big data - 6 steps to success

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© 2014 IBM Corporation Big Data: 6 Steps to Success

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Page 1: Big data - 6 steps to success

© 2014 IBM Corporation

Big Data: 6 Steps to Success

Page 2: Big data - 6 steps to success

© 2014 IBM Corporation@IBMExpOne | #IBMExpOne

Agenda

• The current landscape

• Big data success steps

• Case studies

• Questions

Sameer KhanSenior Product Marketing Manager& Digital LeaderIBM Customer Analytics@sameerkhan

Page 3: Big data - 6 steps to success

© 2014 IBM Corporation@IBMExpOne | #IBMExpOne

Disruptive forces impact long standing business models across industries

““Data is the new oil.Data is the new oil.Data is just like crude.Data is just like crude.ItIt’s valuable, but if unrefined’s valuable, but if unrefinedit cannot really be used.” it cannot really be used.” – – Clive HumbyClive Humby

““We have an economy based on a We have an economy based on a resource that is not only renewable, resource that is not only renewable, but self-generating. Running out is but self-generating. Running out is not a problem, drowning in it is.”not a problem, drowning in it is.”–– John NaisbittJohn Naisbitt

Shift of power to the consumer

Pressure to do more with less

Proliferation of big data

Page 4: Big data - 6 steps to success

© 2014 IBM Corporation@IBMExpOne | #IBMExpOne

Lots of data, not enough answers

Only 26% of companies

have a well-developed strategy in place for improving customer experience.*

58% of companies

have limited or no understanding of which usability issues affect conversion*

91% of companies

have limited or no understanding of why people leave their site without converting*

* Econsultancy - 2013

The departmental analytic approaches of the past are insufficient for the needs of today

Page 5: Big data - 6 steps to success

© 2014 IBM Corporation@IBMExpOne | #IBMExpOne

The demand for big data solutions is real

The healthcare industry spends roughly $250 billion on fraud, per year. By 2016, this could grow to more than $400 billion a year.1

One rogue trader at a leading global financial services firm created $2 billion worth of losses, almost bankrupting the company.

6 billion global subscribers in the telco industry are demanding unique and personalized offerings that match their individual lifestyles.2

$93 billion in total sales is missed each year because retailers don’t have the right products in stock to meet customer demand.

Page 6: Big data - 6 steps to success

© 2014 IBM Corporation@IBMExpOne | #IBMExpOne

Shift In Algorithms: Generalized to Personalized

http://en.wikipedia.org/wiki/Medical_algorithm

Page 7: Big data - 6 steps to success

© 2014 IBM Corporation@IBMExpOne | #IBMExpOne

We all have…

Page 8: Big data - 6 steps to success

© 2014 IBM Corporation@IBMExpOne | #IBMExpOne

Big Data Steps to Success

Step 1: Identify the business problems

Step 2: Seek on the needed data

Step 3: Standardize your data

Step 4: Pick the right model

Step 5: Validate and test

Step 6: Execute and measure results

Page 9: Big data - 6 steps to success

© 2014 IBM Corporation@IBMExpOne | #IBMExpOne

Step 1: Identify the Business Problem

Page 10: Big data - 6 steps to success

© 2014 IBM Corporation@IBMExpOne | #IBMExpOne

Understanding the Business Challenges before Developing Big Data Solutions

External Content (Twitter, News Feeds...)

Internal Content (CRM, Warehouses,

ERP, ECM...)

“I am monitoring all angles – yet I can’t connect the dots.”

“I don’t know what I don’t know – where is my business exposed?”

“I can’t unlock the value in my data to drive economic value to my business.”

“Innovation is falling short as I am unable to see the full research picture.”

“I can’t find the right answers fast enough to support my customers.”

?

Page 11: Big data - 6 steps to success

© 2014 IBM Corporation@IBMExpOne | #IBMExpOne

Step 2: Seek only needed data

Page 12: Big data - 6 steps to success

© 2014 IBM Corporation@IBMExpOne | #IBMExpOne

Identify the Types of Data Sources and its Value

Page 13: Big data - 6 steps to success

© 2014 IBM Corporation@IBMExpOne | #IBMExpOne

Step 3: Standardize Your Data

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Page 14: Big data - 6 steps to success

© 2014 IBM Corporation@IBMExpOne | #IBMExpOne

Leveraging data still faces many obstacles

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

have a limited understanding of how to use analytics

38%

Self-service analytics and expectations to drive better data-driven decisions are rising

of the time is spend on data preparation80%

Making decisions rapidly is no longer a goal; it’s an imperative

find it difficult to get data24%

Access to requireddata sources is critical while maintaining governance standards

Page 15: Big data - 6 steps to success

© 2014 IBM Corporation@IBMExpOne | #IBMExpOne

Even a simple analytics project has multiple steps and people

Data Access

Data Preparation

Analysis

Validation

Collaboration

Reporting

Data Scientists and Statisticians

Business Users

ITBusiness Analysts

Page 16: Big data - 6 steps to success

© 2014 IBM Corporation@IBMExpOne | #IBMExpOne

Step 4: Pick the Right Model

Page 17: Big data - 6 steps to success

© 2014 IBM Corporation@IBMExpOne | #IBMExpOne

Improving the customer experience by better understanding behaviors drives almost half of all active big data efforts

Total respondents n = 1061

Big data objectives

Top functional objectives identified by organizations with active big data pilots or implementations. Responses have been weighted and aggregated.

Customer-centric outcomes

Operational optimization

Risk / financial management

New business model

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

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© 2014 IBM Corporation@IBMExpOne | #IBMExpOne

Customer Centric Model Scenarios

Scenarios

1. Optimize By Channel Approach

2. Integrated Multi-Channel Approach

3. Master Data Management (MDM) Approach

4. Hybrid Approach

Source: CRM Ecosystem, Forrester

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© 2014 IBM Corporation@IBMExpOne | #IBMExpOne

Integrated Multichannel Approach Use Cases

General /Descriptive

Analytics

Predictive Analytics

Prescriptive Analytics

Similar BehaviorsSimilar Needs

Similar Web Navigation Challenges

Predicting Sales Volume

EverydayPrice

Market Trend

Inventory

Market Trend

Competitors

Seasonality Gift Cards

In-store Displays

Cross channel Products/Price

Recommendations

Page 20: Big data - 6 steps to success

© 2014 IBM Corporation@IBMExpOne | #IBMExpOne

MDM provides the enterprise backbone for an extended 360 degree view

Customer

Person

Prospect

Citizen

Member

Provider

Employee

CompanyTrading Partner

Organization Supplier

Distributor

Vendor

Office

Product

Service Financial Account

Agreement

Contract

Assets

Locations

Manufactured Goods

Page 21: Big data - 6 steps to success

© 2014 IBM Corporation@IBMExpOne | #IBMExpOne

Customer search:MDM draws in all related records: J Robertson, Janet Robertson, Jan Baker

Customer search:MDM draws in all related records: J Robertson, Janet Robertson, Jan Baker

Janet Robertson

MDM enables a complete purchase history, including Jan Baker’s records from before 2011

MDM enables a complete purchase history, including Jan Baker’s records from before 2011

Customer’s Products from MDM

Customer’s Products from MDM

Customer info from MDM

Customer info from MDM

Indexed 3rd party information related to customer

Indexed 3rd party information related to customer

Unstructured internal information related to customer

Unstructured internal information related to customer

Page 22: Big data - 6 steps to success

© 2014 IBM Corporation@IBMExpOne | #IBMExpOne

Step 5: Validate and Test

Page 23: Big data - 6 steps to success

© 2014 IBM Corporation@IBMExpOne | #IBMExpOne

Putting the Selected Model to Test

DiscoverDiscoverConnect securely to all data sources Provide unified search and navigationSurface relationships & themes

AssessAssessIdentify the value of the dataRecognize users of the data Establish context of data usage

CollaborateCollaborateAugment the data with user knowledgeCreate personalized views of the dataIdentify ongoing integration points

LeverageLeverage Build compelling applications using all of your data

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© 2014 IBM Corporation@IBMExpOne | #IBMExpOne

Integrated Big Data Infrastructure

Secure access to a broad range of enterprise systems

Integration leverages core components of the platform

Compelling applications incorporating all data types and sources

CM, RM, DM RDBMS Feeds Web 2.0 Email Web CRM, ERPFile Systems

ConnectorFramework

Data Explorer App Builder

BigInsights

Integ

ration

& G

overn

ance

UI / User

Streams WarehouseData Explorer

Page 25: Big data - 6 steps to success

© 2014 IBM Corporation@IBMExpOne | #IBMExpOne

IBM Watson Analytics

Unified analytics experience

Visual storytelling

Intelligent automation

Data access and

refinement

Report and dashboard

creation

Integrated social business

Guided analytic

discovery

25

Free Trial At

WatsonAnalytics.com

Page 26: Big data - 6 steps to success

© 2014 IBM Corporation@IBMExpOne | #IBMExpOne

Architecture Overview – Social Analytics Use Case

Visualization

Geospatial Analysis

Big Data Analytical services

Social Data Analytics

feed

(latitude, longitude); keywords

Trending Analytics (time series)

Notify of event analysis

Existing social media firehose

DiscoverDiscover AssessAssess CollaborateCollaborate LeverageLeverageApps

Page 27: Big data - 6 steps to success

© 2014 IBM Corporation@IBMExpOne | #IBMExpOne

Step 6: Execute and Measure Results

Page 28: Big data - 6 steps to success

© 2014 IBM Corporation@IBMExpOne | #IBMExpOne

Four value pillars represent ROI potential for big data exploration

Improve Productivity

Reduce Risk & Improve Compliance

Leverage Existing Assets Increase

RevenueEliminate data silos

Leverage existing research and knowledge

Eliminate/retire unused systems

Extract value from existing assets

Reduce training costs

Improve staff retention

Improve collaboration

Capture tribal knowledge

Eliminate redundant projects

Equip sales and service staff with current, accurate

info

Increase upsell and cross-sell

Reduce sales cycle

Increase customer lifetime

value

Recommendations

Reduce time to monitor and

comply

Push relevant regulatory

updates/alerts

Honor pricing, NDAs, etc.

Single version of the truth

Avoid penalties

Page 29: Big data - 6 steps to success

© 2014 IBM Corporation@IBMExpOne | #IBMExpOne

Big Data Success Stories

Page 30: Big data - 6 steps to success

© 2014 IBM Corporation@IBMExpOne | #IBMExpOne

Duke University Health System gets smarter for its patients Need

• Transform healthcare to provide patients with the capability to proactively manage their health; adapt best practices to rapidly determine which treatments and approaches work best – and which don’t

Benefits

• Increased patient engagement from zero to 30,000 users in less than three months

• HealthView is now used by more than 150,000 patients, roughly one third of Duke’s overall patient base

• Collected US $16 million in co-pays through the new portal

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Page 31: Big data - 6 steps to success

© 2014 IBM Corporation@IBMExpOne | #IBMExpOne

Will you buy a car today? IBM SPSS Statistics helps Fiat identify the most likely customers and prospects.Need

• Determine the likelihood that future and returning customers would buy specific brands/models of Fiat cars, so dealers could optimize available marketing funds. Also, needed to better understand customer experience w/dealerships and repair facilities.

Benefits

• Improved customer response rate to marketing initiatives by 15-20 percent.

• Improved customer loyalty by 7 percent.• Supports continuous improvement of

dealerships and repair facilities. • Centralized analytical reporting and modeling

system enhances productivity and lowers costs.

• Efficiently works with large Oracle database containing history on 64 million customers.

Page 32: Big data - 6 steps to success

© 2014 IBM Corporation@IBMExpOne | #IBMExpOne

First Tennessee Bank: Analytics drives higher ROI from marketing programs Need

• An accountability framework that looked at overall marketing spending and the results that spending generated for the bank.

Benefits

• 600% overall return on its investment through more efficiently allocated marketing resources

• 3.1% increase in marketing response rate through more accurate targeting of offers to high-value customer segments

• 20% reduction in mailing costs and 17% reduction in printing costs due to the ability to target the most attractive segment for specific offers

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Page 33: Big data - 6 steps to success

© 2014 IBM Corporation@IBMExpOne | #IBMExpOne33

Next Steps and Resources

Resources:IBM Big Data Hubhttp://www.ibmbigdatahub.comWatsonAnalytics.comBigDataUniversity.com

Books / analyst papers

Schedule an IBM Big Data WorkshopFree of charge

Best practices

Industry use cases

Business uses

Business value assessment Thank You