Lean Innovation INCOSE

Knowit Technology Management

Lean Innovation and Knowledge Based Development - or, what would Albert say?

Pär Hammarström Senior Mgmt Consultant

Knowit Technology Management

[email protected]

072 202 6277

Presentation to INCOSE Sweden 2013-02-13 @Knowit TM Linköping

mailto:[email protected]

…in 1950 an average R&D worker in America contributed

almost seven times more to “total factor productivity”—

essentially, the contribution of technology and innovation to

growth—that an R&D worker in 2000 did.

- Azoulay&Jones

“We wanted flying cars, instead we got 140 characters.”

- Peter Thiel

If computers and the internet mattered to the economy—

rather than merely as rich resources for intellectual and

cultural exchange, effect would be seen in the figures. And it

hasn’t been.

- Gordon&Coven

Roughly a century lapsed between the first commercial

deployments of James Watt’s steam engine and steam’s

peak contribution to British growth. Some four decades

separated the critical innovations in electrical engineering

of the 1880s and the broad influence of electrification on

economic growth.

In the end, the main risk to advanced economies may

not be that the pace of innovation is too slow, but that

institutions have become too rigid to accommodate truly

revolutionary changes—which could be a lot more likely

than flying cars.

"Our strong investor base offers a

solid foundation for boo.com. The

fact that such international

investors have invested in boo.com

reflects the power of our business

model and the boo.com brand."

Patrik Hedelin, Executive Chairman. (Press Release, Nov 3 1999)

Technology Management

“A business exist to create a customer.”

- Peter F Drucker


Technology Management Adapted from Larman & Vodde

Continuous

Improvement Respect for

people

Sustainable Success

Management applies and teaches lean thinking

Amplify Learning

Decide as late as possible

Flow/ Cadence

Set-based design

Skilled people

X-Team

Team Room & Visual Mgmt

Entrepeneurial Chief Engineer

Something different that has impact.



Product Development is Learning

Real World

Information Decision

Decision making rules

Mental Model

Feedback

Reflection



GUL BLÅ ORANGE

SVART RÖD GRÖN

LILA GUL RÖD

ORANGE GRÖN SVART

BLÅ RÖD LILA

GRÖN BLÅ ORANGE


Observable data

I make Assumptions based on the

meanings I added

I draw Conclusions

I adopt Beliefs about the world

I take Actions based on my beliefs

The Reflexive Loop

(our beliefs affect what

data we select next time)

The Ladder of Inference

Chris Argyris


What do you believe that only you believe?

"Imagination is more important than knowledge."


Contextual environment

Enacted environment


A Different Perspective

Co-ordinating logic

Transparency

Knowledge transfer

Motivation

Perspective

Sven Hamrefors

• Autonomy – The desire to be self-

directed

• Mastery – The urge to get better –

in search of flow

• Purpose – The aspiration to

contribute to something bigger than ourselves


Intrinsic Motivation

Self Actualization

Belongingness

Survival

Reflecte

d e

xp

eriences

Pre

vio

us e

nactm

ent

Gemba - Go see

Present enactment

+ -

+

-

Perspectives

Conservative Constructive

Superstitious Novel


Directing Factors

Knowledge transfer

To create a better

everyday life for the many

people.

Connecting

People.

Transparency

Co-ordinating logic

Sensemaking, flow

A PC on every

desk running

MS sw

Create experiences

combining the magic

of sw with the power

of internet services

across a world of

devices

Intr

insic

Mo

tivati

on

Directing factors

Targeted Scanning

Scanning in

principle

Anarchistic

Scanning

Private

Scanning

None Enacted situation Contextual situation

Entrepeneurial Behavior

"The secret to creativity is knowing how to hide your sources."



A

B

Mindfuck

1, Line B is longer than line A

2, They are equally long

3, We don’t know


Mindfuck

1, Line A is in line with line C

2, Line B is in line with line C

3, We don’t know

A

B

C


Mindfuck

1, The mid circles are not equally big

2, The mid circles are equally big

3, We don’t know


“I Know That I Know Nothing”


What we know that we

know – Known Knowns

What we know that we don’t

know – Known Unknowns What we don’t know that we don’t

know – Unknown Unknowns

What we don’t know that we

know – Unknown Knowns

What Do We Know

Assumptions Complicated Technical systems Find the facts

Ignorance Complex Sociotechnical systems Probe – Sense - Respond Trust that patterns will emerge

Waste The Tacit Dimension Personal ->Interpersonal through dialogue and visualizations


The Nine Dot Problem


The Problem is about What You See

Emptiness = ”Nothing”

Focus on what you know

Invisible = ”Something”

What could be?

“Common sense is the collection of prejudices acquired by age eighteen.”



4 Mental Models of Innovation

Business as usual Let’s fire all the managers

80/20 Continuous innovation as the bottom line

Gary Hamel


Linear Model of Innovation

Basic Research -> Applied Research -> Development -> Diffusion

Basic Research -> Applied Research -> Development -> Production -> Marketing&Sales

Market needs-> Development -> Production -> Marketing&Sales


“Keeping the Innovators at the Gate”

Unknown

Needs

Unknown Technology


More of the Same

The SCRUM Trap

Things that I

know my

Customers like

Things that I know

how to build

?

? ?

"If we knew what it was we were doing, it would not be called research, would it?”




Competitive Strategy

Low Cost

Un

iqn

ess

Michael Porter

Sustaining Innovation

Competitive Advantage

Co

mp

etitive

Sco

pe

Cost

Leadership Differentiation

Cost Focus Differentiation

Focus


Blue Ocean – Red Ocean

W. Chan Kim & Renée Mauborgne


The Post Competitive Paradigm

New

Market

New Technology

Known

Market

Known Technology

Low Cost

Un

iqn

ess

Value Innovation

Cost

Differentiation

“In order to get to the future first, there is no need to excel competitors trying to get the same prize because

the number of prizes may be the same as the number of runners.”

G. Hamel & C. K. Prahalad


The Innovator’s Dilemma

Time

Pro

du

ct P

erf

orm

ance

High end demand

Low end demand

Sustaining Innovation

Disruptive Technology

Clayton Christenssen


New

Market

New Technology

Known

Market

Known Technology

Low Cost

Un

iqn

ess

Creative Destruction

Disruptive Innovation


Three Distinct Innovation Strategies

New

Market

New Technology

Known

Market

Known Technology

Market Readers Need Seekers

Technology Drivers

1 Apple 70 2,7%

3 3M 86 5,4%

4 GE 32 2,6%

6 IBM 15 6%

10 Facebook N/A

8 P&G 61 2,5%

9 Toyota 6 3,9%

2 Google 34 12,8%

5 Microsoft 4 14%

7 Samsung 7 5,9%

R&D spending is far from proportional to success

Booz&Co: The Global Innovation 1000 – Why Culture is key 2011

Booz&Co: The Global Innovation 1000 – Making Ideas Work 2012

1 Apple 53 2,2%

3 3M 86 5,3%

5 GE 30 3,2%

9 IBM 17 5,9%

10 Amazon 48 6,1%

2 Google 26 13,6%

4 Samsung 6 6%

6 Microsoft 5 12,9%

7 Toyota 1 4,2%

8 P&G 72 2,4%

Need Seekers

Technology Drivers

Market Readers


Strategy and Culture Alignment is Key

Distinct Goal

Advantaged Products

and Services

Distinct Culture

Openess to new ideas

from customers,

suppliers, competitors

and other industries

Distinct Goal

Products customized to

local markets

Distinct Culture

Collaboration across

functions and

geographies

Distinct Goal

Developing low cost products

Distinct Culture

Reverence and respect for

tech talent and knowledge

Common Goals

• Superior product performance

• Superior product quality

Common Culture

• Strong identification with the customer

and orientation toward customer

experience

• Passion and pride for the products and

services offered

Need Seekers

Technology Drivers

Market Readers


Front End Tools Align

Preferred Tools – Market Insight

• Feedback from customer support

and sales

• Traditional market research

• Seed funding for exploratory

research

Preferred Tools – Tech Foresight

• Periodic meetings of technical community

• Technology road mapping

• External idea scouting and technology

• Cross–business unit communities of

practice

Preferred Tools – End-user Insight

• Idea workout sessions

• Social-network data mining

• Focus groups with customers

and end-users

• Direct customer observation


Culture Eats Strategy for Breakfast

Pro

ce

ss F

it

Value Fit

Good

(Sustaining Innovation)

Bad

(Disruptive Innovation)

Good

Bad

Heavyweight Team

within organization

Lightweight Team

within organization

Heavyweight Team

Spinout organization

Heavyweight Team

Spinout organization

for commercialization

Clayton Christensen

Scalable Startup

Large Company

A startup is the temporary organization

used

to explore a market for a scalable business

model under conditions of great

uncertainty.

The purpose is not to remain a startup.

Failure = failure to transition.

Transition

Startups as a Role Model

Technology Management Scaling Agile @ Spotify with Tribes, Squads, Chapters & Guilds – Henrik Kniberg Crisp

100 is the Magic Number

• Entrepeneurs are everywhere

– Product Roadmap -> Business Model

– Product Owner - > Entrepeneur

• Validated learning

– Backlog -> To learn list

– On site customer -> Get out of the building

– Demo -> Perserve or Pivot


The Lean Start-up

Build

Product

Measure

Data

Learn

Idea

Eric Ries


The Adoption Cycle

Geoffrey Moore

Re

lative

% c

usto

mers

Time

Innovators

”Tech entusiasts”

Early Adopters

”Visionaries”

Early Majority

”Pragmatists”

Late Majority

”Conservatists”

Laggards

”Skeptics”


Technology First – Needs Later

Donald Norman

Time

Transition point

where technology

satisfies basic

needs

Technology Dominates

Technology is ”good enough”

User Experience Dominates

(convenience, reliability, cost...)

Excess Technology

Most customers not

interested Required

Performance

Re

lative

% c

usto

mers

Technology

User Experience

Business


Feasible

Viable Desirable

X-Team

Tim Brown

Customer Insight Driven – Not Customer Driven E

mp

ath

ize

Exp

erim

en

t

Concretete

Abstract

Analysis Synthesis

Context Artifacts

Observe how a job is done Prototype and evolve a minimum

desirable, viable and feasible product

Insight

Ask why 5 times

Ideas

Describe the benefits

ABDUCTIVE THINKING


Requirements Analysis vs Design Thinking

Show me the facts. How might we?


T-shaped People


Entrepreneurial Chief Engineer?

“It comes from saying no to 1,000 things to make sure

we don't get on the wrong track or try to do too much.”

- Steve Jobs

Build

Product

Measure

Data

Learn

Idea


What Do I need to Learn?

How can I Measure that?

What do I need to Build?

Experiment!

Technology Management Alexander Osterwalder

Assumptions Assumptions

Assumptions

Assumptions Assumptions

Assumptions

Assumptions

Assumptions

Assumptions


Assumption Feature MVP Validation Result


To Learn List as Strategy

Problem/ Solution

Product/ Market

Scale

Technology/Antropology

Value Proposition Canvas

Minimum Viable Product

Business Model Canvas

Product/Business Model

Crossing the chasm

Explore Execute

“The only real valuable thing is intuition."



Continuous

Improvement Respect for

people

Sustainable Success

Managment applies and teaches lean thinking

Amplify Learning

Decide as late as possible

Flow/ Cadence

Set-based design

Skilled people

X-Team

Team Room & Visual Mgmt

Entrepeneurial Chief Engineer Focus on the

Jobs to solve You are part of a System – Define

your Role

Get out of the office

Diversify your

Perspective

Design is not analysis

People, not process

T-shaped

Facilitate Dialogue

Business is Not a Sport

Expand the Problem Space – Explore the Wider System

“I think and think for months and years. Ninety-nine times, the conclusion is false. The hundred´th time I am right.”
