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Justin Herz
EVP, Digital Strategy,
Products, Platforms
Click to add textClick to add textClick to add text
BIG DATA DAY
LA 2018
0
The Global Leader InThe Creation,
Production, Distribution, Licensing &
Marketing Of All Forms Of Entertainment
&Their Related Businesses.
We Stand AtThe Forefront Of Every Aspect Of
The Entertainment Industry, From Feature
FilmsToTelevision,Animation, Comic Books,
Interactive Entertainment & Games, Product
& Brand Licensing, & Broadcasting.
1
INDUSTRY LEADER ACROSS KEY BUSINESSES
#1 OR #2 WW BOX OFFICE
9 OF LAST 10 YEARS
$4B+ WW BOX OFFICE
7 OF THE LAST 8 YEARS
THEATRICAL
#1 TV STUDIO
FOR LAST 9 SEASONS
ONE OF THE LARGEST LICENSORS OF
US PROGRAMMING
TELEVISION
ONLY STUDIO WITH
SCALED GAMES PUBLISHING
OVER $1 BILLION IN
2017 REVENUE
GAMES
2
SOME OF THE WORLD’S GREATEST FRANCHISES
Classic Animation Horror
3
• Exhibitor – AMC, Regal, ArcLight, etc.
• Digital – iTunes, Amazon, Netflix, Hulu,
etc.
• Physical –Walmart, Best Buy,Target, etc.
• Distribution –Television stations, cable
operators, etc.
4
WB HAS LONG BEEN DISINTERMEDIATED
FROM ITS CUSTOMERS
To better address
its customers,
WB has invested
heavily in a
scaled data &
tech stack
• Hundreds of millions of
addressable entertainment
consumers – industry-wide
• Billions of entertainment
interactions recorded against
consumer database
• Trillions of business records
5
The stack connects the entire studio
Sales
Supply
Chain
Production
Marketing
Physical
Pre-
Production
Ratings
Consumer
Research
Exhibitor
Social
Digital
Linear
Operations
Consumer
Behavior
Inventory
Spend
Competitors
Content
Protection
Over the
Top
Theme Parks
6
And powers data science deployments
across the studio
• AI solutions in visual mastering, e.g. color correction
• Dynamic pricing optimization
• ML selection of audiences for marketing campaigns
• ML forecasting
• ComputerVision Analysis ofTrailers and Ads
• Autonomous vehicle R&D
• AI handling of manual processes
7
Data Science
value is generated
via adoption,
but human
adoption is often
not automatic
Consumer Intelligence - Confidential 8
Data science measures of validity (prediction
accuracy, etc.) are often not enough to create
human adoption of a new data product
Data science adoption among business
stakeholders requires human adoption &
process integration
Integrating data science into a mature company
is not like integrating it into a technology
product
8
Barriers to Data Science Adoption
• Inertia, i.e. businesses and people who
have functioned in a certain way for a
long time
• Data science outputs can look similar to
outputs from traditional methods, e.g.
market research
• Complex methods can have a “black box"
problem
• Fear of automation 9
Deploying data science across the
studio
• AI solutions in visual mastering, e.g. color correction
• Dynamic pricing optimization
• ML selection of audiences for marketing campaigns
• ML forecasting
• ComputerVision Analysis ofTrailers and Ads
• Preparing for autonomous vehicles
• AI handling of manual processes
Consumer Intelligence - Confidential 10
More confounding: the most accurate data
science techniques are often the least explainable
10
Adoption of data science solutions can sometimes
feel like a faith-based religious conversion
Non-believers
Sudden conversion
Gradual conversion
11
Easing adoption
• Data visualization as an entry point
• Interpretability and human
explanation
• Actionability
– Example: how valuable is a prediction
prediction without the ability to affect the
affect the prediction?
• Embedding data scientists within key
business groups, i.e. federated model
• Contextualization of results
12
There is
NO
SILVER
BULLET
for
adoption
• Prioritize activity based on value / upside
• Understand upfront what is most valuable to
the business, e.g. explanatory analysis of the
underlying drivers / dynamics, accuracy of
prediction, etc.
• Deeply understand existing processes &
dynamics
• Remain flexible, work in parallel with existing
routines
• Reinforce the goals of AI, e.g. human
assistance 13
JOIN OUR
TECH TALENT COMMUNITY
WarnerBrosCareers.com
text WARNERBROS to 67076
Incredible OpportunitiesTo Create
BusinessValueThrough Cutting-Edge
Technologies & Data Science

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Data Con LA 2018 Keynote - Keynote deck by Justin Herz

  • 1. Justin Herz EVP, Digital Strategy, Products, Platforms Click to add textClick to add textClick to add text BIG DATA DAY LA 2018 0
  • 2. The Global Leader InThe Creation, Production, Distribution, Licensing & Marketing Of All Forms Of Entertainment &Their Related Businesses. We Stand AtThe Forefront Of Every Aspect Of The Entertainment Industry, From Feature FilmsToTelevision,Animation, Comic Books, Interactive Entertainment & Games, Product & Brand Licensing, & Broadcasting. 1
  • 3. INDUSTRY LEADER ACROSS KEY BUSINESSES #1 OR #2 WW BOX OFFICE 9 OF LAST 10 YEARS $4B+ WW BOX OFFICE 7 OF THE LAST 8 YEARS THEATRICAL #1 TV STUDIO FOR LAST 9 SEASONS ONE OF THE LARGEST LICENSORS OF US PROGRAMMING TELEVISION ONLY STUDIO WITH SCALED GAMES PUBLISHING OVER $1 BILLION IN 2017 REVENUE GAMES 2
  • 4. SOME OF THE WORLD’S GREATEST FRANCHISES Classic Animation Horror 3
  • 5. • Exhibitor – AMC, Regal, ArcLight, etc. • Digital – iTunes, Amazon, Netflix, Hulu, etc. • Physical –Walmart, Best Buy,Target, etc. • Distribution –Television stations, cable operators, etc. 4 WB HAS LONG BEEN DISINTERMEDIATED FROM ITS CUSTOMERS
  • 6. To better address its customers, WB has invested heavily in a scaled data & tech stack • Hundreds of millions of addressable entertainment consumers – industry-wide • Billions of entertainment interactions recorded against consumer database • Trillions of business records 5
  • 7. The stack connects the entire studio Sales Supply Chain Production Marketing Physical Pre- Production Ratings Consumer Research Exhibitor Social Digital Linear Operations Consumer Behavior Inventory Spend Competitors Content Protection Over the Top Theme Parks 6
  • 8. And powers data science deployments across the studio • AI solutions in visual mastering, e.g. color correction • Dynamic pricing optimization • ML selection of audiences for marketing campaigns • ML forecasting • ComputerVision Analysis ofTrailers and Ads • Autonomous vehicle R&D • AI handling of manual processes 7
  • 9. Data Science value is generated via adoption, but human adoption is often not automatic Consumer Intelligence - Confidential 8 Data science measures of validity (prediction accuracy, etc.) are often not enough to create human adoption of a new data product Data science adoption among business stakeholders requires human adoption & process integration Integrating data science into a mature company is not like integrating it into a technology product 8
  • 10. Barriers to Data Science Adoption • Inertia, i.e. businesses and people who have functioned in a certain way for a long time • Data science outputs can look similar to outputs from traditional methods, e.g. market research • Complex methods can have a “black box" problem • Fear of automation 9
  • 11. Deploying data science across the studio • AI solutions in visual mastering, e.g. color correction • Dynamic pricing optimization • ML selection of audiences for marketing campaigns • ML forecasting • ComputerVision Analysis ofTrailers and Ads • Preparing for autonomous vehicles • AI handling of manual processes Consumer Intelligence - Confidential 10 More confounding: the most accurate data science techniques are often the least explainable 10
  • 12. Adoption of data science solutions can sometimes feel like a faith-based religious conversion Non-believers Sudden conversion Gradual conversion 11
  • 13. Easing adoption • Data visualization as an entry point • Interpretability and human explanation • Actionability – Example: how valuable is a prediction prediction without the ability to affect the affect the prediction? • Embedding data scientists within key business groups, i.e. federated model • Contextualization of results 12
  • 14. There is NO SILVER BULLET for adoption • Prioritize activity based on value / upside • Understand upfront what is most valuable to the business, e.g. explanatory analysis of the underlying drivers / dynamics, accuracy of prediction, etc. • Deeply understand existing processes & dynamics • Remain flexible, work in parallel with existing routines • Reinforce the goals of AI, e.g. human assistance 13
  • 15. JOIN OUR TECH TALENT COMMUNITY WarnerBrosCareers.com text WARNERBROS to 67076 Incredible OpportunitiesTo Create BusinessValueThrough Cutting-Edge Technologies & Data Science

Editor's Notes

  1. Warner Bros. is the global leader in the creation, production, distribution, licensing and marketing of all forms of entertainment. . Our EVP of Global Research & Consumer Insights, Liz Huszarik, will talk about first party syndicated data position and compete effectively in the marketplace. Through these two groups we are leading the market in understanding the value and optimization of data for business decisions. We get the value of data
  2. Today, WB is performing at the top of our game. We have lead scale in major areas of entertainment. We are setting records at the box office with recent hits including Wonder Woman and the Oscar-nominated Dunkirk. We've been the #1 TV studio for the last 9 seasons. And we've built a large and growing games business with more than $1B in revenue in 2017 alone.
  3. WB is home to some of the world's biggest brands, including my personal favorite, Lego, As well as DC, Wizarding World, and, among many others. And if you are still having nightmares about a clown and red balloons because of It, yes, we are responsible for that too.
  4. As many of you know, one of the biggest challenges with data analysis is creating the connections between the data sets that you need. Data Intelligence is a centralized group at WB, we bring in different data sets from across the studio and create those connections We can compare box office sales or POS data for games and home video with production and media data, analyze consumer touchpoints from the theatrical to whv to games to consumer products and theme park windows…
  5. If you are really interested in a career in data with a creative studio we are the place to be.