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Luckevich, & Misner, 2002). Therefore, the abil-
ity to quickly take advantage of the exponential
growing amount of information has become an
extremely critical component for the success of
the modern organization (Barlow & Burke, 1999;
Huber, 2003). The need for fast decision making
on the one hand, and the longer time needed to
acquire the right information on the other hand
causes a so-called “information gap” (den Hamer,
2005; van Beek, 2006). Business Intelligence
(BI) is implemented in order to narrow down this
information gap.
Looking from an end-users perspective, end-
users simply want a better way to solve data-related
business problems. The end-user's perception of
the benefits received from a BI solution is depen-
dent on the degree of productivity increase or the
amount of positive results that they receive. If a BI
solution helps them look better, and lets them do
their job better, they will be more likely to use it
(Turban et al., 2007). While BI-software enables
organization-wide decision support, problems
are encountered in the fit between systems' pro-
vision and changing requirements of a growing
amount of (end-) users (Dekkers, Versendaal &
Batenburg, 2007). The main reason why this “fit”
(hereafter referred to as BI-FIT) is missing is that
when BI-solutions are implemented in practice,
end-users are usually considered (if considered at
all) to be equal in their adoption and usage of the
system (Biere, 2003), which is not always the case
(Borgman, 1989). If end-users get provided with
a BI-solution that does not fit their capabilities or
tasks, they will most likely not use it, or use it in
the wrong manner, or even become negative about
the BI-solution, which obviously does not contrib-
ute to a positive result. However, if end-users are
equipped with a BI-system that fits their needs,
they will produce better intelligence to support
their decisions, and in the end reduce uncertainty.
In order to establish this fit, in this chapter the
BI-FIT framework is proposed, which provides
an answer to the following research question:
background
Over the years BI has increasingly been mov-
ing into the mainstream of knowledge worker
computing (Negash & Gray, 2003). No longer
are BI solutions solely being used by information
specialists or analysts. This is reflected in the
population of BI-end users, which is becoming
increasingly more heterogeneous in both the skills
that end-users bring to BI-systems as well as in
the demands they place on them (Gile, 2003).
Unfortunately, according to several authors many
BI projects fall short of their promise to deliver
value. According to Raden (2004, p. 10), “busi-
ness intelligence applications have low adoption
rates within organizations”. Furthermore, Biere
(2003, p. 8) states that “too many organizations
take the easy technology-driven route by selecting
some tools, hoping the end users will “magically”
emerge with what they want.” Finally, Ferguson
(1996, p. 13) states that “less attention is devoted to
actual BI usage on the problem of getting data out
of the system. This approach has diminished the
potential benefit of BI systems since it assumes that
all users are capable of finding their way around
in this 'ocean' of information.” In other words,
an implementation from a technology-driven per-
spective does not ensure the adoption and usage
of end-users, which constrains organizations to
benefit from the potential of their BI investments.
“What are the major factors influencing the fit
between Business Intelligence end-users and
Business Intelligence solutions?”
research Motivation
and Methodology
Although BI is widely applied in practice, scien-
tific research in the field is limited. Several authors
state that BI research “seems to have flown under
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