UK & Ireland SAP User Conference 2013 Analytics Keynote

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Keynote for the Analytics track of the UK & Ireland SAP User Conference 2013, in Birmingham, UK

Transcript of UK & Ireland SAP User Conference 2013 Analytics Keynote

Analytics Keynote

“73% of keynote speakers know that the best way to get an audience’s attention is to present a useless factoid”

Timo Elliott, Innovation Evangelist, SAP

@timoelliott

Questions!

QuestionRater.com/ukisug13

© 2013 SAP AG. All rights reserved. 3

© 2013 SAP AG. All rights reserved. 4

“Every company is an IT company, every budget is an IT budget”

© 2013 SAP AG. All rights reserved. 5

SMAC* Down!*Social, mobile, analytics, cloud

“The real and virtual world will be one, consumer IT and organizational IT will be one”

© 2013 SAP AG. All rights reserved. 6

What Should You Do?

DIGITALIZEBUSINESSPROCESSES

PURSUEDIGITALBUSINESSMODELS

COMPETE FORBUSINESSMOMENTS

© 2013 SAP AG. All rights reserved. 7

© 2013 SAP AG. All rights reserved. 8

YASOHMDTIITW*

Bit, Byte, Kilobyte, Megabyte,

Gigabyte, Terabyte, Petabyte,

Exabyte, Zettabyte, Yottabyte….

* Yet Another Slide On How Much Data There Is In The World

Brontobyte or Hellabyte

© 2013 SAP AG. All rights reserved. 9Public

Information becomes what you sell…

i

i i

Businessownership

ITownership

HBR: “Analytics 3.0”

Descriptive:What happened?

Diagnostic:Why did it happen?

Predictive:What will happen?

Prescriptive:How can we make it happen?

Analytic maturity

Hindsight Insight Foresight

© 2013 SAP AG. All rights reserved. 11Public

No Analytics? Welcome to the HIPPO

Nucleus Research, Gartner, Fortune Magazine Forrester Research

Unlocking the value of “Dark Data”

10%

75%

Use AnalyticsToday

NeedAnalytics by 2020

Ability to manage and consume all data is getting harder

Not utilizing all the information

out there

Not leveraging the power of collective insight

Missing new insights

IT is not agile enough and the business wants to get involved

=

On average, companies only use 12% of their data.

“Big Data”

Transactions, Interactions, Observations

Map Reduce / Hadoop / NoSQL

Data Scientists

© 2013 SAP AG. All rights reserved. 14

Big Data Enterprise Data Warehouses

Scott Sandford, NASA Ames

Research Center

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Slide by Mark Madson, Third Nature Inc

16

Google Spanner

“NoSQL” is out, “NewSQL” is in…

“Data is stored in schematized semi-relational tables… Spanner supports general-purpose transactions, and provides a SQL-based query language”

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Imagine if Your Apps Looked Like a DW to BI Tools

SAP HANA

SAP HANA Live (Virtual Data Model)

Customer Service

Risk Management Team

Finance and Operations

Account Administration

Executive Management

Customers Channel Suppliers Accounting ForecastingInventory Products Pricing Planning

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Data Warehouse? Yes, But “Logical”

Real-Time Data Processing PlatformFewer Layers Same Core Data Simpler Landscape

Analyze &Transact inReal-time

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ns SAP RTDP

Transact

Analyze

Edward James Snowden

Edward Joseph Snowden

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Information Steward 4.2

Data Quality Advisor

Assess Recommend Tune

Data Profiling

Content Type Discovery

Validation Rules

Cleansing Rules

Match Rules

View Before / After Results

Fine Tune With What-If Analysis

Publish Rules

Redundancy Profiling

Address Profiling Validate address data

Dependency Profiling Identify attribute-level

connections in data. (Normalization rules practice)

Redundancy Profiling Identify degree of duplication

Uniqueness Profiling Identify non-unique data

Drill down to duplicate and non-duplicate

records

© 2013 SAP AG. All rights reserved. 25

But It’s Not About Technology

“The stone age was marked by man's clever use of crude tools; the information age, to date, has been marked by man's crude use of clever tools.”

© 2013 SAP AG. All rights reserved. 26

People Are The Most Important “Technology”

It takes expertise and creativity to turn technology into business innovation

80% of CEOs think they deliver a superior customer experience

Source: The New Yorker

-- but only 8% of customers agree.

© 2013 SAP AG. All rights reserved. 28

Engage Your Fans Does This Apply To You?

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Add Customer Value in Real-Time

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Optimize The Customer Experience With “Playnomics”

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Perfect Your Pricing and Packaging

© 2013 SAP AG. All rights reserved. 33

Help Your Partners Sell More

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Make Yourself Invaluable

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Give Your Executives Deep Visibility

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“Data-driven decision making played a huge role in creating a second term for the 44th President. In politics, the era of big data has arrived.”

- Time Magazine

Engage Your Fans

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Track Who Likes Your Products (And Why, And When…)

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Engage Your Students

“In the past five years, taxpayers have spent $9Bn on college students who drop out before year two”

© 2013 SAP AG. All rights reserved. 40

Learn Then Act“Saving 1% in Student Retention can save my University’s bottom line $1M a year”

By 2017, there will be close to $11 Billion in revenue from35-million homes using home automation platforms across the globe.

Source: GIGAom, 2013

Wearable devices have grown by 2x month over monthsince October 2012.

Source: Mary Meeker’s Internet Trends, 2013

Photo: Intel Free Press

© 2013 SAP AG. All rights reserved. 43

“We’ll put more computers in our laundry in a week than we’ve used in our lifetime so far”

Gartner

© 2013 SAP AG. All rights reserved. 44

The “Datification” of Daily Life

© 2013 SAP AG. All rights reserved. 45

The “Datification” of Daily Life

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The “Datification” of Daily Life

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The “Datification” of Daily Life

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The “Datification” of Daily Life

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Never Lose Anything Again

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You Are Being Watched

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Is Your TV Spying On You?

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© 2013 SAP AG. All rights reserved. 54

Discover Hidden Trends

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Optimize Maintenance

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Aggregate Insights

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Faster Iterations

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Experience Intelligence Center

Event Interception

Business Transformation

Make People Happy

I818297

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Make People Happy

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Develop Your Data Scientists

Kaoru Kawamoto – Japan’s First “Data Scientist of the Year”

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What, When, and Where

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Custom Visualization With Lumira

© 2013 SAP AG. All rights reserved. 63

Lumira and Visual Enterprise

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Mapping As New Analytical Tool (ESRI)

© 2013 SAP AG. All rights reserved. 67

Mapping stores on STM lines and stations

• STM Partners’ stores.

Create a Commerce Eco-System

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• Interact with consumer in the field• Run mobile marketing campaigns based

on consumer profile and location

• Interact with consumer in real-time anywhere, anytime.

• Design & run mobile marketing campaigns based on consumer profile and location

• Analyze consumer behavior in the field

Create a Commerce Eco-SystemA platform for real-time interactivity between consumers, STM and partners

SAP Precision Retailing(On-Demand, Multitenant, High Performance, Scalable)

• Receive information, discounts & Special offers

BI

CRM

Merchants

Outings

Transports

Partners

© 2013 SAP AG. All rights reserved. 69

A Personalized, Multi-Vendor Customer Experience

Valid at this time

For my profile (segments)

In the store(s) nearby

Eligible offers

Top x

What time is it ?Where am I?

What is my personal profile?What is my CRM profile?

Select Rate & Order Deliver & Learn

What are my preferences ?Where am I?

What is my personal profile?What is my CRM profile?

The rating is based on the learning engine and on the characteristics of the shopping context, the consumer preferences, and the frequency of presentation.

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Business Networks = information Networks

SuppliersBuyers

ProcurementSales

FinanceLogistics

Supply ChainSustainabilityCompliance

Partners

Ariba Network

More than 1M suppliers in more than 190 countries around the world  

Transact with suppliers – the Network handles over $460 billion per year in commerce  

Reduce supply costs – customers save a combined total of $82M daily

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Adapting to The New World of Analytics

Unleashing the Power of Collective Insight

Instantly predict market trends and customer needs and innovate new product and services quicker

Predict demand or supply across your entire Supply Chain immediately

Provide exactly the right offers and service levels to every customer

Understand what your customers & potential customers are saying about you, right now

Imagine the potential…

ENGAGE PREDICTVISUALIZE

© 2013 SAP AG. All rights reserved. 76

Directions

DECISION MAKER

DESIGNER

ANALYST

Explore Monitor

Design

Govern DATA Enrich Explain

Plan People

Analytics solutions from SAP

Agile Visualization

Advanced Analytics

Big Data

Mobile

Collaboration

Cloud

Enterprise Business Intelligence

© 2013 SAP AG. All rights reserved. 78

Innovation And Design Thinking

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Questions!

QuestionRater.com/ukisug13

Thank you

Timo Elliott, SAP

Email: timo.elliott@sap.comTwitter: @timoelliottBlog: timoelliott.com

Business Intelligence Timeline

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2000-2005 2005-2010 2011

No BI strategy

• No real BI strategy

• IT left to prioritize

• Multiple versions of the truth

One truth

• VELUX Performance model

• Standard reporting

• One truth

• Anchoring in finance

Future vision

• Extend reporting to more users

• Redefine our own role

• More end user flexibility

VELUX deployed our first Global BI solution around 2000 together with the first SAP implementations

A change in user profiles and patternsOver a period of 7 years we have seen several shifts in our BI user group in VELUX

The shifts seem to happen with shorter and shorter intervals

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• System Expert• Favored Excel as front

end• Could live with poor

performance• Primarily used data

from SAP

2005”The controller”

• General analyst• Wanted to use web

reports as well• Interested in data from

several sources• Demanded better

performance

2010”The analyst”

• Expecting BI self service• Want’s information on

mobile devices• Not scared of

technology, uses the right tool for the job

2012”You and me”

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© 2013 SAP AG. All rights reserved. 94Public

Advanced Profiling

Redundancy Profiling

Address Profiling Validate address data

Dependency Profiling Identify attribute-level

connections in data. (Normalization rules practice)

Redundancy Profiling Identify degree of duplication

Uniqueness Profiling Identify non-unique data

Drill down to duplicate and non-duplicate

records

© 2013 SAP AG. All rights reserved. 95Public

Visualization of Data QualityHigh-level balanced Data Quality Scorecard

Data quality score

metrics

Latest quality score

Quality trend over time / run

Key Quality Dimensions (KPI for data), customizable

© 2013 SAP AG. All rights reserved. 96Public

Business Value AnalysisData Quality Financial Impact Calculator

Connect financial ROI to data quality and information governance initiatives

Understand and demonstrate how bad data effects business bottom line

Identify potential savings using what-if analysis of quality level and costs

See drivers and metrics of financial impact calculation per failure