TAKING PRESSURE OFF KNOWLEDGE WORKERS
WITH THE HELP OF SITUATIONAL APPLICATIONS
Improving Time-to-proficiency in Knowledge Work Settings
Daniel Bachlechner, Michael Kohlegger, Ronald Maier and Gabriela Waldhart
Innsbruck Information Systems, Innsbruck University School of Management, Universitätsstraße 15, Innsbruck, Austria
Keywords: Knowledge work, Situational applications, Task-technology fit, Time-to-proficiency.
Abstract: Knowledge work is weakly structured, highly diverse and fast changing and thus needs flexible, personal-
ised support by software. Situational applications are a new breed of software that is assumed to fit to the
types of tasks and contextual requirements encountered in knowledge work settings. Furthermore, their ap-
plication is supposed to result in shorter time-to-proficiency. The main goal of this paper is to discuss these
assumptions taking the constructs of the task-technology fit model as well as the relationships among them
into account. Based on the model, three propositions are developed and discussed.
1 INTRODUCTION
Profound transformations of organisations backed by
information technology (IT) and the shift from tradi-
tional work to knowledge work (KW) (Kelloway et
al., 2000) have substantially changed workplaces for
many employees. From an IT perspective, increas-
ingly complex data need to be handled in weakly-
structured, highly diverse and fast-changing working
environments. Software, designed to support tradi-
tional work, cannot entirely cope with the require-
ments of KW. Furthermore, traditional software
development is slow and often delivering only a
subset of or an approximation to the potentially
useful and required functions.
Cherbakov et al. (2007, p. 2) describe end-user
development of situational applications (SAs) as a
trend promising to better meet the requirements of
KW settings. A recent IBM survey shows that 12%
of business employees and 42% to 68% of IT em-
ployees have already created applications to auto-
mate business functions outside official IT projects
(Cherbakov et al., 2007, p. 3). Enabling the devel-
opment and utilisation of SAs in a governed and
secure environment is a promising approach to pro-
vide knowledge workers access to the software sup-
port they need while avoiding the negative effects of
shadow IT.
The increasing presence of KW (Wolff, 2005, p.
37-42) and grassroots approaches in software devel-
opment suggests rethinking existing models explain-
ing the utilisation of software. In this work, we use
the task-technology fit (TTF) model (Goodhue,
1995; Goodhue et al., 1995) as a conceptual basis for
the analysis of the fit between SAs and tasks of KW.
The applicability of SAs in KW settings will be
discussed with a focus on the time needed to become
proficient in a new position where most tasks can be
characterised as KW.
Time-to-proficiency (TTP) is defined as the
amount of time an individual spends in a new job
environment before it is able to fulfil most tasks
without help from colleagues or supervisors (Wil-
liams et al., 2004). Although numerous factors influ-
ence TTP (Morrison et al., 1992, p. 930ff), changes
in routines and differences between positions are the
most significant ones (Pinder et al., 1987, p. 348).
Studies on potential savings resulting from reduced
TTP have already been conducted in fields such as
health care (Sullivan et al., 2003). The potential of
reducing TTP by means of innovative IT has not yet
been in the focus of research.
The goals of this paper are to discuss the appli-
cability of SAs in KW settings as well as to con-
struct propositions based on the TTF model. Section
2 explains the TTF model and its constructs focusing
on the utilisation of SAs for KW. Section 3 presents
three propositions based on the TTF model and
section 4 concludes with proposals for evaluating the
propositions.
378
Bachlechner D., Kohlegger M., Maier R. and Waldhart G..
TAKING PRESSURE OFF KNOWLEDGE WORKERS WITH THE HELP OF SITUATIONAL APPLICATIONS - Improving Time-to-proficiency in
Knowledge Work Settings.
DOI: 10.5220/0003118203780381
In Proceedings of the International Conference on Knowledge Management and Information Sharing (KMIS-2010), pages 378-381
ISBN: 978-989-8425-30-0
Copyright
c
2010 SCITEPRESS (Science and Technology Publications, Lda.)
2 TASK-TECHNOLOGY FIT
The TTF model explains how technology leads to
performance impacts (Goodhue et al., 1995, p. 215).
The central dependent construct of the model is the
individual’s interpretation of the fit between a task
and a technology. This fit is not only affected by the
task and the technology themselves, but also by
characteristics of the individual and, as it is not di-
rectly measurable, the user’s evaluation of the fit is
taken as a surrogate. It is assumed that a better fit
leads to higher performance.
Within the scope of this work, the task is charac-
terised as KW, the technology as either a traditional
or a situational application and the individual as a
digital native. Below, the TTF constructs and their
operationalisation for this work are explained in
detail. TTP is used as performance indicator.
Task. Tasks are actions performed by individuals to
transform certain inputs into outputs (Goodhue et al.,
1995, p. 216). They are characterised by their variety
and difficulty (routine versus non-routine), interde-
pendence (number of other systems to be integrated)
and degree of hands-on character (flexibility to meet
data needs and access routines) (Goodhue, 1995, p.
1833).
According to Schulze (2004, p. 46), knowledge
workers distinguish themselves from non-knowledge
workers along two dimensions: (1) they possess
mostly abstract knowledge requiring high levels of
formal education and (2) they produce new knowl-
edge rather than merely manipulate knowledge.
Maier (2007, p. 46f) describes KW as creative work,
addressing ill-structured problems in complex do-
mains with a high degree of variety using intellec-
tual abilities and specialised knowledge, organised
decentrally and requiring flexible, personalised IT
support. Concerning IT support for KW, new chal-
lenges are complex synchronisation needs of mobile
workspaces, information sharing within and across
organisational boundaries as well as finding docu-
ments and messaging objects using heterogeneous
formats and residing in a variety of distributed data
sources.
Knowledge workers have to orient themselves in
a dynamic and unpredictable environment requiring
decisions driven by unexpected events and excep-
tions to documented processes. In summary, they
face tasks which can be characterised not only as
particularly non-routine and interdependent but also
as exhibiting a high degree of hands-on character.
Thus, following the line of Goodhue’s (1995, p.
1833) argumentation, we can assume that knowledge
workers find traditional applications less able to
meet their needs than non-knowledge workers.
Technology. Technologies are tools used by indi-
viduals to carry out tasks. They are either computer
systems or user support services (Goodhue et al.,
1995, p. 216). We focus on software as technology
for KW and distinguish between two types of appli-
cations: traditional and situational applications.
Traditional applications usually address anticipated
situations requiring planned responses. KW, how-
ever, is characterised by unanticipated situations
which make unplanned responses necessary.
While developing and maintaining applications
that meet the requirements of KW is expensive, the
number of potential users per application typically is
rather low. Thus, applications supporting KW usu-
ally have low priority for IT departments and
knowledge workers often have no choice but to rely
on shadow IT.
The approach to develop SAs diverges signifi-
cantly from traditional methods (Cherbakov et al.,
2007), allowing solutions that are far more flexible
and dynamic than the ones available today. SAs are
highly context-specific sets of functionalities, ar-
ranged and put into use by an end-user to perform
certain tasks.
In traditional software development, develop-
ment phases are well defined and follow an agreed
procedure. Nevertheless, schedule overruns are fre-
quent. With respect to SAs, there are no defined
phases, milestones or schedules. The focus typically
lies on good-enough solutions that address immedi-
ate needs. Developers of SAs usually expect short
time-to-value from identifying needs to productive
application use.
Functional requirements of traditional software
are usually defined by a limited number of users.
Developers need to finalise requirements specifica-
tions in order to move to design and implementation.
Thus, changing business needs often lead to scope
creep. SAs usually accommodate requirement
changes caused by business changes. While re-
sources are allocated to address concerns such as
scalability and maintainability in traditional software
development, there is little focus on non-functional
requirements in the context of SAs. Thus, traditional
applications are often more robust.
The characteristics of SAs make them particu-
larly interesting for the needs of KW. SAs allow
giving form-fit to solutions with a particular task in
mind. DeSanctis et al. (1994, p. 125ff) differentiate
between the spirit of software (i.e., the developers’
intention) and the expectations of actual end-users.
The union of software developer and software user
TAKING PRESSURE OFF KNOWLEDGE WORKERS WITH THE HELP OF SITUATIONAL APPLICATIONS -
Improving Time-to-proficiency in Knowledge Work Settings
379
seems to be a particularly promising approach in the
context of KW as the knowledge worker’s world is
not easily accessible to outsiders such as members of
IT departments or external service providers.
Individual. Individuals, in the context of the TTF
model, are the persons utilising technologies to as-
sist them in performing tasks. They are characterised
by their training status, computer experience and
motivation (Goodhue et al., 1995, p. 215).
Members of the generation that grew up with the
presence of the Internet are considered digital na-
tives. They are currently joining the workforce and
are supposed to have an unconventional attitude
toward work (Cherbakov et al., 2007, p. 2). They (1)
have different learning preferences than previous
generations, (2) use a broad bandwidth of communi-
cation channels to enter social networks and access
digital resources, (3) see themselves as providers of
digital resources, not only as consumers, and (4)
demand customised instead of one-size-fits-all solu-
tions (Oblinger et al., 2005; Prensky, 2001).
Digital natives feel comfortable doing KW. They
are used to join decentrally organised groups using
flexible IT, proactively provide rather than only
consume knowledge and are able to deal with prob-
lems with a high degree of variety. This enables
them to better retain and use IT in creative and
meaningful ways (Oblinger et al., 2005, p. 2.6).
The concept of the digital native has been criti-
cised because of limited empirical evidence. It is
argued that most of the characteristics can neither be
seen as static, nor as generalisable throughout the
population (Bennett et al., 2008, p. 780). Neverthe-
less, for this work, the concept is perceived to be a
useful proxy for the future employee who might
have an unconventional approach toward work.
3 PROPOSITIONS
The three propositions described below are based on
the TTF model. The first proposition focuses on the
adaptability of traditional applications and SAs as
this attribute is assumed to be particularly important
in the context of KW. With the second proposition
comparing the fit between applications and KW in
general, we go one step further and consider addi-
tional requirements of applications supporting KW.
The third proposition focuses on TTP as a specific
and relevant performance indicator.
Proposition 1: Situational applications better adapt
to variations in tasks than traditional applications.
As mentioned above, KW is characterised by a
dynamic and unpredictable environment, and a low
level of standardisation. It addresses ill-structured
problems in complex domains and requires flexible,
personalised IT support.
In traditional software development projects,
changing business needs often lead to scope creep.
This typically results in overrunning the original
project budget and schedule. SAs, however, can be
adapted to changing business needs, not only in the
stage of development, but also afterwards. SAs can
be changed or reused as patterns for the develop-
pment of new SAs. Additionally, the complexity of
traditional applications makes it unlikely that deve-
lopers and end-users have the same understanding of
the intended purpose of an application. The union of
developer and end-user in the case of SAs avoids the
risk of misunderstandings between the two. This is
not only important in the development phase, but
also when applications are adapted to variations in
tasks.
Knowledge workers in organisations where an
ecosystem for SAs is in place have a clear advan-
tage. Such ecosystems typically provide interfaces to
internal information sources and facilitate sharing
and reusing SAs.
Proposition 2: Situational applications better fit to
knowledge work than traditional applications.
According to the TTF model, the task construct
is characterised by the attributes routineness, inter-
dependence and degree of hands-on character.
Knowledge workers typically deal with a great vari-
ety of issues, non-routine, ad-hoc situations and are
engaged in tasks that are interdependent with respect
to other organisational units. SAs facilitate the ac-
cess to as well as the integration of data from vari-
ous sources. This is useful to accommodate interde-
pendence in decentrally organised environments.
KW also exhibits a particularly high degree of
hands-on character as a considerable share of data
that needs to be accessed is not available in a pre-
programmed way.
Tasks exhibiting high interdependence as well as
a high degree of hand-on character are better sup-
ported by SAs than by traditional applications.
Knowledge workers often have to integrate data
from several information sources within and beyond
the organisation. Software reflecting the specific
requirements and being flexible enough to exchange
data with various other information systems is
needed.
Traditional applications hardly offer the required
features and interfaces. Additionally, SAs fit well to
KMIS 2010 - International Conference on Knowledge Management and Information Sharing
380
the characteristics of digital natives who are appreci-
ating flexibility and creativity.
Proposition 3: Situational applications result in
shorter time-to-proficiency than traditional applica-
tions.
The focus on the most relevant features reduces
the complexity of SAs and also contributes to im-
proved time-to-value. Both result in shorter TTP, the
former by constraining learning efforts and the latter
by reducing the time to productive application use.
While schedule overruns are an issue known from
traditional software development, developers of SAs
consider themselves satisfied once the application is
good-enough to address an immediate need. Particu-
larly digital natives appreciate flexibility and re-
duced TTP.
Short TTP is critical for knowledge workers in
many respects. Becoming proficient quickly after
joining a new organisation or after variations in
tasks is a major challenge for knowledge workers.
The reuse of SAs either with or without adjustments
as well as the availability of a well-documented
collection of electronically accessible information
sources result in improved TTP. Because changes in
routines and differences between positions are the
most significant factors influencing TTP, giving
employees the chance to reuse applications is likely
to affects TTP positively.
4 CONCLUSIONS
In this paper, we discussed the applicability of SAs
in KW settings. The discussion resulted in three
propositions based on the TTF model. These propo-
sitions describe how the constructs task, technology
and individual influence the user evaluation of the fit
between tasks of KW and a traditional as well as
situational applications. TTP was used as perform-
ance indicator.
In order to evaluate the propositions constructed
within the scope of this work, we propose conduct-
ing (1) semi-structured interviews with human re-
source experts for a better understanding of TTP, (2)
an experiment contrasting two groups of digital
natives supported by SAs and traditional applica-
tions, respectively, using observations and question-
naires for data collection and (3) a field study ob-
serving employees taking up new positions in or-
ganisations providing an ecosystem suitable for the
development and utilisation of SAs. This may result
in new theories explaining in what respect and under
what circumstances SAs can benefit organizations,
not only with respect to TTP. To us, the TTF model
seemed to be a good starting point.
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