Innovation @ Google
Scott Thomson - Customer Solutions & Innovation
22 Nov 2016
4 Gears of Innovation
NEXT
PRACTICE
Proprietary + Confidential
4
DISRUPTIVE INVESTMENT
3
LEAN STARTUP PRACTICES
INNOVATOR’S CHASM
BEST
PRACTICE
2
AGILE WORK PRACTICES
1
FIT FOR PURPOSE TECHNOLOGY
4 Pillars of Innovation
Culture
Collaboration
Proprietary + Confidential
Capability
Capital
The Quest for a Perfect Team
Proprietary + Confidential
Psychological
Safety
Emotional
Intelligence
Equal Share
of Voice
Safe Place to Take Risks
Social Sensitivity
Conversational turn taking
Project Aristotle | 180 Teams | Over 3 Years | +50 Years Academic Research
Gender Diversity's Link to Better Stock Returns | Morgan Stanley
10X Thinking
Proprietary + Confidential
Think Big
Hard Tasks First
Failure is OK
10x Moon Shots
Competitive Advantage
Collaboration Essential
Proprietary + Confidential
TGIF (Held on a Thursday in the USA, on Friday elsewhere)
Transparent objectives &
progress reporting
Leadership time
investment
Open Q&A, input &
collaboration
Proprietary + Confidential
How do we turn
Sparks into flames?
How do we turn
Islands of IP into
Crowd-sourced
Knowledge
Pre-to-typing
Proprietary + Confidential
TEST
ILI
OLI
Test Everything
ILI
OLI
Every Opinion
is a Hypothesis
Initial Level
of Interest
Ongoing Level
of Interest
Proprietary + Confidential
Feature ranking & developer utilisation
Priorities
Clients
Impact
Votes
Stakeholder rankings
10
1
2
Developer Utilisation Hours
11%
Feature
requests
28%
Feature ranking
process
Infrastructure
34%
Available
27%
Ranked features
Bugs
Allocated
Release Trains & Dogfooding
Proprietary + Confidential
“Dogfooding”
https://labs.spotify.com/2014/03/27/spotify-engineering-culture-part-1/ - Spotify engineering culture
Developer Metrics (Mostly individual, but...)
IF, new property with 10k users…
Higher: user growth, velocity of features, launch frequency
Lower: release stability and resource usage
Proprietary + Confidential
IF, 500M user property…
Critical: release stability and resource usage/optimisation
Higher: revenue per user metrics
Lower: velocity of features and launch frequency
Executives that adhere to
Metrics that tie directly to
Business objectives
3x
Proprietary + Confidential
more likely to
hit their goals
Source New Study Reveals Why Integrated Marketing Analytics are Critical to Success, Think with Google, Forrester
Growth based metrics
Proprietary + Confidential
Executive
Sponsors
Growth based business metrics plan
Digital
Teams
Business
Outcome
Business
Drivers
Business
Strategies
Digital
Strategies
Digital
Analysts
Strategic
Experiments
KPIs /
Benefits
Analytics
Signals
Real-time
Dashboards
Line of
Effect
1-1 mapping
(Test the mapping)
Also see: http://nerds.airbnb.com/scaling-data-science/
F1
Proprietary + Confidential
15 years of evolution in Big Data
2002
GFS
MapReduce
Dremel
2004
2006
BigTable
Colossus
2008
Spanner
2010
BigQuery
Mesa
Millwheel
Dataflow
2012
2014
Data tools that power Google
Capture
Google App
Engine
Cloud Logs
Google DCLK,
AW, GA360
activity
Process
Proprietary + Confidential
Store
Analyze
BigQuery Storage
(tables)
BigQuery Analytics
(SQL)
Cloud Bigtable
(noSQL)
Cloud Dataflow
Batch
Stream
Cloud Dataflow
Real time analytics
and Alerts
Cloud Pub/Sub
Cloud
Monitoring
Cloud DataStore
Cloud Storage
(files)
Cloud ML
IOT on Google Cloud Platform
Proprietary + Confidential
Cloud
ML
https://cloud.google.com/solutions/architecture/real-time-stream-processing-iot
Proprietary + Confidential
+
Pub/Sub
BigQuery
Building a Scalable Geolocation Telemetry System
in the Cloud using the Google Maps API
Proprietary + Confidential
The sample application
collects street traffic data
captured from freeways
around San Diego, California,
in the United States, and then
shows traffic density heat
maps superimposed on a
Google map.
https://cloud.google.com/solu
tions/scalable-geolocationtelemetry-system-using-mapsapi
Proprietary + Confidential
Self driving car
https://www.google.com/selfdrivingcar/
Proprietary + Confidential
Machine learning
Mastering the Game of Go with Deep Neural Networks and Tree Search - David Silver, Aja Huang et al
Proprietary + Confidential
Machine learning
Google datacenters have half the overhead
of typical industry data centers
Largest private investor in renewables:
$2 billion generating 3.2 GW
https://www.tensorflow.org/
Applying Machine Learning produced
40% reduction in cooling energy
Remind me
AI-First
Show / tell me
how I?
What and
where
Turn on / off
what, when / where
Pay who when,
for what
Proprietary + Confidential
Tell who,
when / what
Meet with who,
when / where
Who is / did
what / when?
Play / Listen to
what / when
AI | Hardware | Cloud | Search | Messaging | Calendar | Maps | Photos | Video
Proprietary + Confidential
Try them yourself in your browser!
cloud.google.com/translate/
cloud.google.com/natural-language/
cloud.google.com/vision/
cloud.google.com/speech/
Conversational agents:
https://api.ai/
AI / Machine Learning: https://www.tensorflow.org/
Productivity & Collaboration
Marketing & Communications
360 Suite Core
Doubleclick
Capture
Process
Store
Analyze
Compute, Big Data
& Machine Learning
Development Tools & Apps
People operations
Logistics
Frontline productivity
In-premise devices
Data analysis & planning
The Future of Jobs - World Economic Forum 2016
“The Fourth Industrial Revolution, which includes developments in previously disjointed fields such as
artificial intelligence, machine-learning, robotics, and 3-D printing,
nanotechnology, genetics and biotechnology,
will cause
widespread disruption
not only
to business models but also to labour markets
over the next five years, with
enormous change predicted in the skill sets needed
to thrive in the new landscape.”
https://www.weforum.org/reports/the-future-of-jobs/
Final Thoughts
Get out of
The process
Proprietary + Confidential
Speak to
Real people
Collaborate
Extensively
Have some
Fun
Proprietary + Confidential
THANK YOU
Scott Thomson
Customer Solutions & Innovation
[email protected]