19
IBM IOD 2012 10/24/2014 Drury Design Dynamics 1 Transforming your Enterprise to Get Value from Big Data and Analytics: How to Get Started Session # 6371 Douglas Dow & Emily Plachy October 27, 2014 © 2014 IBM Corporation Transforming Your Enterprise to Get Value from Big Data and Analytics: How to Get Started The Journey The Value Analytics Drives Analytics Leadership and Governance Analytics Case Studies Best Practices for Getting Started Conclusions 2

Insight2014 transf value_big_data_analytics_6371

Embed Size (px)

DESCRIPTION

#IBMInsight Session presentation "Transforming your Enterprise to Get Value from BigData and Analytics: How to Get Started". Transforming Your Enterprise to Get Value from Big Data and Analytics: How to Get Started The Journey, The Value Analytics Drives, Analytics Leadership and Governance, Analytics Case Studies, Best Practices for Getting Started More at ibm.biz/BdEPRs

Citation preview

Page 1: Insight2014 transf value_big_data_analytics_6371

IBM IOD 2012 10/24/2014

Drury Design Dynamics 1

Transforming your Enterprise to GetValue from Big Data and Analytics:How to Get StartedSession # 6371

Douglas Dow & Emily Plachy

October 27, 2014

© 2014 IBM Corporation

Transforming Your Enterprise to Get Value from Big Dataand Analytics: How to Get Started

• The Journey

• The Value Analytics Drives

• Analytics Leadership and Governance

• Analytics Case Studies

• Best Practices for Getting Started

• Conclusions

2

Page 2: Insight2014 transf value_big_data_analytics_6371

IBM IOD 2012 10/24/2014

Drury Design Dynamics 2

The Journey

IBM’s Transformation Journey has been years in themaking with the analytics portion starting in 2004

4

Sharing & partnering

Making things smarter

Globally integrating

• Deliver a signature IBM client experience with an engaged workforce• Build a Smarter enterprise with data, cloud and systems of engagement• Make IBM essential to clients, partners, investors and communities

Transformationdesigned to:

Early years analytics applied to physical assets, i.e. manufacturing, supply chainThen analytics applied to non physical processes / functional side i.e. salesNow expansion more broadly used across the enterprise

Analytics

Page 3: Insight2014 transf value_big_data_analytics_6371

IBM IOD 2012 10/24/2014

Drury Design Dynamics 3

IBM’s Analytics Transformation is focused on businessoutcomes

5

“Analytics will form asilver thread that weavesthrough the future ofeverything we do.” Ginni

Rometty, Chairman and CEO,IBM Corporation

Fundamental Principles

• Pragmatic approach

• Focus on business outcomes

• Analytics is a way of doing business

Basic Building Blocks

• IBM Institute for Business Value Papers

• Great base for transformation withvalue services structure

• Motivated leadership to make IBMsmarter and essential

The Value Analytics Drives

Page 4: Insight2014 transf value_big_data_analytics_6371

IBM IOD 2012 10/24/2014

Drury Design Dynamics 4

First, what do we mean by analytics?

7

IDC – Independent Financial Impact Studies

8

“The median ROI for the

projects that incorporated

predictive technologies was

145%, compared with a

median ROI of 89% for those

projects that did not.”Source: IDC, “Predictive Analytics and ROI:

Lessons from IDC’s Financial Impact Study”

Update: 2011 study shows ROI for predictive analytics at 250%!

Page 5: Insight2014 transf value_big_data_analytics_6371

IBM IOD 2012 10/24/2014

Drury Design Dynamics 5

Understanding how to create value from data has been thefocus of IBM’s analytics studies for 5 years.

9

Analytics:The new path to value

Operationalizinganalytics in

sophisticatedorganizations

Analytics:The widening

divide

Mastering analyticcompetencies

Analytics:The real world use

of big data

Fundamentalsof big data

Analytics:A blueprint for value

Extracting valuefrom data and

analytics

2010 2011 2012 2013

The intelligent enterpriseand

Breaking away with BAO

2009

Defining analyticsas a strategic

asset

MIT Sloan Management Review & IBM Institute of BusinessValue teamed up in 2010

10

IBM Institute for Business Value

+

•Surveyed 3,000 executives, managers andanalysts plus extensive interviews

•Respondents represent more than 30industries in 108 countries

•Interviews with IBM and MIT thought leaders

•Analysis by IBM and MIT Sloan ManagementReview team

Page 6: Insight2014 transf value_big_data_analytics_6371

IBM IOD 2012 10/24/2014

Drury Design Dynamics 6

The use of analytics correlates to performance

11

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

Top Performers are morelikely to use an analyticapproach over intuition*

Organizations that lead inanalytics outperform thosewho are just beginning toadopt analytics

*within business processes

5.4x3x

Organizational obstacles, not data or financial concernsare holding back adoption

12

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.

Page 7: Insight2014 transf value_big_data_analytics_6371

IBM IOD 2012 10/24/2014

Drury Design Dynamics 7

Where analytics are performed within an organization is not a singlefixed location, but rather a combination of complementaryarrangements.

13

Transformed(21%)

Experienced(46%)

Aspirational(33%)

87%

71%

47%

IT department

At point-of-need

LOB analyticunits

Location analyticsperformed

Centralizedanalytic units

100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0%

Frequency ofanalytics use

Progression of analytics location as demand grows

Source: Analytics: The New Path to Value, a jointMIT Sloan Management Review and IBMInstitute of Business Value study. © 2010Massachusetts Institute of Technology.

Nearly two out of three respondents reports realizing acompetitive advantage from information and analytics.

14

Total respondents n = 11442010 and 2011 datasets © Massachusetts Institute of Technology

Realizing a competitive advantage

Respondents were asked “To what extent does the use of information (including bigdata) and analytics create a competitive advantage for your organization in yourindustry or market.” Respondent percentages shown are for those who rated theextent a [4 ] or [5 Significant extent]. The same question has been asked each year.

Competitive advantageenabler

A majority of respondentsreported analytics and information(including big data) creates acompetitive advantage within theirmarket or industry

Represents a 70% increasesince 2010

Organizations already active inbig data activities were 15%more likely to report acompetitive advantage

A higher-than-averagepercentage of respondents inLatin America, India/SE Asia andANZ reported realizing acompetitive advantage

63%

58%

37%

2012

2011

2010

70%increase

Page 8: Insight2014 transf value_big_data_analytics_6371

IBM IOD 2012 10/24/2014

Drury Design Dynamics 8

Analytics Leadership andGovernance

IBM’s Analytics Transformation Governance Model

16

AnalyticsPractices

AnalyticsCommunities

EnterpriseInformation

Management

CIO Office

GlobalIntegratedEnterprise

Shared Services

Big Data &AnalyticsUniversity

BusinessPerformance

Services

IBM Research

Development

Groups

EnterpriseTransformation

Initiatives

Line of BusinessAnalytic Groups

Network of Analytic Communities

DataStrategy

Infrastructure

InitialDeployment

Channel

Education Portal

Apply and solve business problems

Deepmathematicalskills

Product andSolution offerings

ScalingDeployment

Addressing businesschallenges in LOBs

Page 9: Insight2014 transf value_big_data_analytics_6371

IBM IOD 2012 10/24/2014

Drury Design Dynamics 9

Business Analytics Transformation

17

Mission

Drive the Widespread Use of Analytics across IBM to Elevate BusinessPerformance

Long Term BAT Strategy

Transform for Growth using Analytics via 4 E's:

Evangelize – promote the value gained by using analytics

Educate – provide training in consuming and doing analytics

Enable – assist business leaders in solving their businesschallenges with analytics

Empower – establish business structures to support peopleimplementing analytics

We leverage a rich set of products internally for BusinessAnalytics

18

Bring analytics to strategicdecisions

Collaboration Management

DashboardingReporting

VisualizationFinancial Data

Searching

Smart ApplianceStream ComputingParallelizationEntity AnalyticsCloud Computing

Highly scalable & big datacomputing The Customer-centricity

revolutionSocial Network AnalysisSocial Media Analysis

Voice of Customer

IBM AnalyticsEcosystem

Deployment todecision makers

Complex Event Processing, Business Process ManagementBusiness Rules & Events (ILOG)

Multi-channel deployment & management

GBS

Core AnalyticsTechnologies

DataStage

Page 10: Insight2014 transf value_big_data_analytics_6371

IBM IOD 2012 10/24/2014

Drury Design Dynamics 10

Analytics Case Studies –Emily Plachy

Human Resources: Tailored analytics-drivenrecommendations reduces attrition of high-valueemployees

20

Solution components:

- IBM® SPSS Modeler- IBM® Cognos BI- IBM® ILOG CPLEX

$85M

325% ROI

Estimated net benefit throughreduced attrition in IBM’s growthmarket employee population

For 2012-2013 investment

Business problem: Retaining high-value employees.

Solution: Identify drivers of attrition and risk level for every

employee. Leverage the model to create a customized retention

plan for each high value employee.

Page 11: Insight2014 transf value_big_data_analytics_6371

IBM IOD 2012 10/24/2014

Drury Design Dynamics 11

Finance: Identify and mitigate acquisition risk byleveraging data and analytics

21

Business problem: Acquisitions ‘synergies’ arechallenging to quantify and realize and can significantlyalter performance & financial expectations.

Solution: Use acquisition data and advanced analyticsmodels to create tailored risk profiles for eachcontemplated deal and address throughout theacquisition lifecycle.

80+ Acquisitionsbenefited from headlights intoexecution risks to affect bothdeal pricing and integration plan

Solution components:

- IBM® SPSS Modeler, Statistics- IBM® Cognos BI- IBM® WebSphere

End-to-End RiskManagement across theacquisition portfolioStreamlined tracking andreporting to identify systemic riskand address challenges

Sales: Boost sales effectiveness by applying advancedanalytics to align resources to the market opportunity.

22

Business problem: Deploying sellers for maximum revenue growthby account.

Solution:• Advanced analytical models predicting customer profit contribution

based on historic revenue growth and opportunity for everyaccount.

• Recommendation engine provides Increase / Decrease / Maintainresource shift recommendations at a client level.

$300Mestimated additional revenueduring 2013 due to sales forceproductivity increase

3000% ROIfor 2013, based on a yearlyongoing investment of $10M

Solution components:

- IBM® SPSS Modeler, Statistics- IBM® Cognos BI- IBM® Netezza

Page 12: Insight2014 transf value_big_data_analytics_6371

IBM IOD 2012 10/24/2014

Drury Design Dynamics 12

Services: Develop new business using analytics and socialmedia.

23

Business problem: Developing new business in an existingmarket, finding new customers, finding new products andservices for existing customers.

Solution: IBM Global Technology Services and IBMResearch developed the Long-Term Signings Platform.

• Analyzed over 30 data sources• Discovered associations between clients and products

Millions of dollars in increasedrevenue and millions of dollars incost savings

$M

Solution components:

- IBM® SPSS Modeler, Text Analytics

Best Practices for GettingStarted

Page 13: Insight2014 transf value_big_data_analytics_6371

IBM IOD 2012 10/24/2014

Drury Design Dynamics 13

Developing and deploying an analytics solution consists ofthree elements: data, math/analytics, business process.

25

DescriptiveGet in touch with reality, a single

source of the truth, visibility

PredictiveUnderstand the most likely future

scenario, and its business implications

PrescriptiveCollaborate for maximum business

value, informed by advanced analytics

CognitiveHighly automated optimization

solutions that get smarter over time

What happened?

What will happen?

What should we do about it?

Variety (many forms of data)

Big Data = All Data

Veracity (data in doubt)

Volume (data at rest)

Velocity (data in motion)

How do we optimize a dynamic, BigData environment?

Developing an analytics blueprint is the first step toconverting data and analytic insights into results.

26

Source: Analytics: A blueprint for value – Converting big data and analytics into results, IBM Institute for Business Value © 2013 IBM

StrategyInstill a sense of purpose

Is there a common agenda for analytics among leaders? Are your investments aligned to value delivery? Does the funding structure support cross-silo initiatives?

TechnologyArchitect for the future

Are data and analytics skills nurtured within your organization? Are data management practices strong enough to instill confidence? Is the analytic infrastructure architected for today’s challenges?

OrganizationEnable the organization to act

Are data and analytics part of your decision making processes? Can your define the impact from analytics investments? Is the level of trust sufficient to rely on others for data and analytics?

Page 14: Insight2014 transf value_big_data_analytics_6371

IBM IOD 2012 10/24/2014

Drury Design Dynamics 14

“New path to value” – a five-point approach tooperationalize analytics

27

Recommendation 1:Focus on the biggestand highest valueopportunities

Recommendation 4:Keep existing

capabilities whileadding new ones

Recommendation 5:Use an informationagenda to plan for

the future

Recommendation 2:Within eachopportunity, start withquestions, not data

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

Recommendation 3:Embed insights to drive

actions and deliver value

Best Practice Approach to Analytics Projects

28

• Perfect data is a longjourney and you can’tafford to wait

• Organize & cleansedata incrementally sothat projects can start

Incremental

• To gain business valuestart on analyticprojects right away

• Have businessanalysts work with dataanalysts

Collaborative• Put a stake in the

ground to progress theproject and get results

• Review and makeimprovements

Iterative

Business AcumenData Analysts

Deliver fastThink big Start small

Page 15: Insight2014 transf value_big_data_analytics_6371

IBM IOD 2012 10/24/2014

Drury Design Dynamics 15

Several themes have emerged from our analyticssolutions.

Relationships inferred from data today may not be present in datacollected tomorrow.

You don’t have to understand analytics technology to derive value fromit.

Fast, cheap processors and cheap storage make analysis on big datapossible.

Doing things fast is almost always better than doing things perfectly.

Using analytics leads to better auditability and accountability.

29

Nine levers: Capabilities that enable and enhance big data& analytics value creation

30

Source: “Analytics: A blueprint for value – Converting big data and analytics into results,” IBM Institute for BusinessValue © 2013 IBM

Source of Value Measurement Platform

Enable

Basis for bigdata andanalytics

Culture Data Trust

Drive

Needed torealize value

Actions and decisions thatgenerate value

Evaluating impact onbusiness outcomes

Integrating capabilitiesdelivered by hardware and

software

Availability and use of dataand analytics

Data management practices Organizational confidence

Sponsorship Funding Expertise

Amplify

Boostsvalue

creationExecutive support and

involvementFinancial rigor in analytics

funding process

Development and access toskills and capabilities

Page 16: Insight2014 transf value_big_data_analytics_6371

IBM IOD 2012 10/24/2014

Drury Design Dynamics 16

Several dynamics are underway that are shaping thefuture for big data and analytics

• Growth of data – 2.5 billion gigabytes generated everyday

• Unstructured data – 80% of big data growth isunstructured (social media, video, audio, images, datafrom sensors).

• Cognitive computing – Just when we need it, the third eraof computing, cognitive, offers the promise of allowing usto rapidly explore big data and uncover insights.

31

‒Think Ahead

‒Tell a Story

‒Understand Your Business

‒Get Better Data

32

Page 17: Insight2014 transf value_big_data_analytics_6371

IBM IOD 2012 10/24/2014

Drury Design Dynamics 17

Conclusions

Conclusions

• The use of analytics correlates to organizational performance.

• Developing and deploying analytics solutions consists of threeelements: Data / Analytics / Business Processes

• You can operationalize analytics using a 5-point approach.

• Successful analytics deployments incrementally cleanse data,have collaborative teams, and deliver iteratively.

• The most competitive companies will move from raw big data toinsight-driven actions with speed; and cognitive computing willhelp do this.

34

Page 18: Insight2014 transf value_big_data_analytics_6371

IBM IOD 2012 10/24/2014

Drury Design Dynamics 18

We Value Your Feedback!

• Don’t forget to submit your Insight session and speaker feedback!Your feedback is very important to us – we use it to continuallyimprove the conference.

• Access the Insight Conference Connect tool to quickly submit yoursurveys from your smartphone, laptop or conference kiosk.

35

Acknowledgements and DisclaimersAvailability. References in this presentation to IBM products, programs, or services do not imply that they will be available in all countries inwhich IBM operates.

The workshops, sessions and materials have been prepared by IBM or the session speakers and reflect their own views. They are provided forinformational purposes only, and are neither intended to, nor shall have the effect of being, legal or other guidance or advice to any participant.While efforts were made to verify the completeness and accuracy of the information contained in this presentation, it is provided AS-IS withoutwarranty of any kind, express or implied. IBM shall not be responsible for any damages arising out of the use of, or otherwise related to, thispresentation or any other materials. Nothing contained in this presentation is intended to, nor shall have the effect of, creating any warranties orrepresentations from IBM or its suppliers or licensors, or altering the terms and conditions of the applicable license agreement governing the useof IBM software.

All customer examples described are presented as illustrations of how those customers have used IBM products and the results they may haveachieved. Actual environmental costs and performance characteristics may vary by customer. Nothing contained in these materials is intended to,nor shall have the effect of, stating or implying that any activities undertaken by you will result in any specific sales, revenue growth or otherresults.

© Copyright IBM Corporation 2014. All rights reserved.

— U.S. Government Users Restricted Rights – Use, duplication or disclosure restricted by GSA ADP Schedule Contractwith IBM Corp.

— Please update paragraph below for the particular product or family brand trademarks you mention such as WebSphere, DB2,Maximo,Clearcase, Lotus, etc

IBM, the IBM logo, ibm.com, [IBM Brand, if trademarked], and [IBM Product, if trademarked] are trademarks or registered trademarks ofInternational Business Machines Corporation in the United States, other countries, or both. If these and other IBM trademarked terms are markedon their first occurrence in this information with a trademark symbol (® or TM), these symbols indicate U.S. registered or common law trademarksowned by IBM at the time this information was published. Such trademarks may also be registered or common law trademarks in other countries.A current list of IBM trademarks is available on the Web at

•“Copyright and trademark information” at www.ibm.com/legal/copytrade.shtml

•If you have mentioned trademarks that are not from IBM, please update and add the following lines:[Insert any special 3rd party trademarknames/attributions here]

•Other company, product, or service names may be trademarks or service marks of others.

36

Page 19: Insight2014 transf value_big_data_analytics_6371

IBM IOD 2012 10/24/2014

Drury Design Dynamics 19

Thank You