playing nice in the product playground
TRANSCRIPT
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
2015
Pop quiz …
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 ]
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 ]
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 ]
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?!
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
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?!
2015
Data Science
data product
Product
Engineering
2015
3
Three Steps to Risa**
21
** Risa is to Nirvana as Spark is to Hadoop
2015
321
Build an Awesome Team
2015
awesome team
2015
never settle
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
2015
form pods around product
personalization & reco pod
real time data capture &
stream proc. pod
businesssearch pod
real timecommercegraph pod
2015
blur the boundaries
2015
321
Solve a Big Problem
2015
Solve a big problemidentify big problem
2015
keep score
2015
change, pivot, iterate
2015
321
Get Out of the Way
2015
time
trust the team to become experts
2015
anyone can represent the team
2015
your role as a coach?
2015
engage!
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
2015
Most companies are not there yet
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
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
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
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
2015
3
2
1 awesome team (pods)
solve a big problem (pods)
get out of the way (pods)
2015
Anu Tewary@anutewary
2015
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