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Business Intelligence in Organizational Decision Making

Autor:   •  October 3, 2017  •  6,512 Words (27 Pages)  •  231 Views

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For manufacturers the problem of information quality is relevant at all levels of the supply chain. One reason for this is the fact that manufacturers are dependent on the suppliers, contractors, wholesalers, retailers and consumers for effective search of raw materials, demand forecasting, production and marketing of their products (Tvrdikova, 2007). Manufacturers rarely manage to control the quality and size of the external data. However, with a serial improve data quality in the supply chain manufacturers can significantly improve the effectiveness of their work: improve the speed and efficiency of development of products, expand the possibility of a variety of analytical studies on demand, improve the efficiency of trading partners using timely and accurate information about products and prices, better serve customers using timely and accurate information about them (Noori, et. al., 2005). In order to monitor the implementation of programs to improve the quality of information it is necessary to carry out continuous measurement and evaluation.

Trend №2: managing reference data

Enthusiasm associated with the management of reference data has become particularly noticeable during the past year. According to the forecasts of the consulting company IDC (International Data Corporation), over the next five years, this market will grow at an impressive rate of about 14% per year (Yu, et. al., 2009). Standard-reference information is the data that describes the key components of a business organization: customers, products and suppliers. Its purpose is to ensure the homogeneity of semantic and organizational business processes and simplify the integration of data and processes.

In order to remain competitive, all generating companies have to rely on the most important data about their suppliers, partners, customers, products and even competitors (Wu, 2010, p. 8). Unfortunately, these important data are usually controlled by very disparate, often redundant and external information systems. The complexity of this problem adds that most major manufacturers operate on a global scale. In addition, companies in the development usually go through a number of mergers and acquisitions. This leads to mixing of disparate and redundant data. Ignoring the decision to settle the problem of rising complexity and redundancy of important corporate data may have significant implications for the value chain. This can be expressed in the delay-to-market, reducing productivity, increasing costs and decreasing supply of customer satisfaction (Eckerson, 2007, pp. 14-16).

Starting a project related to the management of reference data, manufacturers should be aware that this information is a problem not only in technology, but in the involvement of business in the process. In addition, the management of this information is not a one-time process, but a rather permanently functioning program. Here a step-by-step implementation is important, as well as the selection of priority projects. This approach ensures fast receiving of tangible benefits (Sen, 2009).

Trend №3: data management

Data management is a business function that sets the strategic direction for projects to improve the quality of information, set standards and processes and ensures that the objectives are related to improving the quality of information. The basic elements of an effective data management are: policy and planning, organization, standards, processes and methods, monitoring and interaction. Without an effective data management efforts to improve the quality of information are doomed to failure. Many organizations still consider corporate governance as an information technology solution that includes data warehouse, the ability to move and transform data using software tools to extract, transform and load (ETL) tools and reporting tools based on BI. Although these technologies are usually part of overall information management solutions, the latter will not be successful without the common organizational changes, including the field of information and data management. Thus, both business and IT-specialists should be involved in the process. Business is very well adjusted for data ownership and management of the organization. Business representatives should monitor business units and divisions to ensure that they have positive dynamics. It is useful to use a third-party consultant to objective mediation discussions and maintain a focus on the main goal of the organization to ensure the quality of information.

Manufacturers are largely dependent on the cooperation between the functional areas that make up the chain of value calculation. In addition, most of the companies included in the list of largest corporations in the magazine Fortune, operate on a global scale. These circumstances make it difficult to design and implement a quality management model data, but nevertheless its creation is an absolute prerequisite for successful enterprise information management.

Trend №4: corporate BI

The driving force behind the needs of many organizations in Business Intelligence is a continuing need for an integrated data picture to be gathered from multiple disparate sources. The need for data integration is dictated by regulatory compliance, increasing activity in the field of mergers and acquisitions, is coupled with economic growth, and the ever-increasing need for senior management in monitoring and analyzing the effectiveness at a global corporate level. Creating corporate Business Intelligence tools requires significant scale of process and organizational changes, as well as robust corporate strategy and architecture of Business Intelligence, aimed at solving problems and achieving the goals of both business and IT-specialists.

Many major global manufacturers have need and a growing desire to create a system of corporate Business Intelligence. Some of them have even started to develop the necessary strategy and approach, but very few actually succeeded in creating a corporate system of BI. The problem is that most manufacturers still only have to prove their leaders need to establish such a system for the funding of these projects and resource planning. In this situation, the supporters of the corporate Business Intelligence system should focus on the development of very visible and demonstrative example of a business that can be presented to senior management and finance for the acquisition of the necessary support. Fortunately, manufacturers are already aware that the Business Intelligence - this is not just another business project, but the approach that requires lengthy investment and programs aimed at improving the competence and the creation of the


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