The paper intends to present more reasons in the favour of promoting the business intelligence (BI) in the managerial practice. Business intelligence is an umbrella term that encompasses the processes, tools, and technologies required to turn data into information, and information into knowledge and plans that drive effective business activity. BI encompasses data warehousing technologies and processes on the back end, and query, reporting, analysis, and information delivery tools (that is, BI tools) and processes on the front end. Organizations need to increase their focus on decision-making. In particular, they need to think again about the relationship between information and decision-making. Business intelligence and its predecessor concepts decision support, executive information systems, have been circulating for several decades in business.business intelligence, decisions, management.

Georgeta BARBULESCU

Laurentiu FRATILA

Robert SOVA

English

Research Papers in Economics

                 Special Number 1/2011                         Review of International Comparative Management  332 
 
THE BUSINESS INTELLIGENCE AND THE BETTER 
DECISIONS IN MANAGEMENT 
 
 
Laurenţiu FRAŢILĂ 
Robert ŞOVA 
Georgeta BĂRBULESCU 
The Bucharest Academy of Economic Studies, Romania  
 
 
 
 
The new view on decision taken with the help of BI tools 
 
The  business  intelligence  applications  and  their  underlying  data 
warehouses  can  support  the  needs  of  the  management  only  if  they  are  tightly 
integrated  into  the  overall  IT  environment.  The  idea  is  that  better  information 
would  lead  to  better  decisions  and  better  ways  of  managing  organizational 
processes. Whether this idea was called decision support, executive support, online 
analytical  processing,  or  business  intelligence,  there  was  always  another  goal 
waiting to be achieved. Because organizations’ efforts and attentions were being 
spent  on  automation,  to  improve  decision-making  was  never  the  primaryfocus. 
Today it has taken center stage [Davenport 2008]. 
The importance of business intelligence and the need to integrate it into the 
enterprise is highlighted in the following representation – fig.1. The main forces 
that drive business operations - people, plans, processes and performance - and the 
IT systems that support them are represented in connection. 
Business  process  management  is  a  growing  technology  for  modeling, 
simulating, deploying, integrating and monitoring business processes. At present, 
process  management  is  used  primarily  with  operational  business  transaction 
applications,  but  the  need  to  manage  document  and  information  workflows  is 
bringing  process  management  concepts  and  technologies  into  the  collaborative 
application environment. 
ABSTRACT 
The paper intends to present more reasons in the favour of promoting the 
business  intelligence  (BI)  in  the  managerial  practice.  Business  intelligence  is  an 
umbrella term that encompasses the processes, tools, and technologies required to turn 
data into information, and information into knowledge and plans that drive effective 
business activity. BI encompasses data warehousing technologies and processes on the 
back end, and query, reporting, analysis, and information delivery tools (that is, BI 
tools) and processes on the front end. Organizations need to increase their focus on 
decision-making. In particular, they need to think again about the relationship between 
information and decision-making. Business intelligence and its predecessor concepts 
decision  support,  executive  information  systems,  have  been  circulating  for  several 
decades in business. Review of International Comparative Management                              Special Number 1/2011  333 
The role of business intelligence applications is to monitor, analyze and 
report on those operations. The output from business intelligence applications is 
used to determine how well actual business operations are doing, compared against 
business  goals  and  targets.  If  these  business  goals  and  targets  are  not  being 
achieved,  then  either  business  plans  or  business  operations  must  be  adjusted 
accordingly.  This  aspect  of  business  intelligence  is  often  called  business 
performance  management,  which  is  easily  confused  with  business  process 
management,  especially  given  that  process  management  also  supports  the 
monitoring of business performance. A genuine business performance management 
application  is  closely  tied  to  business  plans  and  planning  systems  so  that 
performance measures can be related to business goals and targets.  
 
 
 
Figure 1 The Smart BI Framework
1 
 
Most business performance management applications deliver information 
that  is  reactive  in  nature,  i.e.,  the  information  produced  identifies  business 
problems after they have occurred. Ideally, business users would like to be able to 
predict or anticipate business issues before they occur. The integration of business 
intelligence predictive technologies and planning methodologies into the business 
performance management environment helps satisfy this requirement.  
                                                        
1 White Colin - The Smart Business Intelligence Framework, B-EYE Network Copyright BI 
Research and Intelligent Solutions, 2005                  Special Number 1/2011                         Review of International Comparative Management  334 
At present, business intelligence is data-centric, but as it becomes more 
integrated with business operations it will need to become more process-centric so 
that business intelligence results can be more easily related to business processes 
and their associated business activities.Yet, there is obvious that most organizations 
have not deployed BI solutions in a systematic or consistent manner. They have 
allowed individual workgroups, departments, and divisions to build their own data 
warehouses  and  data  marts,  purchase  their  own  BI  tools,  create  their  own  BI 
applications, and define key metrics, data elements, and business views in unique, 
nonstandard ways. Thus, although BI usage has increased overall, BI deployments 
remain small and disconnected. Many organizations today are riddled with these 
“analytic silos”. This proliferation threatens to undermine the promise  of BI to 
deliver business insight and value to the enterprise. Invariably, each analytic silo 
uses a different set of BI tools, leading many BI professionals to complain that 
their organizations have one of every kind of BI tool imaginable. 
The  TDWI  survey  shows  that  organizations  average  almost  three 
production reporting tools, three OLAP tools, two dashboard applications, two end-
user query and reporting tools, 1.5 data mining tools, and 1.5 planning/modeling 
tools [Eckerson, 2005]. Organizations have an average of 13 BI tools, with almost 
four BI tools or modules per vendor (table 1), but signs of improvement do appear 
as  it  seems  that  organizations  plan  to  standardize  on  one  BI  tool  per  category 
within three years. 
 
Table 1 Types of BI applications 
 
  Reported in 2005  Planned for  
3 year horizon  Change 
OLAP  2.7  0.99  -63% 
Production reporting  2.8  1.4  -50% 
Dashboards/scorecards  2.1  1.1  -48% 
Query & reporting tools  2.1  1.2  -43% 
Data mining tools  1.6  1.2  -25% 
Planning/modeling tools  1.5  1.3  -13% 
 
While  organizations  are  trying  to  reduce  the  number  of  BI  tools  they 
possess, they are also looking to expand the number of users who leverage BI tools 
to make decisions. Expanding the use of BI from power users to all users is an 
important priority for organizations that want to empower knowledge workers with 
relevant  and  timely  information  to  make  quality  decisions  and  improve 
performance. The irony of BI tools is that although they have proliferated in most 
companies, their penetration into the user base has been minimal.  
The key to increasing the penetration of BI tools is multifaceted. In the 
past, the lack of adequate training, a perception that BI tools are for power users 
only, and BI tools that are too complex for casual users inhibited the growth of BI 
tools in many organizations.  Review of International Comparative Management                              Special Number 1/2011  335 
In the future, organizations need to make sure they deploy BI tools and 
applications  that  are  fast,  intuitive,  and  customized  to  a  user’s  role  in  the 
organization. The  BI tools and applications  must also provide access to timely, 
relevant, and accurate information and be able to reach into operational systems, if 
required, among other things.  
There are numerous tasks that organizations must undertake to transform 
BI from a departmental resource to an enterprise one. This means aligning the BI 
solution  with  business  strategy  and  making  sure  the  business,  not  the  IT 
department,  owns  the  solution  and  guides  the  IT  project  teams  during 
implementation and beyond – table 2.  
 
Table 2 Recommendation for preparing the organization management  
to implement BI 
 
The business must recognize the need  There must be strong executive support 
The business must own the initiative  Implement a BI strategy, not just a tool 
Standardize and validate data  Standardize architecture, processes, and 
success criteria 
Make BI tools conform to users  Leverage dashboards and scorecards 
Deliver  continuous  iterations  of  the 
project 
Monitor usage 
Deliver right-time data  Develop  functionality  and  reports 
rapidly 
 
There are two main reasons why organizations are intent on standardizing 
their use of BI tools and delivering an enterprise solution: costs and information 
consistency.  Other,  less  pressing  factors  include  the  desire  to  better  integrate 
transactions and analytics, support an expanding user base, and reduce the number 
of suppliers. 
 
Table 3 The main drivers of standardization 
 
Costs 
 
The  overhead  costs  of  supporting  multiple  BI  tools  add  up 
quickly.  Organizations  must  pay  software  licenses  and  annual 
maintenance fees for each BI product they own. In addition, many BI 
tools  require  dedicated  servers,  separate  security  approaches,  and 
proprietary metadata, thus increasing hardware, operating system, and 
administration costs. End-user training and support costs climb with 
each  additional  BI  product.  Organizations  must  assign  and  train 
different  technical  experts  to  configure  each  BI  tool  and  develop 
custom reports. 
 
Consistent 
Information 
Without a common BI toolset, it is very difficult to deliver 
consistent reports and information. Invariably, groups using different 
BI  tools  create  overlapping  reports  with  different  calculations  and 
formats. Even if the reports run against the same data warehouse, the 
information they contain will not be consistent.                   Special Number 1/2011                         Review of International Comparative Management  336 
A  recent  study  on  this  topic
1,  carried  out  the  sponsorship  of  IBM's 
Information  Management  business  unit,  enlists  26  efforts  to  improve  decision-
making in organizations. The following ten things are of the most importance in the 
mechanism envisaged for evolving the role business intelligence (BI) in decision 
making: 
1. decisions are the unit of work to which BI initiatives should be applied; 
2. providing access to data and tools isn't enough if you want to ensure that 
decisions are actually improved; 
3. if there is a need to supply data to a decision-maker, it should be only 
what is needed to make the decision; 
4.  the  relationship  between  information  and  decisions  is  a  choice 
organizations  can  make--  from  "loosely  coupled",  which  is  what  happens  in 
traditional BI, to "automated," in which the decision is made through automation; 
5. "loosely coupled" decision and information relationships are efficient to 
provision  with  information (hence,  many decisions can be supported), but don't 
often lead to better decisions; 
6. the most interesting relationship involves "structured human" decisions, 
in which human beings still make the final decision, but the specific information 
used  to  make  the  decision  is  made  available  to  the  decision-maker  in  some 
enhanced fashion. 
7. one can't really determine the value of BI or data warehousing unless 
they're linked to a particular initiative to improve decision-making. 
8. the more closely one wants to link information and decisions, the more 
specific it has to get in focusing on a particular decision. 
9. efforts to create "one version of the truth" are useful in creating better 
decisions, but one can spend a lot of time and money on that goal for uncertain 
return unless it is very focused on the decisions to be made as a result. 
10.  business  intelligence  results  will  increasingly  be  achieved  by  IT 
solutions that are specific to particular industries and decisions within them.  
The  cited  study  intents  to  search  answer  to  the  question:  How  do 
organizations  ensure  that  decisions  are  made  on  the  basis  of  the  best  possible 
information, and that the right information  is  gathered and analyzed to support 
decision processes? There are at least three different levels of relationship between 
information and decision-making: 
◙  Loosely-Coupled  Information  and  Decisions  -  This  loosely-coupled 
approach  would  characterize  most  organizations’  approaches  to  business 
intelligence, or what was previously called “decision support.” Data suitable for 
analysis  and  decision-making  is  extracted  from  transaction  systems,  and  made 
available in a data warehouse or mart. Standard reports are produced, perhaps in 
easier-to-understand  “scorecard”  or  “dashboard”  formats.  The  appeal  of  this 
approach is that providers of information can supply it without regard to difficult 
                                                        
1  Thomas  H.  Davenport  -  Linking  Decisions  and  Information  for  Organizational  Performance, 
October 2008 Review of International Comparative Management                              Special Number 1/2011  337 
and sensitive issues such as managerial psychology, organizational politics, and 
decision rights.  
◙  Structured  Human  Decision  Environments  -  The  advantage  of  this 
approach  is that these additional  efforts created a stronger  linkage between the 
information  and  the  relevant  decisions,  making  it  more  likely  to  be  used 
effectively. The challenges of this approach relative to the loosely-coupled one are 
its narrower focus on particular decisions, and the additional effort needed to create 
the decision environment. If the decision is an import ant one for organizational 
success, however, it may be worth the additional effort. 
 
 
 
Figure 2 Three approaches - The Relationship Between Decisions and Information
1 
 
◙ Automated Decisions - The closest linkages between  information and 
decisions usually come when decisions are made by computer. When it is critical 
for information to be applied to a decision in a structured, formula-like fashion, the 
answer is automated decision systems. While the majority of press and visibility 
came to artificial  intelligence and  expert systems two  decades ago,  many firms 
have quietly implemented more straightforward automated decision-making in a 
variety  of  business  domains.  In  order  to  optimize  operational  decision-making, 
companies  have  embedded  decision  rules  and  algorithms  into  key  business 
processes. 
There is a range of technical criteria that organizations need to consider. 
The most important is meeting user requirements, selected by 83 % of respondents. 
This is why involving users in any selection process is key. In addition, a majority 
of  respondents  selected  a  half-dozen  other  critical  requirements:  Web  delivery 
(75%), data scalability (i.e., the ability to query large volumes of data 72 %), the 
response time performance (69 %), user scalability (68 %), and integration with 
existing applications (54 %) [Eckerson, 2005]. 
                                                        
1 Davenport, T. - 10 Principles of the New Business Intelligence                  Special Number 1/2011                         Review of International Comparative Management  338 
Conclusions 
 
Given  these  three  options  for  relating  decisions  to  the  information  that 
informs  them,  organizations  should  follow  a  process  for  establishing  and 
maintaining the connection:  
Strategic  Focus  on  Key  Decisions  –  Since  connecting  information  and 
decision-making often requires a major investment of resources, it’s important to 
ensure  that  any  decision  selected  for  intervention  is  actually  important  to  the 
organization’s strategy and performance. 
Information  Provision  -  Given  an  important  decision  that’s  key  to  an 
organization’s strategy, organizations must begin to provide information for it. 
Decision  Design  -  In  this  step,  the  key  aspects  of  the  context  for  the 
decision  being  made  are  designed,  or  at  least  evolve  in  a  preferred  direction. 
Important considerations in the design process include identification of the roles 
different individuals will play in the decision, the level of structure for the decision, 
the ability of human decision-makers to process the relevant information, and the 
roles of humans vs. computers in the decision process. 
Managers have the responsibility to make the best possible decisions based 
on the available date at one specific point in time; the BI instruments can help them 
in analyzing and processing the relevant information but getting insight and taking 
responsibility on the results is only a human ability, yet possible to be improved. 
 
 
References 
 
1.  Davenport  Thomas  H.  -  Linking  Decisions  and  Information  for 
Organizational Performance, October 2008 
2.  Eckerson Wayne W., Howson Cindi  - Enterprise Business Intelligence: 
Strategies  and  Technologies  for  Deploying  BI  on  an  Enterprise  Scale 
(Report Excerpt), August 2005 
3.  Hitachi  Consulting  Corporation  -  Establishing  a  Business  Intelligence 
Competency Center (BICC), White Paper 2009  
4.  IBM - Building an Information Management Competency Center, White 
Paper January 2010 
5.  MarketingProfs LLC - B-to-B Lead Generation: 2009 Marketing ROI & 
Performance Evaluation Study, 2009 
6.  McGrath  Patrick,  Greenbau  David  -  Governance  and  Delivery 
Organization 
7.  Schifft Michael - Business intelligence - The Definite Guide to Midsize 
Organizations, SAP White Paper, 2008 
8.  White  Colin  -  The  Smart  Business  Intelligence  Framework,  B-EYE 
Network Copyright BI Research and Intelligent Solutions, 2005 
9.  Business Intelligence - Driving better business performance for companies 
with  changing  needs,  White  Paper,  Date:  January  2007; 
www.microsoft.com/dynamics/nav 

B-to-B Lead Generation:

Building an Information Management Competency Center, White Paper

Business Intelligence - Driving better business performance for companies with changing needs,

Business intelligence - The Definite Guide to Midsize Organizations, SAP White Paper,

Cindi - Enterprise Business Intelligence: Strategies and Technologies for Deploying BI on an Enterprise Scale (Report Excerpt),

Corporation - Establishing a Business Intelligence Competency Center (BICC), White Paper

The Business Intelligence and the Better Decisions in Management

Abstract

Similar works

Full text

Available Versions

Research Papers in Economics