How can you predict the value of contextual research? What types of insight can you expect to get? @gilescolborne's slides from UPA 2011 I'll be adding speaker notes to these slides shortly.

1. Magic... or structured analysis?
Giles Colborne
cxpartners
@gilescolborne
http://www.flickr.com/photos/stevendepolo/4027405671/

2. This is Sarah. i visited
her researching how
people buy from online
auctions. She said: i’d
never buy clothes
from ebay. But when i
asked her to show me a
favourite purchase...
@gilescolborne

3. ...She ran up to her
room and got
these - designer
trousers bought
on ebay. When you
go into the field,
you discover the
answers you get in
the lab may not be
the whole story.
Dolce & Gabbana!
@gilescolborne

4. We need to get
into the field. And
as context
matters more, the
need is growing.
@gilescolborne
http://www.flickr.com/photos/32615508@N02/3047982712

5. but contextual
research is more
expensive. And it’s
hard to convince
budget holders to
pay it when the
premise is: ‘we don’t
know what we’ll find
out but it’ll be cool.’ They won’t let me
@gilescolborne
http://www.flickr.com/photos/cayusa/2666070091/

6. Field research yields
’s
lots of useless data. it
at
interesting to know th
where you keep your
phone says something
about how you use it -
but that won’t help me
design a mobile app.
@gilescolborne
http://www.flickr.com/photos/niyam/2105979190/

7. And the outside
world is such an
unpredictable
place, that luck
plays a part in
getting field
research right.
@gilescolborne

8. Unknown insights
irrelevant insights
Out of scope insights
Just plain unlucky
So that’s field
research. i need a way
of understanding
where i might get value.
And of training
colleagues to do it.
@gilescolborne

9. years ago, i asked an
d
expert how to plan fiel
research. she said - get
.
out there and just do it
That makes it sound like
we arrive at results by
magic.
@gilescolborne

10. Would you trust
someone who was going
to use magic? i’D want to
know what they had up
their sleeve.
So can we be more
structured?
@gilescolborne
http://www.flickr.com/photos/stevendepolo/4027405671/

11. When we research, we’re
looking for leverage
points - small changes
that can make a big
difference. They’re easy
to find in lab studies
because you cut out all
variables.
the @gilescolborne
http://www.flickr.com/photos/thalamus/2690847744/

12. in the lab, you have a
participant and a
computer. it’s easy to
see where the leverage
points are. you can
change the user (hard!)
or the device (easier).
@gilescolborne

13. in field studies,
it’s harder to
see where the
leverage points
might be.
@gilescolborne

14. Donella meadows was a
ed
systems analyst involv
in environmental
economics. She identified
12 leverage points where
you can influence a
complex system
Donella meadows
@gilescolborne

15. Constants, parameters, numbers
The size of buffers and other stabilizing stocks
More profound effect Structure of material stocks and flows
Easier to notice
Length of delays, relative to the rate of system changes
Strength of negative feedback loops
Strength of positive feedback loops
Structure of information flow
Rules of the system
Power to add, change, evolve, or self-organize system structure
Goal of the system
Mindset or paradigm from which the system arises
Power to transcend paradigms
@gilescolborne

16. Constants, parameters, numbers
The size of buffers and other stabilizing stocks
Structure of material stocks and flows
Length of delays, relative to the rate of system changes
Strength of negative feedback loops
Strength of to
She was applying this positive feedback loops
and
systems in economicsinformation flow
Structure of
the enviro nment, but we
can apply this to our system
Rules of the
information systems,change, evolve, or self-organize system structure
Power to add, s
too. Still a list of 12 item
Goal simplify
is complex. let’s of the system
it to make it easier to
Mindset or paradigm from which the system arises
apply.
Power to transcend paradigms
@gilescolborne

17. Constants, parameters, numbers
Physical
The size of buffers and other stabilizing stocks
Structure of material stocks and flows
Length of delays, relative to the rate of system changes
Strength of negative feedback loops
The physical layer isof positive feedback loops
Strength
about properties and
resources. The speed information flow
Structure of
of a computer Rules of the system
network, the amount
of time it takes to add, change, evolve, or self-organize system structure
Power to
complete a task. of the system
Goal
Para meters that affect
a system. Mindset or paradigm from which the system arises
Power to transcend paradigms
@gilescolborne

18. so a friend creating a
mobile train ticketing
app watched users to
see how long they
stood in line for
tickets at rush hour.
@gilescolborne
http://www.flickr.com/photos/macspite/877883222/

19. He figured that they
had to be able to
download the app and
buy before they got
to the front of a
ticket line. So a
constraint that he
had to meet.
@gilescolborne
http://www.flickr.com/photos/macspite/877883222/

20. Constants, parameters, numbers
The size of buffers and other stabilizing stocks
Structure of material stocks and flows
Length of delays, relative to the rate of system changes
Strength of negative feedback loops
Logical
Strength of positive feedback loops
Structure of information flow
Rules of the system the logical layer is
about what
Power to add, change, evolve, or self-organize is
information system structure
Goal of the system available, to whom and
what it does. You can
Mindset or paradigm from which late that to the
re the system arises
Power to transcend paradigms content and
functionality specs
for a system.
@gilescolborne

21. online
When we redesigned the
r a train
ticket buying service fo
ople at
company, we watched pe
people
train stations. We saw
ains that
arriving, looking for tr
’t
weren’t listed. They hadn
ral
realised there were seve
ey’d gone
mainline stations and th
missed
to the wrong one. They
their trains.
@gilescolborne

22. t
They didn’t have the righ
info. So we added clues
to the buying process so
they’d know which
stations they were
choosing. And we added
maps to the print-outs,
.
so they’d be doubly sure
in other words, we
changed the spec.
@gilescolborne

23. conceptual layer
Constants, parameters, numbers
is about ‘what is it
The size of buffers and other stabilizing stocks
we should be
doing?’ the scope of material stocks and flows
Structure
of the solution.
Length of delays, relative to the rate of system changes
Strength of negative feedback loops
Strength of positive feedback loops
Structure of information flow
Rules of the system
Conceptual
Power to add, change, evolve, or self-organize system structure
Goal of the system
Mindset or paradigm from which the system arises
Power to transcend paradigms
@gilescolborne

24. a
when i was researching
for
travel-agent extranet
an airline i visited travel
agents big and small.
People like Robin who
worked in a big travel Gail
on
agent had strict limits
web access. we’d have
needed to get the it
department to agree to
give him access to the
extranet.
Robin
@gilescolborne

25. ed
People like gail who work
set
at a small travel agent
up their computers just
’s
how they liked. But gail
ed
colleagues each favour
ould
different websites. it w Gail
to
be hard to get them all
adopt the site.
So there was really no
et.
audience for the extran
Robin
@gilescolborne

26. Gail
used
But Gail and Robin both
Robin RSS feeds - getting the
right
airline’s info onto the
ent,
feeds was a more effici
effective solution.
of
so we changed the scope
the project.
@gilescolborne

27. Physical refining
Logical spec’ing
Conceptual Scope
,
So now we’ve got a quick
easy to use model for
of
figuring out what kinds
for
leverage points to look
ject
- and what kinds of pro
they’ll be useful in.
@gilescolborne

28. when you’re planning
research, you can
d the
brainstorm the user an
ht we
context. Ask - what mig
s be
see? what might the user
doing?
This helps prime you
for the kinds of
observation you might
make. Cluster these
into rough timelines.
@gilescolborne

29. Three types of observation Then look for actionab
le
observations (ones you
can turn into physical
constraints, logical
specs or conceptual
Actionable
scopes). Actionable
observation
observations are Things
you can influence.
Link ‘context’
context observations (things
observation context you can’t use, but which
.
observation support and add flavour
Some observations will
be unconnected.
Now you have your
leverage points.
un-connected
observation
@gilescolborne

30. ars
My expert friend had ye
ed
of experience which prim
her about what to pay
attention to. But she
couldn’t explain that
unconscious knowledge.
ne
This method helps anyo
eld
prime themselves for fi
w
research. And helps sho
t you
your budget holder wha
might find.
@gilescolborne

31. What about luck? Can
we get over the risk
of bad luck? Dr.
Richard Wiseman has
studied people who
appear to be ‘lucky’
and noticed that they
have some common
traits.
Dr. Richard Wiseman
@gilescolborne

32. Social connections
Listen to your inner voice
Take control They develop large, stro
ng
can
networks of friends who
Expect mistakes help them. They listen to
ow
their inner voice and kn
eling.
when they have a bad fe
e
They take control of th
ce.
things they can influen
ere
And they accept that th
wilL be mistakes due to
. so
things they can’t change
lves
they don’t beat themse
d you
up. follow this advice an
.
can make your own luck
@gilescolborne

33. Prepare like crazy - so you can wing it.
conan o’brien
@gilescolborne

34. Magic... or structured analysis?
• Prepare by acting out the experience and the context
• Ask yourself where you’d find these points of leverage
• Physical constraints - good for refining
• Logical requirements - good for specing
• Conceptual scope - good for scope
But don’t mistake your
preparation for
g
research. You’re primin
not observing. don’t
let your budget holder
go away thinking you
have the answers. you
don’t.
@gilescolborne

35. keep something up your
sleeve. Tell them: we
found 23 potential
d
leverage points. We nee
e
to validate them. Becaus
the point of all this
planning is to let you go
out and do it all for
real.
@gilescolborne

36. giles.colborne@cxpartners.co.uk
@gilescolborne
follow cxpartners on Slideshare.net
@gilescolborne