place for both analyzing data and executing decisions, this change alone is not enough to drastically improve decision-making processes. The
next step is to combine historical data with
forward-looking scenario-based analysis, or
predictive analytics, thereby equipping knowledge workers with a decision-making platform.
It’s time we went back to the future in business information management. For years as
consumers, we have experienced how helpful it
is to use historical information to make recommendations. Every time someone buys a book
on Amazon, a list of recommended future purchases is provided based on the individual’s
transactional history and profiles of people
who bought similar products. The same user
experience-based offers exist on iTunes. If we
can be predictive with book and song purchases,
why can’t we do the same with suggestions for
new customers to target, new products to add
to our portfolio or new markets to enter?
The enterprise has been pursuing accessible,
real-time BI for well over 15 years, and predictive
analytics technology has been around for about
a decade. However, there is renewed interest in
embedded, predictive BI as a new breed of cor-
porate leaders comes to view their organizations
not as a sum of assets – people, processes and
technologies – but as a series of decisions that
need to be made on a daily basis. Senior execu-
tives recognize the difference they could see in
the bottom line if decisions could be made based
on better insights. In a 2008 Capgemini survey of
international companies across multiple indus-
tries, senior executives said they could improve
business performance by 27 percent if they were
better able to mine the data they collected. These
leaders perceive – rightly so – that access to better
information could enable knowledge workers to
respond proactively in rapidly changing environ-
ments, to use a single view of the truth to make
sharper decisions, and to create sustainable and
measurable value by achieving tactical and stra-
tegic business objectives.
But the desire to have integrated, real-time
and predictive business insights and the ability
to use them to greatest advantage are two different things.
From Fiction to Reality
We recommend a strategy of readiness so that
as BI-muscled ERP applications become available, enterprises will be poised to exploit them
as quickly and effectively as possible.
To understand the relevance of any new technology, it’s best to begin with an information
strategy. What daily decisions have the greatest
impact on the bottom line? Who makes those
decisions today, and at what levels should those
decisions be made in the future? In order to take
advantage of small windows of opportunity,
which decisions can we accelerate or automate
entirely? Are data governance processes in place
to ensure that all decisions are based upon high
quality information?
When these questions are answered and embedded BI is available, enterprises will have that long-desired but elusive single view of the truth shared
by knowledge workers across the enterprise. Not
only would mission-critical processes share up-to-date and timely data, but that data would
“To understand the relevance of any new
technology, it’s best to begin with an
information strategy.”
