Digital Transformation » Technology » Selective thinking

Business Intelligence has a series of complex definitions but they all boil
down to a very simple one: BI is about extracting useful business information
from data.

Most companies have several conventional database systems – finance, HR,
marketing, sales and production. They all collect a mass of data at a truly
paralysing level of detail, which is often far too much for most high-level
decision makers.

Most finance directors don’t need to know that a sales person, Fred Smith,
sold Sally Jones a widget at 11:03am on 23 April 2006. What they need to know is
that sales of widgets by the northern sales force are falling by 3% a month.
There, in a nutshell, is the difference between data and information – and
information is what BI systems are designed to provide.

BI accepts that the existing database systems are doing a great job
collecting the data and leaves them free to do just that. However, the useful
business information that people need is often based on data held in multiple
systems. For example, the sales system may know that Fred sold Sally a widget,
while it’s the HR system that knows that Fred is part of the northern sales

On the face of it, the easiest solution is to move some data from the sales
system to the HR system, but these systems are not designed to accept incoming
data. In addition, the format of the data is usually incompatible. It turns out
that it’s much easier to create an entirely new system (the data warehouse)
which is designed, right from the start, to accept incoming data.

So the first job of a BI system is ETL – to extract the data from the source
systems, transform it into a compatible format and load it into a centralised
repository called a data warehouse.

Data storage

As a general rule, new data is moved into the data warehouse once a night, so
the data warehouse gradually builds into a huge repository of data. This is a
centralised store of all the data that can be used for analytical purposes in
the organisation. Of course, the analytical needs of departments within an
organisation vary hugely, so it’s normal practice to provide a ‘data mart’ for
each department. Only the data that each department needs is transferred to its
data mart and, within each data mart, the data is restructured so that it can be
easily rendered into information.

Very broadly, BI systems come in two versions. You can build an entire system
in-house and, given the complexity of the existing database systems within large
corporations, many take this route reasoning, quite correctly, that
off-the-shelf software may not match their requirements.

There is an alternative. If you type ‘Business Intelligence’ into a search
engine you will soon become aware of a new world of specific BI-type products
out there. These products lean more towards the off-the-shelf end of the BI

Unfortunately, they are often to be found floating in an alphabet soup and
you can rapidly find yourself drowning in a sea of seemingly meaningless
acronyms such as DSS, EIS, ESS, MSS, EPM and BPM.

Worse, you track down what BPM is and then discover that it actually stands
for two things: “Business Process Management” and “Business Performance
Management”. When you decide on performance, you find that it’s defined as:
“consolidation of data from various sources, querying and analysis of the data,
and putting the results into practice.” Which, infuriatingly, sounds exactly the
same as the description given here for business intelligence.

Marketing speak

The bad news for unsuspecting finance directors is that BI has become very
fashionable and as such has been adopted by the marketers. As we are all aware,
it is important for all products to have a USP (unique selling proposition).
This is most easily achieved by inventing a new TLA (three letter acronym) and
bolting it on to the product. Some of these are genuinely useful because they do
help to distinguish specific groups of products (such as customer relationship

For many others, I struggle to see any good reason for the acronym at all. Of
course, we must remember that marketing is simply that. Many perfectly good,
respectable products have suffered the ignominy of acronym marketing, so I am
not suggesting that the addition of a TLA is an indication of a poor product. I
am suggesting that if you elect to go for a BI solution from this end of the
market, buy it because it provides the functionality it needs, not because of
the acronym.

Either way, building a BI system can be a relatively complex, costly and
time-consuming experience. But the return on investment can be huge as your
decision-makers’ decisions are then driven by real information rather than
gut-feel. ROIs of 600% are not impossible.

Although BI has been a long time maturing, it has now reached a stage where
most companies cannot afford not to adopt it.

Dr Mark Whitehorn is a database and business intelligence expert. He
regularly provides BI consultancy to corporate clients and is the author of
several books.