Business Intelligence in Organizational Decision Making

Content

1. Basics of Business Intelligence Systems in Decision Making Process……….        3

1.  Business Intelligence Concepts and Components…………………………..        3
2.  Trends in Business Intelligence System……………………………………..        5

2. Developments in Business Intelligence………………………………………..        10

1.  BI’s Architecture and Components……………………………………….        10
2.  Business Intelligence Implementation and Its Benefits……………………        11
3.  Stages to implement a BI-system successfully……………………………        12
4.  Benefits from BI Implementation…………………………………………        14

Conclusion…………………………………………………………………………        22

References………………………………………………………………………….        24

Appendix…………………………………………………………………………..        26

1. Basics of Business Intelligence Systems in Decision Making Process

1.1 Business Intelligence Concepts and Components

Today's exciting BI market is ripe with opportunities to hit your strategic business targets. Gaining market share, keeping customers and controlling costs remain key objectives. Mid-market executives and big corporate department heads rush to cost effectively meet these complex needs (Davenport, 2006). How? Through improved use of their existing database systems. CFOs require 'business intelligence' systems that display accurate SKU or customer-level P&Ls, permitting reliable channel and store comparisons over time. Improved forecasts are vital, too! Data warehousing and analytical skills are combined with an understanding of industry issues, as we refine and implement your vision (Cudeck, 2007).

According to Gartner survey of 1,400 CIOs, business intelligence was ranked the top technology priority surpassing security. The BI and analytics market is currently valued at $8.5 Billion and is expected to grow to $13 Billion over the next five years. According to the results obtained by Merrill Lynch, business intelligence is among the three major expenditure priorities, as well as a year earlier (Lynch, 2013, pp.13-15).

BI solutions are focused on the analysis of a particular type of business or process (continuous production, retail business, project management, etc.) or a range of problems in business (marketing, inventory management, budgeting, etc.). These include various techniques and automation, which are optional and are used for decision support (Ranjan, 2009).

Decision Support System is a computer automated information system, designed to help decision-makers in the complex for a full and objective analysis of the areas of activity. Support for decision-making in the modern enterprise is a key aspect of business development (Tvrdikova, 2007). To ensure the process of decision support it is necessary to timely provide decision-makers with accurate information as to the current state of affairs and about the opportunities that exist at present and in the future, which should be relevant and coherent.

Today, the creation and implementation of technologies of business intelligence (BI) was formed as an independent dynamic direction of the industry of information technology (IT) (Ranjan, 2009).

BI refers to application and technology, which is used to gather, provide access to, and analyze data and information about the company operations. BI is neither a product nor a system. It is an architecture and a collection of integrated operational as well as decision-support applications and databases that provide the business community with easy access to business data.

In 1989 Howard Dresner, a Research Fellow at Gartner Group, popularized "BI" as an umbrella term to describe a set of concepts and methods to improve business decision-making  by using fact-based support systems.

BI is a conceptual framework for decision support (Figure 4.1) (Frisch, 1989). It combines architecture, databases (or data warehouse), analytical tools and applications. Organizations are being compelled to capture, understand, and harness their data to support decision making in order to improve business operations. Managers need the right information at the right time and in the right place.

Technology of Business Intelligence (BI) is increasingly changing and gaining popularity (Figure 2) (Gangadharan, 2007). In general, companies are making progress in the use of Business Intelligence. Recently a considerable amount of research aimed at identifying the interests of the Chief Information Directors of various companies in the field of Business Intelligence has been carried out. Judging from the results of these studies, it is evident that at the level of senior management ideas about the value and importance of improving the quality and availability of corporate data are becoming more common (Dension, 1997). But while companies are becoming more experienced in the use of options and approaches to BI, they need a lot more to do to fully exploit the potential of their data. Let us analyze the importance of the first five development trends of BI for companies.

1. Trends in Business Intelligence System

Trend №1: quality of information

More and more organizations are coming to the conclusion that the quality of the information is a cornerstone of the majority of the most complex solutions to business problems. The poor quality of information makes it difficult for regulatory compliance, reduces the quality of decision-making and is not conducive to efficient operation. Organizations also realize that to improve the quality of information it is not enough to use traditional cleaning methods and data profiling (Dension, 1997). They should be supplemented by methods of data management, metadata and reference data, the methods of certification and auditability of data, as well as their protection. Accordingly, the quality of the information cannot be considered only as a project or program. Attention to quality should be the "way of life" (Power, 2008). This involves organizational and process changes.