Change Management for Nonprofits Facing Demands for Data: Data is a lively topic in the private and public sectors. In May of last year, the National Endowment for the Arts (NEA) announced that for the first time in its 47-year history grants would be awarded to researchers to investigate the value and impact of the arts using “existing, high-quality data sets.” (NEA Newsroom, May 30, 2012). To date they have awarded $240,000 to 14 projects. Discussion and research are ongoing and resources are proliferating but as technology and methodology evolve so do expectations and standards. Data sets have been (and continue to be) developed and made available to nonprofit groups, as have tools that can be applied to analyze and visualize data to support decision-making and advocacy. However, a nationwide survey of nonprofits conducted in 2012 to investigate their relationships to data uncovered a dichotomy, “…either they were doing a lot with their metrics or not much at all.” (NTEN & Idealware, The State of Nonprofit Data, 2012, p.3). Many of the data sets, research reports, and tools that I have found to support data gathering and analysis would be available to any nonprofits in the survey, which led to my thesis that the adoption of successful data strategies has less to do with the availability of these types of external resources and more to do with internal culture and process. I have investigated strategies used for agile software development and design innovation, models for strategic planning and organizational change management, and principals from leadership theory, the biology of learning and emotional intelligence to propose a framework for thinking about data that can help nonprofit organizations successfully evolve in a data-driven era without undermining the heart or the complexity of their work in the arts and culture sector.

1. SPREADSHEETS stories+ &

2. emotions DATA=
"Fuehlometer" (Feel‐o‐meter) or "Public Face":
Julius von Bismarck, Benjamin Maus, and Richard
Wilhelmer
Lindau Island, Germany 2010
Berlin, Germany 2012‐2013
Algorithm created by Frauhenhofer InsHtute
ReacHve mechanical sculpture broadcasts the
mood of a town by capturing images of ciHzens
from cameras in public spaces and analyzing them
with an algorithm that equates visual expressions
with a happiness level to generate a “feel” average
that is reflected by the angle of the mouth and
eyes on the light sculpture that reacts in real Hme.
richardwilhelmer.com/projects/fuhl‐o‐meter

3. choice DATA=
Invest YYC: City of Calgary, Alberta
Crowd‐funding for local arts projects
Launched Feb 26, 2013
Approx. $400,000 invested to develop custom code
base now available as a “white label” soluHon.
Partnership with Calgary2012, Alberta FoundaHon
for the Arts, Calgary Arts Development and ABT
Financial.
Calgary Arts Development matched first $50,000 to
crowd‐fund over 30 projects in less than 2 months.
First local arts crowd‐funding site in the world that
offers curated local projects for funding (or
volunteering) and tax receipts for local donaHons.
DonaHons go to seamlessly through municipality,
to Alberta FoundaHon for the Arts, then to the
arHst if they reach 60% of their goal. DonaHons for
projects that are not funded are issued as credits
that can be put toward other projects.
www.investyyc.com

4. care DATA=
Improving Care with Data:
Seaale Children’s Hospital
ImplemenHng IBM PureData™
System for AnalyHcs to provide
leading edge care based on real‐
Hme paHent data and innovaHve
treatment with up‐to‐date
informaHon on outcomes for
specific intervenHons.
PaHent spaces in newest hospital
building designed with input
from therapists and specialists
from a range of backgrounds to
opHmize healing.
www.brightlightconsulHng.com/
clients/client‐stories/seaale‐
childrens‐hospital

5. place DATA=
CultureBlocks: Philadelphia, PA
Research 2009‐2012
Public site launched April 30, 2013
Office of Arts, Culture & CreaHve Economy
w/ collaboraHon from SIAP
funding from NEA, Our Town, ArtPlace
Data sets from local and naHonal sources.
Census, SIAP, SEPTA, City of Philadelphia,
NEA, School District, NaHonal Register of
Historic Places, and more...
Free public access.
Layered, filtered, custom maps + reports.
www.cultureblocks.com

6. connection DATA=
Hole in Space: Kit Galloway, Kit & Sherrie Rabinowitz
Los Angeles / New York, November 1980
Funded by The Broadway Department Store, NEA, other
private sponsors.
Public CommunicaHon Sculpture at Lincoln Center, NYC
and Century City, LA for three 3 days.
No signage, explanaHon or sponsor logos.
With image and audio thousands were able to
spontaneously connect with others across the country.
People gathered and made plans to meet. Word spread.
Some saw family or friends for the first Hme in years.
www.youtube.com/watch?v=QSMVtE1QjaU
Photography | © Galloway, Kit; Rabinowitz, Sherrie

7. sharing=DATA
Splash: Seaale, WA
Working with local organizaHons to
build capacity to provide clean
water to children in China,
Cambodia, Ethiopia, Nepal, India,
Thailand, Vietnam.
Established in 2007 and growing.
MulH‐year financials available in
friendly data visualizaHons
and PDF downloads.
NarraHves, photography,
illustraHon and animaHon
combined to tell compelling
personal stories about individuals
being helped.
splash.org/achildsright

8. proof DATA=
Proving.it: Splash
Seaale, WA
Working with local organizaHons to
build capacity to provide clean
water to children in China,
Cambodia, Ethiopia, Nepal, India,
Thailand, Vietnam.
Established in 2007 and growing.
Online mapping and reporHng to
document over 700 clean water
projects in 7 countries.
Striving to provide transparency
about status of specific projects for
sponsors, stakeholders, and to
support organizaHonal learning and
conHnuous improvement.
www.proving.it

9. life DATA=
Social Progress Index
Launched April 11, 2013
Skoll World Forum, Oxford UK
Created by Michael Porter (Harvard
Business School) as an alternaHve
to ranking on GDP. Social Progress
Capacity Index in development.
Data from World Bank, the World
Health OrganizaHon, and other
sources used to rank countries on
50 indicators (outputs not inputs)
related to human needs and
foundaHons of well‐being to spark
discussion on naHonal prioriHes
and guide social investment
decisions.
Network of partners in 50
countries. Goal to grow to at least
120 countries.
www.socialprogressimperaHve.org

10. strategy DATA=
Experience Music Project
TRG Case Study, Seaale WA
EMP engaged TRG to consult
on data processes and strategy
in spring of 2011
Admissions revenue increased $1.5
million in two years—up 37%.
Per Hcket revenue up 27% since 2010.
Improved markeHng ROI: 11% average
monthly cost‐of‐sale, down from 16%.
Online Hcket purchases up from 1% to
22% and growing in 2013.
Patron data captures have tripled.
hap://www.trgarts.com
hap://www.empmuseum.org

11. 5 exabytes every 2 days*DATA =
*enough to fill a stack of CDs that reach past the moon

12. NTEN, The State of Nonprofit Data, p.14 (2012)
DATA challenges are NOT NEW challenges

13. WE COLLECT IT but WE DON’T USE IT
NTEN, The State of Nonprofit Data, p.14 (2012)

14. Adapted from McKinsey & Co.
70% of CHANGE projects FAIL

15. Source: Adapted from Change ConsulHng Associates, and William Bridges, Managing Transi7ons
PRODUCTIVITY
TIME
TRANSITION
BEGIN END
Attentiveness
Comprehension
Undertake
Commit
TRANSITION
BEGINEND
IMPLEMENTATION
IDEA
OUTCOME
Idealized Concept
Logical Plan
Emotional Process
CHANGE = PROCESS of TRANSITION

16. David Poole “The Impact of New Technologies on the Arts” (2013)
SENSE MAKING IS NEEDED

17. Adapted from Gartner, Inc. (1995)
WHAT HAPPENS AFTER THE HYPE?

18. { lesson no. 1 }
DATA does not equal ANSWERS

19. “ere is nothing worse than a sharp
image of a fuzzy concept.”
—Ansel Adams
quoted by Ann Markusen: “Fuzzy Indicators, Proxy Data,” Createquity.com (11‐09‐2012)

20. BE WARY of TIDY METRICS
for COMPLEX PROBLEMS
INDICATORS = cutting CUBES out of CLOUDS

21. REALITY = ENGAGING COMPLEXITY
AMBIGUITY is more INCLUSIVE
+ leads to NEW IDEAS

22. “As we proceed towards profit & progress
with data, let us encourage artists,
novelists, performers & poets to take
an active role in the conversation.”
—Jer orp
New York Times Data Artist in Residence
“Big data is not the new oil,” HBR blog (2012)

23. The Names Arrangement by Jer Thorp. Photo source hap://blog.blprnt.com/blog/blprnt/all‐the‐names
2,982 names + 1,200 adjacency requests
THE NAMES ARRANGEMENT
algorithm by Jer Thorp

24. 9/11 Memorial by architect Michael Arad. Photo source whitehouse.gov
REFLECTING ABSENCE
9/11 memorial by Michael Arad

25. TALENTS for THE ROBOTIC AGE:
WHAT HUMANS can BRING to the TABLE
Marty Neumeier (2012)

26. “Adopt a humble attitude and
look at the problem om
a number of perspectives.”
—Marty Neumeier
Metaskills: Five Talents for the Robo7c Age (2012)

27. Edward De Bono, Six Thinking Hats (1985)
TRY DIFFERENT HATS

28. Edward De Bono, Six Thinking Hats (1985)
MORE BRAINS ARE BETTER THAN ONE

29. { lesson no. 2 }
SYSTEMS shape OUTCOMES

30. ACTIONS exist in a COMPLEX ECOSYSTEM
Adapted from the Monitor InsHtute (2013) with thanks to Kevin Hughes (2012)
*nothing happens without people
?= DATA*

31. System Map with mulHpliers from the NEA’s How Art Works 5‐year research agenda p.14 (2012)
CONSIDER INDIRECT FORCES

32. Thinking In Systems: A Primer (2008)
WE GET WHAT WE ASK FOR
“Systems, like the three wishes in
a fairy tale have a terrible tendency
to produce exactly & only what
you ask them to produce.”
—Dana Meadows

33. METRICS = OUTCOMES
but do better test results = better learning?
(not so far)

34. { lesson no. 3 }
MEASURE what MATTERS

35. good*
*see next slide
ASK
QUESTIONS
SHARE
LISTEN
+
+
+
RESPOND
[ h o w ? ]

36. “Virtuous Loop” concept: Bright Light ConsulHng (2013)
(THINK + ACT + OBSERVE) x infinity
= CONTINUOUS LEARNING

37. Tenet of “good clinical research” cited by The Lancet, leading medical journal
ANSWER IT RELIABLY
&
ASK AN IMPORTANT QUESTION
GOOD CLINICAL RESEARCH

38. *Annabel Beerel, Leadership and Change Management (2009)
ANSWER IT RELIABLY
ASK AN IMPORTANT QUESTION
what will you change?
responsively
&
GOOD ARTS LEADERSHIP

39. Monitor Ins7tute (2012)
EXPERIMENT, THINK BIG, COLLABORATE

40. USE DATA TO SUPPORT ARTS!

42. Adapted from Change ConsulHng Associates, Kubler‐Ross, On Death and Dying, Conner, Managing at the Speed of Change and IMA, Inc.
TIMEPassive
Active
Immobilization
Denial
Response: avoid confrontation,
strengthen relationship, focus on
smaller/first steps
Anger
Bargaining
Response: legitimize — anger
comes from loss of control, don’t
take personally, listen
Response: don’t (will redefine the
change), “there can be no deal”
Exploration
Response: test new options, acknowledge
progress, build confidence
Acceptance
Response: reward and acknowledge progress,
identify lessons learned, prepare for new change
Depression
Response: provide support, note resources available,
encourage responsibility, reframe to test
EMOTIONALINTENSITY
HOPE
Negative Change Reaction
Q: must leaders manage individual
transition through the grief cycle?
CHANGE = LOSS

43. A: only if they are dying!
In longitudinal studies on
loss, nearly 50% of the
population report no
debilitating grief at all.
Another 20% recover on
their own with no lasting
debilitation.
Only 1/3 of the population
is debilitated by loss.
Research by George Bonanno 2002‐2012 cited by Andrew Zolli
CHANGE = LIFE

44. Adapted from James Zull, The Art of Changing the Brain, p. 57 (2002)
CHANGE = FEAR PLEASURE&

45. “People actually like change.
ey just don’t like to BE changed.”
—Marty Neumeier
Metaskills: Five Talents for the Robo7c Age (2012)

46. thank you
Snow Dowd
Arts Leadership MFA
Seattle University 2013
snow@theMAKERS.com
SPREADSHEETS stories+ &