Big data analytics: making it real

December 11, 2015

Jim Ferguson, Practice Principal, US SectorRob Guy, Strategy Consultant, US Public Sector

Agenda

– Context and market dynamics

– Approach: strategic and tactical

– Questions

We

The opportunity

Increasingly government is being asked to:

– Focus more on citizen-centric services

– To Drive operational efficiencies

Often traditional BI isn’t able to provide the analytic insight necessary to help address these demands

Key industry business challenges and opportunities

Consumer Industries and Retail

Manufacturing

‒ Omni-channel success‒ Enabling optimal store execution‒ Digital transformation‒ New product launch success‒ Risk management‒ Supply chain visibility

‒ Warranty and quality analytics‒ Fraud detection‒ Digital asset management‒ Supply chain visibility‒ Vehicle diagnostics analytics‒ Early warning defect detection

Energy Health & Life Sciences

Travel andTransportation

Communications, Media and Entertainment

‒ Optimize operations‒ Improve computing throughput‒ Deliver information remotely‒ Accelerate customer insights

‒ Fraud and abuse‒ Patient engagement ‒ Optimizing patient care‒ Reducing healthcare costs‒ Supply chain / distribution‒ Drug development / scientific

research

‒ Improving operations‒ Maximizing ancillary revenues‒ Customer loyalty‒ Predictive MRO analytics‒ Yield and revenue management‒ Supply chain visibility

‒ Broadcast monitoring‒ Churn prevention‒ Advertising optimization

Public Sector

‒ Critical Infrastructure protection‒ Counter terrorism / citizen safety‒ Transparency in government‒ Transportation‒ Situational awareness‒ Fraud analytics

Financial Services

‒ Regulatory compliance‒ Capital optimization‒ Customer-centricity‒ Cost management‒ Growth/increase wallet share

“…For most legacy companies, data-analytics success has been limited to a few tests or to narrow slices of the business. Very few have achieved what we would call ‘big impact through big data,’ or impact at scale.”

David Court, Director, McKinsey“Getting big impact from big data”, January 2015

Have you achieved revenue or cost improvements from

big data or advanced analytics?

Improvement No improvement

Big Data impact has been limited for most major organizations

75%of major

companies

– The world has become excited about big data and advanced analytics not just because the data are big but also because the potential for impact is big.

– However, most major organizations, public and private sector, are not achieving a significant impact from big data or advanced analytics investments.

Less than 1%

Source: “Getting big impact from big data“, January 2015, McKinsey

Excitement does not equate to success!

Where are the investments being made?

Top 10 reasons we see big data projects struggle

– Incomplete or lack of information strategy

– Equating big data technology with big data strategy

– Alignment of business and technology

– No defined business objective

– No use cases or selecting the wrong use cases

– Lack of management interest or involvement

– Lacking the right skills

– Challenge with data sharing

– Uncertain data quality

– Limited data access

7

What successful business intelligence impacts look likeBusiness intelligence, big data and advanced analytics are a catalyst for growth, innovation and efficiency

Source: “Business Technographics: Global Data and Analytics Survey, 2014”, June 2014, Forrester

Better decision-making

Deeper insightsfrom existingdata

Access to valuable datathat was not used before

Increasedbusinessagility

More employeesusing data /data analytics

Increasecitizensatisfaction

Reducedoperationalcosts

Increasedinnovation

Reduced ITcost

New businessmodels /revenue streams

Increasedrevenue

Big Data Strategy Data Management

Operationalize Analytics

Needs along the Big Data journey

– Create/Update Strategy

– Fast win-quarterly releases

– Buy vs. Build

– Platform options: Open source, proprietary, hybrid, migration to new low cost big data

technologies

– Impact on existing solutions

– Financials & ROI

– Social Media data strategies (tweets, FB, blogs)

– Public data feeds (LexisNexis, regulatory, Govt.)

– Operational data sources (call center, supply chain)

– Existing warehouse (BI, DW, proprietary solutions)

– IOT- new devices, Sensor/machine data

– Resource/expertise for data quality and ETL

– Data Lakes and investigative analytics

– New insights from accumulated data

– Use case development based on business needs

– Data Modeling and Results

– Ad hoc analytics environments, Analytics COE

– Solutions library, Use case libraries

– Data scientist and analysts for building models

– Deployment models: On-premise, Cloud, Hybrid

– “As a Service” Elastic operational models

– Partner with end-to-end solutions

– Business process changes based on analytics

– Decision support & predictive analytics

deployment

– Technical expertise for platform administration, developer support and consulting

4 3

21

Translating the journey to action

– Big Data Analytics Pilot(s)

– Strategy and Planning

– Business Outcomes

Big Data Analytics: Lets not boil the ocean

Discovery Workshop

Discovery Experience

Discovery Production Implementation

Rapid, low risk, secure path to big data value

Big Data discovery approach

Approach

– The ultimate goal is to establish Discovery Production Capability

– Other Discovery steps are positioned with this goal in mind.

– Begin with a Discovery Workshop to identify relevant and measurable business use cases

– Demonstrate the power of analytics by piloting business use cases through Discovery Experience

– Implement a Discovery Production Capability based on success of pilots that show strong existing business case

Ph

ases

Client defined use case examples

– Human trafficking – Leveraging social media to identify victims and traffickers

– Law enforcement – Determining impact of weather on crime

– Social services – Program efficacy and demographic impact of success

– Logistics – Prison inmate transportation optimization

– Quality of citizen services - Sentiment analysis based on social media

– Traffic analytics – Pedestrian fatalities

– Fraud analysis – Underground economy

13

Strategy and Planning

– Need an information strategy aligned with business needs

–Address required skills

–Governance Model

–Technical architecture

– Create an executable action plan

– Prioritized phases

– Flexibility to react to changing priorities

Strategy and Planning: key to an efficient & effective information ecosystem

Lifecycle starts with building a strategy and actionable roadmap, then moves to rapid, iterative implementation, and finally ongoing maintenance and support

Bu

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BI vision & strategy:where are we going?

BI Modernization

Strategy and

Planning

Services

(BI, Big Data,

MDM, IQM/IG)

BI implementation:how do we get there?

BI maintenance & support:how do we sustain success?

How do we improve and continually realize business value?

Deploy 1

Pragmatically adopt rapid,iterative implementation

Start with vision, roadmap and plan

Build effective maintenance and support

Maintenance

& support

Deploy 2

Deploy 3

Deploy N

Project lifecycle

Project lifecycle

Project lifecycle

Project lifecycle

12

3

Outcome:• Improved decision making• Reduced risk• Increased agility

4

Recap

– Business needs should drive big data and analytics

– Balance tactical investment with strategic initiatives

– Proofs of concept based on user defined business use cases

– Enterprise Information Management (EIM) is essential to build foundation

– Measure – Measure – Measure

16

Questions

Thank you

Decades of Experience

Advanced Analysts

Industry Depth

Centers of Expertise

Business Use-Cases

Numerous Projects

HPE delivers numerous business outcome driven analytics and data

management projects every year.

HPE has an extensive library of business-driven use cases relevant

to industries and functions.

HPE has multiple Analytics and Data Management Global Centers of

Expertise around the globe.

HPE has a deep bench of analytics and data management consultants

worldwide with deep industry and domain expertise.

HPE has several global analytics professionals with advanced

statistical and mathematical skills.

HPE has years of experience delivering analytics and data

management services.

1,000analytics and data management project completed annually

9analytics and data management enters of expertise

1,200professionals with advanced analytical skills

200+industry use cases covering twelve major business functions

40+ yearssupporting the industry with business intelligence services

3,500+consultants with expertise in analytics, and data management

Why HPE for Analytics and Data Management ServicesDeep technical expertise and proven delivery methods

Analytics and Data Management Industry Expertise

Financial Services Consumer Industries and Retail

Manufacturing Public Sector

‒ Over 90 financial services clients1

‒ Nearly 30 FSI issue use cases including marketing, IT, finance, communications, procurement, R&D, risk & compliance, sales, and legal2

‒ Nearly 40 consumer industries and retail clients1

‒ Over 25 CI&R business issue use cases including IT, marketing, distribution/logistics, finance, HR, R&D, sales, and manufacturing2

‒ Over 40 manufacturing clients1

‒ Nearly 70 MFG business issue use cases including IT, communications, marketing, distribution/logistics, HR, manufacturing, procurement, R&D, risk & compliance, sales, and finance2

‒ Nearly 60 public sector clients1

‒ Over 20 PS government issue use cases including IT, communications, distribution/logistics, finance, HR, manufacturing, marketing, R&D, risk & compliance, sales, and procurement2

Energy Health and Life Sciences

Travel andTransportation

Communications, Media and Entertainment

‒ Nearly 30 energy clients1

‒ Over 10 energy business issue use cases including IT, distribution/ logistics, manufacturing, R&D, and marketing2

‒ Over 20 health and life sciences clients1

‒ Nearly 15 HLS business issue use cases including IT, marketing, communications, R&D, risk & compliance, distribution/logistics, sales, and finance2

‒ Over 20 travel and transportation clients1

‒ Nearly 10 T&T business issue use cases including IT, communications, marketing, distribution/logistics, procurement, R&D, sales, and finance2

‒ Over 20 communications, media and entertainment clients1

‒ Over 40 CME business issue use cases including marketing, IT, finance, distribution/logistics, HR, manufacturing, procurement, R&D, risk & compliance, sales, and communications2

1 HPE calculations based on 2013, 2014, 2015 A&DM client wins from HeatMap Portal, March 20152 HPE calculations based on A&DM Knowledge Management use case library, March 2015