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Business Analytics Assignment: Efficiency of Analytics in Tesco's Performance Improvement

Question

Task: Tesco is a multi-national retailer with 360000 staff and 5000 stores. Write a report giving examples of how analytics is implemented to improve its performance. You should draw on class materials and discussion as well as the current academic and wider literature. Note that you can write hypothetically if you cannot find information but you must give reasons behind any statements you make.

Your business analytics assignment should answer the following questions:
• What would you expect the analytics function to look like in Tesco? What different analytics staff would you expect them to employ? What software might they use and why?
• Thinking about the functions that Tesco is involved in, what data do you think they might collect or generate and what issues might they need to overcome?
• Discuss three examples of where analytics have been used by Tesco. You should include how the data was sourced, what benefits were gained and any obstacles that were encountered in your discussion.
• What ethical issues do Tesco need to consider with reference to analytics?

Answer

1. Introduction
It is evident herein business analytics assignmentthat the modern technology-oriented business world depends mainly upon data-driven decision-making processes. Analytics provides the opportunity to evaluate the statistical, quantitative, and exploratory data analysis using predictive models to drive actions and decisions (Choi, Wallace, & Wang, 2018). The forthcoming report will evaluate the efficiency of analytics in Tesco's performance improvement. The specific analytics functions will be proposed for Tesco, and the process through which staff in the company can manage the analytics functions using software will also be discussed. The issues in the data collection and generation process will be specified, and the critical data the company must collect depending upon the functions will also be addressed. However, examples will be provided where the analytics have been utilised by the company. The particular ethical considerations will be recommended for Tesco's analytics process.

2. The proposed analytics functions for Tesco
Tesco, the multi-national merchandise and groceries retailer, serves its customers across the world. The company, in the new age of emerging technology, has incorporated sensor-based technologies, Clubcard information for collecting cookies, and Oracle and SAP for its enterprise system. For analysing a large set of consumer information, the company can use statistical techniques and create reports for data analysis. The valuable function of analytics will help the company manage vital information related to its business operations, employee details, and customer data. To keep its supermarket chain active across various countries, Tesco can use the databases of a specific regional market and depend upon that. The company can understand the demands of the consumers of that particular segment. Aiming at the behavioural aspects and choices of people in different geographies, the company needs to improve and locate new opportunities in the analytics process. The data collection process is significant in managing information analysis (Choi, Jeon, & Kim, 2019). The company can acquire data from both primary and secondary sources for maintaining proper data systems and understanding the current market trends.

Identification of the trends and patterns in the complex dataset, such as system data of the company, will help to analyse the specific data related to operational processes in the retail sector, which will help to manage the performance of the company's existing operations. Moreover, filtering and cleaning the data is also required for systematically controlling the large set of consumer data. Tracking the history of data needs to be incorporated into a filtering process. The function of analytics is to prioritise business needs (Mikalef et al. 2019). The company can prioritise the information needs through which it can manage the business requirements. The different functions of the analytics will help the company to analyse the multiple data sources and propose possible solutions for managing problems in strategic planning. Data-driven decision-making can help to gain insight into business problems, and Tesco will be able to utilise specific solutions for customer and employee satisfaction which will eventually improve the performance of the company.

The company can use a big data analytics process for evaluating the large set of information acquired through retailing in different regions of the world. The company's customer data history management is complex as the large consumer base has created an overload of information. The big data analytics process ensures proper data management and analysis (Fosso Wamba, 2017). For statistical analysis of information, the company can use machine-learning methods, which will employ algorithms for data analysis. The machine learning techniques can assure business information management through the different solution implementations (Kumar, Boehm, & Yang, 2017). Using this technique, Tesco's data management process will be flexible. However, the company can use a Regression analysis technique for managing the historical data of the consumers, employees, and business. In the retail sector, the Regression analysis process helps to understand the product quality, consumer service, store design, sales channels, and marketing campaigns, and the overall result. Tesco can use the analytics technique for managing data. MongoDB is a software that provides facilities such as indexing and questing on a cross-platform and helps to improve business performance. The geographical distribution of the database of Tesco can be managed by using the software tool. Google Analytics 360 is another software that provides analytics on investment and returns. For Tesco's marketing data analysis, Google Analytics 360 can help to ensure the ROI.

3. The type of data Tesco needs to collect and the issues in the company's data collection.
Tesco's usage of analytics function for cutting down the heat and light cost requires data regarding the electricity supply and use in different stores (Tyagi, 2020). The regular update ofenergy performance and the hourly temperature rate-related data are also required for controlling the heating and lighting costs in its different stores. The process can be challenging to manage as the various stores need to be observed and monitored. The initiative of Tesco to save cost and energy is a sustainable approach that may face budgetary constraints too. For anticipating sales, the company uses data analytics to evaluate customer data. Through understanding the sales rate around a week, the company evaluates the demand of customers, where utilising the clustering methods, the company tracks the product purchasing habits. The functions of analytics require data of the weekly sales, customer procurement, and the number of customer visits to the stores. However, during the process, the company may face issues understanding the number of remaining stock and the number of items going to the waste items. The consistency in acquiring data that will represent a clear consideration of the nature of consumer behaviour is difficult to manage. The large set of data requires specific techniques to be managed. Big data is helpful in managing a large set of information (Saggi & Jain, 2018).

The functions of data analytics in Tesco helps in the data-driven decision-making process, which provides efficiency in managing the value chain. The company has to collect the information related to multiple channel strategy where the demands of the users, the physical stores, the consumer retailing behaviour, and the product order details need to be collected. However, the data regarding the purchasing patterns, mode of delivery, and logistics requirements are also required for the data-driven decision-making process. Cutting the cost down and maintaining environmental influences are crucial as the company needs to be proficient in managing logistics and circulation services. Using a Clubcard information process, the company has to collect data about purchases and the online behaviour of customers, which helps to improve communication. In this case, security is a significant concern. Data collection through online or internet sources leads to possible threats of data breaching (Sinha, Rai, & Bhushan, 2019). Tesco needs to manage the security of information while data analytics function operation processes which will help to develop a proper data analytics process.

The company uses data analytics to anticipate future trends. The monitoring of current trends and demands provides an idea regarding future trends. The analytics function in Tesco ensures proper data collection and usage for understanding the future trends in retail marketing. For that purpose, the company needs to collect data regarding the global networking stores, most advantageous products in the present market, technology trends, and the changing consumer demands. The data provides valuable ideas regarding future trends, but it has to denounce its evolving business model. Prediction can lead to a misconception that may incur a loss. Tesco requires the challenge of operating a proper data monitoring process.

4. Examples where Tesco used Analytics
Tesco used analytics for customer behaviour analysis. The Clubcard data helps to track the shopping habits of the customers, which provides an understanding regarding the changing behaviours (Hammett, 2018). The usage of data analytics helps to convince shoppers to eat healthily. Through a data analysis process, Tesco influences the choices of its customers, which ensures the healthy habit of eating among the customers. Inspiring towards the more beneficial decision not only helps to change the preferences of consumers but also develops an emotional bond between Tesco and its customers, which gains the confidence of the customers worldwide. The Clubcard data consists of information related to the consumer approach towards supermarkets, their health needs and nutritional habits, and the families concerned for their children's health. The company also collects data related to the rising concerns of obesity in childhood for unhealthy consumption. The data helps the company to formulate a health score for the baskets which it holds to the customers (Hammett, 2018). The strategy of data analytics provides practical support to retain consumer satisfaction in Tesco. However, the data analytics process has various benefits to the company and its customers. It develops a healthy food habit within the customers, which helps Tesco to become favourable among its competitors' market. Tesco, using the technique, can rebuild the trust of consumers (Hammett, 2018).

Big data analytics is used widely in business for analysing the data for market growth and consumer satisfaction (Ardito et al. 2019). Tesco uses a big data analytics process for cutting down the heat and light costs (Tyagi, 2020). Through using big data technology, the company acquires information related to the electricity supply, hourly units, and regular charges of electricity in its different sources. The approach of Tesco is sustainable, where it aims to save cost and energy. For that purpose, Tesco acquires the information through Google Map, which figures out the energy performance in the running store and helps provide specific data to the company regarding the overheating or under heating of the stores (Tyagi, 2020). Through evaluating the data regarding the charges of electricity in different stores and the hourly temperature for energy performance, the company controls the heating and lighting costs. It benefits the company to drive a sustainable approach. However, while implementing the solution, the company faced difficulties monitoring the data of each store and evaluating a large amount of data.

Data-driven decision-making in the data analytics process helps to improve business operations (Ferraris et al. 2019). Tesco, for sales estimation, uses a data analytics process for understanding consumer behaviour (Tyagi, 2020). The customer perception towards the products of the company is observed during sales. The data regarding the weekly sales benefits, number of customers who purchased products, number of customers who visited the stores, and the interest zone of the customers are acquired through the data modelling process. Observation and monitoring of customers' behaviour while sales help the company to understand a preferable zone of the customers, which helps to understand the present market demand. The company uses a clustering method for analysing the behavioural aspect of customers, and the collected database significantly provides support to the company's sales projection process (Tyagi, 2020). The company uses various data points while collecting the information. The significant challenge for the company is to acquire the information during online sales. As the internet data acquisition process has a substantial threat of data breaching, the company needs to be secure while collecting data through online systems.

5. Ethical Considerations in data analytics process of Tesco
Information of the customers and employees requires proper privacy and security. While using internet sources for data analytics processes, the company needs to be aware of the underlying threats in data security. The data management process in the modern technology-oriented world brings various challenges to data security (Ghasemaghaei, 2020). Cybersecurity management of the information is essential while data is sourced from various internet sites and shopping zones. Lack of transparency in the process of data collection and analysis can lead to significant ethical concerns. Tesco needs to clarify the process of data analytics to its customers, employees, and other members so that transparency in the process of data collection can be maintained. Consent of the customers is a must while managing and using their data for the company's benefit. While performing the data analysis process, the breaching of the privacy of the customers can create significant ethical issues for the company. Privacy of the consumer data requires to be maintained (Martin, Borah, & Palmatier, 2017). The basic details and transaction details should be kept confidential. With this respect, the company needs to ensure authentic protocols. Data sharing processes can generate ethical problems because the access of any unauthorised party in the network can create a significant risk of data theft. The company requires it to be more cautious while sharing its information with any authority to strengthen network security.

6. Conclusion
The report depicted the data analytics process, its benefits, and the possible challenges concerning the retail company Tesco's application of the data analytics process in its business operation for understanding the customer behaviour and retaining its performance in the global market. The data-driven decision-making process ensures the proper operations in Tesco. The proposed analytics functions can be used by the company to improve its operational efficiency, which will help to increase consumer satisfaction. Software such as Google Analytics 360 and MongoDB can help the company perform data analytics processes more effectively. However, the issues related to the data collection process can also be mitigated through the proposed data analytics functions. The company incorporates big data technology where the security of data is a concern. Therefore, Tesco needs to strengthen its data ethics for improving performance.

References
Ardito, L., Scuotto, V., Del Giudice, M., & Petruzzelli, A. (2019).

A bibliometric analysis of research on Big Data analytics for business and management. Management Decision, 57(8), 1993-2009. https://doi.org/10.1108/md-07-2018-0754 Choi, J., Jeon, D., & Kim, B. (2019). Privacy and personal data collection with information externalities. Journal Of Public Economics, 173, 113-124. https://doi.org/10.1016/j.jpubeco.2019.02.001

Choi, T., Wallace, S., & Wang, Y. (2018). Big Data Analytics in Operations Management. Production And Operations Management, 27(10), 1868-1883. https://doi.org/10.1111/poms.12838

Ferraris, A., Mazzoleni, A., Devalle, A., & Couturier, J. (2019). Big data analytics capabilities and knowledge management: impact on firm performance. Management Decision, 57(8), 1923-1936. https://doi.org/10.1108/md-07-2018-0825 Fosso Wamba, P. (2017). Big data analytics and business process innovation. Business Process Management Journal, 23(3), 470-476. https://doi.org/10.1108/bpmj-02-2017-0046

Ghasemaghaei, M. (2020). The role of positive and negative valence factors on the impact of bigness of data on big data analytics usage. Business analytics assignmentInternational Journal Of Information Management, 50, 395-404. https://doi.org/10.1016/j.ijinfomgt.2018.12.011

Hammett, E. (2018). How Tesco is using data to help people eat healthier. Marketing Week. Retrieved 27 August 2021, from https://www.marketingweek.com/tesco-clubcard-data-to-help-people-eat-healthier/.

Kumar, A., Boehm, M., & Yang, J. (2017). Data Management in Machine Learning. Proceedings Of The 2017 ACM International Conference On Management Of Data. https://doi.org/10.1145/3035918.3054775

Martin, K., Borah, A., & Palmatier, R. (2017). Data Privacy: Effects on Customer and Firm Performance. Journal Of Marketing, 81(1), 36-58. https://doi.org/10.1509/jm.15.0497

Mikalef, P., Boura, M., Lekakos, G., & Krogstie, J. (2019). Big data analytics and firm performance: Findings from a mixed-method approach. Journal Of Business Research, 98, 261-276. https://doi.org/10.1016/j.jbusres.2019.01.044 Saggi, M., & Jain, S. (2018). A survey towards integration of big data analytics to big insights for value-creation. Information Processing & Management, 54(5), 758-790. https://doi.org/10.1016/j.ipm.2018.01.010

Sinha, P., Rai, A., & Bhushan, B. (2019). Information Security threats and attacks with conceivable counteraction. 2019 2Nd International Conference On Intelligent Computing, Instrumentation And Control Technologies (ICICICT). https://doi.org/10.1109/icicict46008.2019.8993384

Tyagi, N. (2020). 5 ways Tesco uses Big data Analytics | Analytics Steps. Analyticssteps.com. Retrieved 27 August 2021, from https://www.analyticssteps.com/blogs/5-ways-tesco-uses-big-data-analytics.

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