We explain the history of our agile organization with a focus on the latest round of evolution of our Product and Engineering organization, moving from business-oriented feature teams to mission teams.

1. From Feature Factories
to Mission Teams

2. My name is Frédéric Rivain, CTO of Dashlane.
We build a Password Manager,
to help you manage your
identity and your payments in a
simple and secure way
everywhere.

3. A bit of context
Funded in 2009 by Bernard Liautaud and 3 Centrale students
120 employees in Paris and New York
• Product & Engineering in Paris
• Marketing & Sales in New York
• Consumer product (B2C) + Enterprise offer (B2B)
• 8 “product & engineering” teams

4. An Agile Story
• Iterative evolution.
• Learning as we grow.
• Adapting to our needs and scale.
• Various states of maturity.
Garage Mode
2014
Move to Agile. Scrum
by the Book.
Roadmap &
Portfolio
2015
OKR
Feature /
Business Teams
2016
2017
Mission
Teams2018

5. Half-Baked Agility*
* As quoted from Felipe Castro

6. Half-Baked Agility*
Operations
Tactics
Strategy
Culture
Agile Development
Scrum, Kanban…
Lean
Goals / OKR
1
2
3
4
* As quoted from Felipe Castro

7. Running Agile Operations
• Scrum is about operational agility. A methodology for day-to-day organization.
• Wrap the Scrum cycle with a Lean process, to improve Alignement and Visibility
at Company level.
Formalize the
Project
Collaborative
Specifications
Development
Validation
Release to
Production
Assess
results
Evaluate and
prioritize
AGILE PRODUCTION
Stakeholder
Lean overall approach
Agile production cycle

8. Escaping the perfect Feature Factory
• Project-driven roadmaps
• Tracking feature delivery
• Only Agile at the Operations level.
• Strategy is based on annual goals with
overall top-down planning.

9. Expanding to an Agile Strategy
• Goals and Performance Management driven by OKR.
• Change the mindset:
 driving Outcome / Maximizing Value not Output
• More on OKR in Appendix if you are interested
Operations
Tactics
Strategy
Culture
Agile Development
Scrum, Kaban…
Lean
Goals / OKR
1
2
3
4

10. Looking for the
right organization

11. Legacy Platform Teams
• Originally, platform tech teams:
• Desktop, iOs, Android, Web, Server,
Semantic Engine
• Works well for small teams. With one
line of business.
• Starts hurting as you grow the team and
as you diversify:
• Synchronization issues between platforms
• Inconsistency in product
• Technical focus > Business focus
• Conway’s Law
• That structure does not scale well.

12. Transitioning to Business Teams
• Inspired by the Feature Teams model (a la Spotify)
• Cross-functional teams including:
• Product, Development, QA + Design, Analytics, Product Marketing, User Support
• « Mini Startup » inside the company, with end-to-end responsibility on their scope.
• Business focus
• Acquisition
• Conversion
• Retention
• 2 focused on B2B
• 1 for Partnerships
• 1 for our semantic engine

13. Transitioning again to Mission Teams
Business Teams
Mission Teams
Project
Teams
“Increase retention”
Too many ideas, no filtering lens for Product
No clear sense of when to stop and do something else
Lagging indicator-focused
“Get more passwords”
Lots of room for creativity within a boundary
Success is clear
Leading and lagging indicators
“Build feature X”
No room for ideas
Success is delivery not results
Leading indicator-focused

14. Scope is not business only
• Include perspectives from Product, Marketing, Engineering...
• Product Experience Team:
• The teams create the vision, strategy and idea implementation. They are actually shaping it.
• They see the whole: from the origin story all the way to the idea pushed to the customer.
• Teams feel empowered.

15. Upgrading the Feature Team Organization
• Cross-platform teams, with dedicated
resources and skills, based on Missions
• Small teams comprised of one Product
Manager, 2 to 6 engineers, one UX
designer.
• Co-located
• A double organization:
• Mission Teams
• « Platforms » communities of practice
MISSIONS
PLATFORMS
Mission
Team 1
Mission
Team 2
Mission
Team 3
… Mission
Team N
Product
Manager
x x x x
Scrum
Master
x x x x
QA x x x x
Server x x
iOS x xx
Android x xx
Windows x xx
Web x xxx
UX
Design
x x x x
Analytics x x x x
User
Support
x x x x

16. How we run it today
• 3-week Cadence
• 2 week Mission sprint
• 1 Platform Week
• Quarterly Review Meetings (Rodeos)
• Progress
• Mission Team review: Continue, Change, Disband
• Staffing
• Tools
• Jira + Confluence
• ProductBoard
• Communication
• Biweekly sprint reviews (for the teams themselves)
• Sprint Dashboards
• Town Hall Demos

17. Looking for value

18. Getting it “Right” versus to the “End”
EndStart
Right

19. Learning Drives Value
Idea Right
Discovery
Decision
Prioritize
Build
Learn Learn Learn
Build Build
Value Value Value

20. Generating Value
• Each initiative must generate at least one of the below…
1. Adoption: achieving customer value
2. Learning: from the customer
3. Feedback: internal discovery from Tech, Product…
4. Risk Management: reducing risk and unknowns

21. Password Import “Brain Dumps” Easy Account Detection
Area of focus (including
main KPI)
Reduce number of day 1 no password
events by 30%
Increase number of accounts storing >0
passwords on day 1 by 30%
Increase number of accounts storing >0
passwords on day 1 by 30%
Ideas (for how we might
address area of focus)
• Web history import: scan web history
and curate list of likely sites where user
has an account
• Notes app import: build a sync connector
with OneNote, Evernote, and other
popular notes apps to scan and parse
potential account/password pairings
• Pen and paper import: customers can
use their phones to SMS photos of pen
and paper password docs, process with
machine learning OCR (or mechanical
turk) to provide same-day import
• Intermittent questioning: test a
program by which PC users are
intermittently asked to provide
passwords one at a time via a ”brain
dump” request. Ideal frequency and
user experience will be determined via
the test.
• Logos matchmaking: in OOBE, show a
set of logos of popular consumer sites
and have users check all that apply.
Follow-up by asking users to provide
credentials for them (including a bulk
add feature if appropriate).
• Email scan: sync with user’s email to
construct a picture of all likely
accounts a user will have; prompting
user to verify and provide credentials.
• Internet pass-through: test a feature
by which Dashlane monitors the
user’s internet connection for a period
of time, thus creating likely account
lists regardless of which browser is
being used; prompt user for
credentials at the end of the
monitoring period
Additional KPI's (used to
track success)
• % increase in import activity • <% bounce rate from brain dump
prompt experience
• % accuracy in suggested versus
claimed accounts
OKR: Increase desktop week 4 engagement rate from 18% to 30% by significantly increasing day 1 password adds.
Mission Team Prioritization Framework example: Get More Passwords

22. Balancing 10% vs. 10x
10%

23. 10% vs. 10x
10x

24. Product Research: identifying problems to solve at three altitudes
1. Product Vision
2. Future Missions
3. Current
Missions How do we jumpstart our
experimentation with market
and consumer insights?
What missions should we
prioritize next? What do we do
beyond optimization?
What are the big market shifts
and opportunities? Who should
we target and with what value
proposition?

25. Solving for Both Ends of the Spectrum
10% 10x
Experimentation-
led
Research-led
Impact
Certainty
Access control on
voice-powered
assistants will
need to be solved
Users will want
centralized control
over their data
There will be a
Digital Identity
consolidation
Identity will
become social;
users will want to
select and share
access
Users will want to
protect
themselves when
on unsecure WiFi
networks
New users will
immediately want
to secure their
accounts with new
passwords
iOS users will want
to autofill
passwords when
using apps
“Solve this problem” “How will we solve this problem?” “What is the problem we need to solve?”

26. 3 Key Take Aways
1. Trust your teams to be autonomous. Guide but do not
control. Empower.
2. Experiment all the time. Small is better. Aim for learning.
3. Assess for value, not for delivery.

27. Questions

28. Appendix

29. OKR – Objective & Key Results
• A framework of defining and tracking objectives
and their outcomes
• Created by Intel, in the 1970s
• Made popular by John Doerr and Google
• Adopted by most Silicon Valley companies

30. OKR Components
• O = Objective:
• Aspirational.
• Memorable – Simpler, shorter, remarkable.
• Qualitative.
• KR = Key Results:
• 2-5 per Objective.
• Quantitative & Measurable.
• Metrics (recommended) or Milestones.

31. OKR Example
• Objective: Delight our customers
• Key Results:
• Increase average weekly visits from 3.1 to 3.3 per active user
• Improve Net Promoter Score from 46% to 52%.
• Increase non paid (organic) traffic from 70% to 80%.
• Increase engagement (users that complete a full profile) from 60% to 75%.
• Objective: Taming the Autofill Dragon
• Key Results:
• Achieve successful autologin on the top 50 Chinese websites
• Achieve successful autologin on the top 50 Korean websites
O can be fun!

32. Dashlane OKR
• Yearly Company OKR – High-Level Strategy
• KR can be reviewed and adapted every quarter or as needed.
• But O should theoretically remain stable in time
• Team Quarterly OKR – Tactical Short Term
• Impacting Company OKR

33. Moving to OKR
• It is hard, for everybody but especially for engineering.
• Big change of mindset:
• Focus on business impact and value first
• Projects come second.
• In theory, delivering a feature does not really count for success.
• Need to be very data-driven.
• Need to accelerate massively the cycle time and release process.
• Need experimentation tooling such as strong A/B Test Engine and Feature-
Flipping.
• Need to shift to a more bottom-up process (~60% bottom-up, ~40% top-down).

34. OKR learnings
• Don’t be too ambitious, else teams get frustrated with unreachable goals.
Roofshots rather than Moonshots.
• Have fewer O and KR rather than too many. Otherwise you loose focus.
• Not all projects/initiatives are related to OKR.
• Allow for different types of KR:
• Learning metrics
• Business metrics
• Technical metrics
• Time those KR based on the current progress and based on the outcome
you are looking for. Learning first before optimizing and impacting business
for instance.