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Background of The Business Organization

This report depicts the importance of implementation of Business Intelligence solution and Data Analytics solution in a business organization. Both the functional and operational excellence of a business organization gets enhanced after the adoption this kind of business solution. For this particular report the selected organization is John Lewis Partnership. From wide research of the business industry it has been defined that, in order to engage consumers to the company it is very much necessary to apply proper tools and technologies (Williams, Ferdinand & Croft, 2014). After representing the background of the company, a critical appraisal of project management and planning needed to be implemented by the organization to gain competitive advantages from the competitive market.

Different managerial tools and technologies are there those are generally used by the business industries to gain competitive advantages and measurable revenue as well. However, the data management capability of John Lewis Partnership is not enough efficient. Thus, in order to manage data properly without any error it is necessary to implement big data technology and data analytics as a managerial tool. The advantages and disadvantages of big data tool and the way through which the operational and functional excellence of big data and data analytics can improve the existing situation of the company is also elaborated n this report. Not only this but also, the potential business values and even the organizational key challenges could overcome with the help of big data analytics tool and data analytics tool.  

For understanding the role of big data and data analytics tool, the selected business organization is named as John Lewis Partnership. From the background research of the company, the details are identified. It implies that, John Lewis Partnership PLC a British company based Retail Company which operates John Lewis department stores, in waitrose supermarket (Assunçao et al., 2015). This retail company is localized in Oxford Street, London in the year of 1929. Behalf of its owners and partners as well the company generally operates by Trust. The annual and financial turnover of the company is quite high and keeps on increasing every year. The products served by the company include clothing, watches, jewelleries, furniture, bedding, food. Computing and photography services as well. The revenue of the company is calculated to be 11 Billion in the year of 2015. In the year of 2012 and 2013 the net income of the retail company is measured as 409.6 Million. The total numbers of employees working for the company is 88,900. However, due to good service and productivity the number of consumers of the company is keep on increasing and in order to manage the details information about the employees and consumers the traditional data management techniques stood less efficient (Fan & Bifet, 2013). In order to increase the efficiency for managing the business operational data and other confidential information, implementation of big data tools and data analytics tool is very much important. With the help of these tools the managerial level issues will get minimized.

Critical appraisal of project management and planning required implementing and deploying by John Lewis Partnership

Big data analytics tool can help the business organizations to increase the existing situation of the business organization.  Most of the companies are currently adopting big data trending practice tool for enhancing their operation and functional excellence. After getting proper information about the landscape then only an organization should jump their operation from the existing one to the big data analytics (Diamantoulakis, Kapinas & Karagiannidis, 2015). This analytical process helps to gain competitive advantages and new revenue with improved operational efficiency over the business rivals of John Lewis Partnership PLC. Different types of analytical tools are there such as descriptive analytics, perspective analytics etc. With the help of descriptive analytics the performance of the organizations including the performance served by every individual employees as well historical data and  the root causes for different operational and  functional  issues can also be identified with the help if the big data tool.  

Whereas, with the help of perspectives analytics anticipate entrepreneurial opportunities can be developed and eve the business owners of John Lewis Partnership PLC will be able to take effective decision to gain measurable success and competitive advantages from the marketplace (George, Haas & Pentland, 2014). Improper data management might affect the profit of areas and like targeting market campaigns by reducing the consumer churn and avoidance of equipment failure. The demands for advanced analytics application have completely limited the bi data applications. However massive volume of data could be managed well with the help of big data toll within a big data platform.

Figure 1: market revenue of John Lewis Partnership

(Source: Johnlewispartnership, 2017)

After analyzing the current environment of John Lewis Partnership PLC it is found that in order to scale up the business efficiency the data should be managed well both in terms of access and entry (Chen & Zhang, 2014). Again, security is another important aspect that is served by big data analytics tool. In order to store information regarding the employees and consumers big data provides framework, for utilizing the mining technique for analyzing the data, patter discovery and analytical model proposal for recognizing the performance of John Lewis Partnership PLC in terms of operational application and business process (Williams,. Ferdinand & Croft, 2014). Currently in every industry for decision making and managing large set of data, big data analytical tools are widely used. Within the geographic region, massive amount of shipping delivery data, traffic data streaming and vendor performance data could be analyzed well with the help of big data tool (Wamba et al., 2015). Even wider variety of data types such as structured data, semi structured data, and unstructured data can be ingested with big data tool.  

Error identification: The operational and functional issues occurring in John Lewis Partnership PLC can be known instantly with the help of big data analytics. From the real time insight into the errors helps John Lewis Partnership PLC to react fast for mitigating the effect of the operational problems (Schoenherr & Speier?Pero, 2015). It will help the organization to avoid major hardware, software or even functional failure that might reduce the number of consumers.

Implementation of Big Data And Data Analytics Solution

New strategy development: In order to reduce the rate of errors and number of consumer’s reduction it is very much necessary to notice the competition level immediately. With the help of big data analytics John Lewis Partnership PLC can stay one step ahead the competition level (Provost & Fawcett, 2013). With the changing business strategies it will be able to grab new customer and also able to engage the old consumers.

Fraud detection: Intra organizational and inter organizational frauds can be detected when it will took place.  Through proper measurement the damage can be limited. Big data can generate real time safeguard system for those who are suffering from data hijacking. As John Lewis Partnership PLC has been following traditional manual data management system and the company has just currently implemented the new advanced data managerial technology thus they fails to maintain every security aspects (Kim, Trimi & Chung, 2014). In order to detect both the internal and external error big data toll is very much helpful.  

Cost saving: Though implementation of real time big data analytics tool is expensive but still, it eventually helps to save money, for the business leaders there is no such waiting time but it helps to reduce the work burden, from the company’s IT application (Halperin et al., 2014).

Understanding of the consumer’s trend: The big data analytics help to understand the competitive offerings and promotion for the consumers and also helps to identify the current consumer trend.  Proper decision could be undertaken with the help of big data analytical tool.

Big noise: In most of the time big data hold s big noise. It means that due to presence of huge amount of unwanted data points disorder might occur (George, Haas & Pentland, 2014). In order to mitigate this issue, the employees of John Lewis Partnership PLC are required to work hard separating the unwanted data points and required data points.

Privacy error: Security or privacy is another factor that affects the server where the employee’s information is stored. Due to lack of security, the network and data storage might be hijacked or misused by the external attackers.

Lower security: Due to lower level of security, the on house data warehouse of John Lewis Partnership PLC can be accessed by the external attackers easily (Halperin  et al., 2014).

For successful implementation of big data analytics in the operation of John Lewis Partnership PLC, the necessary steps those should be followed by the data analysts are as follows:

  1. The data analyst should work with executives, data owners to create data management strategies considering the process requirement and operational goal of John Lewis Partnership PLC (Williams, Ferdinand & Croft, 2014).
  2. To support and co ordinate with all the data analyst
  3. To perform data analysis and facility for delivering all the end users
  4. To supervise the issues of the clients to facilitate data deliverable (Provost & Fawcett, 2013)
  5. To monitor and organize all the clients feedback to provide the metrics of the company  

Conclusion and Recommendation

Conclusion

From the overall discussion it can be concluded that implementation of big data and data analytics is very much helpful for any business organization to increase the management efficiency of the business organization. John Lewis Partnership PLC should also utilize these tools and technologies for enhancing their operational ability. With the application of newly invented technologies like social media and mobile devices the actionable data keep on generating continuously. For providing improved consumers experiences John Lewis Partnership PLC is required to harness the confidential information. In order to optimize the supply chain oriented issues and for managing the sales price it is necessary for the company to have the ability of use purchase an inventory data accurately. The continuously rising competitive bar is the main reason for which the company is required to use proper tool and technologies. The benefits and disadvantages of big data and data analytics tools are elaborated in this report and from overall analysis it is defined that, different challenges are associated to John Lewis Partnership PLC. In order to gain competitive advantages and measurable revenue from the market it is necessary to implement big data and data analytics tool.  After analyzing the operational tools and technologies of John Lewis Partnership PLC, the data analyst of the company has implemented big data tool in their business organization. Though, different benefits are associated to big data tool but still certain disadvantages are might rise with this approach. In order to mitigate these risks it is necessary to identify certain risk management processes.  The recommendations for the system are elaborated in the below section.

Benefits of Business Intelligence

In order to resolve the issues associated to big data told t is necessary to follow the recommendations instructed below:

Start up with consumer centric outcome: The Company is required to frame their business in such a way so that the service and productivity could meet the requirement of the consumers with perfection. The means starting of analytics strategy with customer analytics provides the consumers a much better service for better consumer retention.

Technical expert: In order to implement the big data tool in the business organization it is very much necessary to hire technical experts I the business organization. By hiring the technical experts in the organizations it can be expected that the business will be able to serve desired outcome to the consumers.

Strategy development: Both the operational and functional business strategies are needed to be adopted by the business organizations so that it can bit the operational excellence of other organizations.  In order to implement proper strategy he business owners should identify the business priorities and based on those priorities strategies are needed to be deployed by the business organization.

Development of business case: Proper business cases are needed to be developed by the management authority so that the expected business outcome of the organization can be measured by the company owners.

References

Assunçao, M. D., Calheiros, R. N., Bianchi, S., Netto, M. A., & Buyya, R. (2015). Big Data computing and clouds: Trends and future directions. Journal of Parallel and Distributed Computing, 79, 3-15.

Chen, C. P., & Zhang, C. Y. (2014). Data-intensive applications, challenges, techniques and technologies: A survey on Big Data. Information Sciences, 275, 314-347.

Demirkan, H., & Delen, D. (2013). Leveraging the capabilities of service-oriented decision support systems: Putting analytics and big data in cloud. Decision Support Systems, 55(1), 412-421.

Diamantoulakis, P. D., Kapinas, V. M., & Karagiannidis, G. K. (2015). Big data analytics for dynamic energy management in smart grids. Big Data Research, 2(3), 94-101.

Fan, W., & Bifet, A. (2013). Mining big data: current status, and forecast to the future. ACM sIGKDD Explorations Newsletter, 14(2), 1-5.

George, G., Haas, M. R., & Pentland, A. (2014). Big data and management. Academy of Management Journal, 57(2), 321-326.

Halperin, D., Teixeira de Almeida, V., Choo, L. L., Chu, S., Koutris, P., Moritz, D., ... & Xu, S. (2014, June). Demonstration of the Myria big data management service. In Proceedings of the 2014 ACM SIGMOD international conference on Management of data (pp. 881-884). ACM.

Hashem, I. A. T., Yaqoob, I., Anuar, N. B., Mokhtar, S., Gani, A., & Khan, S. U. (2015). The rise of “big data” on cloud computing: Review and open research issues. Information Systems, 47, 98-115.

Hu, H., Wen, Y., Chua, T. S., & Li, X. (2014). Toward scalable systems for big data analytics: A technology tutorial. IEEE access, 2, 652-687.

johnlewispartnership (2017). john lewis partnership. [online] john lewis partnership. Available at: https://www.johnlewispartnership.co.uk/ [Accessed 10 Sep. 2017].

Kim, G. H., Trimi, S., & Chung, J. H. (2014). Big-data applications in the government sector. Communications of the ACM, 57(3), 78-85.

Merelli, I., Pérez-Sánchez, H., Gesing, S., & D’Agostino, D. (2014). Managing, analysing, and integrating big data in medical bioinformatics: open problems and future perspectives. BioMed research international, 2014.

Provost, F., & Fawcett, T. (2013). Data science and its relationship to big data and data-driven decision making. Big Data, 1(1), 51-59.Sagiroglu, S., & Sinanc, D. (2013, May). Big data: A review. In Collaboration Technologies and Systems (CTS), 2013 International Conference on (pp. 42-47). IEEE.

Schoenherr, T., & Speier?Pero, C. (2015). Data science, predictive analytics, and big data in supply chain management: Current state and future potential. Journal of Business Logistics, 36(1), 120-132.

Wamba, S. F., Akter, S., Edwards, A., Chopin, G., & Gnanzou, D. (2015). How ‘big data’can make big impact: Findings from a systematic review and a longitudinal case study. International Journal of Production Economics, 165, 234-246.

Williams, N., P. Ferdinand, N., & Croft, R. (2014). Project management maturity in the age of big data. International Journal of Managing Projects in Business, 7(2), 311-317.

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