Sections:

Problem:  How do people interact with technology in organizational settings?
	  Particularly, technology that is designed to be modified by users

	2 interests: 
	  Theoretical:  Extend / enrich existing theory
	  Practical:    Implications for software design and organizational 
			and individual decisions about technology

Background:  Lens Study

	Describe Lens briefly -- allows people to specify how they'd like
		 their email to be processed
	Research strategy:  hold technology constant and study users
		 Research site, subjects, basic findings published elsewhere
	Problem: Technology was not constant, and in fact, users played an 
		 important role in changing it.
	Next:    Re-examine the theoretical issues

Theoretical Model

	Found two main approaches:
		Technology as independent variable, users actions as dep. var.
		Organization as independent variable, technology as dep. var.
	Some people have a different approach: Markus & Robey, Barley
	Structurational model provides a framework for examining both:
		Describe model
	Co-Adaptive phenomena
		Describe additions to the model to account for activities by 
		individuals and the effect of external events.

Lens revisited: Reanalyze the existing Lens data with the
	structurational model

	One example:  Creation of multiple rulesets
	Found it to be useful framework for evaluating both the effects of 
		the technology on individuals and also how individuals affect
		the technology

Athena study:  Explicitly evaluate how users customize their software
	environment, using the structurational model to frame the study

About customizable software:  definition, properties that make it 
	useful

Design of Athena Study
	Note about my relationship to research site
	Research site:  Lead users of a soon-to-be common technology
	Participants:  51/85 staff members (over 60 partial interviews)
	Data collected:
		Background of each person and job description
		Open-ended interviews about individual customization strategies
		Multiple snapshots of records of customization files 
			(variety, size, dates)
		Questionnaire about sources and recipients of files
		Questionnaire about who participants talk to 
		Review of individual customization files
		Records of open vs. closed files
		Screen layouts
		Aliases
		Reports of triggers and barriers
	Additional information: informal discussions, access to staff
		mailing list, on-line consulting logs, organization
		charts, office changes

	Rationale: Identify how users perceive their customization
		process and where possible, check the perceptions
		against actual behavior

Place basic findings back in structurational model:
	users both adapt to the software and also change it to meet
	their needs.  Show mechanism by which individuals can affect
	group norms, technology and organizational properties.

Highlights:
	Sharing:  Overwhelming evidence that users share customization files.
		Customization is not an individual activity
		Sharing occurs most when user first arrives
		Some people donate software to the group without feedback
		Others act as translators for individuals or groups
			One for each group
			Sometimes good, sometimes bad (E2 and E13)

	Stability: over 75% of users figured out a way to maintain the
		same pattern of use when the system changed (100% of
		whom had already invested in customizing the software).

	Context:  As in the Lens study, users use different strategies to 
		organize tasks based on their current work context -- e.g. 
		debugging, or fixing software in the field.

	Encode patterns: One of the most common triggers is when the user
		realizes that a particular pattern is being repeated often.
		Different methods of encoding it: alias, setup file, etc.

	Reflection:  users aren't aware of what they do, but make guesses, 
		which affect their decisions about how much and when to 
		customize.  Aliases example.  Certain external events
		may cause users to reflect on their use of the
		software, which increases the likelihood of customization.

Implications:

	First version of the software is important -- has long-term effect.
		Designers -- test it out carefully on real users
		Managers -- make sure there's a useful set of defaults
		Individuals -- make sure you don't invest too much time 
			in learning something that will soon be obsolete

	Previous software experience affects customizations and first 
		experiences may last for years.  Poor first versions last a 
		long time.

	Support sharing (but recognize that both good and bad files can 
		be shared).

	Maintain skills -- help users stop and reflect about their own 
		use of the technology so that they can benefit from 
		each other's experiences, examine their own behavior, 
		and make a set of choices about how to increase their 
		own productivity.

	Reflection --Provide users and translators with feedback about 
		their customizations.  Help them evaluate when it makes
		sense to customize or learn something new and when it 
		makes sense to continue working in the old way.

===============================================================================

The problems we face are that this technology is dynamic as are the
organizations that use them and methods borrowed from the natural
sciences do not always provide useful ways of thinking about the
problem.  So, I'm interested in extending the theoretical models that
are used to investigate this phenomenon.

My second interest is a practical one.  Software developers are increasingly 
developing software -- particularly software that is customizable -- but 
have no idea how this software is used and what the consequences of various 
design decisions are.  The software design process does not fully take 
into account the activities of users.

Computers have invaded the office environment and yet we have very
little understanding of how people interact with software.  There is
some evidence that suggests that productivity has dropped -- yet how
can this be?

Software environments are moving beyond single user, single terminal
to multi-tasking environments.


Yet, as I conducted the study, which lasted over a period of two years,
I realized that the users were changing Lens as much as being influenced
by it.  Treating the Lens technology as an independent variable providing 
a misleading view of what was happening.

=====================

Problem:  Technology is introduced into organizations with little 
thought as to how it is used - what are the effects of individual 
choices by individual users?  If software is designed without input 
of user's context.

=====================
Key findings:

	Sharing:    Customization is a social activity

	Encoding:   Users encode repeated patterns of use

	Context:    Users impose external context through customization

	Reflection: Users have inadequate information about their own use

	Stability:  Users strive to maintain common patterns of use 


	Decision process:

=====================

Three final Slides:

Limitations of the data

Theoretical implications

Practical Implications

=====================

Theoretical implications

Four key things:

Provided evidence for the co-adaptive nature of the use of
customizable software, situated in an organizational context

Data also speaks to the structurational model 
	social norms and organizational context
	being in one group vs another, 
  all have implications for how people customize

Other relationships not covered by structurational model:
	External events
	individual choice
	decision-making proces  
	individual roles, such as translator (all lumped together in model)

Elaborates the mechanisms in the structurational model
	eg. one powerful individual may have a tremendous influence
	by setting up norms that become the standard for the organization
	it becomes established and lingers for years.

Theoretical contributions about the nature of customization
	Increasingly common, but very little is known
	Not an individual phenomenon -- but a social one

May be relevant beyond information technology to other technologies
	May be relevant to learning and innovation -- where customization 
	and the decisions about it are subsets of the former two.

Implications for computer-supported cooperative work - rather 
	than just the technological fixes, take advantage of 
	the social sharing that goes on and the sharing of norms.

These patterns transcend the context and site.  cite nardi and miller.

======

	Validation of the co-adaptive nature of user's interactions 
		with customizable software

	Validation and elaboration of the structurational model

	Beginnings of a theory about customization


To Wanda, who became dissatisfied with the same things I did -- 


For seeing the same things in our different data and realizing 
that we were on the same track...

