1: Business Intelligence
This report outline meaning and definition of business intelligence and the way it helps firm to create competitive advantage and to make decisions.
Business Intelligence (BI)
BI is an emerging technique, which becomes widely popular among business due to its role in managing information. According to Isike et al., (2011), “BI can be defined as a system comprised of both technical and organizational elements that presents historical information to its users for analysis and enables effective decision making and management support, for the overall purpose of increasing organizational performance”. In this way, BI includes conversion of raw data into meaningful knowledge to facilitate decision making at the operational and strategic level of firm and to create financial benefits.
Currently, firms are used verity of sources to collect data, which develops big data. An insightful analysis of collected data is critical. For collecting and organizing data, firms uses BI as it provides required tool and techniques of data mining and analytics. The implementation and management of BI becomes one of the key priorities of the reputed global firms. In 1990s, the term BI became highly popular in the business world and IT sector. In BI, business analytics was started to consider highly important in 2000s (Chen et al., 2012).
Recently, big data is used to describe the technological application of analyzing large and complex data. These applications are enough advanced and capable to store, analyze and visualize the complex set of data quickly and easily (McAfee et al., 2012). In the study of Shollo & Kautz (2010), BI is defined as composition of processes, technologies and products as in this data collection and analysis processes are conducted through the implementation of range of technologies for producing knowledge or information (product) to facilitate decision making in businesses. This indicates that BI is a composition of these three elements.
In BI, technology play critical role as it provides businesses a means to organize and analyze data quickly. But, human capabilities to interpret and use the provided knowledge are an important factor that can make difference in the use of BI for gaining financial benefits. A firm’s failure to create relevancy of knowledge with strategies and operations is likely to create only cost burden (Vera-Baquero et al., 2013). Thus, the concept of BI becomes important for the contemporary business organization.
Business Intelligence (BI) for Competitive Advantage
BI is quite important tool for the contemporary organizations to create competency due to the increasing importance of knowledge in decision-making. BI enhances ability of firm to visualize the past and current data of different management fields such as production, sales, customer and others. This could be used by the firms to make fact-based decisions, which may help to create competitive advantage. For example: return on investment data may help a firm to determine underperforming products. Through this, firm can take informed decision, which may help to reduce cost and to improve profitability (Shehzad et al., 2013). With this, firm can make efficient use of resources, which leads to the creation of competitive advantage.
Similarly, innovativeness is the other important way of creating competitive advantage in contemporary organization. Through BI, firm can invent unique products or methods to satisfy the customers. It allows firms to analyze own strengths and weaknesses of the company to compare with the competitors. This understanding may help a firm to improve their processes that leads to the cost reduction and quality improvement (Stone and Woodcock, 2014). At the same time, innovations in offering can be introduced by an organization by analyzing trends, market conditions and customers’ preferences quickly. BI provides insights of market and consumers to a firm, which a firm can use to make informed improvement in the offerings and to improve customer satisfaction (Loshin, 2012). With this way, firm can remain innovative and consequently competitive in the market. Burberry, UK based luxury global firm has used BI successfully to become highly innovative and digitalized brand.
Along with this, cost advantage is also a major source of competitiveness as it has positive influence on the bottom line of a firm. BI provides real-time data to the organization regarding operational and strategic performance, which can be used by organization to eliminate sources of waste and to include quality aspects. For example: in healthcare firm, standardized data can be accessed by clinicians in secure manner that may improve accuracy and speed of providing treatment to the patient (Cokins et al., 2010). It may help to reduce operational cost and to improve service quality.
Similarly, BI can be used in healthcare to mange staffing problem without increasing cost and sacrificing quality. For example: In Unites States, healthcare firm have invested millions of dollars in the implementation of IT tools and techniques. ThedaCare, a healthcare organization has number of clinics and hospitals in US uses business analytics applications. Through this, managers get up-to-date information about the staff. It has allowed this organization to save around $850,000, which caused reduction in operational cost (Toussaint and Mannon, 2014).
Impact of Data Mining and Analytics on Decision making
Data mining and analytics are the important elements of BI. Retail industry becomes highly competitive and firms use loyalty cards to attract and attain customers. Wal-Mart, a US based retail firm can use data mining and analytics for making effective use of loyalty card to attract and retain customers. Through loyalty card, firm obtains big customers data that can be used to improve offerings. Data mining can be used by this firm to know customers’ taste and preferences in accordance to their age and other demogrpoahics factors. In data mining and analytics, customers’ information are accessed and presented in a visualize manner (Osei-Bryson and Barclay, 2015). Through this, Wal-Mart can determine purchasing behavior of certain customer group and to make better and faster decision regarding schemes and discounts.
Similarly, data mining and analytics can be useful for retailers to determine expected behaviors of customers for offerings and to tailor the offerings as per their needs. With this, relationship in customer data can be quantified to classify customers into different groups. It will help Wal-Mart to determine relation of customers with the offerings. This knowledge can be used by this firm to take more accurate decisions regarding the improvement in offerings (Raju et al., 2011). It may help firm to provide useful discounts and incentives to the customers and to increase value of loyalty card.
By using data mining and analytics, Wal-Mart and other retailers can segment their customers to determine the major source of revenue. This would be effective in recognizing the needs of most profitable customers segment and to make informed improvements in the loyalty card programs. It could allow Wal-Mart to provide right offer and discounts to the right customer base of the company (Verhoef et al., 2016). This may help to make innovative changes in the loyalty card and to encourage repeat purchase.
Along with this, personalization of offerings encourages customers to make repeat purchases, which can be achieved by data mining and analytics. Wal-Mart can identify communication needs of target market and to draft advertising and promotions accordingly. It would help this firm to encourage repeat purchase and to promote loyalty card (Watson, 2010). In this way, data mining and techniques can allow firms to make quick and more accurate decisions for improving value of loyalty card.
2: Queensland Health Systems Implementation
In this report, factors for information system implementation failure are discussed to inform the management about the potential risk. Queensland Health payroll system implementation failure is one of the major IT collapse and due to this; this case is analyzed to identify factors that may cause system implementation failure, while using Systems Development Lifecycle approach. At last some recommendations are also provided to ensure better management of identified system implementation deficiencies and project success.
Factors for System Implementation Failure
System implementation failure becomes an important concern for firm as it has considerable impact on the profitability and sustainability. System Development Life Cycle (SDLC) is an approach to plan, develop, test and deploy an information system within an organization. It provides systematic guidelines to develop and implement a system within organization successfully. The process of implementing information system can be categorized mainly in five phases such as planning, analysis, designing, testing, implementing and supporting (Marchewka, 2014). For using this approach successfully, it is critical for a firm to understand its each phase effectively. Below figures depicts the steps in SLDC:
On the basis of above figure, planning is the first and highly important step of SDLC as it has capability to influence the other steps of system implementation and their success in considerable manner. Lack of proper planning may cause failure in implementing and upgrading information system through SDLC approach (Rainer and Cegielski, 2011). Below are some factors those have contributed in causing planning and implementation failure of payroll system implementation project at Queensland Health (QH):
Lack of Clearly Defined Scope and Complexity: An effective use of SDLC approach requires clear explanation of scope and complexity of a project to ensure proper planning. It is critical to inform the objectives and deliverable of a project on which basis resources are allocated to the different departments and units. For the development of highly relevant scope and objectives, it is quite critical for firm to clearly identify the requirements of a business in terms of the implementation of a system (Eden and Sedera, 2014). Without acknowledgment of business requirements, it is difficult to bring accuracy and relevancy in objectives and scope that causes poor planning.
Similarly, improper identification and explanation of complexity fails a firm to determine the potential risks in a project and to make proper planning to handle them. In system implementation, some risks such as finance, human resource, technical and others can occur. Lack of planning can affect organization ability to manage risk and to ensure successful implementation of system (Ara and Al-Mudimigh, 2015). For example: IBM underestimated the importance of scope and complexity determination in the planning phase at QH that caused uncertain changes project implementation. It was responsible for cost overrun and project delay (Eden and Sedera, 2014).
Ambiguous Roles and Responsibilities: Planning phase of SDLC also includes delegation of roles and responsibilities for ensuring accomplishment of task within the time limit and defined quality. The absence of clearly defined roles and responsibilities of involved parties was one of the major factors that caused poor planning and system implementation failure in QH (Melton, 2011). For the implementation phase, roles and responsibilities of stakeholder were explained briefly, which causes relationship issues. In QH, unclear delegation of responsibilities caused communication issues, which contributed in the mismanagement of resources. It ultimately caused cost overrun and delay of project (Eden and Sedera, 2014).
Due to this, stakeholders were not clear about what and how to report performance that created accountability issues in the process of system implementation. Absence of accountability discourages stakeholders to perform their duties delicately, which causes failure in successful system implementation in an organization. In a project, it is critical for stakeholders to have acknowledgement regarding their tasks and duties in throughput the implementation (Luckey and Phillips, 2011). Through this, firm can ensure timely and cost effective execution of project.
Communication: It is a key element of project success as lack of communication in planning phase is likely to cause uncertainty in the other phases of SLDC. The planning phase of payroll system implementation project at QH was quite poor as QH, CropTech and IBM were different understanding about the objectives and scope. It was responsible for creating poor relationship between the client (QH) and consultant (IBM). QH appointed CropTech to handle the process of project implementation in QH and to communicate the consultant (Eden and Sedera, 2014). In this case, IBM needed to communicate both QH and IBM effectively, which caused miscommunication of goals, objectives and scope of a project.
The presence of two client organizations was mainly responsible to create miscommunication and consequently complexity. IBM planned to implement another product in QH that also contributed in increasing complexity. The complex relationship among the involved parties caused communication issues, which is one of the major cause of IS implementation. Effective communication among the involved party is critical to utilize the available resources optimally and to ensure project success. It ensures flow of right information to the right people at the right place that reduces complexity and improves relationship (Larson and Gray, 2011). It is because lack of communication caused Information system (IS) failure in QH.
Incompetent Governance: The other important factor for IS implementation failure in QH was lack of competent governance as it raised several issues such as biasness in tendering process, improper planning, conflicts, unaccountability and others, which ultimately caused failure. Competent governance is critical for project success as it ensures application of project management strategies at the different phases of project and better management of resources (Eden and Sedera, 2014). In QH, application of Gantt chart, work breakdown structure, stakeholder analysis and other project planning and management tools were avoided that raises issue of improper planning and clearly defined deliverables with timelines (Stair & Reynolds, 2013). It caused poor control over the resources throughout the implementation that resulted cost and time overruns.
Similarly, governance plays significant role in controlling the use of power of involved stakeholder throughout the process of system implementation. Due to ineffective governance at QH, biasness occurred in the tendering process that hindered the selection of right prime conductors for the project implementation. CorpTech was responsible for providing same information to the all applicants and remaining neutral. But, the project director took side of IBM that caused biasness (Romney et al., 2012). The sense of accountability was also not present among the involved people that contributed in delaying the system implementation and creating huge additional cost for QH.
Political and legal System: Planning phase of SLDC includes analysis of risk that can affect system implementation project and to make strategies. Political and legal risks were completely ignored in planning of system implementation at QH, which caused delay and cost overrun issues. QH is a government undertaking that comprises several layers of bureaucracy that reduced transparency in system implementation process and affected decision-making and accountability. Due to this, delay in execution of project activities became more apparent that increased project cost. (Eden and Sedera, 2014) The complexity of legal system caused complexity, which affected quality of management in this project.
The above are five major system development issues, which caused implementation failure in QH. The planning phase of this project was quite weak in terms of analyzing business requirements and complexity. It failed stakeholders to determine potential risk and to ensure better management.
Below are some recommendations to manage factors for IS implementation failure in an organization and to create benefits:
Adequate definition of requirements: A firm should clearly define the requirements of business to prevent the occurrence of several issues in the system implementation. Organization’s failure in documenting requirements properly may create difficulties for consultant to make robust plan for system implementation. Undefined business requirements have negative impact on the different phases of system development. By analyzing and documenting the business requirements properly, firm can limit the occurrence several functional and technical issues in the process of implementing IS system (Aikins, 2012). It could ensure flawless execution of defined project activities and to limit the issues of overrun of time and cost.
Rigorous implementation of project management methodologies and strategies: It is one of the important ways to ensure informed and timely utilization of available resources. Several project management tools such as Work Breakdown, critical path analysis, gap analysis, action plan, Gantt chart, PERT chart and others could be used by a firm to plan resource allocation and to manage schedule more systematically (Kerzner, 2010). These tools visualize each stakeholder about the process of project implementation, which would be effective to win stakeholder support and to handle the changes effectively. In absence of project management strategy, it would be difficult to implement a project in an organized manner that may increase complexity and delay (Newton, 2013). Project delay ultimately leads to the poor resource utilization that causes cost overrun issue.
Information and Communications Technology (ICT) Audit: An effective communication leads better management and consequently project success. Several communication technologies are used by a project’s stakeholders. The audit of ICT infrastructure and system would be useful for a firm to limit the communication breakdown throughout the process of project management from planning to implementation and closure. It will include assessment of communication tools and processors as well as competency of managerial personals (Beynon-Davies, 2013). Additionally, ICT audit could be an effective mean to ensure application of project methodology and reporting framework. This could be useful to encourage client and consultant organizations to fulfill their responsibilities towards each other and different stakeholders. It would improve communication among stakeholders, which may reduce conflicts and to improve project implementation phase (Eden and Sedera, 2014).
Competent Governance: The establishment of competent governance is critical for implementing IS system successfully in an organization. Firm should focus on establishing a govenmence framework to ensure inclusion of competent personnel and to provide them power for conducting investigation and reporting results to the higher authorities. Due to lack of robust governance, the occurrence of biasness and unaccountability issues becomes more apparent, which causes delay and cost overrun (Kooper et al., 2011). By implementing a govenmence framework, a firm can clearly explain roles and responsibilities and to make them more accountable for their performance. It would be effective to encourage them to take responsibilities and to accomplish and report them properly (Schwalbe, 2010). This could be useful to implement the activities within stated budgeted and timeline.
It can be concluded from the above discussion that an investigation over the previous IS implementation can provide management an ample information and guidelines for limiting the failure. QH case provides an analysis of system implementation failure, which can be used to avoid possible risks and to ensure completion of project within the budgeted time and cost.
Aikins, S. K. (Ed.). (2012). Managing E-Government Projects: Concepts, Issues, and Best Practices: Concepts, Issues, and Best Practices. UK: IGI Global.
Beynon-Davies, P. (2013). Business information systems. Palgrave Macmillan.
Chen, H., Chiang, R. H., & Storey, V. C. (2012). Business Intelligence and Analytics: From Big Data to Big Impact. MIS quarterly, 36(4), 1165-1188.
Cokins, G., Schubert, K. D., Hugos, M. H., Betancourt, R., Farrell, A., Flemming, B., & Hujsak, J. (2010). CIO best practices: Enabling strategic value with information technology (Vol. 34). USA: John Wiley & Sons.
Eden, R., & Sedera, D. (2014). The largest admitted IT project failure in the Southern Hemisphere: A teaching case. In Proceedings of the 35th International Conference on Information Systems: Building a Better World Through Information Systems. AISeL.
Isik, O., Jones, M.C. and Sidorova, A., 2011. Business intelligence (BI) success and the role of BI capabilities. Intelligent systems in accounting, finance and management, 18(4), pp.161-176.
Kerzner, H.R. (2010). Project Management - Best Practices: Achieving Global Excellence. 2nd edn. USA: John Wiley & Sons.
Kooper, M. N., Maes, R., & Lindgreen, E. R. (2011). On the governance of information: Introducing a new concept of governance to support the management of information. International Journal of Information Management, 31(3), 195-200.
Larson, E. W. and Gray, C. F. (2011). Project Management: The Managerial Process. New York: McGraw-Hill Professional.
Loshin, D. (2012). Business intelligence: the savvy manager's guide. Newnes.
Luckey, T. and Phillips, J. (2011). Software Project Management For Dummies. USA: John Wiley & Sons.
Marchewka, J. T. (2014). Information technology project management. USA: John Wiley & Sons.
McAfee, A., Brynjolfsson, E., Davenport, T. H., Patil, D. J., & Barton, D. (2012). Big data. The management revolution. Harvard Bus Rev, 90(10), 61-67.
Melton, T. (2011). Project Management Toolkit: The Basics for Project Success: Expert Skills for Success in Engineering, Technical, Process Industry and Corporate Projects. 2nd edn. USA: Butterworth-Heinemann.
Newton, R. (2013). The Project Management Book ePub eBook. Pearson UK.
Osei-Bryson, K. M., & Barclay, C. (Eds.). (2015). Knowledge Discovery Process and Methods to Enhance Organizational Performance. Australia: CRC Press.
Rainer, R. K., & Cegielski, C. G. (2011). Introduction to information system: Enabling and transforming business. New York: John Wiley & Sones.
Raju, J. J., Zhang, Z. J., Sorensen, H., DeHerder, R., & Blatt, D. (2011).Strategies for Success in Retail (Collection). USA: Pearson Education.
Romney, M., Steinbart, P., Mula, J., McNamara, R., & Tonkin, T. (2012).Accounting Information Systems Australasian Edition. Australia: Pearson Higher Education AU.
Schwalbe, K. (2010). Information Technology Project Management. 6th edn. USA: Cengage Learning.
Shehzad, R., Khan, M. N., & Naeem, M. (2013). Integrating knowledge management with business intelligence processes for enhanced organizational learning. International Journal of Software Engineering and Its Applications, 7(2), 83-91.
Shollo, A., & Kautz, K. (2010, December). Towards an understanding of business intelligence. In Australasian Conference on Information Systems.
Stair, R., & Reynolds, G. (2013). Principles of information systems. USA: Cengage Learning.
Stone, M. D., & Woodcock, N. D. (2014). Interactive, direct and digital marketing: A future that depends on better use of business intelligence.Journal of Research in Interactive Marketing, 8(1), 4-17.
Toussaint, J.S. and Mannon, M. (2014) Hospitals Are Finally Starting to Put Real-Time Data to Use. [Online]. Available at: [Accessed: 2nd September, 2016].
Vera-Baquero, A., Colomo-Palacios, R., & Molloy, O. (2013). Business process analytics using a big data approach. IT Professional, 15(6), 29-35.
Verhoef, P. C., Kooge, E., & Walk, N. (2016). Creating Value with Big Data Analytics: Making Smarter Marketing Decisions. UK: Routledge.
Watson, R. (2010). Future files: a brief history of the next 50 years. USA: Nicholas Brealey Publishing.