Benefits of Business Intelligence

Business Intelligence (BI) remains a vital subject that covers a wide area of interest in the contemporary business environment. As a process of obtaining large amounts of data, evaluating it and presenting reports to the stakeholders to examine the essence of the data, BI is rapidly shifting the organisational operations. Fundamentally changing the decision-making process, the data obtained from BI is necessary for influencing the operational dynamics of a business. BI comprises of both internal and external categories that handle the ability of an organisation to determine the competitive threat. At the internal dimension is the ability of an organisation to maintain the security of their data from outside competition. On the other hand, the external dimension of BI denotes using public domain data to maintain a competitive edge. Through BI, it is outright that the focus on data and its management process is essential within the business framework. In the current competitive marketplace, it has become outright that in-depth analysis of the important aspects of BI translates to an understanding of its benefits and applications across different sectors.

Business Intelligence

            Business intelligence denotes the organisational approach of getting large amounts of data, comprehensively analyzing the data, and making the presentation of conclusive reports that provide information on the essence of the data. Through the data obtained, an organisation can make daily operational decisions in the direction where the data favors. Popovic, (2017, p.918) emphasizes that BI is a technique to improve the organisational performance through the provision of data that assists managerial decision-making since rationale about the data is ascertained. BI depends on technology that necessitates efficiency in organisational operations by providing high-value information that is utilized effectively. Gathering and accessing vital data and presenting it as reports for decision-making forms the basic foundation of BI. Bach, Celjo, and Zoroja, (2016, p.997) assert that the BI tool is the capability of an organisation to collect data from heterogeneous sources that demand advanced analytical techniques. The ability to support the multi-user demands is at the core of organisational BI process. Among the essential activities that make up the BI process are information delivery, reports, statistical evaluation, and predictive analysis.

            BI, from the underlying definition comprises of three main components: online analytical processing (OLAP), advanced analytics, and data warehousing. OLAP denotes the manner in which business users can navigate their way through data by using complex tools that enable maneuvering aspects such as time. OLAP generates multi-dimensional data reports, a summary of the business data and modelling examples for optimization of business operations (Bach, et al. 2016, p.999). OLAP tools and strategies can be adapted to work hand in hand with data warehousing initiatives that are designed for the complex enterprise intelligence systems. The systems are obliged to discover the trends and evaluate the essential factors. On the other hand, aggregation of reports is the role of the reporting software. The emphasis on advancing the operations of the business via data is an outcome of efficiency in data collection and presentation. Therefore, advanced analytics refers to data mining, forecasting, and predicting business outcomes based on data. The approach takes into consideration the statistical analysis techniques that are necessary for predicting certain measures on the set facts. Data housing, as a component of OLAP, is considerably subject-oriented. Data warehouses are efficient at supporting the physical propagation of vital data by handling the numerous organisational records. Activities such as integration, data aggregation, and query tasks circumvent the data warehousing process. Data warehousing also places a significant amount of emphasis on the management of operational data, which can be updated and integrated throughout the organisational performance (Elbashir, Collier, and Davern 2014, p.140). In-depth management of the data warehousing process can provide a platform for the organisation to achieve beneficial strategies in their retrieval and management of data.

Business Intelligence: Benefits

            BI provides a unique approach to organisations through capitalizing on the data collected to inform the decision-making process. The multiplicity of the approach, based on diverse activities that necessitate the managerial decisions, generates various benefits to the organisation (Arnott, Lizama, and Song 2017, p.62). Companies that utilize BI can grapple with positive outcomes in their operational process through the effectiveness that the data generates (Kasemsap 2017, p.24). BI has the capability of eliminating ambiguity in a business, communication enhancement, and improvements in the coordination of activities (Trieu and Burton 2017, p.). Enabling the organisation to respond effectively to the changes in both the external and internal dimensions of operations necessitates successful outcomes. Through BI, it is evident that the organisation can examine customer preferences and supply chain activities to ensure overall positive performance.

            In the present business environment, information is the second most essential resource after human resource (Yeoh and Popovic 2016, p.139). Across the departments, the decision-making process that emanates from timely and accurate information ensures improvement in performance. Yeoh and Popovic, (2016, p.140) argue that BI is necessary at expediting decision-making through quick and accurate evaluation of information prior to the rivals. The reliance on information is an advisable option for organisations in the business environment that is grappling with the increasing social media preference. In addition, the need for organisations to act on the available information and capitalize on social media presence is to enhance the reach to the sources of data from existing and potential consumers through feedback and reviews (Yeoh and Popovic 2016, p.143). Therefore, the ability of BI to improve the clientele experience through in-depth comprehension of their tastes and preferences is necessary to enable quick and effective response to their issues and priorities.

            It is commendable for the organisation to realize the beneficial outcomes that BI necessitates. The multi-departmental benefits of BI are evident from its potential to shift in various aspects of business operations. As an example, the competitively placed BI tools assist employees in their conversion of business knowledge (Arnott, et al. 2017, p.63). The adoption of analytical intelligence enables employees to deal with numerous organisational issues such as increasing customer response rates through the use of information from direct mail, emails, and telephone conversations. Developing internet-based marketing campaigns that originate from customer behaviour information is an outright benefit of BI.

            Across the organisational framework, BI has the potential to revolutionize the customer management process. Identification of profitable customers and underlying reasons for customer loyalty influences the decision-making process. Information on customer behaviour provides real-time solutions in organisational marketing activities (Elbashir, et al. 2014, p.143). The technology-centric marketplace depends on organisational awareness of the behavioural attributes of their customers. Therefore, through BI, the business can analyse the data and improve both in-store and e-commerce strategies.

            On the other hand, BI has the potential to change the financial management process. The adoption of tools such as enterprise resource planning and cloud storage of information provides the necessary data to influence decision-making. Quick accessibility to operational data can enable the company to effectively detect any discrepancies in the financial reporting process.  Internal concurrent financial reports are essential for organisational decision-making since the company can make decisions that are in line with performance trends (Peters, Wieder, Sutton, and Wakefield 2016, p.9). Determining the right combination of product and service lines to suit the consumer tastes and preferences are evident through accessibility to the monthly or yearly reports (Nedelcu 2013, p.16). Further, analysis of the external market operations is vital for the organisation in predicting their competitor’s strategies and countering them effectively. The reliance on information for operational, marketing, and financial decision-making is beneficial as it keeps the management on the know-how regarding the market and the product lines that meet the consumers’ demands.

Application in an Industry

            Across the retail sector, BI has become essential at providing organisations with data that influence the decision-making process in various activities such as customer management and marketing activities. Filtering the essential information on customer sales reports, supply chain process, and monthly revenue streams are some of the essential data that generates an avenue for decision-making (Arnott, et al. 2017, p.66). Among the large retail organisations, the need for data has become evident in a competitive marketplace. Through BI, it provides the organisation access to important data via the use of application software and technologies for their data analysis and performance management process (Peters et al. 2016, 13). At the core of organisational operations is the adoption of efficient information management that leads to ease in the relay across the departments for decision-making. Simplistic presentation of useful data is essential at assisting the organisation in their decision-making process (Yeoh and Popovic 2016, p.144).  Basing the decision on accurate and relevant information provides a feasible source of gaining a competitive edge for retail businesses. Some organisations such as Wal-Mart have been adopting data warehouses since they provide a basis for the logical collection of information from different databases for the purpose of decision-making on pertinent issues.

            Further, the analysis of Wal-Mart and its competitors reveals the need to adopt an accurate and efficient BI system that deals with the potential technical constraints. Addressing issues such as security in user accessibility, data volumes and storage period, and benchmark targets ensure core competency at Wal-Mart and its competitors in the decision-making process (Kohtamaki 2017, p.78). Across the retail sector, it has become evident that the development of data tools to ease the marketing and customer management process serves as a source of competitive edge (Peters et al. 2016, p.14).  Among the popular tools for customer management and marketing are inclusive of Associative Query Logic (AQL), score carding and business process re-engineering (Nedelcu 2013, p.18). The dependence on the various tools has been focusing on transforming the performance mandate of the organisation.

            In organisations such as Bed Bath and Beyond, the development of BI tools that address the daily operations has become evident. One of the most effective operational policies in the management of organisational information has been the goal alignment strategic focus. As per the goal alignment policy, the organisation determines both the short and long-term needs of a BI programme. Without the establishment of a goal, the organisation cannot set up the way forward in the use of BI tools (Sauter 2014, p.132). At the foundation of BI, tool management is the crafting of programmes that can suit the business performance process. The present information gathering process in the retail businesses ought to assess, monitor, and summarize the essential sources of information for decision-making. Therefore, the BI adoption process for retail sector organisations has been based on covering the processes with an aim of sensing, interpreting, predicting, automating, and responding to organisational environments. The minimization of the reaction time for business decisions is via BI and its potential to revolutionize operations. Proposing an event-centric infrastructure for the retail businesses is outright through the use of applications that ensure real-time analytics across the business processes. Therefore, the applications that retail businesses adopt enable ease in the notification of potential changes and generating actionable recommendations that trigger efficiency in business operations. A data architecture that focuses on revolutionizing BI within the retail sector centres on efficiency in marketing and customer management process. 

Conclusion and Research Contribution

            The technological changes within the business environment have led to a shift in the operational process of the organisations. Increasingly, information has become a source of core competency among organisations. Therefore, the need for BI has become evident throughout the operational process of successful organisations. The need to undertake a comprehensive analysis of the relevant information across the business framework is essential to generate an enabling environment for decision-making. Enterprises at the present environment focus on building BI systems that support the diverse business decision-making processes to better comprehend their operations. Competing effectively across the changing marketplace depends on innovation in data management. Technological change in line with the need to progress successfully within the dynamic marketplace depends on BI tools. Therefore, the research on BI provides information that is necessary for all organisations in their future adoption of the tools. Collecting, assessing, and presenting data to inform the decision-making process should be at the core of the business operational policy. Viable and accurate information has the potential to transform the performance prospects of a business.

Reference

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Elbashir, M.Z., Collier, P.A. & Davern, M.J., 2014. Measuring the Effects of Business Intelligence Systems: The Relationship between Business Process and Organisational Performance. International Journal of Accounting Information Systems, 9(3), pp.135-153.

Kasemsap, K., 2015. The Role of Data Mining for Business Intelligence in Knowledge Management. In Integration of Data Mining in Business Intelligence Systems (pp. 12-33). IGI Global.

Kohtamäki, M. ed., 2017. Real-time Strategy and Business Intelligence: Digitizing Practices and Systems. Springer.

Nedelcu, B., 2013. Business Intelligence Systems. Database Systems Journal, 4(4), pp.12-20.

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Sauter, V.L., 2014. Decision Support Systems for Business Intelligence. John Wiley & Sons.

Trieu, V.H. and Burton-Jones, A., 2017. A Model of the Production of Representational Fidelity: Insights from the Business Intelligence Systems Context. In Academy of Management Proceedings (Vol. 2017, No. 1, p. 13316). Briarcliff Manor, NY 10510: Academy of Management.

Yeoh, W. and Popovič, A., 2016. Extending the Understanding of Critical Success Factors for Implementing Business Intelligence Systems. Journal of the Association for Information Science and Technology, 67(1), pp.134-147.