FEATURE: STAFF RESOURCES
To answer this question, you need to
combine data about what happened
with information that helps explain why
it happened…and to do this, you need
a platform that is easy to use, one that
supports the whole process - from loading
data to creating and sharing dashboards
and reports-on any device. Then, you
can dig into the details that drive your
business and see the story unfold.
Let’s create a scenario: To find out what
caused a dip in sales, start by loading
data into a powerful database - the
foundation for a fast, flexible platform
for analysis. You may see that your
revenue data doesn’t tell the whole
story. To dig deeper, you need to
combine revenue and fulfillment details,
and you need to enhance both data sets
by using prebuilt, advanced functions
that extend your analysis. Review your
data to see if the headers and data
types match up across sources, and then
correct the issues inline if they don’t.
Connect different data sets and extend
your analysis by enhancing your data
with intelligent, derived metrics. Do
this by using a best-in-class analytics
platform, one that offers a library of
prebuilt analytic modules and functions.
Now it’s time to see what’s going on.
Illustrating the story should be as simple
as selecting from a gallery of dynamic
visualisations or getting automatic
recommendations if you aren’t sure.
Is there a ‘digital goldrush’ going
on at the moment? What does this
mean and how can employees make
the most of it?
The explosively fast growth in digital
services raises the spectre of disruption
before an incumbent even knows it’s in
trouble. With the increase of digitisation
in every industry, every company has
exposure to data-capital disruption.
The question is what to do about it.
According to the World Economic Forum
“To survive disruption and thrive in the
digital era, incumbent business will
need to rethink every element of their
business; and they need to act now”.
Companies that are doing good business
find it very difficult to suddenly reinvent
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“Unless
employees
develop a
sound data
management
and analytics
strategy,
they may find
themselves
doubting,
mistrusting
and misusing
this asset in the
future as well.”
themselves in order to ensure sales
and profit tomorrow; early indicators
of change are often overlooked or
seen as unimportant. So, regardless of
how well positioned a company is, if
the management underestimates the
potential for change that digitisation
poses to its business model, they run the
ultimate risk. Those who see the change,
but delay their response so as not to
jeopardise their current revenues are
taking a highly risky stance. Some actions
that employees, management and team
alike, can take are:
1. Creating a sense of urgency is the
key challenge
2. Determining the nature of the
change requirements;
3. Identifying barriers to change
early, and
4. Identifying relevant assets and
setting the expectation level.
It is the company’s top leadership team
that needs to initiate these actions.
Is it true to say many enterprise
employees have a treasure
trove of data at their fingertips but
they are failing to make the most of
this resource?
This is indeed true however and they
may fail to make the most of it if the
right strategy, solution and tools are
not applied.
According to an IDC report,
phenomenal volume of data is due to
hit right around 2020. Some would
argue it already has. This applies to
anyone across all lines of business. Let’s
start with trusting the data. Employees
list difficulties in assessing whether data
is truly useful and they cite low quality,
accuracy, or completeness of data as a
barrier to data-driven decision making.
What about analytics solutions?
Nearly 86% of organisations are still
focused only on reporting. Only 14% of
companies have any integrated talent
analytics today. That inevitably leads
to poor use of data and analytics in
decision-making. So how do you fix both
those problems? How do you identify
a solution where you can access any
and all of the data you need, no matter
where it comes from, what type it is, or
how much of it there is? How do you
then apply the right analytics tools and
techniques to answer any question?
Your vision and plan has to be simple: to
allow anyone in the world, to be able to
analyse any type of data from any data
source. Replicate data into the cloud,
process it, summarise it and visualise it.
Employees in an enterprise do indeed
have much data and more will continue
to hit them, but unless they develop a
sound data management and analytics
strategy, they may find themselves
doubting, mistrusting and misusing this
asset in the future as well.
How can enterprise employees use AI
and AR as resources to make money
for their company?
AI has acquired almost a mythical status
when it comes to the promise it holds
for your business. Indeed, it can make
a huge difference, but only if we allow
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