CS183C: Blitzscaling
Instructors: Allen Blue, Reid Hoffman, John Lilly & Chris Yeh
October 20, 2015

Organizational Scale 3: Village

Now for the big shift.

Class Structure: Organizational Scale
Org Scale
(employees)
User Scale
(B2C users)
Customer
Scale (B2B)
Business
Scale (rev)
OS1: Family 1s 10,000s 0 <$10M
OS2: Tribe 10s 100,000s 1s $10M+
O3: Village 100s 1,000,000s 10s $100M+
OS4: City 1,000s 10,000,000s 100s $1B+
OS5: Nation 10,000s 100,000,00+ 1,000+ $5B+

OS1: The Household
Identify a non-obvious market opportunity where
you have a unique advantage and/or approach.
Iteratively build a product with strong product/
market fit

OS2: The Tribe
Execute & iteratively improve a plan which gets you
to significant market share.

OS3: The Village
Identify, plan and execute the core business you
will scale up.

OS3: The Village
Identify, plan and execute the core business you
will scale up.
… with a plan to scale more

OS3: The Village
Identify, plan and execute the core business you
will scale up.
… with a plan to scale more
… and do it fast

OS3: The Village
1. Articulate the core business you will scale up
first
2. Identify critical steps to scale that business
3. (Hyper)grow an organization to execute it
4. Finance for hypergrowth and future growth

OS3: Articulating the Core Business
Goals for the core business:
1. Create continued growth
2. Generate growing revenue
3. Build competitive advantage
4. Grow strategic assets for later opportunities

LinkedIn All-Hands
February 17, 2010

OS3: Critical Components to Scale the Core Business
• What must you do to scale the core business?
• Across growth, revenue
• Product and Technology
• Go-to-market (sales, marketing)
• Partnerships

Product Plan
February, 2010

Viral Growth Engine
Continue viral engine improvements to drive member growth and critical mass within professional context
Example products: Reg. optimization, New User Experience, In-Box, Outlook Integration, SEO, Address Book
Tablestakes
Professional Identity ecosystem
Establish leading identity ecosystem by building upon unique database of 60M+ members
Example products: Profile improvements/game dynamics, SEO, Search, APIs, Mobile
Professional Insights & Knowledge Sharing
Be the essential source for professional shared knowledge and business intelligence
Example products: NUS, Sharing tools, Groups V2, Inapps, Outlook & Twitter Integration
GamechangersValue
Firm Foundation
Improve and scale site resilience & reliability, development productivity, data reliability, API’s
Measurements: uptime, load time, developer activity,
Underlined: New focus in 2010
Data
Targeting &
analytics
WVMP,
MyStats
Matching
PYMK
Warehousing
Mining
Global Monetization
Leverage unique business model to monetize assets while adding value to members on a global basis
Example products: Online Jobs, Recruiter, Premium subs, Display Ads, Self-serve Ads, Business Pages
Strategic Stack

Strategic Stack
Security Addressbook bcard Skills
Code Modularity Profile - Engagement Apps / InApps
Productivity Tools APIs Career Center
Distributed Computing Rec Engine / Intelligence Salary
Data Reliability / Scale Engine / WVMP
Feature APIs Mobile
Reg Optimization / NUX Business Pages
PYMK International - Languages
SEO
Address Book
Profile - Data
Inbox / Comm
Core Search
NUS / Sharing
Groups
Standardization
A/B Testing Platform
Online Jobs
Subs
Recruiter
Payment Platforms
DirectAds
Display Support
CS Tools
Core Strategic Venture

Talent Solutions GTM
March, 2010

LinkedIn 3.0 / Scaling 10x
February, 2010

OS3: Organization
• Your organization has to change fundamentally
• The right CEO
• Key executives for critical areas
• Core mission, culture, and values to enable rapid distributed scaling
• An HR function that can hypergrow
• Necessary processes to allow large groups to work together
• Navigate necessary changes among founders and early employees
• Robust reporting to allow business not only to learn, but also to plan

Leadership, Culture, Hiring, Process
2008-2010

© 2009 LinkedIn All rights reserved. Confidential 60
LinkedIn Values and Culture
Members Come First - Candidates are also our members, leave them
feeling great about LinkedIn regardless of our decision to hire or not.
Be compassionate, offer to take a candidate for a quick walk, for a
break, offer snack/beverages if they look tired.
Relationships Matter - Candidates will either advocate us, say
nothing about us, or speak negatively about us based on how we treat
them. Glassdoor.com and other sites/blogs keep all companies on
their toes in terms of reputation and sharing stories.
Open, Honest and Constructive - consider this as you answer the
candidate’s questions and as you write your own feedback after the
interview.
Demand Excellence - consider this not only of the candidate but
yourself regarding how you conduct the interview... don’t focus too
much on technical/analytical skills so they overshadow your
assessment of the candidate’s creativity and vision.
Take Intelligent Risks - If the candidate doesn’t have the experience
in the talent solutions space or social media, or if you initially rate as B
+ rather than A+, as yourself if they have the raw materials and
potential to become an A+ within a short timeframe.
Act Like an Owner - Talent is our most important asset. We expect
our employees to act as an owner in each decision they make, no
matter how big or small.
Transformation of world,
company and self
Integrity
Collaboration
Humor
Results

Tech All-Hands
December, 2009

People/Recruiting/Hiring
● Best people produce best outcomes
● Need to keep bar high in the hiring/recruiting
process
● Need to understand our limitations and bring
outside expertise where needed
● Need to be flexible in our resource allocation (it is
okay/desirable to move around the organization to
apply key personnel to key projects)
● Onboarding/Ongoing Training/Mentoring are key.

Why technologists want to work at Linkedin
● Having a positive/lasting impact on the world by developing products that create
economic opportunities for people on a global basis.
● Building systems that scale and perform is paramount (think 10X).
● Data drives our solutions: Searching, querying, analysis of this data in real-time, near-
real time, or batch creates value for our users, and our paying customers.
● The business models (Subscription, Corporations, Advertising) are a diverse source of
revenue that require real value propositions, and technical excellence in delivery.
● Combining speed of execution with quality solutions, while still pushing the envelope on
new/improved features requires engineering skill sets that are unheard of in traditional
enterprise computing, and are hard to find even in the Internet.
● Engineers will constantly learn/use new technologies to create leading edge solutions.
● Great engineers want to work with great engineers.
● Constant improvement requires new talent/additional expertise to solve new/difficult
challenges.
● When you come to work here, you will, by definition, have a large impact. ~ 150
technologists today
● Access to the senior leadership is real, actual, and actionable. CEO->VP->Director-
>Manager->Engineer

Site Up -> Company Up

What do we want?
● Scrum vs. Waterfall: not the question; want best quality in timely fashion; good
outcomes depend on good engineers + good engineering practices (AND function
required here)
● Prioritize the list of Infrastructure + Product features merge sorted: We apply
resources against that list, and the result is 2 clear choices, either add more people
or cut the line higher so that some things don’t get done (ideally there is no
distinction between features and infrastructure in our shop)
● Will have multiple serving data centers running: ETA likely > = 1 year
● Architecture: we will tease apart dependencies for our 180 subsystems so that we
can have SLA’s for each one that we can trust and adhere to. All calling services
must be resilient to failure of called services. (Service oriented architecture)
● The Data scaling concern demands a solution: Examples: Comm, DWH, volume of
members, search index.
● Reminder: We have scaled this most excellent service successfully to this point.
Now we need to go to the next level. Think 10X and 100X. How would we solve for
that?

Current Release Process

Release Process Gap – Changes Needed
● The Current Process – What we do today
● Testing earlier for features: Example: the 26 feature branches in R951.
● Stabilizing the code base for integration
● Practice on staging
● Deploy a well tested reliable solution on prod
● Concern with this model
● It’s a long cycle (see previous slide) 2.5 week duration due to merges, compatibility testing, configuration
validation, heavy track team involvement etc…
● We still have large releases with many dependencies (some of which are not understood) which increases our
risk
● Inconsistent tooling across environments (Do we have enough envs?)
● Many release processes are still manual
● Post release hangover that says fix on fail: Bug fix releases are an assumed part of the Release Process. Our
goal should be to eliminate the need for this step.
● What do we want?
● Shorter cycle
● Smaller releases with “no” dependencies decreasing the risk. Each component released must be able to be
pushed and rolled back if needed.
● Automation for push-button releases (What if we were deploying to 5,000 servers not 500?)
● Don’t need to be fixing on fail because there are no bugs introduced into Prod
● Release when ready: (What does this mean?) a) Don’t release it on schedule because it didn’t pass our tests
OR b) Release any module anytime with low risk. I want B.

LinkedIn Series D
Summer, 2008

Global Internet Business Platform and Applications

LinkedIn - Confidential
2
Investment Snapshot
2008E Rev $82 million / 2.6x 2007
Members 20 million, adding 1M+ per month at ~
$0 CPA
Unique
visitors1
6.6 million / 2.8x y-o-y
Email
addresses
384 million
Connections 260 million
Bookings
($MM)
2006 2007 2008
Subscriptions $6.3 $17.3 $33.0
Jobs 2.1 6.3 15.1
Advertising 2.1 7.8 30.1
Corporate 1.8 7.9 34.5
Total $12.4 $39.2 $112.6
Investors Sequoia, Greylock, Bessemer, Marc
Andreessen, Peter Thiel
1 comScore January 2008 data
The next massive business model in
technology
▪ ~ $0 CPA per member, 1M+ / month
▪ High margin product: all digital goods, micro
cost of sale
▪ Highly scalable: digital goods, infinitely
replicable
▪ Network effects: network between users,
network between business lines
▪ Huge markets: recruiting, media, services,
sales, productivity software and others
➢ Google for finding professionals
➢ eBay for Labor Markets
➢ Microsoft for Internet productivity

LinkedIn - Confidential
5
Summary
The Network
Key Differentiation:
- Business focus: features, brand, network
- Viral growth: entirely by individuals’ actions
- Value scales with entire network (network effects)
- Growing in every industry, globally
- Organic growth into every business

LinkedIn - Confidential
6
Largest Professional Network
Domestic
Growth Days
0 to 1MM members 477
1 to 2MM members 181
5 to 6MM members 102
9 to 10MM members 60
18 to 19MM members 28
199 of top 200 markets
grew 70%+ in 2007; 155
grew 100%+
0
5
10
15
20
5/1/03 9/1/03 1/1/04 5/1/04 9/1/04 1/1/05 5/1/05 9/1/05 1/1/06 5/1/06 9/1/06 1/1/07 5/1/07 9/1/07 2/1/08
Domestic International
Millionsofmembers
Globally x4 larger than
nearest competitor; 50x
larger in the U.S.

LinkedIn - Confidential
7
Best and Broad Demographics
School: 58K
HBS: 17K
School: 50K
GSB: 8K
13K
32K
19K
13M University Alumni
31K
Employees: 58K
Alumni: 23K
19K
Employees: 15K
Alumni: 12K
Employees: 116K
Alumni: 71K
1.9M F500 Employees
41
27%
$109,762
Demographics
Average Age
Average HHI
HHI >$150K
78%College Grad
Portfolio
$250K+
28%
1.2M Small Business Owners
2.2M Senior Executives
VPs at every F500 company
Source: @plan Winter 2007/2008, internal data
13K
Employees: 13K
Alumni: 9K

LinkedIn - Confidential
11
Summary
Media
Key Differentiation:
- User generated content
- Best of class demographics
- Unique targeting capabilities
- Organic growth in every industry, globally
- Ability to scale across the web
- Future possibilities with self-service, B2B lead gen

LinkedIn - Confidential
26
0$100
12.5$100
25$100
37.5$100
$100$100
Dice Monster HotJobs eBay Google Xing
LinkedIn Revenue Upside
$86.91
Mean:
$34.05
Mean:
$21.08
Mean:
$10.52
Upside revenue opportunity
Current revenue projections
Job boards Internet
leaders
Business/
social
networking
Revenue/worldwide unique visitors
$0
$200
$400
$600
$800
$1,000
2007 2008E 2009E
($34.05 Ave Rev/User)
x 5.5MM Uniques)
($34.05 Ave Rev/User)
x13.4MM Uniques)
($34.05 Ave Rev/User)
x25.0MM Uniques)
LinkedIn potential revenue

Appendix

Articulating biz

The Bullseye
Jeff’s articulation of LinkedIn’s bullseye: Talent Solutions
Description of the business: Passive Recruiting and how it works.
Main point is the clarity with which we chose this target, and were
willing to subordinate almost everything but user growth to it.

User Growth
User Growth understood as:
Viral tuning
SEO and Public Profiles
Some known user value (network updates via email, receiving job
offers)
Some user value experiments (news, app platform, etc.)

Revenue Growth
Main focus on revenue growth will be growth of field sales
Reasoning for this
Some online sales, but not for big-$$ accounts
Other revenue sources beginning to enter the mix, but not core

Strategic Moats
Professional Identity would be primary moat
Defined roughly as size of network x quality of average profile
Main contributors were user growth and user activity.
Also first-mover advantage on passive recruiting would allow us to
lock in customers.
But we also felt we needed to respond to Facebook’s F8
announcement, which might have created a competitor built on top of
FB.

Future strategic assets
Non-Jobs brand
Potential discover of additional value propositions
improves brand,
Drives growth and profile moats
builds additional platforms for future businesses

Summary
A growing network of professionals with valuable profiles, driven by
viral tuning and value experimentation
Will form the foundation for a sales-driven business focused on large
enterprise accounts…
And we will do some competitive blocking on App Platforms.

Key steps to succed

Changing roles for founders/early team
Jean-Luc, engineering changes
New engineering group leaders
Turnover with new execs

Data
Building our data function

Daily, 7-Day Cumulative Avg, Week over Avg 4 Weeks, Year over YearMetrics:
Signups
0
22,500
45,000
67,500
90,000
112,500
-40%
0%
40%
80%
120%
6/8/09
6/17/09
6/26/09
7/5/09
7/14/09
7/23/09
8/1/09
8/10/09
8/19/09
8/28/09
9/6/09
9/15/09
Daily 7-Day Cumulative Avg Week over Avg 4 Weeks
Year over Year
Guest Invites
0
100,000
200,000
300,000
400,000
500,000
600,000
-100%
0%
100%
200%
300%
6/8/09
6/17/09
6/26/09
7/5/09
7/14/09
7/23/09
8/1/09
8/10/09
8/19/09
8/28/09
9/6/09
9/15/09
Daily 7-Day Cumulative Avg Week over Avg 4 Weeks
Year over Year
Uniques
0
1,600,000
3,200,000
-80%
0%
80%
160%
6/8/09
6/17/09
6/26/09
7/5/09
7/14/09
7/23/09
8/1/09
8/10/09
8/19/09
8/28/09
9/6/09
9/15/09
Daily 7-Day Cumulative Avg Week over Avg 4 Weeks
Year over Year
Page Views
0
10,000,000
20,000,000
30,000,000
40,000,000
50,000,000
-100%
0%
100%
200%
300%
6/8/09
6/17/09
6/26/09
7/5/09
7/14/09
7/23/09
8/1/09
8/10/09
8/19/09
8/28/09
9/6/09
9/15/09
Daily 7-Day Cumulative Avg Week over Avg 4 Weeks
Year over Year
Searches
0
1,000,000
2,000,000
3,000,000
4,000,000
5,000,000
-160%
0%
160%
320%
6/8/09
6/17/09
6/26/09
7/5/09
7/14/09
7/23/09
8/1/09
8/10/09
8/19/09
8/28/09
9/6/09
9/15/09
Daily 7-Day Cumulative Avg Week over Avg 4 Weeks
Year over Year
Premium Subs (New + Recurring)
$0
$40,000
$80,000
$120,000
$160,000
-80%
0%
80%
150%
6/8/09
6/17/09
6/26/09
7/5/09
7/14/09
7/23/09
8/1/09
8/10/09
8/19/09
8/28/09
9/6/09
9/15/09
Daily 7-Day Cumulative Avg Week over Avg 4 Weeks
Year over Year
Members Joining Groups
0
40,000
80,000
120,000
160,000
-80%
0%
80%
160%
240%
320%
6/8/09
6/17/09
6/26/09
7/5/09
7/14/09
7/23/09
8/1/09
8/10/09
8/19/09
8/28/09
9/6/09
9/15/09
Daily 7-Day Cumulative Avg Week over Avg 4 Weeks
Year over Year
Groups Created
0
500
1,000
1,500
2,000
2,500
-100%
0%
100%
200%
300%
6/8/09
6/15/09
6/22/09
6/29/09
7/6/09
7/13/09
7/20/09
7/27/09
8/3/09
8/10/09
8/17/09
8/24/09
8/31/09
9/7/09
9/14/09
Daily 7-Day Cumulative Avg Week over Avg 4 Weeks
Year over Year
Job Dollars
$0
$10,000
$20,000
$30,000
$40,000
$50,000
-80%
0%
80%
150%
6/8/09
6/17/09
6/26/09
7/5/09
7/14/09
7/23/09
8/1/09
8/10/09
8/19/09
8/28/09
9/6/09
9/15/09
Daily 7-Day Cumulative Avg Week over Avg 4 Weeks
Year over Year Add a Comment
Comments
9/9/2009
4:10:27 PM
8/20/2009
9:05:35 PM
8/20/2009
6:13:53 PM
8/19/2009
7:34:57 PM
8/19/2009
6:54:30 PM
8/19/2009
6:54:12 PM
8/19/2009
6:53:46 PM
8/11/2009
8:42:25 PM
W/W jobs increase driven by 10% more
spend per buyer due to job pack purchases
and 8% better conversion
For Jobs on Wednesday, 8/19: Conversion
decreased 9% W/W but spend per buyer
increased 6% and traffic to the flow
increased 3%. We’re investigating the root
cause of the conversion decreases that
we’ve been seeing.
New subs bookings growth driven by
greater number of annual plans purchased
relative to monthly plans (Business YR up
24% wk/wk and Business Plus YR up 18%
wk/wk)
“W/W declines driven by drops in
conversion and spend per buyer. All hands
are on deck investigating if something in
last week's release or Saturday's Oracle
upgrade is causing this.”
Online Job sales were down –17% Y/Y at
$39.7K but are trending towards being up
Y/Y in the next 3 weeks.
Page Views came in at 45.8M for Tuesday,
the largest day since 27th January and the
second highest day ever, up 78% Y/Y.
Signups came in at 108.5K for Tuesday, the
largest day since 27th January.
The spike in the year over year numbers
towards the end of May 09 is due to a site
outage in May 08
Daily Executive Dashboard