessions Paul Hoy / Lester McHargue Dan Barrett Lead Jerry Kurtz Rollin Lovell Jerry Kurtz Time 8:45 8:45 9:30 9:30 10:45 10:45 -11:00 11:00 - 11:30 11: 30 - 12:00 12:00 1:00 Jerry Kurtz Joint Discussion 1:00 1:30 1:30 2:00

3 3



4 4


IBM Center for Advanced AnalyticsRollin Lovell IIIVice President IBM Client Center for Advanced Analytics


Business Analytics and Optimization (BAO) is a priority for IBMIBM Growth Initiatives

Gartner Global BI

Smarter Planet

Growth Markets

Business Analytics and Optimization

Gartner BI Platforms

Cloud and Next Generation Data Center

6 6


Background, Goals and ObjectivesEstablish the Why To explore analytics services associated with a centralized facility and to determine opportunities for repositioning analytical operational resources at an offsite location to meet growing client business needs Establish the What IBM has recently ventured into a first-of-a-kind partnership with The State of Ohio, Ohio State University, and other select partners in the region to announce its first dedicated advanced analytics center in Columbus, Ohio The IBM Client Center for Advanced Analytics. Establish the How The principle mission for this client center is to design, build, implement, and support differentiated analytics solutions and foster a rich environment for collaboration, innovation, and delivery by bringing together business, technical and academic communities. Address top of mind issues How is this facility different from other facilities? How does this facility advance our analytical acumen? Establish our value proposition for Clients How will the facility differentiate Client and IBM? What sets us apart from others? How can we begin? How can we make an immediate impact?

7 7


Why IBM Opened an Analytics CenterTransformed (21%) Analytic use is cultural norm Highest levels of analytics prowess and experience Seeking targeted revenue growth

Experienced (46%) Established users of analytics Seeking to grow revenue with focus on cost efficiencies Seeking to expand ability to share information and insights

Feel the most pressure to do more with analytics

Aspirational (33%) New or limited users of analytics Focused on analytics at point-of-need Turn to analytics for ways to cut costsity bil ion pa ss Ca ogre Pr8 8

Source: Analytics: The New Path to Value, a joint MIT Sloan Management Review and IBM Institute of Business Value study. Copyright Massachusetts Institute of Technology 2010.


Increasing the level of analytical sophistication allows an organization to build breakaway capabilityAnalytics Sophistication

What happened? Captured Detected Inferred How many, how often, where?

What could happen? Simulation

How can we achieve the best outcome? Optimization

Use structured and unstructured Data Numeric Text Image Audio Video

Made consumable and accessible to everyone, optimized for their specific purpose, at the point of impact, to deliver better decisions and actions through:

What exactly is the problem?

What if these trends continue? Forecasting

What actions are needed?

What will happen next if? Predictive Modelling

How can achieve the best outcome and address variability? Stochastic Optimization

Descriptive Analytics

Predictive Analytics

Prescriptive Analytics

9 9


Top performing organizations are most likely to be realizing a competitive advantage from information and analyticsThere were 3.6 respondents who self-identified as a top performing organizations who reported realizing an advantage from information and analytics for each one top performing respondent not realizing an advantage This marks a 80% increase from 2010 when the factor was 2.0 times more likely.* Top performing organizations are enabled by a solid information foundation, strong analytics skills, and top-down business-driven leadership

Competitive impact

3.6xmore likely that an organization is substantially outperforming its competitive peers if it is also realizing a competitive advantage from analyticsAmong respondents who self-assessed their organization as substantially outperforming their competitive peers, there were 3.6 respondents who self-assessed the extent of competitive advantage created by information and analytics as a [4 ] or [5 Significant extent] for every one who rated the advantage to be [1 Very little extent], [2], or [3 Keeps us on par with competitors]. n = 1015 2013 IBM Corporation

*2011 dataset Massachusetts Institute of Technology

10 10

Data Volumes are Exploding Managing the ever expanding data available about the consumer is the next great challenge and opportunity

44xas much Data and Content Over Coming Decade

2020 35 zettabytes

1 in 3 1 in 2

Business leaders frequently make decisions based on information they dont trust, or dont have

Business leaders say they dont have access to the information they need to do their jobs

2009 800,000 petabytes

80%Of worlds data is unstructured

83% 60%

of CIOs cited Business intelligence and analytics as part of their visionary plans to enhance competitiveness

of CEOs need to do a better job capturing and understanding information rapidly in order to make swift business decisions

11 11


IBM launched an Advanced Analytics Center in Columbus, Ohio in November 2012 What our customers asked forDifferentiation Differentiation

Differentiated business outcomes for Marketing/Business & IT audiences Ability to provide a cloud-based solution as a service offering Preferred destination for solution ideation through business outcome realizationdesign, build, run, & continuous improvement Early access to advanced technologies Access to accelerators, resulting in speed to realization Increased efficiencies and agile team synergies In-house Signature Solution development and expertise Collaboration and innovation via ecosystem (academia, business partners, and IBM Research) Global network of IBM Centers with broad capabilities Cross-industry, cross-function, along with industry-specific capabilities Top analytics talent with deep domain knowledge and industry expertise Increased team continuity and client understanding Competitive rates and flexible staffing models, local and non-local

Acceleration Acceleration

Collaboration Collaboration

Talent Talent

12 12


IBM launched an Advanced Analytics Delivery Center in Columbus, Ohio in November 2012 on the IBM Sterling campus Columbus 2020 is an economic development initiative based in Columbus, Ohio in conjunction with OSU and several Fortune 500 based companies in central Ohio engaged IBM to discuss the possibilities of establishing a US based Analytics Center Grand Opening Ceremony November 29th, with over 150 clients present Currently engaging a select group of Seed Clients in the Center by Q1 2013 Go-to market model is industry-driven, Center-managed, with Industry and Solution focus with SWG and GBS Key Business Driver for IBM to develop and grow BAO portfolio and talent Key element of Smarter Planet & Smarter Analytics strategy for 2013 Focus on Signature Solutions offerings Domestic delivery center for US not just for Ohio-based clients Recruiting is underway; staffing model is scalable to demand (65% Basic Analytics & 35% Advanced) One-stop-shop: Briefings Demos, Proof of Concept, Acquisition, Design, Build and Run capabilities Cross-brand investments: Signature Solutions devt teams will move to the Center Preferred rates offering the lowest BAO rates for US BAO engagements

Background Background

Strategy Strategy

Differentiation Differentiation

13 13


The IBM Client Center for Advanced Analytics has been nationally recognized by news, industry and academic communitiesSome highlights from the Centers Grand Opening in November 2012:More than 300 local government officials, agencies leaders, members of academia and business, economic trade organizations, and media attended the ribbon cutting. Featured participation from Ohio Governor John Kasich, Dr. E. Gordon Gee, President, Ohio State University, Columbus Mayor Michael Coleman and U.S. Senator Sherrod Brown with IBM SVP Mike Rhodin and Ron Lovell, VP of the Analytics Center. An AP wire photo of Ohio Governor John R Kasich and Mike Rhodin was issued and appeared in multiple online and print publications. Additional images featuring IBMers, students and faculty have also been shared online. Major media coverage, broadcast and radio appeared both locally and nationally, including the New York Times, a front page story in The Columbus Dispatch, the Associated Press -- picked up by dozens of national newspapers -- Forbes, eWeek, Advertising Age, ABC, NBC and 10TV affiliates. Smarter Planet blog posts from the OSU Fisher College Dean reinforcing the IBM partnership and need for skills. A video from Senator Sherrod Brown on IBM's leadership role in analytics and big data, along with written testimonials from federal and state legislators. Strong social media activity, reaching more than 450,000 social media followers, including tweets from U.S. Senator Rob Portman sharing the news with his 22,500 followers, WCPO-TV (16,000 followers), Innovation4Industry (13,159 followers), The City of Youngstown (4,714 followers), and OSU Fisher College (3,000 followers).

To To find find out out more, more, visit visit www.ibm.com/columbuscenter www.ibm.com/columbuscenter

14 14


The IBM Client Center for Advanced Analytics is located at IBMs Dublin (Columbus), Ohio campusIBM is enhancing its existing site with state of the art infrastructure and IT capabilities Available physical security and management mechanisms are being used to enable new members quickly (site access controls, badge access) Existing communications infrastructure (data / voice) and Center repositories will be extended in collaboration with clients Data governance, security policies and capabilities will be used to operate the Center Network security governance, security policies and capabilities will be used to manage the Centers Intranet and Internet IBMs Columbus Campus

15 15


joining a global network of IBM Advanced Analytics Centers*

The The CCAA CCAA will will be be the the first first Advanced Advanced Analytics Analytics Delivery Delivery (Design, (Design, Build, Build, Run) Run) Center, Center, Proof Proof of of Concept, Concept, Demonstration, Demonstration, Learning Learning Center Center and and can can provide provide clients clients with with a a central central point point to to link link to other Centers to other Centers16 16

*Berlin, Beijing, Dallas, Singapore, Tokyo, London, New York, Washington DC, Budapest, Vienna, and Zurich


IBM Client Center for Advanced Analytics Strategy The IBM Client Center for Advanced Analytics on the IBM Sterling campus in Columbus Ohio is a first of a kind Center whose mission is the Design, Build, Run, Proof of Concept, Demo, Briefing and Learning Center dedicated to End-to-End Analytics. The Client Center for Advanced Analytics will be focused on industry, product (both IBM and non-IBM) and solution-specific capabilities with a focus on our Signature Solutions and Business Value Accelerators (BVAs) The Center will leverage the existing IBM ecosystem. IBM Industry/Sector/Account from GBS, SWG and S&D teams will provide the entrance point for our clients into the Center. Preferred BAO rate structure and world class facilities where Clients and IBM teams collaborate in addressing clients business challenges through Advanced Analytics. Cost rates are 15% lower than standard BAO rates*. Together with 5% reduction on travel and conservatively 10% on facilities, overall client savings of 30% Global Delivery Centers, along with preferred subcontractor partnerships (e.g. ICC), will be leveraged The Center will lead the delivery of client engagements (project management and resources, US and abroad) and jointly manage delivery of client engagements from inception through completion while teaming with GBS Industry leadership

IBM Analytics Center ClientsIBM IBM Analytics Analytics Center Center S&D S&D Industry Industry Teams Teams SWG SWG Industry Industry Teams Teams GBS GBS Industry Industry Teams TeamsIBM Research Research IBM

35% Advanced / 65% Basic Analytics

FSS FSS

DIST DIST

COMMS COMMS

IND IND

PureSystems PureSystems

PUBLIC PUBLIC Global Global Delivery Delivery Centers Centers ICC ICC & & other other business business partners partners

Ohio Ohio State State & & other other academic academic institutions institutions IBM IBM SSG SSG Midwest Midwest Development Development Lab Lab

17 17


IBM Client Center for Advanced Analytics Strategy Research Globalization In-house Signature Solutions development and Analytics SW Demo capabilities for use cases and client briefings is one area of SWG & GBS collaboration Academic partnership with Ohio State will provide local talent funnel and allow IBM to influence Analytics curriculum at OSU for undergraduate and graduate degrees Team composition based on demand planning and workload types driven by Client Contracts, Signature Solutions and anticipated forecast from GBS & SWG Industry leaders The Client Engagement model can range from a multi-yr Strategic Partnership based on a jointly developed Analytics Roadmap to individual Use Cases based on clients business drivers. Center Staffing of 35% Advanced and 65% Basic Analytics work mix is based on history of analytics engagements Synergies and Collaboration with Software Group and The Midwest Development Lab who is moving product development for ECM (Enterprise Content Management), SaaS Cloud Deliver, Watson Development, Social Business-Big Data, Signature Solutions gor Business Analytics and Smarter Commerce.

IBM Analytics Center ClientsIBM IBM Analytics Analytics Center Center S&D S&D Industry Industry Teams Teams SWG SWG Industry Industry Teams Teams GBS GBS Industry Industry Teams TeamsIBM Research Research IBM

35% Advanced / 65% Basic Analytics

FSS FSS

DIST DIST

COMMS COMMS

IND IND

PureSystems PureSystems

PUBLIC PUBLIC Global Global Delivery Delivery Centers Centers ICC ICC & & other other business business partners partners

Ohio Ohio State State & & other other academic academic institutions institutions IBM IBM SSG SSG Midwest Midwest Development Development Lab Lab18 18


IBM Research Globalization

Dublin

Smarter Cities

Zurich AlmadenAnalytics Big Data Storage Nanotech Healthcare

China HaifaBig Data Analytics Security Commerce Health

Internet of Things

Watson AustinSemiconductors Processors Semiconductors Systems Software & Services

Science Nanotech Materials

IndiaServices Mobile Communications

TokyoIndustry Solutions Accessibility

Africa BrazilNatural Resources Smarter Devices Human Systems/Events Next Gen Public Sector Water & Transportation Human Capacity Development

AustraliaNatural Resources Disaster management Healthcare/Life Sciences (60% funding from govt)

IBM Research Labs IBM Research Openings in 2011 IBM Research Openings in 201219 19


Evolution of IBM ResearchThe World is Now Our Lab Joint Projects Isolated ResearchIBM Divisions, Clients, Universities Collaboratories Global Labs Columbus Analytics Center

50s 90s Hardware 90s 00s + Software & Services First-of-a-Kind Program Research Services Intellectual Property 00s + Smarter Planet

20 20


Working with ResearchJoint Development Agreements Strategic Initiatives and Big Bets

First-of-a-Kind (FOAK) IBM Research Services

Innovation Discovery

Industry Solutions Lab

Workshops

GTO Presentation

Days21 21

Months to ~1 Year

Multi-year 2013 IBM Corporation

IBM Client Center for Advanced Analytics (CCAA)Benefit to Clients Talent and industry expertise Accelerated time to value Differentiated outcomes Access to leading edge solutions US-based resources Increased collaboration & ideation Real Estate provided by IBM Network of global IBM Centers Broad scope of capabilities

IBM TeamIBM Global Business Services

IBM SolutionsStrategy Strategy & & Planning Planning Strategy StrategyWorkshop Workshop Business BusinessAnalytics Analytics& &Optimization OptimizationJumpstart Jumpstart Business BusinessAnalytics Analytics& &Optimization OptimizationRoadmap Roadmap & &Value ValueCase Case

Business Business Intelligence Intelligence & & Performance Performance Management Management Operational OperationalReports Reports Management ManagementReports Reports Dashboards Dashboards Scorecards Scorecards On-Line On-LineAnalytical AnalyticalProcessing Processing

Advanced Advanced Analytics Analytics & & Optimization Optimization Predictive PredictiveModeling Modeling& &Data DataMining Mining Optimization Optimization Simulation Simulation Content ContentAnalytics Analytics

IndustryBased

IBM Software

Enterprise Enterprise Information Information Management Management Master MasterData DataManagement ManagementSolutions Solutions Operational OperationalData DataStores Stores Data DataWarehouses Warehouses Analytic AnalyticRepositories Repositories Enterprise EnterpriseContent ContentManagement Management Information InformationLifecycle LifecycleGovernance Governance

Innovation Innovation Solutions Solutions Functional Functional Solutions Solutions Enterprise EnterpriseRisk RiskManagement Management Enterprise EnterpriseMarketing MarketingManagement Management Business BusinessProcess ProcessManagement Management Service ServiceCenter CenterSolutions Solutions Cloud CloudComputing Computing

IBM Research

Proof Proofof ofConcept Concept First Firstof ofa aKind Kind Joint JointInnovation Innovation Signature SignatureSolutions Solutions

Cross Lines of Business

Academia & Business Partners

Customer CustomerNext NextBest BestAction Action CFO CFODashboard Dashboard FAMS FAMSAnti-Fraud, Anti-Fraud,Waste, Waste,Abuse Abuse Big BigData DataSocial SocialMedia MediaAnalytics Analytics Pricing Optimization Pricing Optimization Voice Voice/ /Text Text/ /Speech SpeechAnalytics Analytics Supply SupplyChain ChainOptimization Optimization Information Management Information ManagementFoundation Foundation

Commercial Research & Innovation

22 22


Pre Defined Categories of Offerings will Simplify how Clients Engage the CenterCategory Strategy & Planning Types of Work Analytics Jumpstart Analytics Roadmap & Value Case Reports Dashboards Scorecards OLAP (On-Line Analytical Processing) Functional Solutions Data Mining & Predictive Analytics Optimization Simulation Content Analytics Big Data List of Example Projects (non-exhaustive) EDM (Enterprise Data Management) Roadmap Data Governance Business Value Assessment Big Data Strategy & Roadmap EDM Reports SOA (Service Oriented Architecture) Reporting Reporting CXO (Chief Xcross Officer) Dashboard Claims/Sales Performance Governance, Risk & Compliance Solutions (e.g., OpenPages) Customer/Marketing Analytics Fraud, Severity, Subrogation, Litigation, etc. Process Simulation Distribution/Agency Optimization Risk/Pricing/UW Analytics Text Mining/Analytics IBM Signature Solutions Big Data Solutions CIM (Customer Information Management) MDM (B2B / Business 2 Business) EDM including ETL (Extract Transform Load), DW (Data Warehouse), DM (Data Management), and OLAP Cubes Information Lifecycle Management Content Management EDM Program Management Project Management tasks associated with all listed types of work Non-deliverable based staffing of resources 2013 IBM Corporation

Basic Analytics

Advanced Analytics

Enterprise Data Management

Enterprise Data Assets (DW/DM/ODS) Analytic Cubes Master Data Management Enterprise Content Management

Program/ Project Management Staff Augmentation23 23

Program Management Project Management Staff Augmentation

IBM Smarter Analytics Signature Solutions The Center will focus on building out skills and teams around our Signature Solutions.Industry expertise and state of the art analytics applied to real world problems

How can I increase customer loyalty with every interaction?

How can I predict the impact of financial decisions?

How can I minimize losses stemming from fraud?

CustomerNext Best Action

FinanceCFO Performance Insight

FraudFraud, Waste, and Abuse

Maximize every client interaction and generate insight and loyalty

Improve financial visibility and operational effectiveness

Detect fraudulent behavior and suspicious claims

Cross-industry

24 24


The CCAA will provide cost competitive solutions with domestic resourcesRelative Resource Cost Index

The Center will provide a competitive domestic rate profile for analytics capabilities. Competitive rates, facility and travel savings translate to significant savings to clients. For certain workloads, the Center can serve as a conduit to work with Global Delivery Resources. *Productivity improvements are conservative estimates that do not account for additional productivity improvements resulting from agile center development, synergies of high performing teams, ready local interaction, travel avoidance and familiarity with clients.

Illustrative Travel & Facilities + Lower Rates 30% savings*

US Domestic Resources

Columbus Center Resources serving local clients

Offshore Resources

US-based resources Travel to Client Site

Limited Travel Agile team / Center synergy productivity

Conduit to Global Delivery Center Resources

25 25


Strategic Partnership Engagement Model based on Client Analytic Initiatives

Flex Capacity

Staffing Levels

Baseline Resource Demand

Developing Core Competencies in support of Client Analytics Initiatives

0

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

CCAA Dedicated Resources

Non-Center Flexible Staffing

26 26


Center baseline resource levels and mix will be optimized and increased based on longer-term demand signals augmented by non-Center staffing when requiredFlex Capacity

Staffing Levels

Baseline Resource Demand

Developing Core Competencies in support of both Basic and Advanced Analytics Initiatives

0

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

CCAA Dedicated Resources

Non-Center Flexible Staffing

27 27


IBM has Invested $17B for 30 Acquisitions since 2005

Optimized Business PerformanceLeverage information to better understand and optimize business performance

BI and Performance Management 2008

Business Rules and Optimization 2008

Predictive Analytic Solutions 2009

Advanced Customer Analytics 2009

National Security Services 2010

Advanced Online Web Analytics 2010

On Demand Web Analytics 2010

Integrated Risk Management 2010

Corporate Performance Management 2010

Intelligence Analytics Solutions 2011

Financial Risk & Regulatory Analytics 2011

Advanced Security Analytics 2011

Price and Promotion Optimization 2011

Supply Chain Optimization 2011

Customer Experience Management 2012

Trusted InformationEstablish accurate information for a single version of the truth, managed over timeIdentity Resolution 2005 Enterprise Data Integration 2005 Customer Data Integration 2005 Name Recognition 2006 Metadata Management 2006 Dynamic Data Integration 2007 Assets Data Discovery Software 2009 Master Data Management Solutions 2010

Integrated Data and Content ManagementManage data and content over its lifecycle and as part of processesSearch and Content Management 2005 Business Process and Content Mgmt 2006 Enterprise Data Management 2007 Real-time, Database Monitoring In Memory Data Management Solutions 2008 2009 Data and Document Capture 2010 Data Warehouse Appliances 2010 Information Governance 2010

28 28


in addition to providing services supporting all IBM Analytics products, we also provide services and support other BAO vendors as part of our broader ecosystem. Examples include.

29 29


Premier Executive Briefing Center Serving IBMs Midwest ClientsEstablish Premier Executive Briefing Center with SWG & Advanced Analytics Mission

Smarter Commerce Advanced Analytics B2B & MFT Watson Contact Center Social Business Solutions Enterprise Content Management SaaS Cloud Delivery of Industry Solutions

Refurbish existing Dublin briefing center Q1, upgrade demo facility & equipment, upgrade briefing rooms & customer reception; Cost estimate = $1M - $2M

Work is dependant on approval of RESO A&E study GBS ramp up staffing Center for Advanced Analytics

1Q13 Original plan +25 10 on board + +5 more

2Q13 +25

3Q13 +25

4Q13 +25

Current plan

+50

+50

+35

Targets & Status Press and broad based communication completed externally and internally Conduct 10 briefings per quarter in 2013 Ramp up to 20 per quarter in 201430 30


The Analytics Center is recruiting and developing the best and brightest minds in Analytics in collaboration with The Ohio State University The Ohio State University and other local academic institutions have joined the global IBM Academic Initiative program to help enhance industry and domain-specific curricula, and Co-op programs Guest lecture workshops by Senior IBM Practitioners have been arranged The academic partnership will provide a stream of analytics talent into the Center Academic Partnerships focus on the 6 Rs: 1.Research 2.Readiness 3.Recruiting 4.Revenue 5.Responsibility 6.Regions

IBM IBM has has contributed contributed $100M $100M a a year year for for the the last last five years in a row to higher education five years in a row to higher education

31 31


Analytics Degree Programs with IBM University Partnersts u ll O

Ro t n re r Cu

t en c Re

E

ed h s bli a t s

32 32


Clients Engaged

Ohio Senate Franklin County

33 33


Value PropositionWhat are the advantages for leveraging a centralized analytics center? Gains immediate access to latest technologies, analytical techniques and methods, and unique data sources Enables first mover position in the marketplace for executing new marketing, sales, and service strategies and practices Creates an acutely focused environment for incubating and testing new concepts and strategies Coordinates and organizes high producing teams around core and leading analytical skills Serves as a centralized point of contact for coordination with other offsite and offshore resources Alleviates organizational stress and distractions for executing analytical projects Provides a factory approach for sourcing, conforming and supplying data for downstream consumption

34 34


To learn more about how your organization can benefit from the IBM Client Center for Advanced AnalyticsContact your IBM representative or Visit www.ibm.com/columbuscenter

35 35



36 36


Predictive Asset OptimizationIBM Signature Solution

Jerry KurtzVice President Industrial Business Analytics and Optimization


IBM Institute for Business Value and Oxford University partnered to benchmark global big data activities. More than 1100 business and IT professionals provided a view of their big data activities.Global respondents Functional breadth

54%Business professionalsn = 1144

46%Information technology professionals

Total respondents n = 1144

38

Source: Analytics: The real-world use of big data, a collaborative research study by the IBM Institute for Business Value and the Sad Business School at the University of Oxford. IBM 2012


In IBMs recent Big Data Study, we found a variety of viewpoints regarding the definitions of Big DataDefining big data

Respondents were asked to choose up to two descriptions about how their organizations view big data from choices above. Choices have been abbreviated, and selections have been normalized to equal 100%.

Preferred Definition Big Data applications combine new sources of unstructured data with existing sources of mostly structured data to create new insights39



For most industries, Big Data pilots are focused on Customer-centric analytics. However, in the Manufacturing sector, Operational Optimization is also very popular and importantConsumer Goods Financial Services Healthcare / Life Sciences

Customercentric outcomes Operational optimization Risk / financial management New business model Employee collaboration

Manufacturing

Public Sector

Telecommunications

40



IBM Signature Solutions bring together analytic industry expertise, reusable assets and delivery skills to address highvalue client initiativesA portfolio of outcome-based analytics solutions that address the most pressing industry and functional challenges by bringing together the breadth and depth of IBMs intellectual capital, software, infrastructure, research and consulting services to deliver breakaway results.

TackleHigh-value initiativesAddress industry imperatives and critical processes

DeliverProven outcomesBuilt on a rich portfolio of analytics capabilities and IBM innovations implemented at clients worldwide

AccelerateTime-to-valueFaster return on investment with short-term projects that support the long-term roadmap

41


Predictive Asset Optimization optimizes performance and improves quality by integrating IBM IBMs industry, services, software and research expertiseSignature SolutionsCustomer Next Best Action Anti -fraud, Waste & Abuse CFO Performance Insight Predictive Asset Optimization

New Signature Solution: Predictive Asset Optimization

Monitor, maintain and optimize assets for better availability, utilization and performance Predict asset failure to optimize quality and supply chain processesCombined with user-friendly, industry dashboards, accelerators and methods

Manufacturing42

Energy and Utilities

Oil and Gas 2013 IBM Corporation

Answering the questions associated with better asset and process performanceHow can I perform in depth root cause failure analysis on my process and equipment? How can I optimize my maintenance plan? How can I detect warranty issues sooner?

?What is the life expectancy of an assets component or part? How can I predict an impending equipment failure and the cause?Asset Performance

How can do I create highest quality products?Process Integration

How can I reduce process variability?

How do I achieve optimal equipment efficiency and availability?

How can I ensure supply is aligned with demand?

43


Predictive Asset Optimization: Sample Use Cases Optimizing maintenance intervals Minimize unscheduled maintenance Warranty and Service Prognostics In-Service fleet reliability analysis Early Detection of part quality issues Early Detection of sub-system quality issues (individual + fleet-wide) In depth root cause analysis of failures

44


IBM delivers business value with extraordinary differentiation in analytics skills, products, innovation and marketplace experienceIBM Services GBS Consulting Services analytic expertise Industry expertise and proven accelerators GBS software assets including dashboards, data flows and methods

IBM Software IBM Software Products* Deep information and analytics capabilities Enterprise Asset Management capabilities

IBM Research Advanced technology and expertise Predictive analytics algorithms and techniques Real-world client implementations

Client Value Addresses critical industry imperatives Accelerates timeto-value Outcome-based approach

+

+IBM Systems and Technology

+

=

Smarter Analytics Signature Solutions bring together these capabilitieswhole is greater than the sum of its parts.45 * IBM SPSS, Cognos, InfoSphere, WebSphere, Maximo 2013 IBM Corporation

Predictive Asset Optimization analyzes data from multiple sources and provides recommended actions, enabling informed decisions

3

Conduct Root Cause Analysis

2

Generate Predictive Statistical Models

Predictive Asset Optimization Data agnostic User-friendly model creation Interactive dashboards Quickly make decisions

4

Display Alerts and Recommend Corrective Actions

Collect & Integrate Data 1Structured, Unstructured, Streaming

5

Act upon Insights

Asset Performance46

Asset Maintenance Process Integration 2013 IBM Corporation

Predictive Asset Optimization ArchitectureEnd User Reports, Dashboards, Drill Downs

Statistical Statistical Analytics Analytics (SPSS (SPSS Modeler) Modeler)DB2

Decision Decision Management Management (SPSS (SPSS DM) DM) Analytic Analytic Datastore Datastore

Business Business Analytics Analytics (COGNOS (COGNOS BI) BI)

(Pre-built (Pre-built data data schema schema for for storing storing quality, quality, machine machine and and prod prod data, data, configuration) configuration)

Industrial Industrial Enterprise Enterprise Services Services Bus Bus(Message (Message Broker) Broker)

Telematics, Telematics, Manufacturing Manufacturing Execution Execution Systems, Systems, Legacy Legacy Databases, Databases, Distributed Distributed Control Control Systems Systems47

High High volume volume streaming streaming data data(InfoSphere (InfoSphere Streams) Streams)

EAM EAM System System(Tivoli (Tivoli Maximo Maximo Tririga Tririga or or other) other)


Predictive Asset Optimization integrates Analytics Capabilities with Enterprise Asset Management (EAM) Business analytics can provide insights and actionable events to improve operational efficiencies, extend asset life and reduce costsEnterprise Asset Management Asset maintenance history Condition monitoring and historical meter readings Inventory and purchasing transactions Labor, craft, skills, certifications and calendars Safety and regulatory Requirements48

Predictive Asset Optimization

Advanced Enterprise Asset ManagementOptimized maintenance windows to reduce operating expense Efficient assignment of labor resources Minimize parts inventory Improved reliability and uptime of assets


Why choose IBMs Signature Solution: Predictive Asset Optimization? Industry Expertise Predictive models for a number of specific industry use cases

Big Data, Predictive & Advanced Analytics An enhanced advanced analytics methodology, tailored to the needs of the predictive asset/maintenance space

Accelerators Pre-configured dashboard/visualization templates Pre-integrated software tools, with connectors to a variety of asset management solutions

Talent A resource pool of highly talented advanced analytics SMES and Industry experts with Predictive Asset Optimization experience49 2013 IBM Corporation

IBM offers great value with Predictive Asset OptimizationKey Metric Maximize Maximize Revenue RevenueCompetitive Competitive Advantage Advantage High Availability Lower Start Up Costs Less Unplanned Downtime

Business BenefitProducts and Services

Value New Products and Services. Up Sell Opportunities, Higher product quality Better Asset Utilization, More Production Cycles Fewer Reworks, Fewer Installation Repairs Fewer Failures, Faster Problem Identification, Better processes Issues Cost Avoidance, Faster Root Cause, Higher equipment utilization Proactive Monitoring, Predictable Performance, Identification of factors likely to result in diminished quality Fewer Failures, Fewer Emergencies, Less need for excess MRO inventory Predictive Maintenance, Better Planning Fewer Part Failures, Shorten Issue Resolution

Cost Cost Savings SavingsIncreased Increased Reliability Reliability

Better Productivity Better Quality

Non Production Costs

O&M O&M Costs CostsIncreased Increased Efficiency Efficiency Shorter Maintenance Lower Warranty Costs

Proactive Management

Fewer Surprises, Proactive Communication More Focused Communication, Holistic View Information Integration Across Industry, Better Insight Across Silos 2013 IBM Corporation

Customer Customer Experience ExperienceIncreased Increased Satisfaction Satisfaction50

Individual Experience Better Collaboration

AgendaTopic Welcome and Kick Off IBM Center for Advanced Analytics Preventative Asset Optimization Break Predictive Asset Optimization Case Studies Predictive Asset Optimization Demonstration Lunch Predictive Asset Optimization Roadmap Discussion and Break Out Sessions Lester McHargue Dan Barrett Lead Jerry Kurtz Rollin Lovell Jerry Kurtz Time 8:45 8:45 9:30 9:30 10:45 10:45 -11:00 11:00 - 11:30 11: 30 - 12:00 12:00 1:00 Jerry Kurtz Joint Discussion 1:00 1:30 1:30 2:00

51 51


Paul Hoy, CPIM

Customer Case Studies

Global Industrial Sector Executive IBM Business Analytics


of Predictive Maintenance Predictive AssetVariations Optimization examples

53

IBM Confidential

53

Predictive Quality and Warranty Performance BMW


Case Study Overview: BMW

Customer Overview

Proven Business ValueReduced warranty cases from 1.1 to 0.85 per vehicle 5% reduction in warranty cases

German manufacturer of quality vehicles for worldwide markets Manufacturing plants in Germany and elsewhere Service / Warranty agencies worldwide

Business Challenges Needed to gain deeper insights into the causes and combinations of circumstances which led to warranty issues in each geography Needed to increase customer satisfaction through increased product quality and reduced warranty issues

Annual savings of 30m approx.

Solution ImplementedImplemented a data mining capability to gain actionable insights across a wide range of warranty issues Fed back issue findings into product design process for improvements and modified service patterns where these were demonstrated to have contributed to warranty issues

55


Predictive Maintenance: Reduce warranty claims for new cars byanalyzing historical information and vehicle data using IBM Predictive Asset Optimization (PAO). Reduced warranty costs by 5%, Repeat repairs by 50%

56


After Sales:Minimizing repeat repairs one exampleAutomated Data Mining Services using the SPSS SOA platform Automated analysis of patterns, trends and dependencies of fault memories by using e.g. correlation analysis, neural networks, logistic regression, decision trees etc. Proactive identification of systematics failures and their dependencies Significant reduction of warranty costs

Analysis based on SPSS Data Mining Platform

Example

J F M A M J J A S O N D

Cars in northern regions very often have problems with the side mirror

These anomalies to the rest of the world typically occur in the winter.

The problems occured 1-3 weeks after a service in a garage.

Reduction of warranty claims by 5% equals > 11 mio savings p.a

57 57

IBM Confidential


Predictive Quality: IBM SPSS is used in the BMW light-alloy foundry forthe production process to better understand and eliminate problems quickly.

Reduced scrap rate by 80% in 12 weeks

Recycling

not OK Cooling Processing and Testing OK Process info Database Cooling Processing Customer

Online scoring Information flow58

Material flow 2013 IBM Corporation

Case Study: Arctic Ice Flow Monitoring at Conoco Phillips

Project Objectives and Solution: ConocoPhillips wanted to increase asset utilization and reliability in the Arctic Ocean They wanted to track and forecast ice floes and icebergs to avoid drilling platform damages IBM worked with the client, utilizing real-time streaming and predictive analytics software to predict where and when ice presents a threat to existing drilling platforms The predictive analytics solution analyzes more than 1 terabyte of streaming data daily, including satellite imagery, sonar, radar, water current information, air pressure and wind velocity Business Outcomes: Produces real-time visualization of ice floe positions and trajectory cone forecasts Predictions determine whether and when to move platforms providing significant cost savings

59


Lester McHargueBusiness Solutions Industrial Business Analytics and Optimization

Predictive Asset Optimization Large / Capital Equipment Manufacturers


Capital Equipment ManufacturersManufacturers need to be able to identify potential component failure as well as machine health of in-service equipment by identifying early signs of potential downtime and enterprise component issues. The Opportunity Difficulty in separating the signal from the noise to detect enterprise component problems Unscheduled maintenance and downtime are critical issues costing the end customers from Hundreds of Thousands to Millions of Dollars per hour Most relationships with the user community if reactive in nature. Quality issues are often identified at the site.

What Makes it SmarterThis system uses a variety of Advanced Analytical techniques to monitor Time-Series Machine Data, Site Conditions and Service History to predict component well as system failure

Structured Data Process Data Alarm Data Manufacturing Data

Unstructured Content Work Orders Technical Support Warranty Claims

Business Case Early identification and mitigation of enterprisecomponent and quality issues

Monitor & Track Critical Information Implement Corrective Action Propose Corrective Actions

Provide insight to the health and probability offailure for in service equipment maximizing uptime

Sense & Measure Metrics Detect & Share Critical Issues

Establish a proactive relationship with the usercommunity to increase asset availably, reduce costs, and create new product and service offerings

Early Detection

Better maintenance planning Identification of new product and proactiveservices.

Measure & Decide on Actions 2012 IBM Corporation

61

Predictive Optimization of Assets in the Field A Large Construction Equipment Manufacturer


Predictive Asset Optimization for Heavy EquipmentMachine DataWired or Wireless

A A condition condition monitoring monitoring system system that that will: will: Combine multiple data sources associated Combine multiple data sources associated with with a a piece piece of of equipment equipment Apply predictive analytics to highlight possible problems Apply predictive analytics to highlight possible problems Utilize Utilize interpretive interpretive expertise expertise to to confirm confirm the the problem problem and and identify identify a a solution solution

Events / Trends / Payloads

Work Orders

Inspections and Fluid Samples

View 5 CM Elements and make Maintenance and Repair Recommendations

Condition Monitoring Elements1. Machine Data 2. Fluid Analysis 3. Inspections 4. Site Conditions 5. Repair History

Dealer Condition Monitoring Analyst

Off-board Analytics To Detect Slower Moving Problems

Recommendations Fed into Maintenance & Repair (M&R) Process Analysts Validate Recommendation Effectiveness 2013 IBM Corporation

63

63

Typical PAO Heavy Equipment Use CasesPriority Model Description Predict Major Component Failures 1 Business Value Machine health score used to predict impending failures Modeling Techniques Classification Models Data Sources Repair History (Dealer Source TBD), Fluid Analysis, VIMS, Events, Other Repair History (Dealer Source TBD), Events Business Questions Addressed Are there indications that a major component failure is likely to occur in the immediate future?

2

Predict Component Life Based on Specific Machine History

Understand impacts of individual low level failures, estimate component life

Regression Models

How do low level failures cumulatively affect the life span of components? What are the site specific effects? What kinds of failures are likely to occur together (e.g., failure x happens n hours after failure y, failure x is usually followed by y and z, failure x happens every n hours, when failure x happened, condition y is usually present)? What machines are behaving differently from the others in the fleet or at a site?

Identify Failures that Often Occur Together 3

Based on history, identify machines that have a high probability of experiencing similar failures

Association Models

Warranty Data, Repair History

4

Detect Anomalies within the Fleet

Detect groups of machines experiencing anomalous behavior

Clustering Models

(Trends, Fluid, Events) or Other Electronic Data Source Trends or Other Electronic Data Source

5

Utilize Statistical Process Control

Detect statistically rare conditions that bear further investigation

Runs Chart, Range Chart

What are the rules by which observed changes in electronic data will trigger alerts?

6

Predict Component Life Based on Population

Extend component life, better MARC analysis

Weibull Analysis

Warranty Data, Repair History

How can component life history data be used to make decisions about PM or PCR intervals, 2013 IBM Corporation

64

64

Capital Equipment Manufacturers -Overview of Cross-Industry Standard Process for Data Mining (CRISP-DM)The methodology include six phases: Business Understanding Data Understanding Data Preparation Modeling Evaluation Deployment The first phase, Business Understanding, is critical for successfully turning qualitative and quantitative data into valuable insights that lead to value-added actions. Phases 2 through 5 can occur in any order and almost always include multiple iterations back to the Business Understanding stage. The methodology by itself, however, does not guarantee success with advanced analytics. Success requires deep expertise and experience in evaluating and using a wide range of advanced analytical techniques.

A large equipment manufacturer saved $1 million in just two weeks by using preventive maintenance to proactively identify problems and take action before failure occurred. By minimizing downtime and repair costs across all its manufacturing operations, the manufacturer achieved a 1400% return on investment in just four months. 65 2012 IBM Corporation

Capital Equipment Manufacturers - Creating Client Value Through Integrated OperationsVisibilityIntegrated Operations Services

Prediction

Collaboration

OptimizationOthers

Production and Performance Reporting

Technical Support And Engineering

Maintenance and Service

Warranty and Quality

Collaborative Decision Making

Turnaround Optimization

Predictive Modeling & Maintenance Planning Early Event Warning

Maintenance Service Optimization Enterprise Asset Management Enterprise Document Management

Warranty Analytics

Business Solutions

Consumables Inventory Planning

Advanced Analytics and Discovery

Others

Downtime Optimization

Data Mining for Anomaly Detection

Knowledge Management

Unstructured ContentDowntime Reports Standards Maintenance Reports Trade Publications Manuals Call Logs Service Records

Real-time Data Capturing and Actuation Physical Assets66

DCS, PLCs Historians

RFID & Remote Sensing

MES Application & Facility Monitor

Engineering Equip & Process Doc


US Capital Equipment Manufacturers: A Matrix/Horizontal Approach To Analytic ValueMaintenanceReduce Downtime Better Collaboration Efficiency Asset Utilization

Production / ProcessBetter Efficiency Higher Quality Predictive Performance Holistic View

Field / Plant ServiceProduct Design New Products New Services Proactive Consistent Standards

Technical Support / EngineeringIncident Avoidance Case Reduction Case Resolution Efficiency Root Cause

WarrantyFewer Claims Part Cost Supplier Recovery Reserves

Revenue Growth: Availability, Asset Utilization, New Products, New Services, Proactive Cost Savings : Reduced Downtime, Higher Quality, Better Efficiency, Root Cause Analysis O&M Costs: Enterprise View, Fewer Emergencies, Value Based Decisions, Warranty Costs Customer Satisfaction: More Availability, Better Collaboration, Proactive Communication

Integration of Analytics Across Functional Areas Yields the Best Results67 2012 IBM Corporation

Value of Integrated AnalyticsFaster Alarm Detection Earlier Failure Prediction Proactive Improvements Enterprise Analytics Dependencies Faster Alarm Detection Earlier Failure Prediction Proactive Improvements Enterprise Analytics Dependencies Better Optimization + Next Best Action Better Asset Utilization Process Optimization Customer Impact Analysis +Value Based Decisions Better Optimization + Better Asset Utilization + Process Optimization + Customer Impact Analysis Dependencies + Better Optimization + Asset Utilization

Capability

Faster Alarm Detection Earlier Failure Prediction Proactive Improvements Enterprise Analytics Faster Alarm Detection Early Failure Prediction Proactive Improvements

ce an Fin

ly pp Su

+ Enterprise Analytic + Dependencies + Optimize

& ce an n en tio int uc Ma rod P

d an em dD an

ise pr ter ss En roce P e Tim s al s Re roce P

Alarm Detection Early Failure Prediction Reactive Improvements

Value68 2012 IBM Corporation

Some Example ResultsUse Case Provide Early Detection of factors impacting availability Provide Early Detection of Enterprise Wide component failures, impacting warranty, and asset availability. Provide Early detection of trends that impact quality and performance Provide an indication to the health of in-service equipment, and the probability of failure between maintenance windows Enable proactive customer management through better understanding of individual equipment issues69

PAO Approach Combine operational, environmental, and maintenance information to identify causal factors Integrate process, technical support, and warranty information to identify enterprise wide patterns in component failures Integrate process, technical support, and maintenance information to identify multivariate patterns that lead to poor results Integrate process, environmental, operational, maintenance, and engineering support information for a complete picture to health of an asset. Integrate process, technical support, maintenance, and warranty information to provide individualized products and services

Results Identification of the leading factors impacting up time 10 to 13 month early detection

Identification of primary and secondary causal factors 80% to 90%+ accuracy in predicting equipment downtime.

Identification and proactive delivery of products and services. Direct and through dealers 2012 IBM Corporation


70 70


Predictive Maintenance DemonstrationDan BarrettIndustrial Sector Solutions Leader Business Analytics



72 72


Predictive Asset OptimizationImplementation Methodology

Jerry KurtzVice President Industrial Business Analytics and Optimization


Predictive Maintenance ValueFinancial ImpactImproved revenue growth

Value DriversProduction

Key Performance IndicatorsCost per Ton % improvement / ton % improvement / Hour Comp replacement cost Comp Life Target Achieved Availability Index % scheduled Maintenance MTBS MTTR Maintenance Ratio Parts Ratio Average Inventory value, major components

Revenue Growth

Higher Productivity

Tons per Hour Component Rebuild Cost

Renewal Cost Maintenance Component Life Mechanical Availability Increased Up Time % scheduled Mean Time Between Stops Mean Time to Repair Maintenance cost Labor resources Parts consumption

Improved Cost position

Shareholder Value

Operating Margin

Improved Working capital position

Number of Spares Fixed Asset Fewer Spares TCO Per Spare Infrastructure Inventory

Capital EfficiencyImproved efficiency of capital outlays Reduced Risk

Dedicated Shop space Average Spare Parts / Components Inventory % field repairs Average inventory value Spare Parts / Components Inventory

Fewer Spare Parts / Components

Risk Mitigation

Safety / Compliance

74


Predictive Asset Optimizations pre-integrated solution offers flexibility to meet your companys needsFlexible DeploymentOPTION 1: BUSINESS VALUE ACCELERATORAssess Requirements2-3 Weeks

Flexible Purchases

Develop Business Case2-3 Weeks

Define Solution Roadmap1-2 Weeks

Options

Start Here

OPTION 2: SOLUTION PROOF-OF-CONCEPT or PROOF-OF-VALUEDefine and Implement Pilot6-8 Weeks

Strategy Workshop

Evaluate Pilot1-4 Weeks

Pre-configured individual products and services, or as GBS hosted solution

OPTION 3: SOLUTION IMPLEMENTATIONDefine Use Cases Establish Solution Components Conduct Solution Impact Assessment Design, Build and Deploy

75


IBM Proven Methodology: A Parallel ApproachIBM's approach is tailored to deliver immediate value via a Proof of Value (POV) application as well as provide short and long-term strategic development for initiative planning and capabilities development.

Strategy Development Develop Strategy, Initiative Roadmap & Value CaseStrategy Assessment & Development Formulize Strategy Roadmap & Value Case Strategy & Roadmap

Analytics Proof Of Value Address high-priority business challenge through advanced analytics techniquesPOV Use Case Requirements & Data Understanding POV Build Track & Evaluate POV Analytics POV

76


Patterns of organizational behavior are consistent across four stages of big data adoptionBig data adoption

When segmented into four groups based on current levels of big data activity, respondents showed significant consistency in Total respondents n = 1061 organizational behaviors Totals do not equal 100% due to rounding

77



An Analytics Strategy & Roadmap must address three componentsBusiness Capability

Business outcome based approach to define information-intensive projects Business outcomes to be achieved Initiatives include:Station Health Battery Quality Social Analytics Customer Lifecycle & Warranty Analytics Telematics Governance and Organization Big Data Architecture

Effective people and information governance structure, tools and processes Approach to Data Governance/Management Big Data / Analytics COE Design Approach to Global / Local Projects Funding approach Talent / Skill management Delivery and Support PMO78

A flexible and scalable information management foundation that leverages existing information assets One version of the truth Built to support business outcomes Scalable, leveraged model Multiple computing styles Funded by rollout of business capability/value! 2013 IBM Corporation

Illustrative Example: Business Capability

Project Prioritization Matrix

79


New analytics capabilities skills and software will be requiredAnalytics capabilities

Respondents were asked which analytics capabilities were currently available within their organization to analyze big data.

80



Sample Current State and Target State Analytics Capability Maturity ModelLong Term (36 to 48 months)

Current StateAnalytics Maturity Model

Desired Future StateAnalytics Maturity Model

Illustrative exampleOrganization & Governance Prescriptive Partner Engagement Prescriptive Organization & Governance Partner Engagement

Predictive

CMM

Portfolio Management

Predictive

CMM

Portfolio Management

Culture Descriptive/ BIPM Infrastructure & Data Technology Solutions Descriptive/ BIPM Infrastructure & Data Technology Solutions

Culture

Roadmap for ChangeNOTE: Colors denote the following maturity stages:

Roadmap for Change

Ad-hoc 81

Foundational

Competitive

Differentiating

Breakaway 2013 IBM Corporation

How to learn moreFor additional information including whitepapers and demos, please visit: IBM.com Predictive Maintenancehttp://www-01.ibm.com/software/analytics/solutions/operational-analytics/predictive-maintenance/

Smarter Predictive Analytics:http://www.ibm.com/analytics/us/en/predictive-analytics/

Smarter Analytics Signature Solutionshttp://www.ibm.com/analytics/us/en/solutions/business-need/index.html:

82



83 83


Thank You


Documents

Presentation_PAO Briefing 03-14-13 v5