Barriers To Business Intelligence
Business intelligence suffers from a strange dichotomy: It's among
the most highly desired business technologies, a roughly $10 billion-a-year
market growing at more than 10% a year, yet it has difficulty proving
The main barriers to BI adoption are: cost and complexity.
According to a 2007 InformationWeek survey of 388 business technology
professionals, over 30 percent of respondents claimed that BI
vendors were unable to demonstrate the benefits of BI to internal
Whilst most companies purchase BI software to solve a specific
problem in one business unit, few are able to use the resulting
data silos to explore cross-company impacts, such as how a 5% drop
in market share affects manufacturing, finance, and procurement.
One of the main reasons for this lack of cross organizational capability
is that no vendor excels in all areas of business intelligence.
This means that customers generally have to pull together the various
For instance, some BI users are cutting edge in customer scoring,
operational analysis, and predictive analytics. However, to gain
that capability requires:
- Millions of dollars on data
warehouses and software for moving and analyzing data - 40%
of the cost involved in developing sophisticated analytics and
modeling for a 30-Tbyte Teradata
data warehouse comes from moving data between systems.
- Specialized IT talent
- Significant businesss time to set up and manage.
Although Teradata sells analytical apps for forecasting demand,
a separate application must be implemented to extract data from
the data warehouse and feed it into SAS analytics, which runs models
for that function. SAS is a great analytical tool but not a data
warehouse, and Teradata is the best data warehouse around but not
a good analytical tool.
Businesses also want tools that blur the line between data transactions
and decision support, delivering operational BI applications with
built-in analytics, and performance management software. Could this
be the reason SAP has acquired
SAP CEO Henning Kagermann commented that "blending Business
Objects' data crunching capabilities with SAP's industry knowledge
for end-to-end business processes with embedded analytics."
This statement seems contrary to SAP's promise to keep Business
Objects a separate unit.
How successful that union will be depends upon the level of integration
they will achieve.
Claims that SAP's previous BI tools and data
warehouse have not been successful, requiring an intertweeing
data warehouse between SAP and Business Objects, really don't mean
much when you consider the totally different processing and data
transfer capabilities of a transactional ERP/CRM system compared
to an OLAP analytical application.
Many BI vendors, such as Business Objects are working to better
integrate reports into operational processes. This may include:
- Upgrades to Crystal Reports - to produce reports from data.
- Better support for XML and Adobe Flex - making it easier to
create reports from operational data and act on that information.
- Reporting needs to become an integral part of an operational
Smaller niche BI vendors such as SeeWhy Software are focussing
on enabling "actionable BI." SeeWhy constantly compares
incoming data with historical information and trends, flags anomalies
[such as a regular customer not making a booking at the usual time]
and sends alerts to customer service reps.
investigating how to integrate its ERP applications and data warehouse
with its BI portfolio, which includes Hyperion performance management
tools and Siebel analytics. Oracle Real-Time Decisions, based on
software from Sigma Dynamics, acts a transactional server that combines
rules and predictive analytics to deliver real-time data into business
processes and customer interactions.
And the innovation is not all coming from the Analytics end. Data
warehouse vendors are also getting in on the game. Teradata
is making its way into operational analytics with its Active
The trend toward real-time analysis is gaining pace, but until
the perfect solution appears, companies will still need to filter
through very large data sets, such as customer segmentation analysis,
to choose the right prospects for marketing campaigns. Real time
is just a small part of the challenge.
Either way, businesses not moving towards using modeling and analytics
will fall behind.
Case Study 1 - Medco
BI is a journey, and the preliminary BI program goals do not cover
the navana solution. A case in point is in Healthcare - the BI goal
in healthcare is to move very quickly from cost containment to prevention.
One of the uses of BI for Medco is tracking pharmaceutical transactions
for signs of abuse and fraud. The next BI iteration will develop
analytics to determine, forecast and predict which patients are
most at risk of getting sicker. This will require:
- Integrated prescription, lab, medical history, and demographic
data to develop a "longitudinal" view of individuals'
- Use clustering models to look at patients across different types
By analyzing a cluster of people with complex diabetes, Medco hopes
to identify trends that can predict who among a population of patients
without those complications are at risk enough to suggest an intervention.
How BI Is Used
- A patient previously treated for high cholesterol comes to the
pharmacy for insulin.
- At the point of transaction, Medco could instantly run the patient's
data through SAS analytical models and determine how to reclassify
that patient and whether any type of intervention might be recommended.
The Technology Enablers
The increased use of Web services makes such links between operational
systems and analytics models more feasible.
Real-time BI could have huge implications in customer service.
Case Study 2 - Overstock.com
Overstock, which distributes more than 33 million e-mails a week
in marketing campaigns, segments customers in 55 different ways
in the data warehouse based on their purchase histories. An Overstock.com
customer e-mail initiative that has increased sales significantly
How BI Is Used
- The online retailer scores each customer after every purchase
based on how profitable he or she is to the company
- That information is used for its e-mail blasts and other customer
- If a valued customer clicks on iPod accessories, for example,
Overstock might send a coupon the next day.
These simple case studies demonstrate how the strategic applicBI
for greater business impact, in part by embedding analytical capabilities
right into everyday operations for here-and-now decision making.
Given the costs and complexity, however, few companies are that
far along. The BI vendors--and you can now count SAP among them--are
scrambling to get it right.
NEXT: Understanding The
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