[Ailist] Data Collection Question

[Mimi Delcuze]

Joan,
Thank you for the wonderful summary and expressive details of this
experience.
I also worked on a large project that originally was very data and "outcome"
oriented. As the project unfolded we learned from observation that simply
documenting the experience with photos and a few stories was the most "data"
we needed. We then observed and tracked the resulting activities of the
various groups. The report at the end of three years was full of the
abundance of experience, creativity and connection. Success!

Mimi Delcuze
Delcuze Consulting LLC

-----Original Message-----
From: ailist-bounces at lists.business.utah.edu
[mailto:ailist-bounces at lists.business.utah.edu] On Behalf Of Jody Jacobson
Sent: Tuesday, March 24, 2009 10:49 AM
To: ailist at lists.business.utah.edu
Subject: [Ailist] Data Collection Question

Dear Joan,

I worked on what sounds like a similar project at a multi-campus
technical/community college system. They have 42 cross-functional work teams
across two or three campuses and wanted all to engage in mini AI processes
within their teams. How they approached the project as a whole, and
especially how they collected data to support their subsequent strategic
planning process, were fascinating. 

Their Affirmative Topic and Why They Chose an AI Approach--

Their strategic focus, or affirmative topic was 'being a collaborative
workplace.' They'd gone through a survey-based campus climate review that
placed them in the middle of a five-level scale in which "collaborative" is
at the top. They were rated as being on the border between "coercive" and
"cooperative." (A positive image...) The project sponsors--the HR Director
and new System President--want to take a positive, strength-based approach.
Rather than focusing inquiry on being less coercive, they chose to inquire
into best experiences of collaboration within and across the 42 work teams.
The school's leadership, who first went through a mini AI workshop,
"nominated" (appointed) 15-20 staff members to be trained as AI facilitators
to lead 42 cross-functional work teams through an AI-based teambuilding
process. I can offer process details off-line.

How They Collected Data--

They formed a data/research subcommittee that created a database, including
stories, themes, and interview podcasts. While the data collection
structures and processes they created may be of interest to others (we'll be
sharing them at a Best Practices session through a Quality and Innovation
Network in the State, and may be able to post materials on the AI Commons or
share them in other ways), the reasons and how they created the subcommittee
are most instructive. I say this because they arose from the AI process
itself, after an initial two-day facilitators training, as a way of (a)
reconstructing the meaning of being an AI facilitator and (b) keeping people
engaged who otherwise would have opted out. Among those who'd been selected
to serve as facilitators were several people--primarily faculty, Media and
IT specialists, researchers and statisticians--who pushed back strongly
against the AI process, especially AI's conception of "data." 

Through continued dialog following an initial two-day training, the real
issue behind the push-back was surfaced: they were very uncomfortable about
facilitating, especially with groups of their peers. In a brilliant,
collective effort to keep all involved and for each to contribute their best
to the project, they reconstructed the meaning of "facilitator" and formed
three or four subcommittee, each of which was responsible for supporting a
part of the process. One of those subcommittees was Data and Research. I
believe another was Media-A/V. Because all were part of the facilitators
team, they collaborated within the team to create ways of collecting and
entering stories (from summary sheets) and themes (data) into a database.
The Media-A/V group provided video services to create podcasts of stories
that individuals and/or their work teams wanted to share broadly, like the
team member whose young daughter had cancer and to whom work team members
 contributed their vacation and sick leave time so she could be with her
daughter 24/7.

Socially Constructing "Data"--

The case supports what Jane Watkins says (she's in my head...) about
experience-based learning design in AI: "____(fill in your name), it's not
about you; it's about they-em!" While most of the groups I work with do not
create databases or podcasts, as this group did, most do want a record of
some sort--whatever form is most meaningful to them and their organizational
culture and forms of dialog--to spark conversation and both capture and
inform ongoing organizational learning. I've found that the best
"technologies" emerge from the Sponsor, Advisory Group, or Planning Group
and/or during the AI process itself.

Cheers,
Jody

Jody Jacobson, President 
Aerial View Consulting, LLC 
Clear Thinking ... Breakthrough Results!
www.aerialviewconsulting.com 
Phone/ 608.347.9961 

Fax/      608.204.0039

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