A key component of a company’s IT framework is a business intelligence (BI) system. BI enables business users to report on, analyze and optimize business operations to reduce costs and increase revenues. Organizations use BI for strategic and tactical decision making where the decision-making cycle may span a time period of several weeks (e.g., campaign management) or months (e.g., improving customer satisfaction).Competitive pressures coming from a very dynamic business environment are forcing companies to react faster to changing business conditions and customer requirements. As a result, there is now a need to use BI to help drive and optimize business operations on a daily basis, and, in some cases, even for intraday decision making. This type of BI is usually called operational business intelligence and real-time business intelligence.Operational Business Intelligence, Real Time Business Intelligence, strategic, tactical, operational, real-time.

Daniela Ioana SANDU

English

Research Papers in Economics

Revista Informatica Economică nr.3(47)/2008  33
Operational and real-time Business Intelligence 
 
Daniela Ioana SANDU 
IBM Italy 
 
A key component of a company’s IT framework is a business intelligence (BI) system. 
BI enables business users to report on, analyze and optimize business operations to reduce 
costs and increase revenues. Organizations use BI for strategic and tactical decision making 
where the decision-making cycle may span a time period of several weeks (e.g., campaign 
management) or months (e.g., improving customer satisfaction). 
Competitive pressures coming from a very dynamic business environment are forcing compa-
nies to react faster to changing business conditions and customer requirements. As a result, 
there is now a need to use BI to help drive and optimize business operations on a daily basis, 
and, in some cases, even for intraday decision making. This type of BI is usually called opera-
tional business intelligence and real-time business intelligence. 
Keywords:  Operational Business Intelligence, Real Time Business Intelligence, strategic, 
tactical, operational, real-time. 
 
he history of the informatics systems for 
management is marked by 3 key mo-
ments. 
The first key moment was at the beginning 
of the 70s when operational transactional 
systems (OLTP) first appeared. The goal of 
these systems was to structure and automate 
the business processes. They were optimized 
for transactional operations and were static in 
architecture, structure and logic. 
The second key moment was the moment 
when analytic applications appeared. The 
analytic applications offer feedback about 
how well the organization is doing. They 
adapt to the business model, answer ques-
tions about business, are designed and opti-
mized for answering to user queries and are 
continuously evolving; in other words they 
suffer changes in architecture, structure and 
logic.    
Here is where data warehouses (DW), busi-
ness intelligence (BI) and business perfor-
mance management systems (BPM) can be 
found. 
Business intelligence refers to technologies, 
applications and practices for the collection, 
integration, analysis, and presentation of 
business information. Business intelligence 
uses key performance indicators (KPIs) to 
assess the present state of business and to 
prescribe a course of action. Examples of 
KPIs: lead conversion rate (in sales), invento-
ry turnover (in inventory management). Prior 
to the widespread adoption of computer and 
web applications, when information had to be 
manually input and calculated, performance 
data was often not available for weeks or 
months. 
 
 
Transactional Operational 
System  (OLTP) 
Analytic Applications 
Traditional approach 
Transactional Operational 
System  (OLTP) 
Analytic Applications 
New approach   
Fig.1. Communication between OLTP sys-
tems and analytic applications 
 
The communication between the two types of 
systems (operational transactional and ana-
lytical) is unidirectional because analytic sys-
tems are fed with data from the operational 
systems. Is true analytic systems offer feed-
back about the business processes and help 
the management in making decisions, but 
they have a great disadvantage:  they cannot 
modify or influence the operational systems.  
The competitive and very dynamic business 
environment puts pressure on businesses. In 
order to be competitive companies are forced 
to react faster to changing business condi-
tions and customer requirements. This is how 
a new need appeared: the need for the analyt-
T Revista Informatica Economică nr.3(47)/2008 
 
34
ic systems to influence the operational sys-
tems. This is the third key moment in the 
history of informatics systems for manage-
ment, moment that markets the born of the 
Operational Business Intelligence.  
Operational BI allows bidirectional commu-
nication between the operational systems and 
the analytic applications. The information 
and knowledge obtained from the analytic 
systems is used not only for decision making 
but to improve the business processes and to 
adapt the operational systems for better res-
ponsiveness to the changing conditions in the 
market. 
 
Fig.2. Maturity model for Business Intelligence (source: Wayne W. Eckerson, TDWI) 
 
Wayne W. Eckerson, research director at the 
TDWI - The DataWarehouse Institute, in his 
paper  [WAECK07] created a maturity model 
for BI presented in figure 2. 
The model is based on the concept of latency. 
Latency is the temporal delay between the 
moment of an event initiation and the mo-
ment the event’s effects show up. 
The red line in the model stands for the 
freshness of the data (indicate how new or 
old the data is). The blue line in the model 
stands for the latency of the decision process. 
There are three types of latency in a decision 
making process. 
• data latency: the period of time needed to 
collect the data from the source systems, to 
prepare it for analysis and save it into the da-
ta warehouse or data centers; 
• analytic latency: the period of time needed  
to access and analyze the data, to transform 
the data in information, to apply the business 
rules.  
• decisional latency: the period of time 
needed to review the analysis, decide the ac-
tion to be taken and implement the action. 
In the Wayne Eckerson’s model, traditional 
business intelligence corresponds to the pre-
natal and child phases. These are phases cha-
racterized by high latency in the decision 
making process and low freshness of data. 
Phases teenager and sage correspond to op-
erational business intelligence. These phases 
are characterized by low latency in the deci-
sion making process and high freshness of 
data. 
We can say that a business intelligence sys-
tem becomes more operational with the 
age. 
In conclusion we can identify 4 types of 
business intelligence. 
 
1. Strategic BI. 
Focuses on reaching long term objectives, 
strategic goals such as: increase profit, cut 
costs, gain new market shares, improve cus-
tomer relationships. Strategic BI is used by 
top management and financial analysts who 
are interested in analyzing the company’s 
performance in areas with a key role in 
reaching the strategic objectives. The analy-
sis is done on data with a temporal window 
of months - years of historic data. Revista Informatica Economică nr.3(47)/2008  35
2. Tactical BI. 
Focuses on reaching the tactical objectives 
defined for the strategic goals. Marketing and 
publicity campaigns for releasing a new 
product on the market, new promotions pro-
grams and so on are subject to tactical BI. 
Tactical BI is used by top management, fi-
nancial analysts and line of business manag-
ers. A line of business manager is responsible 
for managing and monitoring daily business 
operations (for example: risk managers, retail 
merchandisers, plant floor managers). The 
analysis is done on data with a temporal win-
dow of days - months of historic data. 
Strategical and Tactical BI form the tradi-
tional BI. In the traditional BI the valuable 
information needed to monitor the key per-
formance metrics is available only to senior 
executives and analysts, not the operational 
workers on the front lines of business. In 
fact, according to IDC, only 15% of em-
ployees in an average organization have 
access to business intelligence information. 
According to Gartner, the three key barriers 
to widespread use of BI are: 
• Users lack the necessary skills to use 
complex BI tools. Operational workers in 
functional areas such as logistics and call 
centers often lack the necessary skills to han-
dle BI software that was designed for ana-
lysts and power users. 
• The cost of ownership of deploying tra-
ditional BI tools to a large number of users 
is too high. Between seat licenses and user 
maintenance, traditional BI software is too 
costly to deploy to large numbers of opera-
tional users. And scalability is also a major 
issue: the performance of traditional systems 
deteriorates dramatically as more users are 
added, which means more servers must be 
deployed, adding to the cost and maintenance 
headaches. 
• Existing BI tools are difficult to learn 
and to use.  Companies have found that 
training thousands of workers to slice and 
dice data with traditional BI tools just isn’t 
feasible. 
 
3. Operational BI 
In spite of the obstacles presented above, the 
concept of operational BI has tremendous 
momentum. Companies are eager to provide 
visibility into the current status of business 
operations to thousands of users across the 
organization. They want to be able to set key 
performance metrics and then actively track 
execution against those goals. They want 
their workers to be able to spot emerging 
trends, make faster decisions, immediately 
take action when problems arise and posi-
tively affect their company’s bottom line.  
There are strong reasons that generated this 
kind of shift in the company’s attitude re-
garding the BI visibility to all categories of 
users. Nowadays the business environment is 
extremely competitive (from the competitors 
point of view) and dynamic (clients have 
changing and higher expectancies).  The law 
for surviving in such conditions is the 4R 
law: the right information, in the right 
format, to the right people, at the right 
time. Only abiding to this rule the company 
has a competitive advantage on the market. 
With unlimited access to the BI information, 
all categories of users – including the opera-
tional users – can identify trends, take deci-
sions, and act as soon as a problem appears 
in order to correct it. This way all categories 
of users work together for reaching the com-
pany’s strategic goals. 
Operational BI touches a bigger number of 
business decisions than the traditional BI and 
the BI functionalities are seen as daily opera-
tional transactions.  The data analysis is 
made within a day frame time (a couple of 
hours, at maximum 1 day). For example op-
erational BI allows monitoring the current 
marketing campaign or the order status with-
in a working day. This kind of analysis in-
volves immediate access to the detailed, op-
erational and refreshed data (data describing 
the business processes now, today) but also 
access to historic data (for trend analysis).  
 
4. Real-Time BI 
Operational BI evolves into Real-Time BI. In 
Real-Time BI the data is analyzed as soon as 
it enters the organization. In this context, 
real-time means delivering information in a 
range from milliseconds to a few seconds af-Revista Informatica Economică nr.3(47)/2008 
 
36
ter the business event.  
The latency in this case is reduced to zero (no 
data, analysis, decision latency). For exam-
ple, a line of business manager can monitor 
the stock level in order to assure that the on-
going online marketing campaign will not 
fail because of unavailable stock situations. 
An operational / real time BI system is based 
on an operational / real time data ware-
house, a data warehouse with increased re-
fresh cycles to update the data more frequent-
ly. These real-time data warehouse systems 
can achieve near real-time update of data, 
where the data latency typically is in the 
range from minutes to hours out of date.  
Operational and real-time BI optimize the 
decision making process by reducing to eli-
minating latency. Implementing real-time BI 
is extremely costly and not always necessary. 
However companies do not always need to 
reduce latency to zero and do not always 
need to take and implement decisions in real 
time. The important issue is to define an op-
timum frame time, the right-time for any de-
cision process, an interval that should reflect 
the business needs and that should offer the 
best risks-costs ratio.  
Table below reviews the differences in the 
various types of Business Intelligence. 
 
Table 1. Business Intelligence types 
 
Characteristics 
Business Intelligence type 
Strategic  Tactical  Operational/ Real-Time 
Business objectives Long term (strategic)  Tactical  Manage and optimize daily business 
operations 
User type  Top/senior manager, 
financial analysts 
Top/senior manager, 
financial analysts, op-
erational managers 
Top/senior manager, financial ana-
lysts, operational managers, opera-
tional users (call center, sales agent), 
User population  Tens  Tens- hundreds  Tens - thousands 
Time framework 
for analysis 
Months – years  Days - months  1 day  / seconds 
Data type  Historic  Historic  Historic, current (zero latency) 
Query response 
time 
Hours – minutes  Hours - seconds  Minutes - seconds 
Instruments for da-
ta access 
Excel, BI specific 
tools 
Excel, BI specific 
tools 
Portals, Dashboards, Scorecards, 
Alerts 
Data disponibility  Non critical: Tolerant 
to non-disponibility 
Non critical: Tolerant 
to non-disponibility 
Critical: Cannot tolerate  non-
disponibility 
Latency High  High-medium  Low 
Data freshness  Old  Old-new  New 
 
References: 
• [DAJU06] „Using Operational Business In-
telligence for intra-day analysis and decision 
making”, Judith. R. Davis, research report 
published by BEYE Research, 2006. 
• [AJU05]„Right Time Business Intelligence 
Optimizing the Business Decision Cycle”, 
Judith. R. Davis, research report published by 
BEYE Research, December 2005. 
• [CELEQ05]„Operational Business Intelli-
gence: Bringing BI to the Masses”, product 
documentation Celequest Software published 
by The Data Warehousing, Institute 2005 
(TDWI, http://www.tdwi.org). 
• [WAECK07] „Operational BI architec-
tures: Converting Analytical and Operational 
Processes”, research report published  by 
Wayne Eckerson, The DataWarehouse Insti-
tute, 2007  (http://www.tdwi.org) 
• [KNSOL07]„Top 10 Trends In Business 
Intelligence for 2007”, research report pub-
lished consultancy firm Knightsbridge Solu-
tions LLC, (TDWI, http://www.tdwi.org). 
• www.hyperion.com 
• www.cognos.com 
• www.ibm.com 
 

[AJU05]„Right Time Business Intelligence Optimizing the Business Decision

[CELEQ05]„Operational Business Intelligence: Bringing BI to the Masses”, product documentation Celequest Software published by The Data Warehousing, Institute

Operational BI architectures: Converting Analytical and Operational Processes”, research report published by Wayne Eckerson, The DataWarehouse Institute,

Using Operational Business Intelligence for intra-day analysis and decision

Operational and real-time Business Intelligence

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Operational and real-time Business Intelligence

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