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Business Intelligence Summit

Parthiv sheth2014

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About Hyatt Hotels Corporation

55+ years young550+ hotels/resorts47 countries95,000+ associates10 premier brandsGold PassportPublicly held (NYSE: H)$4.2B in FY2013Hyatt.com

Analytics mission

Descriptive Analytics

• Reports• Dashboards

Diagnostics Analytics

• Drilldowns• Link to

transactions

Predictive Analytics

• Event analysis

• Forecasting

Prescriptive Analytics

• Modeling

What’s best that can happen?

What will happen?

Why it happened?What happened?

Evolution of Analytics

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How to get here?

Data• Getting access is relatively easy

Analysis• Objective and rigorous analysis is difficult

Insights• Finding insights is hard

Action• Acting on insights to produce favorable outcomes is harder

Operations

• Operationalizing all of the above with consistency and continuous improvement is nearly impossible

5

Data, Analysis & Insights Scale

We saw We conquered

Analysis Insights

Access

Quality

Timely

Action

Operations

We came

6

Winning Formula

Org. Issues

Leaders

SiloesAssets

People

Process

People

Issues

Control

WIIFMSkills

7

People & Organizational Issues

Easy

Tough

Analytics Maturity

Leader

Culture

Structure

Incentive

8

Ingredients

CEO

Marketing CxO

Operations CxO

Finance CxO

Analytics CxO

Customers

Product

Service

...

9

What Success Looks Like

10

Tipping sacred cows

Are You Ready?

Should IT Lead?

Data overload

?

Got Big Data?

Is Tech A Silver Bullet?

12

What Do You Believe?

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Are You Ready for Analytics?

“On average, people should be more skeptical when they see numbers. They should be more willing to play around with the data themselves.” – Nate Silver• Analytics is sexy again! Consumerization of Analytics• Data and statistics literacy gap• Analytics revolution has to precede data democracy

Image source: cnn.com

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Engineers

Image source: Dilbert.com

15

Should IT Lead an Analytics Program?

“Stop being engineers” – Dilbert’s pointy haired boss• Analytics ≠ Reporting & Data Warehousing• Analytics projects unlike IT projects – data, methods, scope.• IT is often a cost center, lacks strategic influence• HBR - “Why IT Fumbles Analytics” • Conflicts with core IT tenets• Engineers vs. Scientists

Image source: Dilbert.com

IT

Business

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Suggestions for Alignment Conundrum• Put yourself in their shoes

• Market IT

• Understand Engineers vs. Scientists

• Transform from inside out to outside in

• Avoid new shiny object syndrome

• Cross-pollinate – people, training

• Adopt agile (iterative) vs. waterfall (linear)

• Done is better than perfect

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Can you have too much data?

“Not everything that can be counted counts and not everything that counts can be counted” – Albert Einstein

• Can possibly eliminate sampling issues.• Half-life of data. Add a new V – volatility• Tyranny of choice. Less is more• eDiscovery

Image source: Fotolia

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Got Big Data?

“Every day, three times per second, we produce the equivalent of the amount of data that the Library of Congress has in its entire print collection, right? But most of it is like cat videos on YouTube or 13-year-olds exchanging text messages about the next Twilight movie.” – Nate Silver• NASA exploration requires Petabytes, many analyses do not.• Requires a new mindset• Possible enabler, but not a strategy.

Image source: alleywatch.com

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Is Technology a Silver Bullet?

“The computer is a moron” – Peter Drucker

• If it is broke, tools alone will not fix it!• Data quality – garbage in, garbage out• Evaluation of new technologies:

– What will it tell you or let you do?– What can you do about it or with it?– How will it make you more profitable?

People• Literacy• Skills• Incentives

Organization• Assets• Leadership• CAO/CDO

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Food For Thought“In God we trust, all others must bring data.” – W. Edwards Deming

“There are lies, damned lies, and statistics.” “Facts are stubborn, but statistics are pliable.” – Mark Twain

“It is not information overload. It's filter failure.” – Clay Shirky

“All models are wrong, but some are useful.” – George E. P. Box

"What's the use of having developed a science well enough to make predictions if, in the end, all we're willing to do is stand around and wait for them to come true.“ – Sherwood Rowland

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Questions?

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