As it incorporates a gamut of functions from business activity monitoring to performance management and business planning, business intelligence attracts a growing number of companies who earlier specialized in individual functions

1. THE USES OF PERVASIVE INTELLIGENCE

2. Business Intelligence is an evolving industry with growing market potential which has attracted a
swarm of players who are serving their customers in several different novel ways. It has grown
from a technology focused on decision support and performance management in some
departments to increasingly ubiquitous tool that spans operations management across the
enterprise. As it incorporates a gamut of functions from business activity monitoring to
performance management and business planning, business intelligence attracts a growing
number of companies who earlier specialized in individual functions. Customers have a daunting
task of choosing from a rich crop of innovative packages; they will have to make a judgment
about the products that will become the standard for the industry in the future.
The growth of the business intelligence industry has been propelled by convergence of several
factors which will continue to fuel rapid expansion and innovation. Regulatory compliance is
inescapable and the need to monitor operations risks is the baseline for additional applications to
reduce costs, fraud detection, accelerated responses to market changes, better targeting of
customers, detection of latent opportunities for product development and a personalized
approach to selling among several other applications.
Keeping an eye on all activities
The process of selection from several different offerings will be influenced by enterprises’
preference for tactical or strategic goals or a combination of them. While decision-support
analysis or performance management in selected functional areas are possible in isolation with
business intelligence tools alone, companies will need a comprehensive strategy, including
business process management, content management and performance management, when they
weave business intelligence into the fabric of their daily business activity for rapid responses to
market changes. Dell, for example, has embedded intelligence into its daily business and is able
to set in motion its business processes all along the supply chain, once a configuration for a
computer is spelt out by a customer, including orders for its contract manufacturers and shipping
companies.
In the past, spreadsheets, OLAP tools, management report generation and query tools were the
preferred tools as they catered to decision-support and performance management in selective
functional areas. Enterprises will need more of dashboards and performance management tools
as they look to monitor and evaluate business activity across the enterprise. They also need to
able to collaborate and communicate rapidly for a coordinated response to contingencies facing
the enterprise based on the information received from performance metrics. In general, they need
to aggregate, analyze and act in near real time.
For their tactical or their operational needs, companies need information on all the metrics that
govern their performance metrics and the parameters that form the co-ordinates of their
decisions. In the past, companies could barely integrate information from a few of their

3. operational data stores and create standard reports to make decisions quickly; they looked for
tools where they could drill down and view from different angles. Increasingly, enterprises will
need to inter-connect all their sources of data to take actions that are consistent with their
enterprise strategy.
One instance of the use of performance measures is La Suisse Insurance which set targets for
its sales force based on a multi-dimensional view of data. The company was losing up to $50,000
per salesperson each year by paying monthly allowances to salespeople who were
underperforming. An OLAP tool helped in gaining multiple views of sales performance — by
salesperson, branch, and region— which uncovered opportunities for raising productivity. Data
warehouses can extend the capability and include the analysis of impact of prices, advertising,
etc. on the results achieved.
Alternatively, companies can focus on decision-support tools which involve ad hoc queries and
make considerably greater demands on the analytical and data management capabilities of
business intelligence software. This kind of query requires much larger data sets for cross-
referencing across several dimensions of data as well as over time. Companies need to be able
to integrate data from several transaction data bases, usually in a data warehouse environment,
and need the IT horsepower to conduct such complex queries. The typical applications of ad hoc
queries are customer segmentation and response modeling.
Strategic decisions, unlike operational decisions, take a longer time as companies need to be
able to parse current and historical data before they can come to decisions. They involve the use
of statistical and data mining tools to consider alternative scenarios, predict future financial
performance, conduct customer segmentation for product positioning and make decisions about
the choice of their channels. This is typically done with data stored in data warehouses and
updated periodically, typically overnight or on the weekends, in order not to interrupt analysis
during the day.
A growing number of companies favor using business intelligence tools to align their strategy and
tactics. They want to be able to make course corrections to ensure that their tactical initiatives are
in line with their strategic direction including coping with contingencies which could roil their best
laid plans. With the advent of active data warehousing and rule based decision engines, they are
able to compare actual figures with benchmarks to come to decisions about routine decisions
such as inventory replenishment, yield management or pricing decisions. This kind software
allows companies to embed rules that prompt decisions when an expected event happens.
Integration of decision and business process management for linking strategic and tactical
management is rare (not impossible) but immensely beneficial for those who succeed. PSS World
Medical based in Jacksonville, Fla. has a sprawling network of 44 distribution centers selling
medical equipment and supplies. Each of the centers is tied, by a dashboard, to its own P&L
statement and to the performance goals of each individual who are rewarded according to the

4. achievements of their metrics. An integrated network business processes and information flows
ensures that the drivers of performance are transparent to the senior corporate management. In
the past, performance measures relied on one measure such as productivity often at the expense
of quality. In a business intelligence context, balanced scorecards help to assemble a groups of
metrics which best represent the correlation between individual performance and the company
overall.
Teradata’s Active Data Warehousing is one instance of a data warehouse concept which updates
data, in real time, for operational and strategic decision making. Companies are then able to
respond to significant events affecting their financial performance. In the past, batch processes in
data warehouses prevented quick responses to events. An alternative method of achieving the
same objective is the standards based Service-Oriented Architecture (SOA) which pieces
together components of business processes, data services and applications and each of them
can be invoked by a web service.
An instance of the use of event-based decision making is Land’s End which progressed from
using dashboards for reporting to more event-based decision making. In the first stage of
implementation of a BI solution, it began to provide figures of inventory as well as supplies in the
pipeline and compared them with incoming customer demand to make decisions about orders to
be placed with vendors. Now it has embedded triggers in its systems so that alerts are
automatically sent out whenever inventory runs low.
Event based monitoring does not stop at single or discrete situations but extends to responses to
a sequence of events. Thus, the monitoring of the supply chain would involve the movement of
goods from the vendor to the transportation company and then to the buyer. The events along the
way can have consequences for inventory holdings and financial payments. Delays can occur on
the way due to weather changes or congestion on the roadways or the vehicle carrying the goods
could meet with an accident. Based on preset rules, the BI software can make simultaneous
decisions for alternative means to replenish inventories as well as financial payments to
transportation companies.
An example of responses to complex events management is the experience of American Electric
Power Company which often made duplicate payments to its numerous suppliers who submitted
invoices under different numbers and in several different formats such as e-mail, snail mail, etc.
The complex event management software helps to detect duplicate payments by looking at
addresses, dates, amounts submitted and names of vendors to check for overpayments.
Business Activity Monitoring provides the infrastructure to monitor events, compare metrics to
standards and sends out alerts when action is required. In the daily routine of business,
companies need to keep track of their supply position. Often, supply will either exceed or run
short of requirements. BAM tools enable companies to compare the actual situation with
thresholds and send out alerts if the situation warrants action by decision makers.

5. BAM has been widely adopted in the financial services, logistics and the telecommunications
industry and its acceptance in the mainstream is expected to be completed by 2008. In the
financial services industry, it has been readily accepted as a large majority of trading decisions is
triggered by news feeds about financial events. In the logistics industry, a large number of
scheduling decisions are prompted by information on progress of shipments. Similarly, the
telecommunications industry uses BAM to monitor the observance of service level agreements.
One example of a product that servers such needs is Celequest's ActivityServer suite which
processes data flowing continuously from transaction systems. It compares standards of
performance and the actual metrics to determine when production yields are lower than the norm
or alerts store manager when inventory is running low. The standards of performance are
determined by comparing historical data in data warehouse with the actual achievements.
Brocade Communications uses Celequest’s Activity Server to monitor product yields achieved by
its contract manufacturers.
Enterprises would rather be naked
In order to test their strategic assumptions and to be able to see how they play out in practice,
company managements need greater visibility into their business processes before they can
evaluate the impact of their actions. A recent survey of 300 business-technology executives found
that close to 60% of them want greater visibility into their business processes while nearly 80% of
them are interested in data on performance metrics. The implication of an interest in visibility of
their business processes is that companies are looking for ways to monitor the ebb and flow of
business activity and take preventive measures if adverse situations are encountered.
For a closer integration of operational management and analytical capabilities for strategic
management, companies need to lower the information and decision latencies to be able to
respond to situations in real time. Business Activity Monitoring helps to lower information
latencies as it monitors current event data and uses BI to compare it to expected performance.
Business Process Management (BPM) software has the tools to make corrections rapidly. For
example, customer satisfaction will be affected by call wait time before customer representatives
can respond to customer queries. Business Process Management has to be able to use this
information to reroute calls to another call center or representative. This would involve the tasks
of finding the most efficient alternative route (modeling), ensuring that the traffic flow through
alternative routes to proportionate to capacity and the pathways are interconnected (integration).
(BPM), which is designed to work across departments, enables organizations to alter automated
and coded processes, without major re-investments in IT, prompted by analysis of event
information. At its efficient best, companies will be able to automate marketing by defining
customer data in a manner that is consistent with business decision rules and any turn in events
will change the approach to marketing campaigns. Software such as Fair Isaac's Blaze Advisor,

6. Ilog's JRules or Pegasystems' PegaRules are designed to read customer data and change the
offers made based on the customer information received.
BPM is intelligible to business users and helps to manage workflows and the process design. The
centerpiece of a BPM implementation is the process engine which monitors processes as well as
operational and business metrics, watching for exceptions that may require human intervention.
One of the benefits of rapid feedback from tactical decisions is business activity monitoring (BAM)
or the ability to take impromptu actions to remain on course to reach strategic objectives. Portfolio
managers, for example, have to be able to makes adjustments in their holdings based on news
feeds received. Delta Air Lines monitors the impact of unexpected events, such as weather
conditions and gate changes, to alert its employees and to update its gate display systems. This
would not be possible unless the analytical and operational systems are not integrated.
Increasingly, business process management software provides a graphical view of the design of
workflows as well as progress achieved all on a web site where it is transparent to the entire
company. Blue Rhino, a gas distribution company, used BPM to optimize the flow of shipments of
full gas tanks, inventories and empty tank returns among the company's 200 distributor locations.
An interlinked inventory tracking system continuously updates data on stocks and obviates the
need to manually reconcile the numbers and to issue paper bills of lading. The more advanced
BPM software also allows event management and triggers responses as exceptions are recorded
such as the actions asset managers need to take following interest rate changes.
IBM’s WebSphere Business Integration Monitor and TIBCO’s BusinessFactor have the
capabilities to use transaction data and conduct analytics to find out whether they meet standards
and they assess the ability of business processes to facilitate the expected performance metrics.
These products can also retrieve historical data from a data warehouse to provide the
benchmarks. The more recent acquisitions of these two companies, Alphablox product by IBM,
and TIBCO’s OpsFactor, have capabilities to monitor the impact of current events. This would
enable companies to analyze the impact of events such as delayed shipments on their financial
health.
Business intelligence software needs to be seamlessly integrated with operational data
management, business process management and visualization to meet operational objectives. In
one survey of users of BI software, it was found that 32% of the respondents consider pre-
packaged integration of BI software with existing enterprise applications as one of the most
sought after attribute. One instance of such an approach to product offerings is the case of Siebel
Business Analytics platform which has web services interfaces that enable it to insert analytical
results into Java or .Net and display the results in any application. Furthermore, its analytics are
closely intertwined with its CRM packages and directs the workflows for real time information
flows.

7. Visualization is essential for rapid collaborative decision making as illustrated by the case of Sun
National Bank, a regional bank, which needed to compete with much larger banks. It created a
single data warehouse for all its branches and provided analytical software to monitor
performance metrics such as the fastest growing products, regional variations in revenue, all
visualized as charts and graphs, on dashboards for rapid decision making.
A larger number of business and operational users need analytical tools that cater to their specific
needs. Consequently, analytical software needs to be scalable and designed for role-based
customization. A case where a customer switched from reporting tools to more scalable
enterprise software is the Ministry of Tourism in Bahamas which had used an OLAP tool, within
its offices, for its processing power and analytical capabilities. Later, the ministry needed to
communicate with 400 local hotels and regional tourist boards and switched to an enterprise
reporting tool with server-based computing environments. Lately, OLAP providers have upgraded
their scalability.
As information is drawn from a growing number of functional departments, business intelligence
software should be able to draw data from a variety of repositories. Information Builders product,
WebFocus 7, for example, provides access to more than 200 data sources and data formats,
including relational and legacy data.
An all-encompassing use of business intelligence is that companies find themselves looking at
both structured and unstructured data. Regulatory compliance, as required by Sarbanes Oxley,
requires detailed monitoring of controls which often means finding a record among million others.
Similarly, fraud detection in the corporate sector often requires sifting through thousands of e-
mails which would be impossible with manual methods. It would be hard for companies to
uncover pain points in customer experience unless they are able to mine call center
conversations. Similarly, companies invariably experience delays in understanding the causes of
warranty claims while shipments of the same product continue and later add to the costs of
refunds or product recalls. It is important to be able to correlate structured and unstructured
information to complete the analysis. Attensity is one company which has products that can read
as well as store structured and unstructured information in a relational form. Whirlpool uses its
Relational Extraction Server to extract information and develop insight about warranty claims,
customer feedback and service records.
One of the pioneers of an integrated use of structured and unstructured data is EDS, a systems
integrator for over 9,000 corporate customers. Its large client base implies that it buys countless
servers, PCs, networking gear, software and services from numerous suppliers who sell to its
offices spread in 65 countries. The contracts with its suppliers are a valuable source of
information to find ways to lower prices, as well as to evaluate suppliers based on their response
times and other metrics.

8. The benefits of integrating unstructured data can extend to streamlining the business processes
including increasing the efficiencies in the supply chain. Motorola has used EII to integrate its
information flow to be able to see the order status at every stage of its supply chain network.
Modern text mining technology has progressed beyond keyword searches of familiar search
engines and increasingly looks for items that fit a pattern. Searching by keywords often throws up
irrelevant results because the meaning of words can change with context. This is achieved by
using taxonomies, while mining textual information, which can ferret out results that are inter-
related. The significant difference in searching by taxonomies is illustrated by the experience of
Chelsea & Scott Ltd., a retailer of children's products under the OneStepAhead and Leaps and
Bounds brands. Customers could not often find the relevant products because they were not
aware of their existence. They could, however, describe the needs of their babies such as their
need for comfort. Installation of a natural language search engine change matters and a search
by comfort yields results of all the products that meet this need.
An all encompassing view of the enterprise
The integration of analytical and business processes requires additional choices involving
technologies that help to integrate them. Applications, content and data repositories, analytical
software and workflows management software have existed independently as discrete processes.
Increasingly, they will operate as a seamlessly integrated, continuous process that can be
monitored from an all embracing GUI or an enterprise portal. The analytical tools are integrated
by “portlets” or web services. These portals are available from companies like BEA Systems
which earlier specialized in application servers or players like Vignette which earlier specialized in
enterprise content management or from companies like Plumtree, the only remaining company
from the former ‘pure-play’ portal providers.
Alternatively, companies can also decide to integrate their analytical software with their
operational applications such as Customer Relationship Management Software. In such a
situation, they expose their Application Programming Interface to inter-link BI software or
components.
Similarly, relational data base companies have increasingly integrated analytical applications on
their databases. Microsoft, for example, now supports analytical applications on its ‘Yukon’ SQL
Server which includes support for OLAP, statistical and data mining functions besides database
queries.
The integration of business and analytical applications has to extend to linking content
repositories; this was not possible with the available integration technologies. With the advent of
web services, XML and a gamut of object-oriented, component based technologies enables
integration of structured and unstructured data. IBM has bolstered the prospects of the
technology by acquiring Venetica and uses its content integration middleware into its DB2
Information Integrator suite.

9. Depending on their business needs, companies can decide on the kind of package they want to
buy. If they would rather focus on specific departments, they can decide to buy packaged
analytical applications such as especially the finance department. On the other hand, they could
opt for integrated packages which include data management and integration, analytical tools and
applications and collaboration software. Companies can also decide to customize their business
intelligence software and elect to buy analytical development environment which allows them to
use components to build applications for their needs.
The overlapping functions of business intelligence and enterprise management have also
attracted many different types of vendors from the enterprise resource planning, performance
management and business process management space besides best-of-breed innovators who
excel in some segments of the process. Buyers, therefore, have to weigh the benefits of staying
with their familiar ERP vendors who increasingly have the ability to package business intelligence
packages versus choosing the richer functionality of ‘pure-play’ business intelligence vendors or
the niche ‘best-of-breed’ innovators. While the increasing availability of integration tools, with the
advent of web services, XML and Java, afford the ability to conveniently extend ERP packages,
management of a diversity of vendors does increase costs.
The sum of the parts is higher
Buyers of business intelligence software have to weigh the often conflicting needs of
standardizing the source of their software to realize cost economies as against acquiring
innovative software from ‘best-of-breed’ companies who often do not have the ability to provide a
package of transaction data software, ETL and business intelligence tools. The quality of
middleware has vastly improved in recent years with the advent of web services but companies
still prefer a solution from a single vendor as we will discuss later. While business transaction
database companies are increasingly incorporating business intelligence software, they are still
not functionally as rich in business intelligence functions.
At this point of time, the industry is divided between vendors who excel in implementation of
business intelligence software, as assessed by Gartner, and many of them are cash-rich
companies from the mature segments of the enterprise software sector. On the other hand, the
pure-play business intelligence software companies have stood out for their visions; they are
emerging companies which are relatively weak in their capabilities to develop the infrastructure
for business intelligence. None of the companies have both the capabilities for users to be able to
make a clear choice of a vendor.
The players from the traditional segments of the enterprise software industry, i.e., Enterprise
Resource Planning, RDMS, Customer Relationship Management and Supply Chain Management
companies have added Business Intelligence functions in their offerings. They stress their proven
track record and familiarity while the ‘pure-play’ BI companies berate this ability as commonplace
in an environment where web services facilitate convenient integration with existing applications.

10. According to estimates of Gartner, the users who decide to opt for ERP companies, who are also
able to meet the application requirements of customers including BI, will incur costs that are 25%
lower than those who decide on ‘best-of-breed’ or more specialized innovative companies by
2005. The best of breed companies are more innovative and find new ways to compete but the
fact remains that the older companies are either buying them or are able to incorporate or embed
their software within their package and lower costs of servers and license fees.
The merits of these contradictory claims can be judged from a recent survey of BI and DW
professionals who are members of TDWI. The data from 552 BI and DW professionals indicates
that 56% of them use BI solutions from their transaction database providers either exclusively or
jointly with third-party solutions. On the other hand, 61% of them are using either third-party
solutions exclusively or in combination with the transaction database providers. Users are more
likely to prefer transaction database providers when they need to access information from their
software and when the data is used for routine analytical functions like fraud detection and
profiles of customers for contact management. Also, they are more likely to use software from
transaction database providers when they also provide the ETL solution as well saving them the
job of extracting the data. On the other hand, third-party solutions are likely to be preferred for
advanced analytics like predictive analysis or ad hoc queries. Also, companies have a less
compelling need to stay with their transaction database providers when they already have legacy
software installed and need to use integration technologies. In all, companies are more likely to
use transaction database providers as they increasingly use BI for improving operational
management as is the case today.
The leap towards enterprise wide intelligence
Businesses have to often choose between data marts implemented in some departments in
contrast to the bolder alternative of investing in a data warehouse or an enterprise wide real time
intelligence infrastructure from the very beginning. A smaller data mart can be a test case and is
more likely to be accepted by a minority of technology buffs in an organization while a data
warehouse or enterprise intelligence is more efficient. If companies opt for a data warehouse,
they will encourage standardization of data definitions and planning for business process
management across the enterprise which is not a pressing concern when data marts are
implemented in some divisions. Furthermore, data marts require a different kind of technology
which is rendered obsolete later when enterprises decide to accept data warehouses or
enterprise wide real time intelligence. Also, data marts, duplicate data which has to be cleaned
later when companies switch to data warehouses.
One case where a company had to abandon its investments in a data mart is GE Real Estate
which has investments in over 8,000 properties around the world. The management of such a
portfolio required information that was often available in the individual countries where the
operating units were located. GE decided against the ideal solution of a web based data

11. warehouse solution primarily because reconciliation of a variety of data definitions used by its
departments seemed much too daunting. After the modest success of its data marts, GE had to
entirely abandon its Microsoft server which could not scale for a data warehouse and had to
instead change to a UNIX server with an Oracle database.
A more comprehensive survey of 150 technology executives, who have implemented business
performance management (BPM) across the enterprise, shows that a step-wise process has
been more successful for most companies. Twenty percent of the respondents have implemented
BPM and 60% of them implemented them for particular problems before expanding their scope to
the entire enterprise.
The decision to buy software for a specific department or the company as a whole is not simply a
technical decision. While the more skilled or “power users” are avid consumers who relish new
software, the risk of provoking a more political response from other employees is much greater
especially if they are either wedded to the tools they have used in the past (typically, Excel) or are
not sophisticated users of some arcane business intelligence software. The choice to use more
integrated software should be preceded by finding a sponsor with the clout to implement new
business intelligence software. Also, companies have to find the means to customize the software
according to the roles of each individual in the enterprise.
On the other hand, the benefits from enterprise business intelligence yield the greatest benefit.
Companies can more effectively align their strategies with the resources and tactics of their
company. They can also monitor performance in real time to ensure that their actions are able to
achieve their goals.
Intelligence for all decisions
Analytical software is not any longer a stand-alone application that is the preserve of power users
who have special skills to use arcane tools. Instead, analytical applications permeate the
enterprise and they have to be adapted for users who are pre-occupied with solving business
problems or just daily operations and do not want to bog down in mastering the technical nuances
of sophisticated tools. While power users require data exporting, cube and data modeling options,
business users need the ability to manipulate data, at a granular level, locally in Excel. Casual
users prefer dashboards and canned reports.
The business users are also interested in sharing information with their team members. Tools like
Crystal Reports and Actuate Corp.'s e-reporting disseminate information to many casual users and high-
level decision makers.
Finally, analytical tools have to be seamlessly integrated with business process management as
well as tools for evaluation of results of actions taken based on the initial analysis. An example of
this kind of software is Customer Power 5.0, a tool developed by NCR, which is targeted at
customers in the retail, financial and catalog marketers. They are able to use customer
information and analytics for improving the effectiveness of marketing campaigns. One clothing

12. company is able to use transaction information to create catalogs specially designed for its best
customers.
Enterprise users look for tools that have an intuitive interface and are customized for their
industry and functional area of expertise; generic analytical tools are less likely to meet their
needs. The need to expand the functionality of analytical tools stretches the technical capability of
vendors. In the past, analytical software companies specialized in a limited range of functional
expertise. Some companies like Hyperion excelled in performance management while others like
SAS and SPSS distinguished themselves in statistics. In their efforts to meet a more diverse set
of needs of customers, analytical software vendors are now entering a risky terrain where they
have to acquire companies to provide a portfolio of products including integration with business
process management software. Furthermore, they have to be able to gain domain knowledge of a
variety of industries where they have customers. Finally, customer needs are evolving as
knowledge workers in enterprises find ingenious ways to use information. It is unlikely that all
customers will be able to find the entire range of functionality they need.
An alternative possibility is that customers can buy a package of tools and have the ability to build
new applications using development tools and a platform. Custom applications, developed by
customers themselves, are more likely to take advantage of the domain knowledge than vendors.
Customers would prefer component based application development with graphical tools so that
they don’t have to invest inordinate amount of resources in programming. A typical product of this
nature which bundles a package of software tools and a development environment is Oracle’s
10g which combines business analytic and reporting tools, Oracle Discoverer for querying
analysis and dashboard features; Oracle Spreadsheet Add-In, which allows direct access to
Oracle's online analytical processing (OLAP) from within Microsoft Excel spreadsheets; Oracle
Warehouse Builder with extract, transform and load (ETL) capabilities; and Oracle BI Beans, a
set of custom developing tools.
The advantage of custom applications is that they readily adapt to the existing infrastructure of
the company including the data warehouse. In addition, companies have already implemented
their data categories, dimensions and the data model and their customized applications will adapt
better to this ensemble while packaged applications would require considerably greater
adjustment within the enterprise including changes in the data warehouse.
Weaving the information fabric
The latest research, based on feedback from users, indicates that ease of integration is the single
most important criterion for selection of Business Intelligence software. More than 75% of the
users consider this to be the most important factor in the selection of BI software. The high level
of significance of integration is illustrated by the case of Alaska Airlines which preferred Siebel
Analytics for the ease of integration of the software in its heterogeneous environment especially

13. the data warehouse. The metadata that came with Siebel Business Analytics is especially useful
in the integration process.
Data warehouses have been the lynchpin of strategic applications of business intelligence; they
enabled companies to coalesce information from disparate sources. In addition, the data
warehouse stores data only after it has been cleaned for inconsistencies and when it conforms to
standard definitions. Data is prepared for use in data warehouses by ETL (extraction,
transformation and loading) tools which extract data from operational data stores, transform the
data so that data definitions are consistent and duplicated data is removed and the output is
loaded into data warehouses in line with its metadata. The data warehouse updates the same
information. The downside of the data warehouse is that it can update information only when
analytical functions are interrupted while data can be updated usually on weekends or beyond
work hours. As the volume of data grows, the time spent on loading increases to an extent where
it would conflict with data analysis functions. Also, real time analytics is really not feasible with the
latencies that are inescapable with the data warehouse.
The alternatives to ETL technologies are the EAI (Enterprise Application Integration) and EII
(Enterprise Information Integration) technologies which can access data from a variety of
sources. The EAI integrates applications and helps to access data from them. One example of
how a company leverages such a technology is Virgin Mobile which needed to rapidly expand its
services in the USA without sinking investments in an elaborate IT infrastructure. It struck an
agreement to use Sprint’s operating infrastructure, for the phone service, which was integrated
with its CRM and financial software using process integration software.
The problem with simple integration of applications is that their data definitions or the metadata
may not be the same so that it would be hard to extract data without standardizing their
definitions. On the other hand, EII helps to both integrate the applications and uses XML to match
the taxonomy of the data extracted.
For real time applications, BI software will have to work with both historical and current
information. Enterprise Information Integration software is able to draw information from both the
data warehouse as well as operational data stores in real time as transactions happen. When the
data is drawn directly from operational data stores, it is not cleansed of inconsistencies in data
definitions or duplication. A BI tool, such as Cognos ReportNet, uses Composite Software’s
Composite Information Server, to extract information from data repositories throughout an
enterprise and create a single, more comprehensive data source.
One application of the EII technology is the case of Owens Corning which combined its EII
software and the BI software to generate reports on gross margins earned every day. The data
was extracted from its numerous ERP databases. In the past, the same exercise took about a
month. The reduction of the lag time in reporting has helped Owens to make mid-course
corrections.

14. An increasingly preferred means of integrating software is the Services-Oriented Architecture
(SOA) which reduces the monolithic applications of the past into components or services which
construct the larger applications. These services or applications are mounted on a single user
web based user interface. Users can choose the services they need instead of buying a package
which often has components that are not relevant for them. Each of these components are inter-
connected by web services which use XML tags to build an interface which can be used to
access services using web technology. Web services can be used to provide access to business
processes, applications, BI cubes, reports, queries and data integration functions, databases etc.
The web services are indexed in a UDDI registry. In order to connect to a web service, an
application or portal simply queries the UDDI registry, finds the service and then dynamically
connects to it by sending it an XML message known as a SOAP (Simple Object Access Protocol)
message. The Service Oriented architecture is a more cost effective since it does not require IT
people to inter-connect applications.
An example of a SOA implementation is Siebel 7.5.3, released in mid-2003, which is expected to
crystallize with the Siebel 8.0, due in 2006. The complete Web-services-oriented software will
include workflow management tools.
The cross-point of all data
At the heart of efforts at integration is the task of creating taxonomy and metadata or descriptions
of data which helps to describe data across any application, repository or database. Most
metadata is sui generis and hard to relate to other descriptions of data associated with another
application.
Data is fragmented for a variety of reasons. Structured and unstructured data is hard to correlate
because the former is stored in a relational data base and the latter in a content repository.
Content itself is divided between document, web and digital asset management repositories. It is
hard to find related structured and unstructured information in a relational database and a content
repository because the former uses SQL to extract data and the latter uses a search engine. The
descriptions of the data vary depending on the function of the person who is using it. A marketing
person is concerned about customer acquisition while a sales person is interested in prospects,
orders and closures. The information systems they use will differ; a marketing person will use a
CRM system while a sales person will typically use Salesforce.com. Both will enter customer
reference data often with different conventions about recording first names and second names,
address entries, etc. When the units of a company are spread across the world, each national
subsidiary uses a different language which often means they also use another information
system.
Increasingly, companies need to be able to correlate information. They need to be able to see
inter-related information about customer purchases and their behavioral traits which are best
described in text. Similarly, they need to correlate information about customer acquired and the

15. sales earned from them. They also want to share content created in one subsidiary with another
in another country and translate and use it rapidly.
A real time enterprise needs not only gain access to all this information in a cohesive manner but
also be able to do this quickly. The advent of XML has considerably simplified the process of
correlating disparate information by described its components at a more granular level with the
help of tags. Once content descriptions are available at this level of detail, some extracts can be
reused rapidly. With the use of XML, it is now possible to search simultaneously in relational
databases as well as content repositories. Companies are now able to translate content in a
repository in one country for use by another country without requiring the intervention of skilled
translators.
MacDonald is a classic instance of a company that operates across national boundaries and has
to work with repositories located in several different countries. In addition, it has numerous
franchises working independently and loose time when they recreate the same content. In order
to collate information from its subsidiaries, MacDonald has to be able to translate the content
from several different languages and draw them from several different information systems. It
also benefits from centralizing content creation and redistributes it to local units where it can be
customized. All the content can be accessed from a portal.
Golden Gate Software’s Data Synchronization solution is an example which helps to use data
from disparate sources in real time. It has been used in the health care industry by hospitals to
collate information from individual hospitals and patient care centers in a single repository. With
synchronized clinical and administrative data, one of its customers is able to produce detailed
analytic reports to track patient metrics, length of stay, and other care management data.
CONSIDERATIONS ABOUT THE FUTURE
RFID
Radio Frequency Identification is used to identify, track and sort objects. A tag is inserted in an
object for transmitting information about the product identification; the data is transmitted by radio
waves and received in a digital form for storing in computers. The tag is a tiny antenna with the
ability to send radio signals to a reader or a mechanism that is able to receive radio signals. RFID
is presumed to have potential applications in supply chain management which is expected to
generate enormous data for BI analysis purpose even though applications development is
uncertain.
Wal-Mart’s declared its plans to use RFID with much fanfare but the effort petered off after the
suppliers balked at the idea. The aggregation of the RFID data will be a complex task of
integration as the data will be received from a plethora of often small companies involved in
logistics management.
Yet, some companies have found ways to use RFID data to their advantage. Graniterock, a
Watsonville, California based company, has installed a BI system to monitor time spent by trucks

16. in its quarries. The clerical tasks of identifying incoming and outgoing trucks don’t need to be
done any more, as their movements are recorded electronically, so that Graniterock saves time.
The customers benefit as they are able to monitor the costs they incur on the time spent by
individual trucks and the relative efficiency of each company.
RFID has potentially profitable applications in several different industries. Tracking baggage in
the airlines industry is an enormous cost and pioneers like Delta Airlines is already using RFID to
trace lost baggage. The drug industry also has an intractable problem of controlling the diversion
of drugs for intoxication.
Complex Business Event Monitoring
Investment in Information Technology infrastructure creates new possibilities. CRM paved the
way for business analytics. In turn, business analytics afforded opportunities for event based
business activity monitoring. Even as companies are implementing simple event based business
activity monitoring technology, conditions have been created for more complex event based
business activity monitoring which enables decision making including pre-emptive actions, based
on predictions, which help to avert a crisis or an adverse situation from happening.
An example of more advanced event based monitoring is the action that can be taken in
response to news feeds in the financial services industry. A simple event based business activity
monitoring would be a stop-loss routine which triggers a sale whenever the price of a stock falls
by a given percentage amount. A relatively more complex business activity monitoring would be
to monitor trading activity to determine whether the patterns in bids by traders in an auction
suggest that they are colluding and are violating SEC regulations. This could go further and rules
could be written which help to predict the future performance of the stock and investment
decisions are triggered when expected events actually occur.
The use of complex event monitoring is expected to rise with the use of RFIDs when a lot more
data is expected to be gathered. Several different applications are possible with the data
gathered from the scanning of the codes embedded into products. The obvious application of
RFIDs is to monitor trends in inventory depletion. The more important applications would be to
monitor the time of delivery by different transportation companies which could be affected by the
conditions along the route, the quality of maintenance of vehicles or by the driver’s efficiency.
Companies can begin to analyze the data and find better means for routing, loading and
unloading techniques as well as data on congestion along the way.
A recurring issue with retailers is out-of-stock items (OOS) which lead to lost sales opportunities.
According to a study conducted by Andersen Consulting, 53% of OOS situations happen as a
result of poor stocking decisions. Another 8% of OOS situations happen as a result of lags in
moving inventory from the warehouse to the shelves. Some pioneers, like U.K. supermarket chain
Tesco, have taken the lead in adopting RFID technology to monitor shipments of high-value
nonfood goods to avoid OSS.