Playing Nice in the Product Playground
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Transcript of Playing Nice in the Product Playground
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2015
Playing Nice in the Product Playground
Building Data Teams:data scientists, engineers, and product managers
working together to create innovative data products
Anu TewaryOctober 15, 2015
#GHC15
2015 Anu Tewary@anutewary
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2015
Pop quiz …
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2015
product vision
business impact
success measures
effective architecture
scalability & robustness
metrics & monitoring
not sure what this product does, but look at the 2% lift I can get from this model...
ooh, ooh, a Dirichlet prior is what this needs!!
is this good for an ICML or KDD paper?
[ 1 ]
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2015
product vision
business impact
success measures
effective architecture
scalability & robustness
metrics & monitoring
not sure what this product does, but look at the 2% lift I can get from this model...
ooh, ooh, a Dirichlet prior is what this needs!!
is this good for an ICML or KDD paper?
Data scientists navel gazing in a corner?!
[ 1 ]
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2015
product vision
business impact
success measures
rapid experimentation
simple models first
right metrics
let’s write a new streaming framework for the weekly dashboard!
we’re not meeting our SLAs, let’s write a faster json parser!
let’s write an optimized distributed graph database for our data scientist.
[ 2 ]
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2015
product vision
business impact
success measures
rapid experimentation
simple models first
right metrics
let’s write a new streaming framework for the weekly dashboard!
let’s write a faster json parser in Clojure!
silver bullet: graph database, fp, lambda arch
[ 2 ]
Engineers reinventing the tech wheel?!
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2015
rapid experimentation
simple models first
right metrics
forget A/B testing, my gut tells me this is the way to go...
revenue impact? Who cares! Build it anyway!
no time to instrument! Let’s go to market and we’ll do that later - I’m sure that the numbers will look good!
[ 3 ]
effective architecture
scalability & robustness
metrics & monitoring
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2015
rapid experimentation
simple models first
right metrics
forget A/B testing, my gut tells me this is the way to go...
revenue impact? Who cares! Build it anyway!
no time to instrument! Let’s go to market and we’ll do that later - I’m sure that the numbers will look good!
[ 3 ]
effective architecture
scalability & robustness
metrics & monitoring
Product in a bubble?!
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2015
Data Science
data product
Product
Engineering
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2015
3
Three Steps to Risa**
21
** Risa is to Nirvana as Spark is to Hadoop
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2015
321
Build an Awesome Team
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2015
awesome team
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2015
never settle
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2015
find the right mix
minimum
prodds
eng
good
good
good
target
great
good
good
prodds
eng great
good
good
prodds
enggreat
good
great
prodds
eng
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2015
form pods around product
personalization & reco pod
real time data capture &
stream proc. pod
businesssearch pod
real timecommercegraph pod
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2015
blur the boundaries
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2015
321
Solve a Big Problem
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2015
Solve a big problemidentify big problem
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2015
keep score
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2015
change, pivot, iterate
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2015
321
Get Out of the Way
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2015
time
trust the team to become experts
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2015
anyone can represent the team
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2015
your role as a coach?
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2015
engage!
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2015
Three Steps to Risa**
3
2
1 awesome team (pods)
solve a big problem (pods)
get out of the way (pods)
** Risa is to Nirvana as Spark is to Hadoop
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2015
Most companies are not there yet
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2015
Example 1: Multinational banking and financial services company
Took a “technology first” approach: wanted to build a hadoop cluster, because they had heard they should
No product vision, but tremendous (!) possibilities
Not connected closely with business needs
No data science
build an awesome team
solve a big problem
engage
prodds
enggood
tinytiny
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2015
Example 2: Large media company
Excellent engineering team
Good product team, but not data driven
Good metrics and beginning data science. Did not iterate quickly; data and product were too decoupled
build an awesome team
solve a big problem
engage
?
prodds
engamazing
tinygood
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2015
Example 3: Large advertising firm
Data-driven product team, but limited vision
Engineering team not product focused. Could not iterate quickly
Non-existent data science
build an awesome team
solve a big problem
engage
good
tiny
ok
prodds
eng
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2015
Example 4: Attempt at Introspection
An awesome team with data, product and engineering working together
Solving hard problems – for individuals and small businesses
Need to do a lot more work to get the right metrics in place – need more work to be 100% eyes on, hands off.
build an awesome team
solve a big problem
engage
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2015
3
2
1 awesome team (pods)
solve a big problem (pods)
get out of the way (pods)
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2015
Anu Tewary@anutewary
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2015
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