The paper "Analytics of Business Operations Management: River Island Clothing Company" is a perfect example of a business case study. The River Island Clothing Company is a United Kingdom (UK) Company whose area of operation includes designing clothes and accessories that it sells to the targeted customers. By approximation, the Company sells between 4,000 and 7,000 different accessories monthly, a projection that has helped it understand its marketing niche (Fosso et al. 2017). Recent studies have observed that the Company is rated one of the top-performing design companies due to its continued rebranding and market positioning when compared to its rival companies (Chambers 2014).
Currently, the Company is owned and managed by Lewis trust investment firm and sells its products mostly in Turkey, Ireland, UK, Singapore and Middle East markets. Additionally, River Island Clothing Company is a private company limited by shares capital which was incorporated in (1959). Theoretically, the internal factors for the River Island Clothing Company establish a framework the Company is using so as to determine its competitive advantage, an approach that has helped it dictate operations in the already competitive environment.
Currently, the main competitors of the Company include Sewport and Bridge and Stitch. The examination of its business operation management shows that River Island Clothing Company is dealing with its competitors by formulating frameworks that are geared towards maximizing profits when they apply different strategies in their areas of operations including production, research & development (R& D), total quality management (TQM) and human resources (HR) (Sharma et al. 2014). Identification of the Problem The broad topic of the study is the analytics of business operations management. This report is concerned with data analytics of River Island Clothing Company.
The report uses the Company’ s data to address the organizational approach to business operations, approach to competitiveness with regard to both the internal and external environment including economic, socio-cultural, political, technological and natural environmental conditions in the last 5 years (between 2010 and 2015). We recognise from preliminary data obtained about the company that it has moved from its traditional model of operation to embrace a modern approach in its operations and design of their products (Seddon et al.
2016). However, the Company’ s business analysis will put the finding above into context so as to understand different variables including areas of core competence, operations management, financial performances, future forecast and the extent to which its operations will align with its competitors or general demand in its areas of operations. According to Laursen and Thorlund (2016), business analysis acts as an integrated analysis of business operations so as to understand how companies are making attempts to remain competitive and how they balance their financial performance in the market. Based on this study, we pick the Company’ s financial data to understand among other variables, its financial positions, and competitiveness and future forecasts. Literature Review There are different authors who have presented their arguments regarding the analytics of business operations management.
According to Tremblay et al. (2016), this topic deals with the analysis of company’ s data with the aim of understanding objective assurance as well as independent process the company has designed to look at their financial operations, marketing environment and competitiveness in terms of market penetration. While Tremblay et al. (2016) findings try to understand the company’ s position with regard to its financial operations, there is consensus among other studies that business analytics is a broad concept that stretches beyond gathering data on financial performance.
Accordingly, recent studies look at this topic (analytics of business operations management) as a broad spectrum where researchers attempts to companies use to meet its objectives and systematic approaches such objectives steer the company’ s governance processes, risk management and marketing approaches (Qie et al. 2016; Tremblay et al. 2016). Based on Qie et al. (2016) research, data search from River Island Clothing Company focuses on its risk management and governance processes.
What these authors suggest when it comes to governance structure is those analytics of business operations management assess numeral values of companies that help them approach and determine their competitive advantage. Recent scholars have view attempted to separate the concepts of business analytics from business operations management (Asadi Someh et al. 2017; Qie et al. 2016; Tremblay et al. 2016). According to Asadi Someh et al. (2017), business analytics should be seen as a comparative discourse or analysis where actors attempt to define the financial positions of companies.
On the other hand, studies that have focused on business operations management uses business analytic data to understand socio-cultural, economic, political, technological and natural environment conditions of a given company. The understanding that these studies draw is that analytics of business operations management should be concerned with company’ s data that when analysed, will reveal among other parameters, pricing model, marketing audit to its brand, competitiveness with niche operators and product design.
Appelbaum, D., Kogan, A., Vasarhelyi, M. and Yan, Z., 2017. Impact of business analytics and enterprise systems on managerial accounting. International Journal of Accounting Information Systems, 25, pp.29-44.
Asadi Someh, I., Wixom, B., Davern, M. and Shanks, G., 2017, January. Enablers and Mechanisms: Practices for Achieving Synergy with Business Analytics. In Proceedings of the 50th Hawaii International Conference on System Sciences.
Chambers, D., 2014, April. ASOA Course: Business Analytics: Real-time Dashboards and Increasing Capacity. In The Annual ASCRS and ASOA Symposium and Congress. Ascrs.
Côrte-Real, N., Oliveira, T. and Ruivo, P., 2017. Assessing business value of Big Data Analytics in European firms. Journal of Business Research, 70, pp.379-390.
Fosso Wamba, S., Ngai, E.W., Riggins, F. and Akter, S., 2017. Guest editorial: transforming operations and production management using big data and business analytics: future research directions.
Kache, F., Kache, F., Seuring, S. and Seuring, S., 2017. Challenges and opportunities of digital information at the intersection of Big Data Analytics and supply chain management. International Journal of Operations & Production Management, 37(1), pp.10-36.
Laursen, G.H. and Thorlund, J., 2016. Business analytics for managers: Taking business intelligence beyond reporting. John Wiley & Sons.
Marjanovic, O. and Dinter, B., 2017, January. 25+ Years of Business Intelligence and Analytics Minitrack at HICSS: A Text Mining Analysis. In Proceedings of the 50th Hawaii International Conference on System Sciences.
Panigrahi, R., 2017. Incidence of Green Accounting on Competitiveness: Empirical Evidences from Mining and Quarrying Sector. In Business Analytics and Cyber Security Management in Organizations (pp. 270-278). IGI Global.
Qie, A., Fok, D. and Paap, R., 2016. Efficiency Analysis of Chinese Banks Master Thesis for Business Analytics And Quantitative Marketing.
Seddon, P.B., Constantinidis, D., Tamm, T. and Dod, H., 2016. How does business analytics contribute to business value?. Information Systems Journal.
Sharma, R., Mithas, S. and Kankanhalli, A., 2014. Transforming decision-making processes: a research agenda for understanding the impact of business analytics on organisations. European Journal of Information Systems, 23(4), pp.433-441.
Sorooshian, S., 2017. Structural Equation Modeling Algorithm and Its Application in Business Analytics. In Organizational Productivity and Performance Measurements Using Predictive Modeling and Analytics (pp. 17-39). IGI Global.
Tremblay, M.C., Deckard, G.J. and Klein, R., 2016. Health informatics and analytics–building a program to integrate business analytics across clinical and administrative disciplines. Journal of the American Medical Informatics Association, p.ocw055.
Wang, Y. and Byrd, T.A., 2017. Business Analytics-Enabled Decision Making Effectiveness through Knowledge Absorptive Capacity in Health Care.