2014 edison ceo summit - day 1 waves concurrent session

Waves Conference Room

Concurrent Session: 1:15 – 2:15pmWhat’s Your Big Data Credo?Phil Simon, author of The Visual Organization: Data Visualization, Big Data and the Quest for Better Decisions; and

Too Big Too Ignore: The Business Case for Big Data

Understanding Big Data

Edison Ventures

Phil Simon

Atlantic City, NJJune 18, 2004

Who am I?

@philsimon 4

• Award-winning author of six books, most recently The Visual Organization

• Speaker, consultant, and technology authority

Agenda

• Introduction• Who I am

• What is Big Data and why does it matter?

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Agenda

• What are companies currently doing with Big Data and what can we learn from them?

• Tips on getting started• Discussion• Big Data: Moving from buzzword

to practice

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What is Big Data, anyway?

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Big Data: Major Characteristics

• The 3 v’s• Mostly external to the

enterprise• Mostly unstructured data

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Data 101: Some Major Types

• Structured• Semi-Structured• Unstructured• Metadata

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Big Data: Major Characteristics

• Increasingly generated by machines, not people

• Inherently “unmanageable” in the traditional sense

• Doesn’t play nice with SQL

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Small Data Still Matters

• The era of Big Data does not mean that Small Data has become irrelevant

• Rather, Big Data extends the power of Small Data

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The Ability to Know Why

• Determine why things happen: • Why do customers buy what

they buy? • Why are some campaigns and

promotions are effective than others?

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1 + 1 = 5

• New data sources create new opportunities and potential value

• We can ask better questions of our data

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Big Data Tools

• Different statistical packages (R)• Hadoop• NoSQL/NewSQL• Sentiment Analysis• Text Analytics/Text Mining

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Big Data Tools

• Natural Language Processing

• A/B Testing• Predictive Analytics• Data Visualization

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Source: The Visual Thesaurus

How does Netflix use Big Data?What can we learn from it?

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Netflix Stats

• Roughly 48M customers• Nearly $28B market cap • Responsible for 34% of all

US weeknight Internet traffic

Data as of June 9, 2014

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The Netflix Data Credo - 1

• Data should be accessible, easy to discover, and easy to process for everyone.

Source: Netflix - tinyurl.com/tvo-netflix

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The Netflix Data Credo - 2

• The longer you take to find the data, the less valuable it becomes.

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The Netflix Data Credo - 3

• Whether a dataset is large or small, being able to visualize it makes it easier to explain.

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What does Netflix know about each of its 48M streaming customers?

• What they watch• When they watch• The device on which they’re

watching• When they pause and/or

resume watching

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How are other organizations currently using Big Data?

What can we learn from them?

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Other Big Data Examples

• Insurance• Healthcare• Financial Services

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Insurance

• Most car insurance companies base rates on simple demographic variables

• Progressive Pay as you Drive program collects real-time driver data

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Lessons

• Collect as much data as you can• Be transparent with your

customers about what you’re collecting—and what you’re going to do with it.

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Healthcare

• Used patient medical record data to identify nearly 200 people with diabetes who hadn’t been diagnosed yet.

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Lessons

• Go beyond structured data. There’s tremendous potential valuable to be gleaned from unstructured data.

• Act on insights without scaring customers.

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Financial Services

• RavenPack turns text from traditional and social media into structured feeds for quantitative applications

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Lessons

• Information like this can potentially help determine when sentiment towards a particular stock or set of stocks has changed

• Coupled with traditional investment measures, better decisions may very well result

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Getting Started with Big Data

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Big Data: Human Considerations

• Threatens the status quo and takes people out of their comfort zones

• Often meets with resistance—and lots of it

• Essential to the future of business• Often requires new skills.

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• Embrace data discovery• Think incrementally and

add new types of data• Don’t try to boil the ocean• Think description first,

prediction later

Recommendations on Getting Started

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• Manage expectations, under-promise, and over-deliver

• Build internal momentum• Aim for little victories—and the

communicate them• Make the skeptics and dataphiles

come to you

Recommendations on Getting Started

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• Reject “set it and forget it.”• Look outside of the organization• Lead, follow, or get out of the way• Describe first…predict later

Recommendations on Getting Started

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• It’s a marathon…• not a sprint

Recommendations on Getting Started

Discussion

Big Data: Moving from Buzzword to Practice

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• How can our organization use Big Data?• How can we learn more about our

customers? Increase retention? Upsell?• How do I monitor trends and my

competition?• How can I use new data sources to inform

product and positioning?

Discussion and Food for Thought

Connect with me

www.philsimon.com@philsimon

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Networking BreakPlease be seated back in WAVES at 2:30pm for the next concurrent session

Concurrent Session: 2:30 – 3:30pmCreate a Repeatable Winning Sales EngineElay Cohen, Co-founder & CEO SalesHood, former SVP Sales Productivity, salesforce.com

Elay Cohen Founder & CEO

How To Scale Deal and Ramp Velocity?

Elay CohenFounder, CEO, and Author

Former Senior Vice President, Sales Productivity salesforce.com

Creator of the Partner Relationship Management Category

Sales Productivity Is A $60B+ Problem

Sales training & meetings are

ineffective

Sales and Marketing GTM are not aligned

Reps aren’t ramping fast

enough

Difficult to scale velocity, certainty &

repeatability

We Solved These Sales Productivity Problems

From $500M to $3B

Deal Velocity

Ramp to Revenue

Revenue & rep productivity trend line

Think Like A CEO and Act Like an Entrepreneur

Own outcomes Pipeline Revenue Customer success Skills & development Marketing programs

First line sales managers make it happen

What It Takes To Win?

Sales Values & Process

Ongoing Learning & Sharing

Recruiting Machine

Sales Management Cadence

Go To Market

TEACH LEARN

B U S I N E S S T E C H N O L O G YE M O T I O N A L

P R E F E R E N C E R E A D I N E S S

PROVE

SIGN

CLOSE

L E G A L P U R C H A S I N G

You Need Culture,

Process, & Domain to

Create

1. What are they buying?

2. Why are they buying?

3. When are they buying?

4. Who is buying?

5. Who is paying?

Answer These Questions In Every Deal

Compelling Events Drive Urgency

Compelling Event Date

Internal Pressure

External Pressure

Personal Impact

Consequences of Inaction

Be Transparent About Metrics & Results Follow

Activity Emails Calls Connects

Pipeline1. Created2. Ratios3. Activity

Revenue1. Bookings2. New logos3. Cross-sell

Winning Sales Managers Create Team Cadence

Monthly Sales Team CalendarWeek 1: Kick Off & Forecast

Increase predictability

Week 2: Sales Topic & Pipeline

Improve sales skills

Week 3: Sales Topic & Pitch

Share best practices

Week 4: Close & Celebrate

Energize the team

Learning is Relevant, Ongoing, & Immediately Usable

World-class OnboardingPre-work, boot camps & coaching

Best Practice SharingPeer to peer deal strategies, pitches & proposals

Ongoing LearningSales meetings, 1:1s, mentors

1

2

3

Balance Best Practice Execution with Inspection

Focus rep on customer activity that matters

Share best practices across the team

Build a Recruiting Machine

Recruiting Scorecard1. Domain knowledge2. Success selling technology3. Quota accomplishments4. Customer references5. Peer references6. Presentation skills7. People skills8. Social selling9. Business acumen10. Sales pitch

The Pitch Try before you buy

Team Everyone interviews

Execute a Winning Go To Market Strategy

Marketing & sales alignment Product launches Partners & Resources Customer success Right leadership team

Internationalization Maturity Localization Inspection Balance cultures

Thank you.

Networking BreakPlease be seated back in AQUA at 3:45pm