A new era in BI: Overcoming low adoption to make smart decisions accessible for all

Organizations
today
are
both
empowered
and
overwhelmed
by
data.
This
paradox
lies
at
the
heart
of
modern
business
strategy:
while
there’s
an
unprecedented
amount
of
data
available,
unlocking
actionable
insights
requires
more
than
access
to
numbers.

The
push
to
enhance
productivity,
use
resources
wisely,
and
boost
sustainability
through
data-driven
decision-making
is
stronger
than
ever.
Yet,
the
low
adoption
rates
of
business
intelligence
(BI)
tools
present
a
significant
hurdle.

According
to
Gartner,
although
the
number
of
employees
that
use
analytics
and
business
intelligence
(ABI)
has
increased
in
87%
of
surveyed
organizations,
ABI
is
still
used
by
only
29%
of
employees
on
average.
Despite
the
clear
benefits
of
BI,

the
percentage
of
employees
actively
using
ABI
tools
has
seen
minimal
growth
over
the
past
7
years.
So
why
aren’t
more
people
using
BI
tools?

Understanding
the
low
adoption
rate

The
low
adoption
rate
of
traditional
BI
tools,
particularly
dashboards,
is
a
multifaceted
issue
rooted
in
both
the
inherent
limitations
of
these
tools
and
the
evolving
needs
of
modern
businesses.
Here’s
a
deeper
look
into
why
these
challenges
might
persist
and
what
it
means
for
users
across
an
organization:

1.
Complexity
and
lack
of
accessibility

While
excellent
for
displaying
consolidated
data
views,
dashboards
often
present
a
steep
learning
curve.
This
complexity
makes
them
less
accessible
to
nontechnical
users,
who
might
find
these
tools
intimidating
or
overly
complex
for
their
needs.
Moreover,
the
static
nature
of
traditional
dashboards
means
they
are
not
built
to
adapt
quickly
to
changes
in
data
or
business
conditions
without
manual
updates
or
redesigns.

2.
Limited
scope
for
actionable
insights

Dashboards
typically
provide
high-level
summaries
or
snapshots
of
data,
which
are
useful
for
quick
status
checks
but
often
insufficient
for
making
business
decisions.
They
tend
to
offer
limited
guidance
on
what
actions
to
take
next,
lacking
the
context
needed
to
derive
actionable,
decision-ready
insights.
This
can
leave
decision-makers
feeling
unsupported,
as
they
need
more
than
just
data;
they
need
insights
that
directly
inform
action.

3.
The
“unknown
unknowns”

A
significant
barrier
to
BI
adoption
is
the
challenge
of
not
knowing
what
questions
to
ask
or
what
data
might
be
relevant.
Dashboards
are
static
and
require
users
to
come
with
specific
queries
or
metrics
in
mind.
Without
knowing
what
to
look
for,
business
analysts
can
miss
critical
insights,
making
dashboards
less
effective
for
exploratory
data
analysis
and
real-time
decision-making.

Moving
beyond
one-size-fits-all:
The
evolution
of
dashboards

While
traditional
dashboards
have
served
us
well,
they
are
no
longer
sufficient
on
their
own.
The
world
of
BI
is
shifting
toward
integrated
and
personalized
tools
that
understand
what
each
user
needs.
This
isn’t
just
about
being
user-friendly;
it’s
about
making
these
tools
vital
parts
of
daily
decision-making
processes
for
everyone,
not
just
for
those
with
technical
expertise.

Emerging
technologies
such
as
generative
AI
(gen
AI)
are
enhancing
BI
tools
with
capabilities
that
were
once
only
available
to
data
professionals.
These
new
tools
are
more
adaptive,
providing
personalized
BI
experiences
that
deliver
contextually
relevant
insights
users
can
trust
and
act
upon
immediately.
We’re
moving
away
from
the
one-size-fits-all
approach
of
traditional
dashboards
to
more
dynamic,
customized
analytics
experiences.
These
tools
are
designed
to
guide
users
effortlessly
from
data
discovery
to
actionable
decision-making,
enhancing
their
ability
to
act
on
insights
with
confidence.

The
future
of
BI:
Making
advanced
analytics
accessible
to
all

As
we
look
toward
the
future,
ease
of
use
and
personalization
are
set
to
redefine
the
trajectory
of
BI.

1.
Emphasizing
ease
of
use

The
new
generation
of
BI
tools
breaks
down
the
barriers
that
once
made
powerful
data
analytics
accessible
only
to
data
scientists.
With
simpler
interfaces
that
include
conversational
interfaces,
these
tools
make
interacting
with
data
as
easy
as
having
a
chat.
This
integration
into
daily
workflows
means
that
advanced
data
analysis
can
be
as
straightforward
as
checking
your
email.
This
shift
democratizes
data
access
and
empowers
all
team
members
to
derive
insights
from
data,
regardless
of
their
technical
skills.

For
example,
imagine
a
sales
manager
who
wants
to
quickly
check
the
latest
performance
figures
before
a
meeting.
Instead
of
navigating
through
complex
software,
they
ask
the
BI
tool,
“What
were
our
total
sales
last
month?”
or
“How
are
we
performing
compared
to
the
same
period
last
year?”

The
system
understands
the
questions
and
provides
accurate
answers
in
seconds,
just
like
a
conversation.
This
ease
of
use
helps
to
ensure
that
every
team
member,
not
just
data
experts,
can
engage
with
data
effectively
and
make
informed
decisions
swiftly.

2.
Driving
personalization

Personalization
is
transforming
how
BI
platforms
present
and
interact
with
data.
It
means
that
the
system
learns
from
how
users
work
with
it,
adapting
to
suit
individual
preferences
and
meeting
the
specific
needs
of
their
business.

For
example,
a
dashboard
might
display
the
most
important
metrics
for
a
marketing
manager
differently
than
for
a
production
supervisor.
It’s
not
just
about
the
user’s
role;
it’s
also
about
what’s
happening
in
the
market
and
what
historical
data
shows.

Alerts
in
these
systems
are
also
smarter.
Rather
than
notifying
users
about
all
changes,
the
systems
focus
on
the
most
critical
changes
based
on
past
importance.
These
alerts
can
even
adapt
when
business
conditions
change,
helping
to
ensure
that
users
get
the
most
relevant
information
without
having
to
look
for
it
themselves.

By
integrating
a
deep
understanding
of
both
the
user
and
their
business
environment,
BI
tools
can
offer
insights
that
are
exactly
what’s
needed
at
the
right
time.
This
makes
these
tools
incredibly
effective
for
making
informed
decisions
quickly
and
confidently.

Navigating
the
future:
Overcoming
adoption
challenges

While
the
advantages
of
integrating
advanced
BI
technologies
are
clear,
organizations
often
encounter
significant
challenges
that
can
hinder
their
adoption.
Understanding
these
challenges
is
crucial
for
businesses
looking
to
use
the
full
potential
of
these
innovative
tools.

1.
Cultural
resistance
to
change

One
of
the
biggest
hurdles
is
overcoming
ingrained
habits
and
resistance
within
the
organization.
Employees
used
to
traditional
methods
of
data
analysis
might
be
skeptical
about
moving
to
new
systems,
fearing
the
learning
curve
or
potential
disruptions
to
their
routine
workflows.
Promoting
a
culture
that
values
continuous
learning
and
technological
adaptability
is
key
to
overcoming
this
resistance.

2.
Complexity
of
integration

Integrating
new
BI
technologies
with
existing
IT
infrastructure
can
be
complex
and
costly.
Organizations
must
help
ensure
that
new
tools
are
compatible
with
their
current
systems,
which
often
involve
significant
time
and
technical
expertise.
The
complexity
increases
when
trying
to
maintain
data
consistency
and
security
across
multiple
platforms.

3.
Data
governance
and
security

Gen
AI,
by
its
nature,
creates
new
content
based
on
existing
data
sets.
The
outputs
generated
by
AI
can
sometimes
introduce
biases
or
inaccuracies
if
not
properly
monitored
and
managed.

With
the
increased
use
of
AI
and
machine
learning
in
BI
tools,
managing
data
privacy
and
security
becomes
more
complex.
Organizations
must
help
ensure
that
their
data
governance
policies
are
robust
enough
to
handle
new
types
of
data
interactions
and
comply
with
regulations
such
as
GDPR.
This
often
requires
updating
security
protocols
and
continuously
monitoring
data
access
and
usage.

According
to
Gartner,
by
2025,
augmented
consumerization
functions
will
drive
the
adoption
of
ABI
capabilities
beyond
50%
for
the
first
time,
influencing
more
business
processes
and
decisions.

As
we
stand
on
the
brink
of
this
new
era
in
BI,
we
must
focus
on
adopting
new
technologies
and
managing
them
wisely.
By
fostering
a
culture
that
embraces
continuous
learning
and
innovation,
organizations
can
fully
harness
the
potential
of
gen
AI
and
augmented
analytics
to
make
smarter,
faster
and
more
informed
decisions.

Read
the
report