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LEAN ANALYTICS & LOCAL GOVALISTAIR CROLL
April 22, 2013
Tuesday, 23 April, 13
Alistair CrollCo-Author, Lean Analytics
Tuesday, 23 April, 13
www.leananalyticsbook.com@leananalytics@byosko | @acroll
Lean AnalyticsUse data to build a
better business faster.
Tuesday, 23 April, 13
http://www.flickr.com/photos/itsgreg/446061432/
Analytics is the measurement of movement towards your business goals.
Tuesday, 23 April, 13
Most startups don’t know what they’ll be when they grow up.
Tuesday, 23 April, 13
Paypalfirst built for Palmpilots
Most startups don’t know what they’ll be when they grow up.
Tuesday, 23 April, 13
Paypalfirst built for Palmpilots
Freshbookswas invoicing
for a web design firm
Most startups don’t know what they’ll be when they grow up.
Tuesday, 23 April, 13
Paypalfirst built for Palmpilots
Freshbookswas invoicing
for a web design firm
Wikipediawas to be written by
experts only
Most startups don’t know what they’ll be when they grow up.
Tuesday, 23 April, 13
Paypalfirst built for Palmpilots
Freshbookswas invoicing
for a web design firm
Wikipediawas to be written by
experts only
Mitelwas a
lawnmower company
Most startups don’t know what they’ll be when they grow up.
Tuesday, 23 April, 13
Hotmailwas a
database company
Paypalfirst built for Palmpilots
Freshbookswas invoicing
for a web design firm
Wikipediawas to be written by
experts only
Mitelwas a
lawnmower company
Most startups don’t know what they’ll be when they grow up.
Tuesday, 23 April, 13
Hotmailwas a
database company
Flickrwas going to be an MMO
Paypalfirst built for Palmpilots
Freshbookswas invoicing
for a web design firm
Wikipediawas to be written by
experts only
Mitelwas a
lawnmower company
Most startups don’t know what they’ll be when they grow up.
Tuesday, 23 April, 13
Hotmailwas a
database company
Flickrwas going to be an MMO
Twitterwas a
podcasting company
Paypalfirst built for Palmpilots
Freshbookswas invoicing
for a web design firm
Wikipediawas to be written by
experts only
Mitelwas a
lawnmower company
Most startups don’t know what they’ll be when they grow up.
Tuesday, 23 April, 13
Hotmailwas a
database company
Flickrwas going to be an MMO
Twitterwas a
podcasting company
Autodeskmade desktop
automation
Paypalfirst built for Palmpilots
Freshbookswas invoicing
for a web design firm
Wikipediawas to be written by
experts only
Mitelwas a
lawnmower company
Most startups don’t know what they’ll be when they grow up.
Tuesday, 23 April, 13
Kevin Costner is a lousy entrepreneur.
Don’t sell what you can make.Make what you can sell.
Tuesday, 23 April, 13
Tuesday, 23 April, 13
The basic Lean message islearn and adapt, fast.
Tuesday, 23 April, 13
“What information consumes is rather obvious: it consumes the attention of its recipients.Hence a wealth of information creates a poverty of attention, and a need to allocate that attention efficiently among the overabundance of information sources that might consume it.”
(Computers, Communications and the Public Interest, pages 40-41, Martin Greenberger, ed., The Johns Hopkins Press, 1971.)
Tuesday, 23 April, 13
http://www.flickr.com/photos/art_es_anna/288880795/Tuesday, 23 April, 13
Tuesday, 23 April, 13
Tuesday, 23 April, 13
Tuesday, 23 April, 13
Lean Analytics lesson 1:Most government projects have an attention or a connectivity problem. This is where you will spend most of your time innovating.
Tuesday, 23 April, 13
Empathy stage:Localmind hacks Twitter
• Stage: Empathy• Model: UGC/mobile
• Real-time question and answer platform tied to locations.• Needed to find out if a core behavior—answering questions about a place—
happened enough to make the business real
Tuesday, 23 April, 13
Localmind hacks Twitter
• Before writing a line of code, Localmind was concerned that people would never answer questions.• This was their biggest risk: if questions went unanswered users would have a
terrible experience and stop using Localmind.• Ran an experiment on Twitter
• Tracked geolocated tweets in Times Square• Sent @ messages to people who had just tweeted, asking questions about
the area: how busy is it; is the subway running on time; is something open; etc.
• The response rate to their tweeted questions was very high.• Good enough proxy to de-risk the solution, and convince the team and
investors that it was worth building Localmind.
Tuesday, 23 April, 13
Tuesday, 23 April, 13
Hits A metric from the early, foolish days of the Web. Count people instead.
Tuesday, 23 April, 13
Hits A metric from the early, foolish days of the Web. Count people instead.
Page views Marginally better than hits. Unless you’re displaying ad inventory, count people.
Tuesday, 23 April, 13
Hits A metric from the early, foolish days of the Web. Count people instead.
Page views Marginally better than hits. Unless you’re displaying ad inventory, count people.
Visits Is this one person visiting a hundred times, or are a hundred people visiting once? Fail.
Tuesday, 23 April, 13
Hits A metric from the early, foolish days of the Web. Count people instead.
Page views Marginally better than hits. Unless you’re displaying ad inventory, count people.
Visits Is this one person visiting a hundred times, or are a hundred people visiting once? Fail.
Unique visitors This tells you nothing about what they did, why they stuck around, or if they left.
Tuesday, 23 April, 13
Hits A metric from the early, foolish days of the Web. Count people instead.
Page views Marginally better than hits. Unless you’re displaying ad inventory, count people.
Visits Is this one person visiting a hundred times, or are a hundred people visiting once? Fail.
Unique visitors This tells you nothing about what they did, why they stuck around, or if they left.
Followers/friends/likes
Count actions instead. Find out how many followers will do your bidding.
Tuesday, 23 April, 13
Hits A metric from the early, foolish days of the Web. Count people instead.
Page views Marginally better than hits. Unless you’re displaying ad inventory, count people.
Visits Is this one person visiting a hundred times, or are a hundred people visiting once? Fail.
Unique visitors This tells you nothing about what they did, why they stuck around, or if they left.
Followers/friends/likes
Count actions instead. Find out how many followers will do your bidding.
Time on site, or pages/visit
Poor version of engagement. Lots of time spent on support pages is actually a bad sign.
Tuesday, 23 April, 13
Hits A metric from the early, foolish days of the Web. Count people instead.
Page views Marginally better than hits. Unless you’re displaying ad inventory, count people.
Visits Is this one person visiting a hundred times, or are a hundred people visiting once? Fail.
Unique visitors This tells you nothing about what they did, why they stuck around, or if they left.
Followers/friends/likes
Count actions instead. Find out how many followers will do your bidding.
Time on site, or pages/visit
Poor version of engagement. Lots of time spent on support pages is actually a bad sign.
Emails collected How many recipients will act on what’s in them?
Tuesday, 23 April, 13
Hits A metric from the early, foolish days of the Web. Count people instead.
Page views Marginally better than hits. Unless you’re displaying ad inventory, count people.
Visits Is this one person visiting a hundred times, or are a hundred people visiting once? Fail.
Unique visitors This tells you nothing about what they did, why they stuck around, or if they left.
Followers/friends/likes
Count actions instead. Find out how many followers will do your bidding.
Time on site, or pages/visit
Poor version of engagement. Lots of time spent on support pages is actually a bad sign.
Emails collected How many recipients will act on what’s in them?
Number of downloads
Outside app stores, downloads alone don’t lead to lifetime value. Measure activations/active accounts.
Tuesday, 23 April, 13
2-sided market model:AirBnB and photography
• Stage: Revenue• Model: 2-sided marketplace
• Rental-by-owner marketplace that allows property owners to list and market their houses. Offers a variety of related services as well.
Tuesday, 23 April, 13
AirBnB tests a hypothesis
• The hypothesis: “Hosts with professional photography will get more business. And hosts will sign up for professional photography as a service.”
• Built a concierge MVP
• Found that professionally photographed listings got 2-3x more bookings than the market average.
• In mid-to-late 2011, AirBnB had 20 photographers in the field taking pictures for hosts.
Tuesday, 23 April, 13
2008 2009 2010 2011 2012
2 million
4 million
6 million
8 million
10 million
NIGHTS BOOKED
20 photographers
Friday, November 9, 12Tuesday, 23 April, 13
http://www.flickr.com/photos/bootbearwdc/1243690099/
Pick the right experiments
Tuesday, 23 April, 13
If it won’t changehow you behave,it’s a
badmetric.http
://w
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flickr.
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circa
sass
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5676
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Tuesday, 23 April, 13
The five Stages of Lean Analytics
Tuesday, 23 April, 13
The five Stages of Lean AnalyticsTh
e st
age
you’
re a
t
Tuesday, 23 April, 13
The five Stages of Lean Analytics
Empathy
The
stag
e yo
u’re
at
Tuesday, 23 April, 13
The five Stages of Lean Analytics
Empathy
Stickiness
The
stag
e yo
u’re
at
Tuesday, 23 April, 13
The five Stages of Lean Analytics
Empathy
Stickiness
Virality
The
stag
e yo
u’re
at
Tuesday, 23 April, 13
The five Stages of Lean Analytics
Empathy
Stickiness
Virality
Revenue
The
stag
e yo
u’re
at
Tuesday, 23 April, 13
The five Stages of Lean Analytics
Empathy
Stickiness
Virality
Revenue
Scale
The
stag
e yo
u’re
at
Tuesday, 23 April, 13
The five Stages of Lean Analytics
Empathy
Stickiness
Virality
Revenue
Scale
The
stag
e yo
u’re
at
E-commerce SaaS MediaMobile
appUser-gencontent
2-sidedmarket
The business you’re in
Tuesday, 23 April, 13
The five Stages of Lean Analytics
Empathy
Stickiness
Virality
Revenue
Scale
The
stag
e yo
u’re
at
E-commerce SaaS MediaMobile
appUser-gencontent
2-sidedmarket
The business you’re in
One MetricThat Matters.
Tuesday, 23 April, 13
Lean Analytics lesson 2:Choose one metric around which to rally support, and reject vanity metrics ruthlessly.
Tuesday, 23 April, 13
Choose only one metric.
Tuesday, 23 April, 13
http://www.flickr.com/photos/connortarter/4791605202/
Metrics are likesqueeze toys.
Tuesday, 23 April, 13
Metrics in practice:The Lean Analytics Cycle
Tuesday, 23 April, 13
Metrics in practice:The Lean Analytics Cycle
Pick OMTM
Tuesday, 23 April, 13
Metrics in practice:The Lean Analytics Cycle
Draw a linein the sand
Pick OMTM
Tuesday, 23 April, 13
Metrics in practice:The Lean Analytics Cycle
Find a potential
improvement
Draw a linein the sand
Pick OMTM
Tuesday, 23 April, 13
Metrics in practice:The Lean Analytics Cycle
Without data: make a good guess
Find a potential
improvement
Draw a linein the sand
Pick OMTM
Tuesday, 23 April, 13
Metrics in practice:The Lean Analytics Cycle
With data:find a
commonality
Without data: make a good guess
Find a potential
improvement
Draw a linein the sand
Pick OMTM
Tuesday, 23 April, 13
Hypothesis
Metrics in practice:The Lean Analytics Cycle
With data:find a
commonality
Without data: make a good guess
Find a potential
improvement
Draw a linein the sand
Pick OMTM
Tuesday, 23 April, 13
Make changes in production
Hypothesis
Metrics in practice:The Lean Analytics Cycle
With data:find a
commonality
Without data: make a good guess
Find a potential
improvement
Draw a linein the sand
Pick OMTM
Tuesday, 23 April, 13
Make changes in production
Design a test
Hypothesis
Metrics in practice:The Lean Analytics Cycle
With data:find a
commonality
Without data: make a good guess
Find a potential
improvement
Draw a linein the sand
Pick OMTM
Tuesday, 23 April, 13
Measure the results
Make changes in production
Design a test
Hypothesis
Metrics in practice:The Lean Analytics Cycle
With data:find a
commonality
Without data: make a good guess
Find a potential
improvement
Draw a linein the sand
Pick OMTM
Tuesday, 23 April, 13
Did we move the needle?
Measure the results
Make changes in production
Design a test
Hypothesis
Metrics in practice:The Lean Analytics Cycle
With data:find a
commonality
Without data: make a good guess
Find a potential
improvement
Draw a linein the sand
Pick OMTM
Tuesday, 23 April, 13
Success!
Did we move the needle?
Measure the results
Make changes in production
Design a test
Hypothesis
Metrics in practice:The Lean Analytics Cycle
With data:find a
commonality
Without data: make a good guess
Find a potential
improvement
Draw a linein the sand
Pick OMTM
Tuesday, 23 April, 13
Pivot orgive up
Success!
Did we move the needle?
Measure the results
Make changes in production
Design a test
Hypothesis
Metrics in practice:The Lean Analytics Cycle
With data:find a
commonality
Without data: make a good guess
Find a potential
improvement
Draw a linein the sand
Pick OMTM
Tuesday, 23 April, 13
Draw a new linePivot orgive up
Success!
Did we move the needle?
Measure the results
Make changes in production
Design a test
Hypothesis
Metrics in practice:The Lean Analytics Cycle
With data:find a
commonality
Without data: make a good guess
Find a potential
improvement
Draw a linein the sand
Pick OMTM
Tuesday, 23 April, 13
Draw a new linePivot orgive up
Try again
Success!
Did we move the needle?
Measure the results
Make changes in production
Design a test
Hypothesis
Metrics in practice:The Lean Analytics Cycle
With data:find a
commonality
Without data: make a good guess
Find a potential
improvement
Draw a linein the sand
Pick OMTM
Tuesday, 23 April, 13
Lean Analytics lesson 3:There’s no “finished.” Just more iterations.
Tuesday, 23 April, 13
The B2B stereotype
http
://w
ww.
tech
dige
st.tv
/200
7/02
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l
Domainexpert
Disruptionexpert Operations
• Domain expert knows industry and the problem domain. Has a Rolodex; proxy for customers.
• Disruption expert knows tech that will produce a change Sees beyond the current model.
Tuesday, 23 April, 13
The B2B stereotype
http
://w
ww.
tech
dige
st.tv
/200
7/02
/im_a
_pc_
im_a
_ma.
htm
l
Domainexpert
Disruptionexpert Operations
• Domain expert knows industry and the problem domain. Has a Rolodex; proxy for customers.
• Disruption expert knows tech that will produce a change Sees beyond the current model.
Tuesday, 23 April, 13
Three typical approaches
Enterprise pivot
Copy and rebuild
Disrupt a problem
Create a popular consumer product then pivot to tackle the enterprise
Dropbox
Take an existing consumer or open source idea and make it enterprise-ready
Yammer, MapR
Convince the enterprise to discard the old way because of overwhelming advantages.
Taleo, Google Apps
Tuesday, 23 April, 13
Lean Analytics lifecyclefor an enterprise-focused startup
Empathy Consulting to test ideas and bootstrap the business
Lock-in, IP control, overfitting
Stage Do this Fear this
Tuesday, 23 April, 13
Lean Analytics lifecyclefor an enterprise-focused startup
Empathy Consulting to test ideas and bootstrap the business
Lock-in, IP control, overfitting
Stickiness Standardization and integration; shift from custom to generic
Ability to integrate; support
Stage Do this Fear this
Tuesday, 23 April, 13
Lean Analytics lifecyclefor an enterprise-focused startup
Empathy Consulting to test ideas and bootstrap the business
Lock-in, IP control, overfitting
Stickiness Standardization and integration; shift from custom to generic
Ability to integrate; support
Virality Word of mouth, references, case studies
Bad vibes; exclusivity
Stage Do this Fear this
Tuesday, 23 April, 13
Lean Analytics lifecyclefor an enterprise-focused startup
Empathy Consulting to test ideas and bootstrap the business
Lock-in, IP control, overfitting
Stickiness Standardization and integration; shift from custom to generic
Ability to integrate; support
Virality Word of mouth, references, case studies
Bad vibes; exclusivity
Revenue Growing direct sales, professional services, support
Pipeline, revenue recognition, comp
Stage Do this Fear this
Tuesday, 23 April, 13
Lean Analytics lifecyclefor an enterprise-focused startup
Empathy Consulting to test ideas and bootstrap the business
Lock-in, IP control, overfitting
Stickiness Standardization and integration; shift from custom to generic
Ability to integrate; support
Virality Word of mouth, references, case studies
Bad vibes; exclusivity
Revenue Growing direct sales, professional services, support
Pipeline, revenue recognition, comp
Scale Channels, analysts, ecosystems, APIs, vertically targeted products
Crossing the chasm; Gorillas
Stage Do this Fear this
Tuesday, 23 April, 13
The Zero Overhead principle
A central theme to this new wave of innovation is the application of core product tenets from the consumer space to the enterprise.In particular, a universal lesson that I keep sharing with all entrepreneurs building for the enterprise is the Zero Overhead Principle: no feature may add training costs to the user. DJ Patil
Tuesday, 23 April, 13
Lean Analytics lesson 4:Government can learn from enterprise-focused startups: Disrupt a known problem with new technology.
Tuesday, 23 April, 13
Skunk Works for intrapreneurs
• The Lockheed Martin Skunk Works
Tuesday, 23 April, 13
Span of control and the railroads
• Daniel C. McCallum
Tuesday, 23 April, 13
The BCG matrix
Question marks!(low market share, high growth rate)
May be the next big thing. Consumes investment, but
will require money to increase market share.
Stars!(high growth rate, high market share)
What everyone wants. As market invariably stops
growing, should become cash cows.
Dogs!(low market share, low growth rate)
Barely breaks even, may be a distraction from better
opportunities. Sell off or shut down.
Cash cows!(high market share,
low growth rate) Boring sources of cash, to be milked but not worth additional investment.
Gro
wth
rate
Market share
Pivot to increasemarketshare
throughvirality,
attention
Pivot toincrease growth
rate throughdisruption
Pivot toredefine problem/solution through
empathy
Milk withrevenue
optimization asgrowth slows
• How businesses think about products or companies
• Lean is about moving up and to the right
Tuesday, 23 April, 13
BCG and policy
Publ
ic s
uppo
rt
Impact on society
Widelypopular
Widelyridiculed
Tiny Huge
Tuesday, 23 April, 13
BCG and policy
Pork
Publ
ic s
uppo
rt
Impact on society
Widelypopular
Widelyridiculed
Tiny Huge
Tuesday, 23 April, 13
BCG and policy
Banningleaded gasoline
Pork
Publ
ic s
uppo
rt
Impact on society
Widelypopular
Widelyridiculed
Tiny Huge
Tuesday, 23 April, 13
BCG and policy
“I Declare today Jebbediah Springfield day”
Banningleaded gasoline
Pork
Publ
ic s
uppo
rt
Impact on society
Widelypopular
Widelyridiculed
Tiny Huge
Tuesday, 23 April, 13
BCG and policy
“I Declare today Jebbediah Springfield day”
Banningleaded gasoline
No more big soda
Pork
Publ
ic s
uppo
rt
Impact on society
Widelypopular
Widelyridiculed
Tiny Huge
Tuesday, 23 April, 13
The Lean Analytics lifecyclefor an Intrapreneur
Empathy Find problems; don’t test demand. Skip the business case, do analytics
Entitled, aggrieved customers
Stage Do this Fear this
Beforehand Get buy-in Political fallout
Tuesday, 23 April, 13
The Lean Analytics lifecyclefor an Intrapreneur
Empathy Find problems; don’t test demand. Skip the business case, do analytics
Entitled, aggrieved customers
Stickiness Know your real minimum based on expectations, regulations
Hidden “must haves”, feature creep
Stage Do this Fear this
Beforehand Get buy-in Political fallout
Tuesday, 23 April, 13
The Lean Analytics lifecyclefor an Intrapreneur
Empathy Find problems; don’t test demand. Skip the business case, do analytics
Entitled, aggrieved customers
Stickiness Know your real minimum based on expectations, regulations
Hidden “must haves”, feature creep
Virality Build inherent virality in from the start; attention is the new currency
Luddites who don’t understand sharing
Stage Do this Fear this
Beforehand Get buy-in Political fallout
Tuesday, 23 April, 13
The Lean Analytics lifecyclefor an Intrapreneur
Empathy Find problems; don’t test demand. Skip the business case, do analytics
Entitled, aggrieved customers
Stickiness Know your real minimum based on expectations, regulations
Hidden “must haves”, feature creep
Virality Build inherent virality in from the start; attention is the new currency
Luddites who don’t understand sharing
Revenue Consider the ecosystem, channels, and established agreements
Channel conflict, resistance, contracts
Stage Do this Fear this
Beforehand Get buy-in Political fallout
Tuesday, 23 April, 13
The Lean Analytics lifecyclefor an Intrapreneur
Empathy Find problems; don’t test demand. Skip the business case, do analytics
Entitled, aggrieved customers
Stickiness Know your real minimum based on expectations, regulations
Hidden “must haves”, feature creep
Virality Build inherent virality in from the start; attention is the new currency
Luddites who don’t understand sharing
Revenue Consider the ecosystem, channels, and established agreements
Channel conflict, resistance, contracts
Scale Hand the baton to others gracefully Hating what happens to your baby
Stage Do this Fear this
Beforehand Get buy-in Political fallout
Tuesday, 23 April, 13
Lean Analytics lesson 5:When working from within, the difference between a special operative and a rogue agent is a mandate.
Tuesday, 23 April, 13
E-commerce enterprise
• Stage: Scale• Model: e-commerce
• EMI was a big music company trying to understand how its customers bought content
Tuesday, 23 April, 13
David Boyle tackles a small problem
• David Boyle, SVP Insight, EMI Music, ran the insight group
• Had billions of rows of data, but nobody wanted to analyze it
• Instead started a survey project, got a million responses, used this data to sell the idea of “data-driven” business
• Then got support for the broader data initiative.
Tuesday, 23 April, 13
David Boyle tackles a small problem
• Talked to 1M people in 3y
• At any point, surveying 12 people in the world
• Boiled this down to a few fundamental profiles
Tuesday, 23 April, 13
Lean Analytics lesson 6:Start with a less important project (preferably one that involves intelligence gathering.) Then use that success for bigger undertakings.
Tuesday, 23 April, 13
Where your lean lives:It’s learning: Places with lots of dataIt’s rapidly iterated: Apps or softwareIt’s popularizing: Moving up a boxIt’s impact-increasing: Moving right a boxIt has high uncertainty: De-risk with an MVPIt’s boundable: Lean hates molasses
Tuesday, 23 April, 13
Pic by Twodolla on Flickr. http://www.flickr.com/photos/twodolla/3168857844Tuesday, 23 April, 13
ARCHIMEDES HAD TAKEN
BATHS BEFORE.
Tuesday, 23 April, 13
Once, a leader convinced others in the absence of data.
Tuesday, 23 April, 13
Now, a leader knows what questions to ask.
Tuesday, 23 April, 13
Thank you!
Further discussion:[email protected]
Contact staff: [email protected]
Tuesday, 23 April, 13