 AgilePracticeLibrary

THE LEAN STARTUP

the following are my notes from [The Lean Startup] by Eric Ries. see also [Ries' blog] and [TheLeanStartup.com]

INTRO

entrepreneurs are everywhere - startup is human institution designed to create new products and services under conditions of extreme uncertainty
entrpreneurship is management
validated learning - empirical testing of business hypotheses
build-measure-learn - cycle, MVP makes faster cycling/learning possible
innovation accounting - metrics that matter for growth, learning

VISION

DEFINE

a comprehensive theory

vision and concept
product development
marketing and sales
scaling up
partnerships and distribution
strucutre and org design

vision - rarely changes
strategy - changes sometimes, as fundamental assumptions are tested
product - changes often, toward optimization

LEARN

validated learning

not an excuse for failures
based on observed behavior, in live tests
observe what customers do, not what they say they want
test with real customers
learning is the essential unit of progress for startups

EXPERIMENT

every product = an experiment, and vice versa, taken directly to customers

more accurate data, observing real behavior
interact with real customers, learn about their needs
allow to be surprised when customers behave in unexpected ways

break down vision into component parts

leap-of-faith assumptions, the things we can't prove or know with facts
two most important assumptions: value hypothesis and growth hypothesis

answer all four of these questions, not just last one:

do consumers recognize that they have the problem we're trying to solve?
if there was a solution, would they buy it?
would they buy it from us?
can we build a solution for that problem?

STEER

LEAP

strategy is based on assumptions, leaps of faith
first challenge is to build an organization to test those key assumptions
many assumptions are not exceptional, have some basis in fact or experience
need to isolate key leaps of faith, about value/growth, not paper over them
"analogs" show where business can work, "antilogs" show where it might not work
- walkman as analog for ipod (mobile music works), napster antilog - want it free
need to get out and learn the territory directly, see how people live/work/use/value
exploration/observation leads to customer archetype, an essential guide for product dev
customer archetype is a hypothesis, not a fact
need to avoid "just do it" avoidance of research, and also analysis paralysis
need to study the right things: the truth about key hypotheses

TEST

minimum viable product (MVP)

helps start the process of learning quickly
not necessarily the smallest product imaginable, should be fastest way to get through the first cycle of build-measure-learn
purpose is to start learning, not achieve perfection
unlike "protype," MVP tests product but also key business hypotheses
target early adopters, target small groups
challenge is to avoid temptation to make it perfect, even non-automated
- dropbox was started as "video mvp" - essentially an animation of the product
- concierge mvp has humans taking care of processes ultimately to be automated
MVPs allows cycling through multiple versions or different opportunities
even low quality MVP can serve the building of high quality product
sometimes low quality allows for discovery of value in roughness or work arounds, allowing to avoid building the expensive things you thought you needed (craig's list)
MVPs have risks, branding risk (can create a different brand), legal risks (impact on patenting options), morale risk, competitors (not really focused on stealing ideas from startups)
need to prepare ee's and investors for MVP failures, helps to have locked in contract/agreements for several rounds
need system approach to measuring progress, to not be overcome by failed experiments... innovation accounting

MEASURE

startup's job is to (1) rigorously measure where it is right now, confronting hard truths that assessment reveals, and then (2) devise experiments to learn how the real numbers closer to the ideal reflected in the business plan.
innovation accounting guards against entrepreneurial optimism and against languishing in the land of the living dead, with a company that's not failing but not growing.
three steps (learning milestones): (1) use an MVP and establish a baseline for growth and value, key rates, (2) attempt to tune the engine from the baseline toward the ideal, optimize product and learn what works or doesn't to drive key metrics (3) pivot or persevere decision regularly
use cohort analysis: study sales, activation, conversion rates for monthly cohorts of new leads/customers... see changes in monthly experience as product changes, e.g. registration, logins, one use, multiple uses, paid, referred others.
establish baseline - test riskiest, most important assumptions first
avoid vanity metrics - gross revenues, total customers - need to track/match recent changes with recent metrics - not just optimize product, but optimize and learn which changes generate desired customer behaviors
split tests run two versions of a product/feature change against each other in two different (small) groups, for short time... pull the one that doesn't work as well... gives immediate feedback and helps refine understanding of what customers want and don't want, based on observed behavior.
kanban - do/doing/done plus VALIDATED buckets, limit (e.g. three pieces) work items/features in each one, require validation in split test before it can be moved off board
metrics should be
- actionable (clear cause and effect) - cohort analysis, split tests, kanban
- accessible (open shared data in clear understandable form, available to dev team)
- auditable (easy to track and calculate so no errors, spot check with real customers)
innovation accounting => product prioritization decisions, customer targeting decisions (and who to listen to), courage to constantly test the grand vision/key assumptions

PIVOT (OR PERSEVERE)

pivot is decision to change strategy, vs. product optimization decisions, based on test of key business assumptions (value, customer, growth engine, etc)
schedule meetings in advance, less than a few weeks too often, more than a few months is not frequent enough
innovation acctg leads to faster pivots
startup's runway is not cash and burn rate, but number of strategic pivots it can still make, the number of opportunities it has to make a fundamental change to biz strategy
pivots require courage - vanity metrics conceal need to change, sap motivation - "launch it and see what happens" always works, you always see what happens, but might take time to see what really happens, ambiguous results - acknowledging failure of part of strategy is tough on morale, usually requires throwing work away.
failure to pivot - get caught up in optimization and vanity metrics, fail to see plateau and fail to use learning milestones to understand what's driving growth, or not ** can still be growing but not making progress on strategic learning, esp in shift from early adopters to mainstream adopters, who might need different product features
catalog of pivots:
- zoom-in pivot - a single feature becomes the whole product
- zoom-out pivot - product becomes feature of larger product
- customer segment pivot - product solves real problem for real cust's but not the group we've been chasing/serving so far
- customer need pivot - sometimes in getting to know customers, we discover the need we're serving isn't that important, need to shift to another need
- platform pivot - move from mobile app, for instance, to other platforms, sometimes multiple times
- business architecture pivot - low volume/high profit to low margin/high volume, or b2b to b2c, changes length and nature of sales cycle
- value capture pivot - shifts to how the business monetizes value, how it gets paid
- engine of growth pivot - sticky, viral or paid
- channel pivot - how product is distributed, sold
- technology pivot - sometimes find different ways to solve the customer problem
a pivot is a strategic hypothesis - to test fundamental business assumptions

ACCELERATE

key assumptions

what products do customers want?
how will our business grow?
who is our customer?
which customers should we listen to? (and which ignore)

BATCH

small batches, even batches of one, more efficient production and faster learning
toyota mastered small batches after wwii when couldn't afford large-batch equipment
use "andon cord" to "stop the line" when defects noticed
small batches moves toward continuous deployment - (1) hardware becoming software in devices, cars, etc. - (2) fast production changes/product evolution, (3) 3D printing and rapid prototyping tools.
small batches in education => School of One
large batches result in lots of rework, slower feedback, higher inventories, slower adapt
PULL don't PUSH - lean inventory lets sales pull production through distribution channel, lean startup lets hypotheses that want/need testing pull work from development teams

GROW

sustainable growth: new customers come from the actions of past customers

four ways existing customers drive new customer growth:

word of mouth
side effect of use (fashion, hotmail invite in every msg footer, network effects)
paid advertising/sales
repeat use

can burn resources debating choices between:

finding new customers
serving existing customers better
improving overall quality
driving down costs

engines of growth

sticky, viral, paid (ads, sales, mktg)
designed to point to small set of metrics to focus on

sticky

rely on long-term retention
track attrition rate or churn rate (attrition net of new customers) very carefully
need to make customer acquisition > customer attrition rate
track also: rate of compounding = net % gain per period, same effect as financial compounding => drives growth over time, independent of revenue, quality, etc - numbers of customers and revenue per customer are not what drive growth in this situation

viral

not just word of mouth, but powered by USE of product: fashion, network, hotmail
track viral coefficient: # of new customers who will use product for each new customer who signs up. <1.0 is nearly flat, =1.0 is linear up trend, >1.0 is explosive, exponential
no reason to try to maximize revenue from customers, cuz that's not what's driving growth here

paid

cost per signing up new customer, cost per acquisition (CPA), drives growth
growth requires revenue > cost of acquiring customers
to increase growth, increase rev per customer or decrease cost per acquisition
cost includes ads, sales staff, other marketing
cpa will normalize across industry, trend toward rev per customer, >>> need to get better at getting revenue out of customers

summary

can have more than one engine active, but should focus on one as primary
each engine's key metric tells you if you're close to marc andreesen's "product/market fit" that drives explosive growth
all engines of growth eventually run out >>> need new startups inside biz, or new customer groups to reach with same product

ADAPT

an adaptive organization

automatically adjusts its process and performance to current conditions... and that conscious adaptation creates its own orientation program for new hires
speed needs regulation - can't trade quality for time, accepting defects to go fast now, will slow you down later
as quality and learning increase, product complexity increases over time, too
challenge: achieve scale and quality in just-in-time fashion
adaptive process, natural feedback loop, force you to slow sown and prevent kinds of problems that are currently causing waste - as efforts pay off, you naturally speed up again

the five whys

to make incremental investments and evolve processes gradually
root of every technical issue is a human issue
ask WHY five times... this is happening, why? and why that? and why that? ...
consistently make incremental investments, proportional to the problem identified at each level of the inquiry
make small investments/fixes for small problems and more if they recur
natural speed regulator - more problems pull more investment in process
use for any kind of failure - tech fault, business results miss expectations, unexpected customer behavior changes, etc.
some say 5whys + small batches is enough to generate whole of lean startup method
must avoid: "5 blames" targeting "bad people" rather than bad systems/process
must include: everyone connected with problem, absentees become targets for blame
executive mantra: "if a mistake happens, shame on us for making it so easy to make that mistake" >>> take systems-level view
have people who made the mistake lead effort to prevent repeats
turns up unpleasant realities within org, esp at beginning
calls for investments that slow development (even though only temporarily)
need authority present, supporting, insisting on good practice at difficult moments
need mgr/exec buy-in and support - for more than one round - commit to ongoing use
start small, with new issues, be specific: don't try to process old baggage, small avoids blame, specific makes need for addressing clear to all and gains attendance at meeting
appoint a 5whys master: for each area where it's used, senior enough to make sure stuff gets done
if too many issues, pick a subset/cluster of the whole
keep meetings short and identify relatively simple changes at each level
brief the process with explanation of purpose (adaptation, not blame) and example from book or elsewhere
commit to 5whys as learning, iterative experience and learning curve for master and all participants

simplified version of 5 whys - when trust/mutual support are low

ask teams to adopt these two rules: (1) be tolerant of all first-time mistakes, blame systems not people, and (2) (work together) to never allow same mistake to happen again
simplified version not a long-term solution: invites debate about what constitutes the "same mistake repeating" and about individual vs. categories of mistakes

learning requires more than culture shift

treat work as system
deal with batch size and cycle time
might require new tools and platform changes to support faster ways of working

INNOVATE

need to balance needs of existing customers with challenge of finding new ones, manage existing lines of business while exploring new models and opportunities

nurture disruptive innovation

teams need scarce but secure resources - internals need to be protected from budget raids and org politics
independent development authority - teams need complete autonomy to develop and market new products, within limits of their mandate - need to be pan-functional so need to get outside experise/approvals doesn't slow build-measure-learn cycle
personal stake in outcomes - not to be overly reliant on financial, esp in nonprofit/govt

creating platform for experimentation (esp for internal startups)

protect parent from start-up not vice versa - experiments can threaten existing customer relationships, brand image, lines of business
hiding innovation in black box, off-site, skunkworks creates suspicion long-term, not sustainable innovation and learning
innovation sandbox - empowers innovation teams out in the open - contains the impact without constraining the methods/people

sandbox rules

any team can create true split-test experiment that affects only the sandboxed parts of the product or service or only certain customer segments or territories
one team must see the whole experiment through from end to end
no experiment can run longer than a specified amount of time (usually a few weeks for simple feature experiments, longer for more disruptive innovations)
no experiment can affect more than a specified number of customers (usually expressed as % of customer base)
every experiment has tobe evaluated on te basis of a single standard report of five to ten (no more) actionable metrics
every team that works inside the sandbox and every product that is built must use the same metrics to evaluate success
any team that creates an experiment must monitor the metrics and customer reactions (support calls, socual media reaction, forum threads, etc.) while the experiment is in progress and abort it if something catastrophic happens.