1. Making
sense
of
messy
problems
Johanna
Kollmann
@johannakoll
!
Lean
UX
NYC
2014
Systems
thinking
for
complex
business
models
Illustration
by
David
Wicks:
http://www.flickr.com/photos/sansumbrella/467998944/

2. Intro
about
me:
worked
on
a
range
of
complex
systems
such
as
a
voice
communica;on
system
for
the
NASA,
before
learning
more
about
systems
thinking
as
part
of
my
HCI
degree
in
London.
Interest
in
systems
theory
and
organisa;onal
structures
remained
when
I
was
consul;ng,
e.g.
a
large
retailer
who
was
reshaping
their
en;re
business
and
data
structure
to
enable
mul;-­‐channel.
While
geFng
interested
in
business
models
and
the
startup
world,
I
realised
that
systems
thinking
is
also
core
to
business
models,
lean
manufacturing,
and
lean
startup.

3.
The
next
3
hours
of
your
life:
Introduction
to
Systems
Thinking
Tools
for
modeling
systems
(collaborate!)
Systems
behavior
over
time
Change
ASK:
What’s your current understanding of systems thinking - share with neighbour
What are your expectations for today
Ask a few people to share

4. Monitor
changes
in
the
system
Understand
people’s
worldviews
To
reduce
uncertainty
NUTSHELL!!!!

5. Systems
Thinking?
Why
you
should
care
about
it
!Increasing
complexi;es
and
dependencies
require
us
to
think
holis;cally.
We
need
to
think
dynamic
and
over
;me
rather
than
sta;c
and
short-­‐lived
Technology
and
business
context
changes.
!ST
is
relevant
to
both
UX
and
LS.

6. http://visitmix.com/work/descry/awebsitenameddesire/
The
systems
we
deal
with
in
the
world
of
a
website
Running
a
business
is
taking
this
to
a
different
level
-­‐
being
a
founder
is
taking
the
running
around
and
coordina;ng
to
a
different
level!

7. In
the
past
the
man
has
been
first;
in
the
future
the
system
must
be
first.
!
~
Frederick
Winslow
Taylor
(1911)
father
of
scien;fic
management
and
efficiency
movement

8. In
the
past
the
man
has
been
first;
in
the
future
the
system
must
be
first.
!
This
in
no
sense,
however,
implies
that
great
men
are
not
needed.
!
~Frederick
Winslow
Taylor
(1911)
According
to
Eric
Ries,
forgeFng
the
human
part
has
led
to
2
problems:
1)
overly
rigid
business
systems
that
failed
to
take
advantage
of
adaptability,
crea;vity,
and
wisdom
of
individual
workers
2)
overemphasis
on
planning,
preven;on
and
procedure,
which
enable
organisa;ons
to
achieve
consistent
results
in
a
stable
world.

9. “At
the
root
of
every
seemingly
technical
problem
is
a
human
problem.”
~ Taiichi Ohno

10. “A
system
is
~ Donella Meadows
a
set
of
elements
or
parts
o[en
classified
as
its
func;on
or
purpose.”
that
is
coherently
organized
and
inter-­‐connected
in
a
pa]ern
or
structure
that
produces
a
characteris;c
set
of
behaviors,

11. Peter
Checkland
Human
activity
systems
Soft
Systems
Methodology
Examples:
hard
system
=
thermostat,
motherboard.
so[
system
=
game
of
poker,
soccer
game,
mee;ng,
healthcare.
Human activity systems, on the other hand are essentially complex, indefinable and purposeful.
!He
developed
the
“so[
systems
methodology”,
sugges;ng
that
most
problems
in
systems
are
caused
because
“human
beings
are
hard
to
predict”.
He
did
not
think
that
there
were
things
you
could
“fix”
with
systems
thinking,
instead
there
were
“situa;ons
you
could
improve”.
!4
ac;vi;es
of
SSM:
-­‐
Finding
out
about
the
situa;on
-­‐
Making
purposeful
ac;vity
models
based
on
par;cular
world
views.
-­‐
Using
the
models
to
ques;on
the
situa;on
-­‐
Defining
ac;on
to
improve
the
situa;on.

12. Peter
Checkland
Soft
Systems
Methodology
Activities:
Finding
out
about
the
problem
situation
Making
purposeful
activity
models
Using
the
models
to
question
the
situation
Defining
action
to
improve
the
situation
Examples:
hard
system
=
thermostat,
motherboard.
so[
system
=
game
of
poker,
soccer
game,
mee;ng,
healthcare.
Human activity systems, on the other hand are essentially complex, indefinable and purposeful.
!He
developed
the
“so[
systems
methodology”,
sugges;ng
that
most
problems
in
systems
are
caused
because
“human
beings
are
hard
to
predict”.
He
did
not
think
that
there
were
things
you
could
“fix”
with
systems
thinking,
instead
there
were
“situa;ons
you
could
improve”.
!4
ac;vi;es
of
SSM:
-­‐
Finding
out
about
the
situa;on
-­‐
Making
purposeful
ac;vity
models
based
on
par;cular
world
views.
-­‐
Using
the
models
to
ques;on
the
situa;on
-­‐
Defining
ac;on
to
improve
the
situa;on.

13. !

14.
Leverage
points…
…places
within
a
complex
system
where
a
small
shift
in
one
thing
can
produce
big
changes
in
everything.
…are
often
counterintuitive.

15. Systems
Thinking
&
UX

16. 1)
Modeling

17. 2)
Behavior
over
time

18. 3)
Change

19. 1)
Modeling
Models are tools for understanding complex situations.
Models are tools for communicating complex situations.

20. !
“Only
by
building
a
model
of
customer
behaviour
and
then
showing
our
ability
to
use
our
product
or
service
to
change
it
over
;me
can
we
establish
real
facts
about
the
validity
of
our
vision.”
~ Eric Ries

21. Personas
from
Design
Jam
London,
by
Jeff
Van
Campen
http://www.flickr.com/photos/otrops/tags/designjamlondon/
This
is
where
UX
offers
lots
of
tools:
personas,
customer
journey
maps;
Lean
Startup’s
hypothesis-­‐driven
approach
also
is
modeling.

22. Flickr
User
Model
by
Bryce
Glass
http://www.flickr.com/photos/bryce/58299511/
Models
help
us
understand
how
things
work.

23. 1)
Modeling 2)
Behavior
over
time 3)
Change
Rich
Picture
1.
Construction
of
the
Humber
Bridge
(adapted
from
Stewart
and
Fortune,
1994)
©
The
Open
University
2.
Distance
Learning
Situation
©
Wood-­‐Harper
et
al,
Information
Systems
Definition:
The
Multiview
Approach,
Blackwell
Scientific
Publications
1985

24. 1)
Modeling 2)
Behavior
over
time 3)
Change
Rich
Picture
elements
Stakeholders
Worldview
Connections
Conflicts
2.
Distance
Learning
Situation
©
Wood-­‐Harper
et
al,
Information
Systems
Definition:
The
Multiview
Approach,
Blackwell
Scientific
Publications
1985
Worldview
is
a
concept
for
empathy
!Consider:
-­‐
roles
that
people
adopt
in
the
situa;on
(which
may
be
formally
recognised
or
quite
informal);
the
norms
which
govern
people’s
behaviour;
and
the
values
they
espouse.
-­‐
poli;cal
aspects
of
the
situa;on,
in
other
words
recogni;on
of
the
different
interests
that
are
represented
and
how
these
different
interests
are
accommodated.

25. 1)
Modeling 2)
Behavior
over
time 3)
Change

26. 1)
Modeling 2)
Behavior
over
time 3)
Change

27. 1)
Modeling 2)
Behavior
over
time 3)
Change
!

28. 1)
Modeling 2)
Behavior
over
time 3)
Change

30. Handout:
http://bit.ly/OQzwza

31. 1)
Modeling 2)
Behavior
over
time 3)
Change
Rich
Picture
elements
Stakeholders
Worldview
Connections
Conflicts
2.
Distance
Learning
Situation
©
Wood-­‐Harper
et
al,
Information
Systems
Definition:
The
Multiview
Approach,
Blackwell
Scientific
Publications
1985

32. 1)
Modeling 2)
Behavior
over
time 3)
Change
Rich
Picture
applications
Framing
the
problem:
Checkland’s
root
definition
Understanding
and
communicating
a
complex
situation
Uncovering
assumptions
and
knowledge
gaps
Research
planning
Stakeholder
risk
matrix
CATWOE
1. A system Transformation – ie a clear relationship between system inputs and outputs.
2. A system Owner – ie someone who is ultimately responsible for the system. This person, or persons, can often be identified by asking the question ‘who can stop the activity’?
3. Actors – those people who take action within the system.
4. Customers for the system – ie the beneficiaries, or intended beneficiaries, of the system.
5. The system Environment within which the activity takes place.
6. The World view which enables all of the above to make sense.

33. 1)
Modeling 2)
Behavior
over
time 3)
Change
Business
Model
Canvas
Job
seekers
Recruiters
Jobs
Candidates
Manage,
promote
platform
Platform
Manage
and
develop
platform
Marketing
costs
Job
ads
Hiring
fee

34. 2)
Behavior
over
time

35. 1)
Modeling 2)
Behavior
over
time 3)
Change
Flows
inflow outflow
information
feedback,
control
stock
Bath
tub
example
-­‐
overflow
pipe
!2
types
of
flows.
First
one
is
material
and
stock
flows.
Stocks
change
over
;me
through
the
ac;ons
of
flow.
Stocks
act
as
buffers
or
delays,
and
help
a
system
to
stay
in
balance.
You
can
also
apply
this
to
people.
Shows
limits
to
growth
if
your
resources
aren’t
endless.
Key
is
to
understand
and
monitor
system
behaviour
over
;me.
Do
not
focus
on
only
individual
events.
!The
second
type
are
informa;on
flows.
While
it’s
hard
to
change
physical
structure,
materials,
resources,
changing
how
informa;on
is
distributed
and
presented
in
a
system
can
have
major
impact.
"Informa)on
holds
systems
together
and
plays
a
great
role
in
determining
how
they
operate.
Most
of
what
goes
wrong
in
systems
goes
wrong
because
of
biased,
late,
or
missing
informa)on."
(Meadows)
Adding
or
restoring
informa;on
can
be
a
powerful
interven;on,
usually
much
easier
and
cheaper
than
rebuilding
physical
infrastructure.
!Notes
on
John
Seddon:
interes;ng
to
consider
how
customer
inquiries/feedback
come
in
and
flow
through
the
system

36. 1)
Modeling 2)
Behavior
over
time 3)
Change
Feedback
loops
George’s
ability
to
solve
problems
Number
of
problems
solved
Number
of
remaining
problems
Time
available
per
problem
Project
in
trouble
Management
pressure
to
solve
problems
R1 R3
R2
Need
to
involve
Paul
B1
Reinforcing
feedback
loops
A
posi;ve
feedback
loop
is
self-­‐reinforcing.
The
more
it
works,
the
more
it
gains
power
to
work
some
more.
Posi;ve
feedback
loops
drive
growth,
explosion,
erosion,
and
collapse
in
systems.
A
system
with
an
unchecked
posi;ve
loop
ul;mately
will
destroy
itself.
Usually
nega;ve
feedback
loop
kicks
in,
eg
epidemic
runs
out
of
infectable
people—or
people
take
increasingly
strong
steps
to
avoid
being
infected.
Reducing
the
gain
around
a
posi;ve
loop—slowing
the
growth—is
usually
a
more
powerful
leverage
point
in
systems
than
strengthening
nega;ve
loops,
and
much
preferable
to
leFng
the
posi;ve
loop
run.
(...)
control
must
involve
slowing
down
the
posi;ve
feedbacks.
!Balancing
feedback
loop
A
nega;ve
feedback
loop
needs
a
goal
and
a
response
mechanism.
Self-­‐correct
the
system,
o[en
inac;ve
=
emergency
mechanisms.
Seem
costly
as
inac;ve,
removing
them
has
li]le
impact
in
the
short-­‐term,
neglect
the
long-­‐term
impact.
Here
are
some
other
examples
of
strengthening
nega;ve
feedback
controls
to
improve
a
system's
self-­‐correc;ng
abili;es:
preven;ve
medicine,
exercise,
and
good
nutri;on
to
bolster
the
body's
ability
to
fight
disease,
pollu;on
taxes.
!The
informa)on
delivered
by
a
feedback
loop
-­‐
even
nonphysical
feedback
-­‐
can
only
affect
future
behaviour;
it
can't
deliver
a
signal
fast
enough
to
correct
behaviour
that
drove
the
current
feedback.
There
will
always
be
delays
in
responding.
The
loop
that
dominates
the
system
will
determine
the
behaviour.
Consider
the
driving
factors,
how
they
might
behave,
and
what
drives
them.
!
Dynamic
systems
studies
are
not
designed
to
predict
what
will
happen,
but
to
explore
what
would
happen
if...
-­‐-­‐>
system
dynamics
models
explore
possible
futures
and
ask
'what
if'
ques;ons.
!Causal
Loop
Diagrams
help
reveal
system
dynamics.
Crea;ng
the
diagrams
involves
more
work
than
reading
them,
but
can
be
done
by
anyone
willing
to
take
;me
to
think
things
through
and
look
for
rela;onships.
For
example,
what
problems
might
arise
by
involving
help?
Is
it
possible
that
things
will
get
worse
before
they
get
be]er?
And
why
would
that
be?
!Rela)ng
loops
to
Eric
Ries’
engines
of
growth
word
of
mouth,
side
effect
of
use,
paid
adver;sing,
repeat
use
S;cky
-­‐
make
me
come
back
Viral
-­‐
word
of
mouth
Paid

37. 1)
Modeling 2)
Behavior
over
time 3)
Change
Behavior
over
time
graphs
inventory
days
perfect
informa;on
scenario
!

38. 1)
Modeling 2)
Behavior
over
time 3)
Change
Behavior
over
time
graphs
inventory
days
what
really
happens
!What
came
before?
What
might
happen
next?
!Focus
on
trends
over
;me
rather
than
single
events.
Learn
if
the
system
is
approaching
a
goal
or
limit.
Inventory
=
stock
(could
also
be
informa;on)

39. 1)
Modeling 2)
Behavior
over
time 3)
Change
Cohort
analysis

40. 1)
Modeling 2)
Behavior
over
time 3)
Change
Cohort
analysis
Eric
writes:
Cohort
analysis:
This
technique
is
useful
in
many
types
of
business,
because
every
company
depends
for
its
survival
on
sequences
of
customer
behaviour
called
flows.
Customer
flows
govern
the
interac;on
of
customers
with
a
company's
products.
They
allow
us
to
understand
a
business
quan;ta;vely
and
have
much
more
predic;ve
power
than
do
tradi;onal
gross
metrics.
p
145
Cohort-­‐based
reports
are
the
gold
standard
of
learning
metrics:
they
turn
complex
ac;ons
into
people-­‐based
reports.

42. 1)
Modeling 2)
Behavior
over
time 3)
Change
Custom
tools
to
monitor
interactions
by @lukew

43. 1)
Modeling 2)
Behavior
over
time 3)
Change
Photo
by
Anders
Zakrisson
http://www.flickr.com/photos/anders-­‐zakrisson/4982281184/
Talking
to
people,
empathy,
intui;on

44. DATA
MEANING
humanise
the
data
–
tell
a
story
!Informa;on
flows
enable
other
things
in
the
system
to
happen
Consider
the
feedback
loops
Observe
customer
behavior
over
;me
Use
qualita;ve
findings
and
your
gut

45. 3)
Change

46. 1)
Modeling 2)
Behavior
over
time 3)
Change
inventory
days
Flows
and
loops
Donella
Meadows
also
says
that
its
quite
tricky
to
properly
monitor
a
system
and
react
appropriately,
because
the
delays
in
observing,
and
then
the
delay
in
ac;ng
means
that
by
the
;me
your
change
goes
into
place,
the
system
is
probably
in
a
different
state.
Its
easy
to
over
compensate.
It
seems
to
me
that
you
need
to
try
to
get
both
stats
as
real-­‐;me
as
possible,
and
gain
a
good
understanding
of
natural
flows
over
;me.
shi[
a]en;on
from
the
abundant
factors
to
the
next
poten;al
limi;ng
factor.
layer
of
limits.
!If
a
decision
point
in
a
system
(which
can
be
a
person)
is
responding
to
delayed
informa;on,
or
responding
with
a
delay,
the
decision
will
be
off
target.
Ac;on
taken
too
fast
can
cause
unnecessary
instability.
!When
there
are
long
delays
in
feedback
loops,
some
sort
of
foresight
is
essen;al.
To
act
only
when
a
problem
becomes
obvious
is
to
miss
an
important
opportunity
to
solve
the
problem.
!genchi
gembutsu
from
Lean:
understands
that
a
small
change
can
affect
the
overall
system.
the
person
close
to
the
problem
is
trusted
with
solving
it.
You
have
to
'go
and
see
for
yourself'.
don’t
change
your
strategy
on
a
whim!

47. 1)
Modeling 2)
Behavior
over
time 3)
Change
systems
with
different
users:
consider
how
role
changes
will
impact
everything.
Some
of
this
is
quite
hard
to
implement!
Understand
the
system
structure
you’re
building!
Work
with
developers
who
draw
diagrams
about
the
so[ware
system,
so
you
also
understand
technical
legacies
and
ripple
effects.

48. 9.
Numbers
(subsidies,
taxes,
standards).
8.
Material
stocks
and
flows.
7.
Regulating
negative
feedback
loops.
6.
Driving
positive
feedback
loops.
5.
Information
flows.
4.
The
rules
of
the
system
(incentives,
punishment,
constraints).
3.
The
power
of
self-­‐organization.
2.
The
goals
of
the
system.
1.
The
mindset
or
paradigm
out
of
which
the
goals,
rules,
feedback
structure
arise.
1)
Modeling 2)
Behavior
over
time 3)
Change
Leverage
points
Mention how we often find ourselves as consultants in a situation where we are working on one level - eg improving information flows - but effectiveness of the solution we are implementing is constrained by leverage points of a higher level (eg rules).

49. 1)
Modeling 2)
Behavior
over
time 3)
Change
Disruptive
startups
change
existing
systems
Behaviour
at
scale
Emergence
of
culture
Environment
readiness
Why certain businesses emerge from certain locations, contexts

50.
Take-­‐aways
The
‘worldviews’
that
people
and
elements
in
the
system
hold
The
processes
that
are
necessary
to
deliver
value
to
customers
!
How
to
gather
and
visualize
information
holistically
How
user-­‐centered
design
and
empathy
help
to
reduce
uncertainty
!
What
is
the
right
level
for
the
impact
you
are
aiming
for?
What
enables
the
change,
where
are
conflicts,
who
can
be
your
change
agent?

52. This
matters
because

53. Business
trends.

54. Humane
systems.

55. The intuitive mind is a sacred gift and the rational
mind is a faithful servant. We have created a society
that honors the servant and has forgotten the gift.
!
We will not solve the problems of the world from the
same level of thinking we were at when we created
them. More than anything else, this new century
demands new thinking:
!
We must change our materially based analyses of the
world around us to include broader, more
multidimensional perspectives.
!
~Albert Einstein

56.
Resources
The
Lean
Startup
by
Eric
Ries
!
Systems
Thinking,
Systems
Practice
and
Soft
Systems
Methodology
by
Peter
Checkland
!
Thinking
in
Systems:
A
Primer
by
Donella
Meadows
!
Business
Model
Generation
by
Alexander
Osterwalder
and
Yves
Pigneur
!
Donella
Meadow’s
article
Places
to
Intervene
in
a
System
can
be
found
at
http://
www.developerdotstar.com/mag/articles/places_intervene_system.html
!
Peter
Senge
is
a
key
systems
thinker,
I
haven’t
included
any
of
his
material
directly,
but
read
about
this
perspectives
especially
on
organisational
change.
Check
him
out.
!
For
the
design
geek
in
you,
read
up
on
Buckminster
Fuller’s
Design
Science.

57. Handout:
http://bit.ly/OQzwza