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International Journal of Industrial Engineering and Management (IJIEM), Vol.5 No 4, 2014, pp. 221-232
Available online at www.ftn.uns.ac.rs/ijiem
ISSN 2217-2661
IJIEM
UDK: 005.591.6:005.32
UDK: 004.42InnoTrace
The Emergence of Creativity, Innovation and Leadership in Micro-
level Social Interactions and How to Research it
Hans Lundberg
Assistant Professor, Linnaeus University, School of Business and Economics, Universitetsplatsen 1, SE-351 95 Växjö, Sweden,
hans.lundberg@lnu.se
Ian Sutherland
Deputy Dean for Research and Director of PhD Studies, IEDC-Bled School of Management, Prešernova cesta 33, 4260 Bled,
Slovenia, Ian.Sutherland@iedc.si
Paul Blazek
Visiting Scholar, RWTH Aachen University, TIME, Kackertstr. 7, 52072 Aachen, Germany,
blazek@time.rwth-aachen.de
Birgit Penzenstadler
Assistant Professor, University of California, School of Information and Computer Sciences, Irvine, CA 92697, USA,
bpenzens@uci.edu
Hagen Habicht
Executive Director and Senior Research Fellow, Center of Leading Innovation & Cooperation, HHL Leipzig Graduate School of
Management, Jahnallee 59, 04109 Leipzig, Germany, hagen.habicht@hhl.de
Received (02.08.2014.); Revised (26.10.2014.); Accepted (18.11.2014.)
Abstract
The moment-to-moment unfolding of innovation, creativity and leadership is complex, non-linear,
recursive, largely tacit and influenced by micro-level social interactions. The methodology
InnoTracing supported by the software InnoTrace enables insights into the black box of such
emergent, situated processes by visualizing what participants regard as their particular ‘‘moments of
significance’’ (MOS) as they (according to participants subjective opinion) relate to creativity,
leadership, and innovation unfolding in real time. By gathering, aggregating, and analyzing real-time
data with a software tool InnoTrace, previously invisible micro-level social interactions are observed.
The InnoTracing methodology, a complement to the software InnoTrace, is a further development of
ethnomethodological methods, aiming to deal with such user-generated data. This provides a way to
study creativity, innovation and leadership processes as they unfold in real time among various actors.
This paper explains the InnoTrace software and InnoTracing methodology and presents first data
results from one empirical study.
Key Words: creativity, innovation, leadership, methodology, software
1. INTRODUCTION
For decades researchers and practitioners have
theorized and modeled group processes of creativity
[23], knowing in action [4], co-operation and competition
[5], [34] and the implications of management/leadership
in these [2], [14], [29], [39], [54]. However, a grounded
understanding of these processes, from the micro-
levels of interactions up, remains a black box. Their
complexity, non-linearity, unpredictability and largely
tacit nature are elusive [52], [61]. In our attempts to
enter this black box, we as researchers have faced a
central methodological problem, the imposition of
ourselves on the systems we seek to study. To the
phenomena we bring our own biases and beliefs, and
set out to identify and interpret what the significant
moments, events, actors and interactions are [35], [61].
To more effectively, robustly and objectively investigate
the ephemeral and emergent social interactions of
creativity, innovation and leadership, we argue for the
empowerment of research participants in generating the
data themselves; participants identifying the significant
moments, actors and interactions and working with us
to co-create understandings of what is going on at the
micro-foundations of these processes.
To this end, we discuss the InnoTrace software and
InnoTracing methodology, as a means of more
effectively removing the researcher from the processes
by affording the systematic collection and
representation of participant generated data. InnoTrace
puts data gathering directly in participants’ hands. It is a
222 Lundberg et al.
IJIEM
bespoke tool for researchers to engage participants
themselves to capture the “moments of significance”
(MOS) they experience in unfolding processes. The
software gives participants the ability to document
(through text, photos or videos) the MOS they
experience and aggregates this data into individual and
group cognitive maps. These maps represent a rich
tapestry of “what is going on” from the perspectives of
the actors most directly involved, and serves as in
depth data for researchers to investigate group
processes underlying creativity, innovation and how
management and leadership are implicated in them.
In what follows, we first provide a brief overview of
methodological changes within the study of creativity,
innovation and management/leadership. Here we
highlight sociological currents calling for more situated,
micro-level investigations. We then move to a
description of the InnoTracing methodology and the
InnoTrace web-based application, indicating how it
meets these currents and calls for methodological
innovation. We then provide an overview of one pilot
study that focused on an international leadership and
innovation conference in Germany. We conclude with
reflections on the use and outcomes of the software
and methodology as well as implications for practice.
2. LITERATURE REVIEW: A CALL FOR
METHODOLOGICAL INNOVATION
Over the last decade there has been a sociological turn
in research on creativity, innovation and
management/leadership within them. This turn has cast
our gaze towards the micro-level, seeing creativity,
innovation, management and leadership as social
processes that unfold in real time from moment-to-
moment in and amongst a group of individuals. As the
gaze has shifted there has been a breaking of
traditional phenomenological and methodological
boundaries in recognition of the need to consider “on
the ground” interactions of multiple participating agents
who make up these processes [35], [61].
Leadership studies are exemplary within this.
Traditionally leadership has taken a positivist stance. It
has sought its subject matter in individuals researching
the inaction of top-down, hierarchically derived
authority. In the last couple of decades the field has
been broadening its focus from studying singular
leaders and followers towards more contextual relations
of interacting, subjective social agents [35], [36].
Part and parcel of this shift has even been the
questioning of the basic ontological (does it “really” exist)
and epistemological (how do we come to know and
research leadership) assumptions of leadership [37],
[59], [2], [3]. This has led to a growth in social-
constructivist views – that leadership is a phenomenon
constructed, maintained, changed and distributed across
a variety of social agents who interact within certain
contexts, times and spaces developing shared and
conflicting values, beliefs and meanings of leadership [1],
[18], [28], [39], [43], [47], [54]. This “in action” view has
given birth to a number of closely related new theories:
distributed leadership [11], [29], [51], collective
leadership [20], [42], shared leadership [47], [48] and
relational leadership [54]. Often connected with more
complex processes such as creativity and innovation,
these theories approach leadership not as a given
hierarchically derived flow of power, but as a much more
complex, dynamic, and often times “messy” nexus of
processes.
During this same period, research on innovation has
also been shifting its focus. The innovation field has
been moving from placing attention on coordination
issues of specific R&D teams or departments towards
collaborative efforts spanning organizational boundaries
[5], [6], [23], [34]. Key to these changes has been social
software-enabled innovation methods involving
communities of practitioners [23] and including
organized contests [25], [34], [45] and innovation
toolkits [27]. Today, the innovation landscape is much
wider and richer than its original coordination stance.
Various forms and processes – e.g. open innovation –
are recognized and many of them are taking the form of
inter-organizational networks and crowd sourcing
mechanisms [45].
Changes in both leadership and innovation research
have amplified and challenged our understandings of the
phenomena. For example, we know more about
individual characteristics [23], [25], [40], [56], participant
motivation [27], [44], [32], [57], [33], management and
organizational characteristics linked to innovation
success [15], [62], [24], [41], [34] as well as insights on
outcome expectations [22], [27], [56], [55]. We still
though lack an understanding of how these processes
work from the micro level up. We know that innovation,
management and leadership emerge from individuals
interacting, but we know relatively little about how these
interactions play out. Consequently, we are often walking
blind when trying to improve these processes. Issues
such as constellations of actors, places of interaction,
times of day/night, and the subtle implications of the
subjective, sensory and emotional nature of group,
organizational and inter-organizational behaviour remain
hidden. What we propose is a focus on the in situ
unfolding of creativity across a variety of actors. To do
this we need to engage in tracing the actual process of
identifying and spanning of boundaries, or the self-
reporting about direct group-level effects of self-
rewarding activities (e.g. group flow [50]) and how all this
plays out through multiple series of moments-of-
significance as perceived by the participating agents.
Such subtle and grounded information would lead to new
insights on the actual foundations of collaboration. To
engage at such levels we need to re-invent our
methodological approaches, particularly in relation to
data gathering methods. We need data that allows us to
visualize the intangible and the invisible, moment-to-
moment emergence of collaborative processes and to do
so by operating at the situated level of individual work
and social interaction.
There are movements within our fields of interest,
particularly leadership, which have increasingly called
for such methodological approaches. For example,
Crevani, Lindgren and Packendorff [18] have posited
“…an analytical focus on leadership as it is practiced in
daily interaction” (p. 77). In a related call, Iszatt-White
has brought forward the need to consider ‘mutual
Lundberg et al. 223
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elaboration’ – “ …the idea that an action only makes
sense, has meaning, in the specific setting in which it is
enacted – to explore leadership practices as irreducibly
‘events in a social order’” [35] (p. 120). This
ethnomethodological tact, focused on understanding
how interacting agents produce the nature of their
interaction and consequent groups and outcomes,
“pays attention to, and seeks to make visible, the
‘ethno-methods’ [26] through which the social order of
[a] setting is inter-subjectively constructed…” [35] (p.
124).
As Parry [46] and Kempster & Parry [36] write,
Grounded Theory [16], [16] is a fertile ground for this
type of future research: “Leadership research has
begun to embrace the necessity of incorporating
context and process into an understanding of the
manifestation of the leadership phenomenon” (p. 106).
Others have also brought into the conversation the
aesthetic nature of social processes, focusing on the
felt, sensory-emotional aspects of leadership in action
[9], [31], [38]. Central to all these calls and approaches
is recognition of the need to explore systems of human
beings interacting from phenomenological angles. This
requires us to study the nature of social interactions and
how these processes emerge. To do this we need to
balance the individual and the group, to capture and
investigate the moment-to-moment experiences and
perceptions of what is going on.
An exemplary study is the process philosophy approach
of Wood & Ladkin [61]. In their work they involved a
number of research participants in photographing (at that
time using disposable cameras) moments that
contributed to their experience of leadership in the
organizations in which they worked. “Rather than
focusing primarily on the individual leader, or even the
dyadic relationship between leaders and followers, the
lens of process philosophy frames leadership as an
unfolding, emerging process; a continuous coming into
being” [61] (p. 15). Over a period of several months their
participants, notably not the researchers themselves,
took pictures of moments-of-significance that they felt
were ‘leaderly’ moments. What arose surprised the
researchers. These moments were not what one would
have expected. They were not pictures of great
speeches, or senior managers bustling over strategic
plans. Rather, they were photographs of consultants
helping secretaries with photocopying and cleaning staff
working late at night to make sure the premises were
ready for the next work day.
As insightful as Wood & Ladkin’s [61] work is, the viability
of such research was limited by available technology
(disposable cameras were less than optimal) and the
discontinuous nature of multiple, unconnected agents in
different organizations. We have lacked a
comprehensive tool and method to empower research
participants to more seamlessly collect such data, and to
systematically archive and visualize that data. This has
limited our ability to investigate the continuously “coming
into being” of human interactional phenomena. The
InnoTracing project meets this methodological gap. It
affords researchers and participants the ability to
document and comment upon significant moments
(MOS) as they relate to leadership, and innovation
unfolding in real time. Through the InnoTrace software
participants themselves can easily generate data on the
MOS they experience – via picture, video or text notes.
By doing so they generate individual and interacting
cognitive process maps of those moments they, not the
researchers, feel are significant and contributing to the
unfolding of creativity, innovation and leadership. The
InnoTracing methodology, largely based on a grounded,
ethnomethodological epistemology, provides researchers
with ways to then work with this data.
3. INNOTRACING: A NEW METHODOLOGY
FOR RESEARCHING MICRO-LEVEL
PHENOMENA IN COLLABORATION
InnoTracing* answers the methodological calls
discussed above. It is an approach combining a
bespoke data gathering and aggregating software
(InnoTrace) with grounded, ethnomethodological
methods for researchers and participants to work with
the data gathered. The data, focusing on MOS of
creative work, is generated directly by participants and
together with researchers opens, visualizes and helps
us investigate the black box of the micro-foundations of
creativity, innovation and leadership.
The InnoTrace tool, designed to be user-friendly and
configurable, is software that empowers participants to
document the momentary nature of ‘what’s going on’
(MOS) in the work and processes they are involved
with. The software, a web-based application that can be
run on any mobile device or PC, allows individuals to
take photographs, videos or write text messages on the
moments they experience. As users generate data the
software collects and organizes this data in a variety of
ways. Each photograph, video or text message is
uploaded to the individual user’s profile and archived
chronologically in an ongoing process map. Each data
point is a participant making “visible” what they perceive
as significant (whether the significance is of something
positive, negative or even mundane).
The process of InnoTracing has an anthropological
lineage drawing inspiration from studies, such the
aforementioned Wood & Ladkin [61] work, in which
participants have visually documented their perceptions
of the world around them. In organizational studies,
other examples include those by Buchanan [13] and
Warren [58] where they explored the aesthetic
experiences of work from individual social agents
questioning, “how it feels to work here” [58]. Within
innovation studies considering the micro-phases and
participant roles within teams, both in physical and
virtual settings, a variety of tracing approaches have
been leveraged in which audio and video recording,
screen shots, and versioning/history functions of
activities on collaboration-supporting innovation
software have been gathered [7], [8].
* http://www.innotracing.org
224 Lundberg et al.
IJIEM
What all of these approaches have lacked is a
comprehensive, systematic means of gathering,
aggregating and analysing participant-generated data.
InnoTrace and InnoTracing overcome this boundary. In
what follows we describe the standard four-step
process employed to leverage the web-based
application for participant generated data:
1. Phenomena of Interest: With each project the
researcher(s) indicate to the participants the
phenomena of interest around which they would
like to gather MOS. For example, a researcher
may say, “We would like you to capture all those
moments you experience as contributing to
innovation in your organization”.
2. MOS Tagging: Every MOS can be given a
descriptor – a tag. Within the tool, researchers can
include a variety of classification options (tags) or
leave tagging open to the discretion of research
participants. With each data entry participants can
provide their own tag, or in the case of researcher
specified tags select from available tags.
Additionally, in the case of open tagging, all tags
that have been generated appear as a word cloud.
Participants may select a tag from this cloud or
create a new one. The tags briefly describe what
was going on, from the participant’s perspective, in
that moment such as a “leadership moment” or
“idea generation” or “insight” and/or they may be
evaluative elements that classify the importance of a
moment (e.g. a star rating indicating relative level of
importance or impact of a moment).
3. Participant Generated MOS: The tool is made
available to research participants who, following
the Phenomena of Interest outline and using MOS
Tagging, engage in gathering data on the MOS of
processes in which they are involved.
4. MOS Aggregation and Visualization: As research
participants gather data the InnoTrace software
collects and organizes this data by user, time,
format and tag:
a) User: Each data element is registered as
generated by a unique author. This provides
indication of who generated the data as well as
frequency and quantity analyses of the overall
data set by individual author. Through this the
data set can be viewed as a whole, or
segmented to look at individual participants or
groups of participants.
b) Time: Each data element is registered by when
it was created. This provides indication of the
frequency and quantity of data as it was
generated chronologically. Through this the
data set can be viewed as a whole (providing a
distribution view of MOS over time) or
segmented to look at specific time periods.
c) Format: Each data element is registered by the
type of format used (photograph, video, text).
Through this the data can be viewed as a whole
indicating the overall types of formats used, or
segmented to look at one format type at a time
(e.g. to look at all photographic data).
d) Tagging: Tagging is the process of using a
descriptor or evaluator tag for data points. This
may be left to the discretion of users or
specified by researchers. Through this tagging
the data set can be segmented by participant
generated classifications.
As the data gathered grows it represents cognitive
maps of the individuals involved as well as the whole
cohort of participating agents: it is a shared or
composite cognitive map [18], [52] of group processes.
The perspectives of the group members are aggregated
in the form of a joint context map (as opposed to a strip
map) [53], [21] representing significant events captured
within their respective contexts. It thereby enables a
better understanding of the boundary conditions of
activities [53].
The meanings of these events, for example as
represented in open tagging, is not determined by a
researcher. Researchers do not decide what moments
are important or not, nor do they initially generate the
meanings of those events [12]. The data contained in
the cognitive maps is, as much as is possible,
unbiased, uninfluenced, situated data collected by
participating agents in the field.
In the following section we present some initial findings
from a pilot study carried out at an innovation and
leadership conference in Germany.
4. A PILOT STUDY
4.1 Overview
This pilot study focused on gathering participant
generated data on knowledge/information exchange
and learning – central processes to creativity,
innovation and leadership – amongst a group of
researchers and practitioners participating in the
Leadership for Innovation conference of the Peter
Pribilla Foundation. The conference was held at the
Technische Universität München April 25-26, 2013. The
conference provided a readymade temporal and spatial
event in which people were engaged in presentations,
formal/informal discussions and debates about
innovation and leadership. As such, the pilot study was
looking directly at moments of significance in
knowledge, information exchange and individual and
group learning – all essential to creative and innovative
processes in groups, teams and organizations. For the
pilot study we gathered a group of 22 conference
participants who, together with the five-member
research team, used InnoTrace to capture moments of
significance during the two-day conference. Participants
were instructed to “Trace any significant moment
connected to knowledge, information exchange and
learning”. Additionally, we decided to follow an open
tagging process, allowing participants to decide what
tags, if any, to use for the MOS they captured. Later,
working from a grounded theory approach, we drew
upon the participant generated data (in terms of
frequency, format and content) and conversations with
participants about their data and InnoTracing
Lundberg et al. 225
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experiences to analyse the MOS captured to gain
insights on the underlying individual and group
processes happening during the conference.
4.2 Participant gathering
Three weeks prior to the start of the PPS Leadership for
Innovation conference, an invitation email was sent to
conference participants inviting them to participate in
the pilot study. Follow up invitations were sent again ten
days prior to the conference. Additionally, during the
opening day of the conference, any other interested
parties were invited to join the process.
To incentivize participation, the project was described
as a launch event and a means by which volunteers
could document their conference experience and
capture the moments of learning that were particularly
impactful for them. We also gave each participant a
unique InnoTrace cow tag, created by cyLEDGE. In
addition to the 5-member InnoTrace team, we gathered
22 active volunteers who “InnoTraced” their moments of
significance of the conference. Anonymity of the data
gathered was assured and participation was completely
voluntary. In what follows we discuss the analysis of
this data and our findings.
4.3 Analysis and findings
Data gathered through the InnoTrace tool can be used
for most forms of qualitative analysis as well as for
descriptive statistics and quasi statistics (using
numerical/quantitative data in qualitative research
studies). The data is open to all the forms of analysis
that have been developed for participant generated
data including cognitive maps such as the creation of
sub-maps, e.g., identity maps, cause maps,
categorization maps, social system maps, hierarchic
maps, and cybernetic maps [30]. Moreover, quasi
statistics can help in estimating the centrality of issues
or incongruences between different views present.
While the earlier-described process is the essential
methodological approach offered by InnoTracing, it is
purposefully open-ended, particularly regarding
analysis. InnoTracing is itself a researcher-configurable
methodology. Using this basic structure, researchers
may approach the data gathering and analyzing
methods in ways best suited to their research questions
and goals.
For the Munich study we were both interested in what
and how participants documented. Our analysis was not
only focused upon what was captured – the pictures,
videos, texts and tags – but on the experiences of the
InnoTrace user. For the analysis we focused on
frequency of data points – looking for particular areas of
concentration and patterns in user tracing, a grounded
theory approach to content analysis and finally
reflections on the user experience. Below we present
the findings in this format covering: i) data point
frequency, ii) content analysis, iii) user experience.
i) Data point frequency analysis:
An important aspect of the InnoTrace software is the
ability to visualize the entire data set regarding time and
user activity. This provides researchers insights into
when MOS occur, and where MOS occur
simultaneously for multiple participants. Table 1 (below)
summarizes the frequency of traces by participants
from the pilot study.
Table 1. Summary of frequencies from Peter Pribilla Conference, April 25-26, 2013
226 Lundberg et al.
IJIEM
Before the conference, we registered 40 user
positions. Of these 40, 33 were signed up for. Of
these 33, 28 were active during the conference. Of
these 28, 22 were participants, 5 were the InnoTrace
team and 1 was a cyLEDGE software developer. As
this was the pilot run of both the software and the
methodology, we saw it as crucial that we as
researchers actively participated in order to speed up
our own learning curves regarding the hands-on use
and functioning of InnoTrace and InnoTracing. That
said, we analytically separate our data from the “real”
participants, as summarized in table 2.
Table 2. MOS per category of users
Category of Users No of MOS In %
Researchers/Developers 131 57,8
Top 3 most active
Participants 46 20,3
(Users 1,
10,15)
The other 19
Participants 50 22,0
No of MOS total 227
Not surprisingly, we as researchers were frenetically
engaged in seeing how the things we developed
worked. This explains why the activity of the five
researchers and the developer constitute over half of
all MOS (57,8 %). Regarding the 22 “real”
participants, we can observe the early adopter
pattern, in which a few technology enthusiasts keen
on anything new in the tech world, make up for
almost half (46 of 96 MOS in total) of the activity at
the conference. The average “normal user” did
between 2-6 MOS during the two conference days, in
summary as follows from table 3:
Table 3. Low frequency users vs. heavy users
7 out of 22 Participants did no MOS at all
6 out of 22 Participants did 1-3 MOSs
3 out of 22 Participants did 4-6 MOSs
6 out of 22 Participants did 7 or more MOSs
We can also observe another common pattern when
adopting/testing new technology/new methodology;
as can be seen in table 4, the activity is considerably
higher in the beginning (=day 1) and drops
dramatically as time pass by (= day 2).
Table 4. MOS per day
MOS per Day No of MOS In %
April 24 (Arrival Day) 5 2,2
April 25 (Event Day 1) 149 65,6
April 26 (Event Day 2) 71 31,3
April 27 (Post Event Day) 1 0,45
May 2 (Ad Hoc Outlier) 1 0,45
No of MOS total 227
Partly, the dramatic drop can be explained by the fact
that some participants only attended day 1, but that
said, it only accounts for a minority of the reduction in
amount of MOS from day 2; clearly, engagement
went down during day 2, and it was an important
indication to us as researchers to reflect upon how to
maintain engagement over longer periods of times for
the tool and for the methodology.
Table 5. Photos per category of users
Photos by Researchers/Developers 85
Photos by top 3 most active
Participants 23 (Users
1,3,10)
Photos by the other 19 Participants 26
To our surprise, the 22 participants shot only 2 videos
during these two days. By far, photos were the
preferred format for documenting MOS. In
conversations with users we followed up on this
insight asking them why they took pictures more than
any other data format. The responses indicated two
primary reasons. Firstly, taking pictures is quick and
efficient, particularly if using a mobile device such as
a smart phone or tablet. Secondly, users described
this as normative behavior:
“We take pictures of what’s going on all the time
these days. This is just a nice extension of that which
also gathers those pictures all together in one place”.
As for the usability of the tool, this speaks well to its
design and how it relates to contemporary normative
behavior with mobile devices. Indeed it has become
ubiquitous to take a picture of events, notes on a
white board, slides of a presentation, selfies, and
more. The feedback from users indicated that
InnoTrace smartly leverages this behavioural shift for
data gathering.
However, the frequency and data formats do not tell
us much about “what’s going on”. In our content
analysis we found the MOS relating to idea
visualization and social interactions.
ii) Data content analysis:
Above we indicated key findings from the frequency
of the MOS captured in the pilot study. Here we
reflect on the significance of the content, what
InnoTrace makes visible. In our initial analysis of the
data we saw two interrelated findings on participants’
moments of significance at the conference: a)
visualizations of ideas and b) visualizations of social
interactions.
a) Visualization of ideas:
The primary type of MOS documented during this
pilot study was ‘idea captures’. As participants
InnoTraced, they were most often documenting ideas
that they encountered (i.e. ideas from others) or
created themselves. Primarily they came in the form
of screenshots with text notes, i.e. pictures of a
speaker and/or presentation slide accompanied by a
short text message. Though the types of ideas
captured were wide ranging, they can be grouped
into two categories: inspirational and practical
insights.
Throughout the conference participants and
presenters alike shared inspirational ideas. What we
have classified as inspirational ideas are ideas that
are more abstract, wide-ranging, and somehow
capture the attention and imagination of participants.
For example, user ‘test19’ traced “you have to stay
curious, no matter [how] young or old!” while ‘test15’
Lundberg et al. 227
IJIEM
traced “the limits of innovation are no longer in the
technology, they are in our heads”.
While many participants documented such
inspirational ideas, they also captured more practical
insights. For example, ‘test10’ traced the idea
“colored screens for cellphones are overestimated”
while ‘test14’ traced “managing public transportation
by cellphone user density… Nice!”.
Two important insights begin to emerge here
centered around the convergence and divergence of
the ideas captured. What the InnoTrace cognitive
map showed was the diversity across the group in
what was seen as significant. The group, as a whole,
documented a wide range of ideas from the
inspirational to the more practical. As a visualization
of the invisible, what we saw was a rich tapestry of
discreet but intersecting ideas. Of particular
importance to this was the tag cloud that emerged.
As discussed below, one user (‘test8’) noted the
significance of the tag clouding providing “an idea of
the thinking already out there”. As an indication of
what the group was doing and finding significant,
what we saw was a map of the diversity. However,
while there was divergence, there was also
convergence – moments that multiple users captured
as significant. For example, three users – within 1
minute of each other – traced the idea that innovation
constraints are “in our heads”:
- Test10: “The limit of innovation is our
imagination”
- Test15: “The limits of innovation are no longer in
the technology, they are in our minds”
- Researcher (InnoTrace team): “Leading
innovation is difficult to make happen, requires
looking into the fog, the real limit is imagination,
we need to build systems and networks”
This visualizes not only the divergence of ideas in
knowledge and information exchange but also the
congruence that happens. Importantly, it also shows
how people interpret the same ideas in different
ways. While ‘test10’ hit particularly on imagination,
‘test15’ and ‘Researcher’ also noted technology,
leadership, systems and networks.
In sum, what the data indicated was the differences
and similarities in perceptions of significant moments,
both in terms of diverging moments captured and in
terms of different perspectives on convergent
moments. The cognitive map was effective as a
visualization of the “messiness” of information,
knowledge and social exchange occurring across the
group. Next we discuss insights regarding the social
interactional elements captured during the study.
b) Visualization of social interactions:
In addition to ideas, the social interactions at the
conference were significant in the data. There were
three types of social interactions captured: community
celebrities; new contacts; conversations in action.
The conference involved talks and presentations by a
number of “celebrities” (well known scholars and
practitioners from the leadership and innovation
community). Within the data, participants often
documented invited talks with photos accompanied
by texts about their enthusiasm for the presenter, or
meeting speakers during coffee and lunch breaks. As
MOS they were significant as participants met, often
for the first time, individuals whose work and ideas
they know and respect. They were documenting
these moments of connection and networking.
There were also traces of participants meeting other
new contacts. These were moments where a new
connection was made with another conference
participant with whom ideas were shared. In both the
cases of community celebrities and new contacts, the
cognitive map that developed indicated new social
connections giving insights into the developing social
networks of individuals involved.
In this vein, a number of InnoTracers also captured
conversations in action. These were primarily
pictures of fellow conference participants engaged in
conversation during coffee and lunch breaks. These
conversations were occurring inside and outside,
around tables, on the open terrace, just about
anywhere. Such MOS give an indication of the
community in action through information and
knowledge exchange in a variety of social areas.
In total, the InnoTrace data collected gave significant
insights into the micro-level interactions of individuals
and groups within the overall conference format. The
cognitive map created gave us insights into the kind
of moments that were perceived as significant. These
were primarily around new ideas and social
interactions. In terms of idea captures, the data
indicated participants’ divergence and convergence
around the many inspirational and practical ideas that
were shared. Additionally, traces of community
celebrities, new contacts and conversations in action,
began to visualize the social experiences and
networks that underlay the ideas experienced.
iii) User experience:
A particular area of focus for the InnoTrace project is
how the user experiences the process of tracing
moments of significance and how the tool becomes a
mediating technology for group processes in which
they are involved. Through the data, conversations
with participant InnoTracers and from the
experiences of the InnoTrace team, we noted three
significant aspects of the user experience: personal
diary; motivational tool; medium of interconnection.
In discussions with InnoTracers and the InnoTrace
team, we found that a significant aspect of the user
experience was the ability to create a personal diary of
MOS. There was a clear indication that the tool was
being used to document personal insights (ideas
encountered or created) and social connections. Users
noted the ease at which they learned to use the tool
and could quickly capture MOS and have them
chronologically organized by the software. Additionally,
each individual was able to look back on all the MOS
captured, to relive the moments. This personal diary
aspect also served as a motivation, an innovative way
to capture their conference experience.
228 Lundberg et al.
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A second significant finding relates to how the
InnoTrace tool mediated user experience of the
conference. A number of participants, as well as the
InnoTrace team itself, noted that the tool heightened
attention and focus. With the ability to capture MOS,
individuals found that they paid more attention to
what was going on around them, both in formal
sessions and in informal gatherings (coffee breaks,
lunch). The empowerment of being able to gather
data itself motivated participants to look for data.
This indicates the influence of the InnoTrace tool on
the phenomenon being studied. Any research will
ultimately influence the system being researched, just
by choosing to research something we influence the
system. However, with the case of InnoTrace, the
data gathering by participants had the added, positive
effect of enhancing their experience. They felt
motivated to really investigate what was going on be
attuned for things of significance. This was no doubt
partly influenced by the newness of the tool and
experience, and biased by the community of early
adopters (discussed above regarding frequency).
However, given that taking pictures, videos and notes
of one’s experiences of group activities (such as
conferences) is a regular occurrence, one important
factor of InnoTrace is the focusing of that kind of
activity towards data gathering and the automatic
aggregation of that data by the software. This in itself
seems a significant motivator for participants.
However, as noted above, there was a significant
drop of user activity by the second day. In
subsequent projects we devise ways of keeping
people engaged beyond the initial enthusiasm.
As a final point of interest from the user experience
perspective, we found that InnoTrace served as a
powerful medium of interconnection. This happened
both virtually – i.e. within the software itself, and
physically – the community of InnoTracers present at
the conference. In terms of the virtual
interconnectivity, users such as ‘test8’ noted how
InnoTrace – particularly the tag cloud – provided an
insight into the invisible nature of information and
knowledge exchange: “I like the way the tags
everyone else has used appear. Helps to give me an
idea of the thinking already out there”. In this sense,
the tag cloud served as a virtual means of seeing and
experiencing others’ experiences in real time during
the conference. As the tag cloud grew, this crowd-
sourcing of perceptions was mobilized by many
participants who re-used existing tags, thereby
connecting their experiences, thoughts and ideas to
others. This developed a sense of community. The
“InnoTracers” (as they became self-named) became
a sub-group of the conference, notably identified by
their InnoTrace cow tags. There developed
camaraderie around the process of tracing MOS, an
additional community of interconnection and
interaction.
This initial study provided valuable insights around
InnoTrace with respect to frequency of MOS, data
formats used, types of MOS captured and how
InnoTrace helped focus attention on the phenomena
of interest. The data provided researchers unique,
first level insights, through cognitive maps, in
individual and group level interactions.
5. CONCLUSION AND IMPLICATIONS
Responding to calls for methodological innovation in
leadership and innovation studies, the methodology
InnoTracing is a means of focusing on the micro-
level, situated action of participating agents in real
time. It does so by empowering participants to
generate data related to what they see as moments
of significance (MOS) in leadership and innovation
processes. This provides researchers with a powerful
entrée into the black box of emergent, situated
processes.
Within the pilot study discussed above we found the
software tool InnoTrace to be highly effective in
generating the kinds of unfiltered data – the moments
of significance of individuals within group settings –
with which researchers may investigate the micro
level of daily interactions. This initial study clearly
pointed to the fluidity of the web-based application
interface, the usability of the application, and the
feeling of empowerment individuals found by using
the application.
What emerged from the case was a participant
generated visualization of the moments of
significance (MOS) in relation to idea generation and
social interactions. Through the data we could “see”
the diversity of moments perceived as significant by
participants, as well as the divergence and
convergence around these moments. Additionally,
the tracing of social interactions indicated how, where
and when social networks were developing. This
provides us with important information on what
captures the attention of multiple group members and
how these moments coalesce in groups to move
processes forwards.
One key finding relating to the usability of the
application is the drop-off rate of users. As with any
new technology, early adopter enthusiasm is often
followed by a drop off of intensity. For future studies,
InnoTrace must become a habitual activity for users.
To accomplish this we suggest longer training, initial
test periods and intermittent communication (e.g.
emails or SMS prompts) with participants to remind
them of their InnoTrace activity.
Additionally, we found that the tool itself becomes a
mediating technology for peoples’ experience of the
world around them. InnoTrace, particularly in the
opening stages of using the tool, became an
intensifier of experience. It became a means of
creating a personal diary as well as feeling more
connected to the wider social setting – both virtually
through tag clouds, and physically as part of an
InnoTrace community. In this vein, the axiom that
researchers always influence the systems they study
holds true. By virtue of our decision to research
something, we have already existentially influenced
the phenomenon by giving it value. However, in the
hands of participants, InnoTrace encouraged
individuals to be more fully present, to be more aware
of what was going on, and to pay attention to and
Lundberg et al. 229
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document those MOS that they have. Additionally,
the novelty of any such technology eventually wanes
as its use becomes more habitual. We would
anticipate that in long term studies, the InnoTrace
application would become a normal, everyday tool for
capturing daily group interactions and less of an
intensifier of experience, just as our smart phones,
tweeting and facebooking have become normal,
everyday events in a social setting.
Fundamentally, InnoTrace is a unique, systematic,
user-friendly and configurable tool to capture the
complex, non-linear, recursive, unpredictable and
largely tacit phenomena of leadership and innovation.
It does so by, through the methodology InnoTracing,
bringing together researchers and empowered
participants in a process of gathering, aggregating
and analyzing data that visualizes the invisible
aspects of leadership and innovation. This software
and methodology combination offers researchers the
ability to work with participants to capture the
subjective messiness of these processes by
documenting moments of significance as they are
perceived in real time by involved participants. This
software and methodology combination affords a
wealth of visual, audio-visual and textual data and
insights into group processes. By empowering
individual participants it gives a more intimate and
multi-perspectival view to the individual and group
experiences and interactions of the moments
constituting leadership and innovation.
While there is great value and potential of this
combined software and methodology as a means for
research, there are implications for practitioner work
as well. In particular, the software InnoTrace is
proving to be highly useful in capturing and tracing
the work of individuals and groups, particularly in the
space of creative work. It is a means for documenting
the plethora of thoughts, ideas and connections that
occur as people work together and individually. In this
sense it has practical applications as an archival
resource to develop a repository of ideas developed
which may otherwise be lost. Additionally, as the
methodology InnoTracing provides insights into how
a group interacts, the outcomes can be used to
optimize group processes. Understanding more
clearly where, when and with whom the most
productivity arises is a key managerial tool for
enhancing the creative, and ultimately innovation,
work of a team, department or organization. Finally,
as has been commented on above, the InnoTrace
tool has the added effect of motivating people to
become more focused and conscious of what is
going on around them. When asked to document
MOS, individuals are more attentive to the moments
they are experiencing. This behavioral shift is
potentially highly valuable in enhancing individual and
group work within organizations.
InnoTrace and InnoTracing hold much promise. As a
combined software tool and methodology we have
found this combination a useful entrée into the micro-
level moments of interaction that constitute group
processes. However, the major limitation at this point
is the limited use of the tool. In addition to the above-
mentioned pilot, a four-month study has been carried
out at a Mexico City firm. The data of this is currently
under analysis. What is required at this point are
additionally studies in a variety of organizational
contexts.
We thank the Peter Pribilla Foundation who made
this project possible by bringing us together as a
team and by funding part of this research.
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Pojava kreativnosti, inovativnosti i liderstva na mikro nivou
društvenih odnosa i kako ih istražiti
Hans Lundberg, Ian Sutherland, Paul Blazek, Birgit Penzenstadler, Hagen Habicht
Primljen (02.08.2014.); Recenziran (26.10.2014.); Prihvaćen (18.11.2014.)
Rezime
Odvijanje inovativnosti, kreativnosti i liderstva iz trenutka u trenutak je kompleksan
process, nelinearan, rekurzivan, uglavnom prećutan i pod uticajem društvenih odnosa na
mirkro nivou. Metodologija ,,InnoTracing” podržana softverom ,,InnoTrace” omogućava
uvid u crnu kutiju takvog pojavnog, situiranog procesa vizualizujući ono što učesnici
smatraju svojim trenutkom od posebnog značaja, kojeg oni (prema subjektivnom
mišljenju učesnika) povezuju sa kreativnošću, liderstvom i inovativnošću, a sve u
realnom vremenu. Prikupljanjem, objedinjavanjem i analizom podataka u realnom
vremenu primenom softvera ,,InnoTrace”, posmatra se ranije nevidljiv mikro nivo
društvenih odnosa. Metodologija ,,InnoTracing” kao dopuna softvera ,,InnoTrace”
predstavlja dalji razvoj etnometodoloških metoda, sa ciljem upravljanja podacima
generisanim od strane korisnika. Ovo obezbeđuje način da se analiziraju procesi
kreativnosti, inovativnosti i liderstva koji se odvijaju u realnom vremenu između različitih
učesnika. Ovaj rad objašnjava softver ,,InnoTrace”, metodologiju ,,InnoTracing” i
prezentuje prve rezultate iz jednog empirijskog istraživanja.
Ključne reči: kreativnost, inovativnost, liderstvo, metodologija, softver.
IJIEM
