Software EMEA Performance Tour 2013 - Hewlett Packard · • Analytics is seen to augment/ tune rather than “rip and replace” an existing system and personnel • Iterative and

Software EMEA Performance Tour 2013 London, UK 2 July

© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.

Big Data Analytics: Generate Return on Information Gary Palmer July 2nd, 2013

© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. 3

The Big Data reality

• Digital information will grow by a factor of 44, to 35 ZB in 2020

• Includes data both in motion and at rest

• Need for more agile, flexible technologies for analysis

• Massive amounts of data can provide more accurate insights, better decisions

2009 2020

35 Zettabytes*

Source: IDC Digital Universe Study, 2010

0.8 ZB


50 million voice recordings

7 million chat sessions

6 million email interactions

CONTACT CENTRE

100 million web visits

WORD OF MOUTH >1 billion indirect insights

WEB

Over 160 million customer interactions per year

One organisation’s global complexity


At a scale never seen before

Data is being shared in ways never imagined

Source: Company Data

Waze • 48MM users, +2xY/Y

• 1B+ miles driven per month w/Waze Open

Jawbone UP • Billions of steps/day

• 700K+ hours of sleep/day

• 5x App interactions per user/day

Yelp • 102MM users, +43% Y/Y

• 39MM user-generated reviews, +42% Y/Y


The lost opportunities of Big Data

Today’s reality

3% 23%

% of data that would be

potentially useful IF tagged and analysed

actually being tagged for Big Data value

% of the digital universe that is

actually being tagged, analysed and

leveraged ¹Source: IDC The Digital Universe in 2020, December 2012

0.5%


Big data: volume, velocity, variety and complexity

Extreme information challenges

Extreme information is becoming routine generated by a sea of mobile devices, social media, sensors

Social computing Context-aware computing

Pattern-based strategy

Information sources

Social Media Video Audio Email Texts Mobile Transactional Data

Documents IT/OT Search Engine Images

Velocity Volume

Variety Complexity

Big Data


Lots of interesting data, but often locked away in siloes Inhibits ability for organisations to understand what is happening in a timely way

Social Media

Audio

Texts

Word, Excel

Images

Email

Financials

Legal Documents

Call centre

Cloud

Cloud

Archive

Laptop

Mobile Phone

Data Centre

Data Center

Remote Office

Video


Clickstream Data

Transactional Data

Logs

ERP CRM

HRMS Procurement Supply Chain Management/

Inventory Mgmt

Human information—the big data challenge & opportunity

“Missed opportunity” “Increased risk” “Cost & complexity”

Social Media Video

Audio

Email

Texts Messages

Word, Excel

Images

Need to handle 100% of the information

Unstructured Structured

10% 90%


The 800 lb gorilla is in the room

• Human information is diverse: text, audio, video, social

• Information is dynamic

• Information is complicated

• Meaning is relative

• Ideas don’t match - they have distance

Keywords and metadata do not solve this problem.

“After putting the vase securely in the box he tied a bright red bow around Jennifer’s birthday gift.”

“The lead singer took a final bow following a wonderful performance.”

“The Captain pointed the bow of the ship into the wind.”

A majority of big data is “human information” which is fundamentally different


Understanding the “what” and “why” of your business performance

When to consider Autonomy for big data

• Analyse unstructured and semi-structured data from a wide variety of sources

• Analytics is seen to augment/ tune rather than “rip and replace” an existing system and personnel

• Iterative and exploratory analysis can be of value

• Sampling of data yields insufficient results

• Business measures or KPIs are not predetermined

• Data needs to be worked by non-technical staff – i.e. marketing, LOB, etc.


Answer questions that could not be answered before

Trending big data use cases

Customer sentiment & intent “Love the new DreamWorks app”

Fraud detection looking for outliers Russian accents, 212 area code, replacement phones

Real-time dynamic retail Make an offer that can’t be refused – now!


Draw up your game plan before taking the field

Big data starts with big preparation

1. Gather business requirements before gathering data

2. Implementing big data is a business decision, not IT

3. Use agile and iterative approach to implementation

4. Evaluate data requirements

5. Ease skills shortage with standards and governance

6. Optimise knowledge transfer with a centre of excellence

7. Embrace and plan your sandbox for prototype and performance

8. Align with the cloud operating model

9. Associate big data with enterprise data

10. Embed analytics & decision-making into operational workflow


Autonomy IDOL is designed to tackle the challenges of multichannel analytics

Need the right technology to make it matter

• Single processing layer for all data

• Conceptual and machine learning capabilities

• Proven, mapped security model

• Pre-built connectors to most common repositories

• Ubiquity: Supporting 1,000+ file types

• Language independence – over 150 languages

• Process data in-memory, in-time, and in-place


500 functions & 400 connectors

Autonomy IDOL: the OS for human information

• Conceptual distance understanding

• Meaning extraction

• Meets most demanding security requirement

• Language agnostic

• Supports over 1,000 file types and 400 content repositories

• Automates processes in real time

• Social, audio, video, text

• Manage in place

• Petabytes beyond scalability

Over 400 Connectors


IDOL architecture supporting next gen apps

Social Media Video Audio Email Texts Mobile Transactional Data

Documents XML Search Engine Images

HP Autonomy

IDOL Applications

Autonomy Connectors

eDiscovery

Enterprise Search

Media Monitoring

Social Media Analytics

Decision Support

Augmented Reality

Partner/ In-house apps

HC Analytics

Repositories

Information Types

Apps

500 Functions

IDOL Services Multimedia Informatics

Enrichment Capture

Interaction Analytics Discovery

Concept Clouds

Active Matching Visualisation

ACA

MediaBin

Connected LiveVault

TRIM

AeD

Data Protector

WorkSite

DigitalSafe

Connectors

…

Cloud Enterprise

IDOL OS for Human Information

ERP

CRM

Database Jive…

Image

HIS

Data Warehouse

Hadoop

SharePoint

http://www.google.com/url?sa=i&rct=j&q=nielsen&source=images&cd=&cad=rja&docid=9oFmhGnnOdvBOM&tbnid=LgoI1Et8EmV-xM:&ved=0CAUQjRw&url=http://www.eduserv.org.uk/lns/agreements/nielsen-2012&ei=Hg-uUbrkE5CY9QTawICoBA&bvm=bv.47244034,d.dmQ&psig=AFQjCNFPX4QNo0IDoR-KskVj_4t-scg14w&ust=1370448012311156

http://www.google.com/url?sa=i&rct=j&q=assocaited+press+logo&source=images&cd=&cad=rja&docid=f8UCG2z28aThjM&tbnid=EsBwmElHlK2-sM:&ved=0CAUQjRw&url=http://www.webpronews.com/the-associated-press-goes-bold-with-new-logo-2012-02&ei=iQ-uUbfKBo7U9ASixYGIAw&bvm=bv.47244034,d.dmQ&psig=AFQjCNEjliIZp-EU48v5JX73h4FrftK1SQ&ust=1370448130400528

https://www.google.com/url?sa=i&rct=j&q=&esrc=s&frm=1&source=images&cd=&cad=rja&docid=jG3mv_TI7NpzwM&tbnid=iN7L2G4LTCNgLM:&ved=0CAUQjRw&url=https://itunes.apple.com/us/app/salesforce-mobile/id281826146?mt=8&ei=gT2uUYbFKOeOiALkoYCICA&bvm=bv.47380653,d.cGE&psig=AFQjCNGfIxs5Oh83SXl3FQi87Z3LKQ_yxg&ust=1370459891742010

http://www.google.com/url?sa=i&rct=j&q=goggle+plus+logo&source=images&cd=&cad=rja&docid=_z-k-jknbj4N3M&tbnid=MnEsWj9pm2a7JM:&ved=0CAUQjRw&url=http://www.johnkamal.com/why-use-google-plus-for-business/google-plus-logo/&ei=osauUdqFDua8igKt7oDYCw&bvm=bv.47380653,d.cGE&psig=AFQjCNGYoWHFbLjU617HdvAFRlA0oIt9AA&ust=1370495005252767


Digital Marketing

Information Governance

Information Analytics

HP Autonomy solutions family, powered by IDOL

IDOL

Compliance, Litigation Readiness, Storage

Optimisation, Database Archiving

Supervision & Policy Management

eDiscovery

Supervision

Legal Hold

Unified Information Access & Analytics

Voice of the Customer

Media Intelligence

Video Surveillance

Big Data Analytics

Enterprise Search

Knowledge Mgmt

Content Access & Extraction

Policy-Driven Info Mgmt

Records Mgmt

Legal Content Mgmt

Business Process Mgmt

Document Mgmt

Records Mgmt

Workflow Automation

Legacy Clean Up

Server Data Protection

Virtual Server Data Protection

Remote & Branch Office Data Protection

Endpoint Device Data Protection

Enterprise Content Mgmt

Information Archiving & eDiscovery

Data Protection

Digital Experience Mgmt

Web Optimisation

Search Engine Marketing

Marketing Analytics

Contact Centre Mgmt

Rich Media Mgmt

Augmented Reality

Marketing Optimisation

Hybrid

OEM

Software

Cloud the OS for human information


Autonomy IDOL Big Data Use Cases


Inflexible analytical technologies inhibit effective comprehensive analysis

Big data infrastructure best practices

Risk Exposure: poor performance and suboptimal resource / storage usage

Cost: degraded performance, poor scalability & inability to rapidly iterate and tune queries increases probability that you will not generate the insight sought in a timely manner

Best Practice: Design the index structure to support the intended use cases needed by the application. Many technologies are not forgiving after setup. Pick a flexible technology like Autonomy IDOL that allows for configuration/ optimisation before and after deployment.


Aircraft manufacturer streamline finding the right data

Real world: expertise networks Business need

• Employees waste 30 min/day finding info, duplicate work of others

• Identify expertise across global community of 35,000 engineers

• Avoid traditional, manual approaches such as users describing areas of interest with predefined keywords

IDOL Solution

• Generate user profiles automatically and in real time based on the pages visited and documents read

• Alert employees when documents, other employees match the work they are doing

Business benefits

• Reduce time spent retrieving information by over 90%

• Identify teams working on similar projects across the globe



IDOL-powered automatic categorisation and intelligent sectioning


Risk Exposure: Manual categorisation and sectioning is slow and lends itself to human error. Important information can be missed.

Cost: Increased labour overhead time for processing and searching data increases spend while effectively restricting an organisation's ability to conduct comprehensive intelligent, context based analysis. Net result: missed opportunities and poor decision making.

Best Practice: Incorporate technology such as Autonomy IDOL that can automatically categorize, tag and section data


Consumer services company

Real world: understanding customers

Business need

• Need better data mining of customer and affiliate calls into the call centre (average of 20,000 calls / day)

• Build better understanding of the customer to drive additional revenue, more personalised offers

IDOL Solution

• Use of Autonomy Qfiniti and IDOL to create a detailed record of customer contact sessions

• Generate reports to better assess the performance of each representative and improve processes / customer service

Business benefits

• Improved efficiency of the call centre / First Call Resolution

• Enhanced upsell opportunities as agents make offers to callers



IDOL-powered solution to combine unstructured and structured data


Risk Exposure: Existing information silos inhibit comprehensive data analysis leading to inaccurate misinformed decision-making lacking discovery and analysis

Cost: Limited dataset that is bounded by existing institutionalised KPIs and rigid analytical processes increases the probability that key trends and business opportunities will be missed.

Best Practice: A proper big data infrastructure such as Autonomy IDOL should be able to analyse all file types from as many relevant repositories as possible, including Hadoop, to perform the analysis.

Use case: Government agency sensitive document management


Re-insurance company

Real world: understanding risk Business need • Understand risk exposure across many different contracts based on a variety of

factors (i.e. geography, sector, relationships between entities)

• Information heavily fragmented across repositories / subsidiaries, not normalised, and details are in text files

Solution • Use IDOL to index data across structured and unstructured repositories

• Present data to analysts in a very intuitive information discovery interface

Business benefits • Reduced risk / increased profitability

• Increased employee productivity



Demo – Autonomy Explore


Designed to tackle the multichannel / big data analytics

Autonomy Explore Connectivity to touch points across websites, contact centres and the social web drive broad user applications

IDOL

Autonomy Explore

Brand reputation

mgmt.

News Email Blog Voice Web Video Apps Review Survey

Cross channel optimisation

Next-gen speech

analytics

Voice of the

customer

Social media

monitoring

Customer interaction

survey

First contact

resolution

Customer experience analytics

Operational efficiency

IDOL


Return on Information How do you measure value?

Time

Data value

Delivery cost

= ROI Return on Information

Data sources

Data volumes

Depth of analytics

Role of users

Hardware Software Services Support


HP Autonomy IDOL – the OS for Human

Are You Ready for Big Data?

Key big data best practices • Legacy data clean-up

• Proper field handling & query syntax

• Automatic categorisation and intelligent sectioning of data

• Combine unstructured and structured data

• Optimised business outcomes

Drives these big data benefits • Enables collaboration and innovation

• Improves productivity

• Delivers better, faster decision making

• Enables you to predict and act on real-time information

• Optimises your business outcomes


Thank you

Gary Palmer

Sales Manager UK- Unified Information & Access Analytics

[email protected]

HP Autonomy