lean launchpad, izmir turkey, december 2015
TRANSCRIPT
LEAN LAUNCHPADINTRODUCTION TO THE PREMIER PRE-ACCELERATOR STARTUP ENTREPRENEURSHIP EDUCATION PROGRAM
WITH VIDAR ANDERSEN
ABOUT VIDAR ANDERSEN
FOUNDING PRINCIPAL +ANDERSEN & ASSOCIATES
• NORWEGIAN LIVING IN COLOGNE, DE SINCE 2005
• WORKING WITH F500 CORPORATIONS AND GOS SOLVING PROBLEMS WITH TECHNOLOGYSINCE 1996
• SERIAL STARTUP FOUNDER & ENTREPRENEUR WITH HITS & MISSES
• EDUCATOR (UNIVERSITY LECTURER ON STARTUP ENTREPRENEURSHIP, STARTUP NEXT INSTRUCTOR & CERTIFIED LEAN LAUNCHPAD EDUCATOR @ STANFORD)
+ANDERSEN & ASSOCIATESCORPORATE INNOVATION & GROWTH THROUGH ENTREPRENEURSHIP + SCIENCE
[email protected]+49 151 40 133 149
+20 YEARS EXPERIENCE
TEACHING AT E.G.
ANDERSEN FOUNDED E.G.
FEATURED & RECOGNIZED
& more…
“[Vidar Andersen] one of the most important persons in the German startup scene.” –
Wirtschafts Woche, April 2015
CERTIFIED LEAN LAUNCHPAD (LLP)EDUCATOR @STANFORD
LLP LECTURE MARCH 2015 @ QAZVIN ISLAMIC AZAD UNIVERSITY, IRAN
METHODOLOGY FOR HORIZON 1
INNOVATIONS
PRODUCT MANAGEMENT
GATE 1STAGE 1
GATE 2STAGE 2
GATE 3STAGE 3
GATE 4STAGE 4
GATE 5STAGE 5
PROCESS INNOVATION
HORIZON 1 EXTEND THE CORE
USE TRADITIONAL METHODOLOGIES FOR HORIZON 1 PROJECTS
IDEA SCREEN
SCOPING
SECOND SCREEN
BUILD BUSINESS CASE
GO TO DEVELOPMENT
DEVELOPMENT
GO TO TESTING
TESTING & VALIDATION
GO TO LAUNCH
LAUNCH
METHODOLOGIES FOR HORIZON 2 & 3
INNOVATIONS
1. METHODOLOGIES
BUSINESS MODEL GENERATION
CUSTOMERDEVELOPMENT
AGILE ENGINEERING+ +
THE
LEAN
STARTUP HORIZON 3 DISRUPTS THE CORE
CUSTOMERDISCOVERY
CUSTOMERVALIDATION
CUSTOMERCREATION
COMPANYBUILDING
SEARCH EXECUTE
PIVOT
2. PROCESS
EVIDENCE-BASED, DATA-DRIVEN PROCESS
OUTSIDEWORK MEETUPS MENTORING
VIDEO LECTURESWRITTEN MATERIALCUSTOMER INTERVIEWS EXPERIENCE-BASED
DISCUSSIONS - INSIGHTS ADDITIONAL LECTURESACCOUNTABILITYFEEDBACK, PEER REVIEW
DURING MEETUPS BETWEEN MEETUPS WITH EXPERIENCEDENTREPRENEURS
THE LEAN LAUNCHPAD (LLP)
LLP +4.000 TEAMS WORLD WIDE
• THE LEAN LAUNCHPAD CURRICULUM
• NATIONAL SCIENCE FOUNDATION’SINNOVATION-CORPS
• +200 UNIVERSITIES WORLD WIDE
• +40 ACCELERATORS / INCUBATORS
• GROWING NUMBER OF FORTUNE 500 CORPORATIONS
CERTIFIED LEAN LAUNCHPAD (LLP)EDUCATOR @STANFORD
IN EUROPE WITH +ANDERSEN
LLP @ UNIVERSITY OF COLOGNE (ONE OF 4 GERMAN ELITE UNIVERSITIES) LARGE CORPORATIONS
THE NATIONAL SCIENCE FOUNDATION (NSF) IS A UNITED STATES GOVERNMENT AGENCY THAT SUPPORTS FUNDAMENTAL RESEARCH AND EDUCATION IN ALL THE NON-MEDICAL FIELDS OF SCIENCE AND ENGINEERING
THEY DECIDE WHICH PUBLIC SCIENTIFIC RESEARCH PROJECTS WILL GET FEDERAL FUNDING FOR COMMERCIALIZATION IN THE US
BUDGET: $7B ANNUALLY
NSF'S iCORPS ACCELERATOR PROGRAM WENT FROM A 18% TO A +60% FUNDING RATE OF PROJECTS AFTER REQUIRING APPLICANTS TO TAKE THE LEAN LAUNCHPAD AS A PREREQUISITE FOR FUNDING & USING LAUNCHPAD CENTRAL AS THE MANAGEMENT TOOL
LLP - TRAINING +300 EDUCATORS A YEAR
• LEAN LAUNCHPAD EDUCATORS TRAINING & CERTIFICATIONS
• STANDARDIZED PROCESS & CURRICULUM
• STANDARDIZED, VALIDATED TRAINING & CERTIFICATION
• HELD AT STANFORD, BERKELEY, COLUMBIA AND MORE ON A REGULAR BASIS
• MORE INFO AT NCIAA.ORG/LLP
2. EVIDENCE BASED PROCESS
BUSINESS MODEL GENERATION
CUSTOMERDEVELOPMENT
AGILE ENGINEERING
HYPOTHESES EXPERIMENTS DATA
METHODOLOGIES (THEORY)
+ +
MENTORSHIP
LEAN LAUNCHPAD CURRICULUM
3. TOOLS & METRICS
INNOVATION MANAGEMENT TOOL
GATHERS & TRACKS DATA ON HYPOTHESES, PIVOTS, MVPS, METRICS EVIDENCE & TRAJECTORY
3. INNOVATION MGMT TOOL
WEEKLY PROGRESS
EXPERIMENTSCORECARD
DATA, TRAJECTORY EXPERIMENTS,
READINESS LEVEL+ =
BUSINESS MODEL GENERATION
CUSTOMERDEVELOPMENT
AGILE ENGINEERING
HYPOTHESES EXPERIMENTS DATA
METHODOLOGIES (THEORY)
EVIDENCE BASED PROCESS
+ +
MENTORSHIP
KPI
FIND FILTER FUNDEARLY STAGE
POTENTIAL
RIGOROUS TESTING AND VALIDATION TO FILTER IDEAS
INNOVATION VENTURES RIPE
FOR INVESTMENT
COHORT LEADERBOARD
ALL COHORTS (SIMULTANEOUS TEAMS, PROJECTS, IDEAS)
CUSTOMER INTERVIEWS
HYPOTHESES TO TEST
INVALIDATED HYPOTHESES
WEEKLY CANVAS UPDATES
TRACK ALL HYPOTHESES TESTING
SCORECARD: 9 WAY KANBAN BOARD, DATA
ADVANCED DATA MINING
WHAT TO DO WITH ALL THIS DATA?
INTRODUCING A METRIC FOR INNOVATION READINESS LEVEL
NASA/DOD TRL:TECHNOLOGY READINESS LEVEL
• FORMAL WAY TO ASSESS TECHNOLOGY PROJECT MATURITY
• QUANTIFY RELATIVE RISKS
• DATA DRIVEN
• ADOPTED BY NASA, DOD, FAA, ESA AND SO ON
• INTRODUCED IN 1974 BY NASA JPL
• ALSO SEE: HTTP://WWW.WIKIWAND.COM/EN/TECHNOLOGY_READINESS_LEVEL TRL 1
TRL 2
TRL 3
TRL 4
TRL 5
TRL 6
TRL 7
TRL 8
TRL 9
NASA/DOD TECHNOLOGY READINESS LEVEL 1 & 2
BASIC TECHNOLOGY RESEARCH:
• BASIC PRINCIPLES OBSERVED
• TECHNOLOGY CONCEPT FORMULATED
CONCEPTTRL 1
TRL 2
TRL 3
TRL 4
TRL 5
TRL 6
TRL 7
TRL 8
TRL 9
NASA/DOD TECHNOLOGY READINESS LEVEL 3 & 4
RESEARCH TO PROVE FEASIBILITY:
• EXPERIMENTAL PROOF OF CONCEPT
• BREADBOARD VALIDATION IN LABRESEARCH
TRL 1
TRL 2
TRL 3
TRL 4
TRL 5
TRL 6
TRL 7
TRL 8
TRL 9
CONCEPT
NASA/DOD TECHNOLOGY READINESS LEVEL 5 & 6
DEMO PROTOTYPE:
• BREADBOARD VALIDATION OUTSIDE OF BUILDING
• SYSTEM DEMO IN REAL WORLD
DEMO
TRL 1
TRL 2
TRL 3
TRL 4
TRL 5
TRL 6
TRL 7
TRL 8
TRL 9
RESEARCH
CONCEPT
NASA/DOD TECHNOLOGY READINESS LEVEL 7, 8 & 9
DEPLOYMENT:
• SYSTEM DEVELOPMENT
• SYSTEM DEVELOPMENT IN REAL WORLD
DEPLOYMENT
TRL 1
TRL 2
TRL 3
TRL 4
TRL 5
TRL 6
TRL 7
TRL 8
TRL 9
CONCEPT
RESEARCH
DEMO
WHAT DOES THIS MEAN FOR AN INNOVATION METRIC?
INTRODUCING THE INNOVATION READINESS LEVEL KPI
INNOVATION READINESS LEVEL
• WE CAN DO THE SAME FOR NEW INNOVATION VENTURES
• EMPHASIS IS ON DATA
IRL 1
IRL 2
IRL 3
IRL 4
IRL 5
IRL 6
IRL 7
IRL 8
IRL 9
INNOVATION READINESS LEVEL
• A FORMAL WAY TO QUANTIFY RELATIVE RISK
• DATA DRIVEN
• ANALOG TO NASA/DODTECHNOLOGY READINESS LEVEL (TRL)
• ADAPTABLE TO YOUR INDIVIDUAL CORPORATE GOALS, URGENCY, VERTICALS AND RISK AVERSION (I.E. RELATIVE NOT ABSOLUTE SCALE)
IRL 1
IRL 2
IRL 3
IRL 4
IRL 5
IRL 6
IRL 7
IRL 8
IRL 9
INNOVATION READINESS LEVEL 1 & 2
HYPOTHESES:
• VALUE PROPOSITIONS SUMMARIZED
• BM CANVAS HYPOTHESES ARTICULATED
HYPOTHESESIRL 1
IRL 2
IRL 3
IRL 4
IRL 5
IRL 6
IRL 7
IRL 8
IRL 9
INNOVATION READINESS LEVEL 3 & 4
PROBLEM / SOLUTION FIT:
• PROBLEM SOLUTION FIT
• LOW FIDELITY MVP PROBLEM /SOLUTION
IRL 1
IRL 2
IRL 3
IRL 4
IRL 5
IRL 6
IRL 7
IRL 8
IRL 9
HYPOTHESES
INNOVATION READINESS LEVEL 5 & 6
VALIDATE:
• PRODUCT / MARKET FIT
• RIGHT SIDE OF BUSINESS MODEL CANVAS
• VALUE PROPS, CUSTOMER SEGMENTS, CHANNELS, CUST REL & REVENUE SOURCES
PRODUCT/MARKET
IRL 1
IRL 2
IRL 3
IRL 4
IRL 5
IRL 6
IRL 7
IRL 8
IRL 9
PROBLEM /SOLUTION
HYPOTHESES
INNOVATION READINESS LEVEL 7 & 8
VALIDATE:
• LEFT SIDE OF BUSINESS MODEL CANVAS
• ACTIVITIES, RESOURCES, PARTNERS & COSTS
VALIDATE LEFT BMC SIDE
IRL 1
IRL 2
IRL 3
IRL 4
IRL 5
IRL 6
IRL 7
IRL 8
IRL 9
PRODUCT/MARKET
PROBLEM /SOLUTION
HYPOTHESES
INNOVATION READINESS LEVEL 9+
METRICS THAT MATTER
METRICS THATMATTER
• SALES & REVENUE METRICS
• USER & CUSTOMER GROWTH METRICS
• ENGAGEMENT METRICS
• COHORT, FUNNEL, ATTRITION & CHURN METRICS
• ETC
IRL 1
IRL 2
IRL 3
IRL 4
IRL 5
IRL 6
IRL 7
IRL 8
IRL 9
PRODUCT/MARKET
PROBLEM /SOLUTION
HYPOTHESES
VALIDATE LEFT BMC SIDE
IRL 1
IRL 2
IRL 3
IRL 4
IRL 5
IRL 6
IRL 7
IRL 8
IRL 9
INNOVATION READINESS LEVELIDENTIFY AND VALIDATE METRICS THAT MATTER VALIDATE VALUE DELIVERY (LEFT CANVAS SIDE) PROTOTYPE HIGH-FIDELITY MVP VALIDATE REVENUE MODEL (RIGHT CANVAS SIDE) VALIDATE PRODUCT-MARKET FIT PROTOTYPE LOW-FIDELITY MVP PROBLEM-SOLUTION VALIDATION MARKET SIZE & COMPETITIVE ANALYSIS COMPLETE FIRST-PASS OF BUSINESS MODEL CANVAS
COMBINING IT ALL FOR HORIZON 3
INNOVATIONS
BUSINESS MODEL GENERATION
CUSTOMERDEVELOPMENT
AGILE ENGINEERING
HYPOTHESES EXPERIMENTS DATA
WEEKLY PROGRESS
EXPERIMENTSCORECARD
DATA, TRAJECTORY EXPERIMENTS,
READINESS LEVEL
1. METHODOLOGIES
3. EVIDENCE BASED PROCESS (LLP)
3. INNOVATION METRIC & MANAGEMENT TOOL
+ +
+ =
MENTORSHIP
THE LEAN
STARTUP
WHAT WE KNOW NOWWHY STARTUPS ARE NOT SMALLER VERSIONS OF COMPANIES
STARTUPS ARE NOT SMALLER VERSIONS OF LARGER COMPANIES
A COMPANY IS A PERMANENT ORGANIZATION
DESIGNED TO EXECUTE A REPEATABLE AND SCALABLE
BUSINESS MODEL IN A PREDICTABLE AND STABLE
ENVIRONMENT
A STARTUP IS A TEMPORARY ORGANIZATION DESIGNED TO SEARCH FOR A REPEATABLE AND SCALABLE BUSINESS MODEL IN
AN ENVIRONMENT OF EXTREME UNCERTAINTY
A STARTUP IS A TEMPORARY ORGANIZATION DESIGNED TO SEARCH FOR A REPEATABLE AND
SCALABLE BUSINESS MODEL
COMPANY LIFE-CYCLE
SCALABLESTARTUP TRANSITION LARGE
COMPANY
SEARCH BUILD GROW• BUSINESS MODEL FOUND • PRODUCT-MARKET FIT • REPEATABLE SALES MODEL • MANAGERS HIRED
• CASH-FLOW BREAK-EVEN • PROFITABLE • RAPID SCALE • NEW SENIOR MANAGEMENT • AROUND 150 PEOPLE
SEARCH
BUSINESS MODEL GENERATION
CUSTOMER DEVELOPMENT
AGILE ENGINEERING
EXECUTION
LARGE COMPANY
WHAT WE KNOW NOW• STARTUPS ARE NOT SMALLER VERSIONS OF LARGER COMPANIES
• STARTUP IS TEMPORARY ORG, IN SEARCH OF SCALABLE REPEATABLE BUSINESS MODEL
• NO BUSINESS PLAN EVER SURVIVES FIRST CONTACT WITH CUSTOMERS
• BUSINESS MODEL CANVAS INSTEAD OF BUSINESS PLANS
• CUSTOMER DISCOVERY INSTEAD OF EXECUTION
• AGILE ENGINEERING PROCESSES INSTEAD OF WATERFALL
• MINIMUM VIABLE PRODUCT INSTEAD OF BETAS
• BUILD - MEASURE - LEARN: ITERATION AND SPEED OF THE ESSENCE
THE LEAN STARTUP
BUSINESS MODEL GENERATION
CUSTOMER DEVELOPMENT
AGILE ENGINEERING
THE LEAN
STARTUP=
WHAT IS A BUSINESS MODEL?
INTRODUCING BUSINESS MODEL GENERATION
BUSINESS MODEL GENERATION
CUSTOMER DEVELOPMENT
AGILE ENGINEERING
VALUE PROPOSITION CANVAS
https://www.youtube.com/watch?v=aN36EcTE54Q
CUSTOMER DEVELOPMENTCUSTOMER DISCOVERY & VALIDATION
BUSINESS MODEL GENERATION
CUSTOMER DEVELOPMENT
AGILE ENGINEERING
AGILE ENGINEERINGMVP, BUILD-MEASURE-LEARN IN SMALL ITERATIVE BATCHES
BUSINESS MODEL GENERATION
CUSTOMER DEVELOPMENT
AGILE ENGINEERING
AGILE ENGINEERING• MINIMUM VIABLE PRODUCT INSTEAD OF FEATURE-COMPLETE
• BUILD-MEASURE-LEARN ITERATIONS IN SMALL BATCHES INSTEAD OF VERSION COMPLETE & WATERFALL PROCESS
• GOOD ENOUGH VS PERFECT - SPEED IS OF THE ESSENCE
• DATA / TEST DRIVEN DESIGN - HYPOTHESIS TESTING
• AUTOMATED ACCEPTANCE TESTING + USER STORIES / SCENARIOSDESCRIBE WHAT WE WANT TO SEE THE SOFTWARE DO, THEN AUTOMATE THE VERIFICATION THAT THE SOFTWARE ACTUALLY DOES IT
• CONTINUOUS DEPLOYMENT, MULTIVARIABLE A/B TESTING, PAIR PROGRAMMING (XP), SCRUM & KANBAN
DEFINE YOUR PASS / FAIL CRITERIA
PASS / FAIL CRITERIA
• TESTING YOUR CRITICAL ASSUMPTIONS, YOU NEED TO DEFINE THE SUCCESS AND FAIL CRITERIA IN ADVANCE TO KEEP YOU FROM FUDGING THE FINDINGS TO FIT YOUR BELIEFS AFTER THE FACT
• IT NEEDS TO BE A QUANTITATIVE OR QUALITATIVE RESULT
• 40% IS OFTEN USED AS THE SUCCESS LIMIT
EXAMPLE
I BELIEVE THAT PEOPLE LIKE (CUSTOMER SEGMENT ) HAVE A NEED FOR OR P R O B L E M D O I N G ( N E E D / A C T I O N /BEHAVIOR) AND I WILL KNOW THAT I HAVE SUCCEEDED WHEN (QUANTITATIVE / M E A S U R A B L E O U T C O M E ) O R (QUALITATIVE / OBSERVABLE OUTCOME)
THE MINIMUM
VIABLE PRODUCT
(MVP)
MVP: THE SMALLEST BATCH THAT
WILL TEACH YOU SOMETHING
MORE THAN ONE WAY TO MVP
THERE ARE SEVERAL TYPES OF MVPS
THE EXPLAINER VIDEO
THE LANDING PAGE
THE WIZARD OF OZ
THE WIZARD OF OZ - ZAPPOS
MVP
THE CONCIERGE
THE CONCIERGE - FOODONTHETABLE
THE PIECEMEAL
MVP
THE PIECEMEAL - AARDVARK
CROWD FUNDING
CROWD FUNDING - COOLEST: $13.4M
MVP - SEVERAL TYPES:• EXPLAINER VIDEO (DROPBOX)
• A LANDING PAGE
• WIZARD OF OZ MVP (ZAPPOS)
• CONCIERGE MVP (FOOD ON THE TABLE)
• PIECEMEAL MVP (WIZARD OF OZ + CONCIERGE)
• CROWD FUNDING (SELL BEFORE YOU BUILD)
• SINGLE-FEATURE MVP (GOOGLE)
• ETC
DEFINE YOUR MVPWHAT CAN YOU RELEASE IN ONE DAY TO START
TESTING YOUR HYPOTHESES?
HOW AND WHAT WILL YOU TRACK?
MEASURE THE DATA FROM YOUR MVP
COMPARE DATA TO PASS / FAIL CRITERIA
ACT & ADJUST ACCORDINGLY
AND TEST AGAIN
IN BUILD - MEASURE - LEARN CYCLES
ITERATE OR PIVOT AS NEEDED
RELEASING SMALL BATCHES
IN BUILD-MEASURE-LEARN CYCLES
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