Tesco Big Data Case Study: Implementing BDA

Question

Task:
Objective
In this assessment you will have to research a small case study and you will need to apply your knowledge to identify the main issues, prioritise, provide insights and to discuss alternatives. You must write a Case Study Report about your company discussing the strategic plan of an organization. To present a case study based on the selected organization’s current analytics strategy and your recommended strategy. Identify a key business initiative for your organization, something the business is trying to accomplish over the next 9 to 12 months. It might be something like improve customer retention, optimize customer acquisition, reduce customer churn, optimize predictive maintenance, reduce revenue theft, and so on. Brainstorm and write down what (1) customer, (2) product, and (3) operational insights your organization would like to uncover in order to support the targeted business initiative. Start by capturing the different types of descriptive, predictive, and prescriptive questions you'd like to answer about the targeted business initiative. Tip: Don't worry about whether or not you have the data sources you need to derive the insights you want (yet). Case Study Weightage: 10% Submission deadline: Session 5 MITS6005 Case Study Copyright © 2020 VIT, All Rights Reserved. 3 Write down data sources that might be useful in uncovering those key insights. Look both internally and externally for interesting data sources that might be useful. Tip: Think outside the box and imagine that you could access any data source in the world. Be analytical within your report and examine key terms and theoretical relationships in depth.
1. Structure of the written report: Background information is relevant, issues are logically ordered, recommendations clearly relate to the issues.
2. Identify main issues: Prioritize choices, justify and prioritize issues chosen.
3. Analyze the issues: Each issue is discussed using relevant concepts and principles, insight is shown in analyzing the information.
4. Discuss alternatives: Consider all viable short-term and long-term alternatives to potentially solve each issue, examine the advantages and disadvantages of each alternative.
5. Explain resources: Identify individuals from the case study, enumerate the time frame and monitoring processes required for the recommendations to be put into practice.
6. Write clearly and concisely: Arguments are explicit and succinct, appropriate headings are used, grammar and spelling are accurate

Answer

Introduction
The storage of big data is the main issue for industries which is the major concern of this Tesco big data case study and also for facilities as they are revolutionizing the manner they store and analyze intelligence. The highly connected digital economy with the help of the IoT is changing the financial system of data as a commodity. Although big data analytics and storage bring many advantages to the company, it often needs industries to cross associational boundaries. Compared with traditional methods, data identification through analysis is a very complicated process [1]. Those who perform data analysis should be proficient in the areas and technologies utilized for analytics and data solutions. Still, this is a growing field, and the isolation between analysts and the preparation of data and decision-makers is disappearing. The Business Analytics and Big Data division is expected to develop by 29% over the next five years. The mixture of simple access to quality tools and data for analysis will help to attain a good quality of life and higher operational competence. It will help to establish evidence-based standards for policy development. Small public sector entities now apply big data analytics to multinational companies such as Tesco in developed markets. However, due to the lack of data, big data analysis is not general in emerging countries. It is stated in the Tesco big data case study that in the absence of data, big data analysis methods cannot be applied. Big data and Tesco can be synonymous with their size because big data has the same probability as Tesco, and Tesco can be as large as big data [2]. Nowadays retail stores not only accumulate customer information to share product discounts and offers but however they also know, interpret and integrate consumer data to make the best use of that data to drive sales and revenue. The starting point is usually a business challenge, product or idea. It can be optimizing pricing, making predictions before technical problems occur, personalizing customer communication for products, maintaining business security, managing risk, reducing fuel costs or almost anything else. Within an hour, cross-functional teams in any business can often solve hundreds of problems that can be solved with data. The next step mentioned in this Tesco big data case study is to prioritize several issues that can achieve a clear return on investment in the short to medium term with relatively limited effort. Addressing several different types of problems first ensures that the solution is flexible and extensible and supports more than a single-use case.

Identify issue
Tesco big data case study
Tesco: Tesco plc, operating as Tesco, is the British international grocery or department store retailer headquarters in Hertfordshire, Welwyn Gardens, UK, and England. It’s the third biggest retailer in the whole world in the phrase of total revenue and the ninth leading retailer in the whole world in the revenue terms. According to the study considered to prepare this Tesco big data case study, Tesco acquired Kosmix in April 2011 and changed its name to TescoLabs to develop software for a real-time data stream analysis. The business announced its Polaris search engine the following year. Tesco went through data collection; moreover, analytics went through a focus on consumer data privacy. Walmart has already collected information in 2012, or its transaction data is approximate to have 2.6 PB of data associated with consumers. Kosmix allowed the idea of big data, although the word was not coined at the time, it was provided by developing software applications to search and analyze media (for example Twitter, Facebook, and Blog Points) applications in the real-time, users Personalized insights. Social genomic applications have also been developed to capture data about people from aspects such as information, events, people, topics, locations, associations, as well as product relationships. The application always executes social semantic analysis or provides its output to Tesco's customized application of e-commerce. Apply cutting-edge analytic and latest data is the answer to various challenges that supermarkets face, including evolving customer behaviour and facing new competitors. Several of these products (for example, Amazon, which started offering fresh food recently) are built entirely by digital furthermore data-driven associations. Constantly better understand the nature changing of customer behaviour [3]. It is discussed in this segment of Tesco big data case study that Tesco facing the challenges of rising business models competing with and reduce the amount of food wasted in stores. Other issues illustrated in the context of Tesco big data case study encountered by the company include a lack of qualified data scientists, poor integration between departments, and inability to manage expectations. UPS operates one of the world's largest logistics businesses, delivering millions of packages daily. If even one of their trucks had a glitch, it could be a big deal, causing drivers to stop, delay packages and angry customers. There are usually two types of problems, such as storage problems and processing problems. Especially if Tesco is processing large amounts of data, they will face this problem.

Analysis
Customer
Customers are the most significant asset mentioned in the Tesco big data case study that every business based on. No company can claim achievement without first building a solid consumer base. Nevertheless, even with the consumer base, companies cannot ignore the fierce competition they face. If a company considered in this Tesco big data case study is slow to understand the needs of its customers, it's simple to start offering inferior products. In the end, it will lead to customer churn, which will have a negative overall impact on business success. The use of big data enables companies to observe several patterns and trends associated with consumers. Observing consumer behaviour is significant in triggering loyalty. In the modern world of business as well as the present era of technology, companies can simply collect each of the consumer data they need. It means that it's simple to know modern customers [5]. All organization have to do is have a big data analytics strategy to get the most out of your data. With the right consumer data analytics in place, businesses will be able to gain critical insight into the actions they need to take to retain their consumer base. The findings obtained in the Tesco big data case study signifies that understanding consumer insights will enable your company to deliver what consumers need. This is a basic step to attain high consumer retention.

Operational Insights
Big data analytic can also help transform all the operations of the business. This will include the capability to meet consumer expectations, change business product lines, and ensure strong marketing campaigns. Let face the bare truth here. After a year of careful enthusiasm, the advertising and marketing technology industry can now embrace big data in a big manner. The advertising and marketing department can achieve a complex analysis. Understanding consumer behavior requires analyzing and collecting consumer data. As shown in this Tesco big data case study, this is complete through the same approach utilized by advertisers and marketers. In this way, highly targeted and targeted exercise can be achieved [6].

Product
More personalized and targeted campaigns mean businesses save more money as well as make sure efficiency. This is because they target probable consumers with the correct products. BDA is best for advertisers because industries can utilize this information to know their customers' buying behavior. With predictive analytics, organizations can define their target customers. As a result, industries can have effective and appropriate coverage to avoid vast losses due to advertising fraud.

Tesco leverage big data
Initially, data collection started in 2012, and it is an experienced Hadoop cluster with 10 nodes moreover increasing that quantity to 250 nodes. The goal of Hadoop's migration is to combine its 10 sites into its homepage to collect every unstructured data into a Hadoop cluster. This is a starting of the speed of the big data analysis and has been a key factor to this day. Not only increases revenue, but it also provides the highest-quality consumer experience.

Additionally to Kosmix, it is mentioned in this Tesco big data case study that Tesco also acquires Inkuru Inc. to target merchandise sales, fraud prevention, and targeted marketing. The forecasting technology they use has begun to pull in huge amounts of data from a variety of different sources. It helped Tesco improve customer service through personalized services. Prediction technology combines machine learning techniques to automatically improve the accuracy of algorithms and integrate them with various internal and external data sources.

Big data analysis can only be executed using large amounts of data, so it cannot be applied in numerous developing finances where the essential data cannot be obtained. Such as, in developing countries like southern Sudan, it's not probable to perform data analysis to predict vaccine immunization requirements because of insufficient information. In Ukraine, information restrictions sometimes lead to stock-out. Both private and public sector entities must make an evidence-based decision. However, in this Tesco big data case study, it is ordinary to use inadequate data for uncertain analysis [7].

Big data is very large, complex and huge data sets so that current and contemporary or traditional data processing applications will become insufficient. Big data can more effectively address the modern challenges of the traditional data processing applications, such as data search, management, sharing, visualization, updating, transmitting, querying, analyzing, information privacy, and capturing. It refers to utilize predictive analytics to remove some value from the raw data that will serve as a reference and basis for surer decision-making. Correct outcomes from the big data may reduce costs, reduce risk and increase operational efficiency. Big data also has been rapidly applied in several industries to combat crime, prevent disease and identify business trends.

Predictive analysis
Predictive analysis outlined in the context of Tesco big data case study uses machine learning algorithms and statistical models to identify patterns and predict future trends based on past data. Tesco uses this analysis for marketing, forecasting, consumer service, fraud detection, and product quotes to take advantage of various benefits such as gaining a competitive benefit, innovative revenue opportunities, improved profitability, and improved operational efficiency and customer service.

Descriptive analysis can be used when companies need to know the overall performances of the business as a whole and describe various aspects. Tesco uses descriptive analysis which is the most basic form of analysis. These types of analysis analyze the data that comes in real and historical data for insights to move into the future.

Prescriptive analytics: Big data maybe not a consistent crystal ball that predicts the correct winning lottery number; nevertheless it can highlight issues moreover help businesses know why these issues occur. Businesses can also utilize data support and data discovery elements to create recipes for business issues that may lead to observation and realization. This Tesco big data case study examines that the prescriptive analytics is the further step in Tesco's predictive analysis, which adds to the joy of influencing the future. Prescriptive analytics advises on probable results as well as leads to actions that may maximize key business indicators.

Tesco uses descriptive analysis, which is the basic variety of analysis. The easiest method to define a descriptive analysis is to answer the question. This kind of analysis analyzes data from historical data and real-time to understand how to deal with the future. The major purpose of descriptive analysis is to identify the causes behind past valuable successes or failures. "Past" refers to some specific time when the event occurred, possibly a month ago or even a minute ago. Companies learn from previous behaviours to know how they affect future results. This predictive analysis explored in this section of Tesco big data case study is at the core of the supply chain method, helping to maintain the proper inventory of the most needed products and reducing the backlog. It negotiates with suppliers about the use of real-time supplier inventory management to help reduce the inventory of specific products in a case expected sales cannot be achieved. It supports retailers in buying much-needed products by saving money. In the end, it increased sales, which increased profits [9].

Justify recommendation
Media solutions: A new competition, crowdsourcing, was introduced on media, which allowed entrepreneurs to add new products to the shelves, earning 5,000 entries in the United States. The best product was chosen as the winner or displayed in-store, making it available to the millions of consumers.

Mobile big data analysis solution: As per the research on Tesco big data case study, over half of consumers utilize smartphones, of which 36% are adults, who make up 3/4 of Tesco's total consumer base. Smartphone consumers made 4 trips moreover they spent almost 78% in the store. Every year, mobile phone users account for almost a third of Tesco's traffic and about 40% during the holidays. Whenever a customer enters a Tesco store in the United States and changes the mode to "Store Mode", they can use the geo-fence feature of the mobile app for sensing. Blueprint of Tesco's big data strategy should include the overall strategies, vision, and needs, not on the departmental basis, however on the enterprise basis. This will give an enterprise-wide consensus on how a company wants to use the big data to enhance the business objectives and goals. It enables businesses to overcome major business challenges, use the big data that business processes require, and define the hardware needed to implement architecture, data, tools, and blueprints. It likewise provides the base for the roadmap that guides organizations to develop and implement their big data strategies in a practical way.

It is noted in this Tesco big data case study that companies need to be realistic about what can be achieved initially to achieve the short-term impact when big data execution begins and converges. The easiest way for Tesco to execute successful strategies and provide business value is to gather information that is already in the enterprise. Doing so allows companies to use not only readily available data, however also existing skills as well as software. Increasing BD analytics to cover more complex sources and types of information makes it an immediate advantage as it becomes a business case. While expanding the data warehouse to handle large amounts of data for future insights, many successful strategies have begun to analyze existing data stores [10] As the market grows, Tesco is forced to choose more and more analytical tools, while simultaneously, they have to deal with a severe lack of analytical skills. Successful settlement of big data depends on finding it. But right now, companies need to work in an existing marketplace, which requires investment skills and tools. As a part of such process, research on Tesco big data case study has shown that the new career frameworks will be provided for individuals who have reached the required balance in terms of analysis, work and IT skills. Tesco should focus on the professional development as well as clear career development; Investing in these people must be the main concern for executives now. Tesco must ensure that current investments are based on measurable business results, develop a viable big data strategy, and moreover make sure that decision makers continue to receive interest and investment. Hence, business leaders must be capable to see the benefits. Tesco can do this by developing proactive strategies and ensuring that it is actively involved and sponsored by one or more business leaders when it is first implemented. Equally important is the continued cooperation between IT departments and business. All investments in big data in Analytics must be properly understood about business value [12].

Conclusion
By concluding the above discussion on this Tesco big data case study, it is stated that Tesco stores have been the most successful retail business, not only in the United States but also worldwide. The secret of success lies in the correct delivery of the product, the right place and right time. The success of stores has achieved remarkable results in climbing the ladder of retail success, primarily throughout utilize of big data analytics. By implementing BDA, companies can gain competitive benefits, decrease operating costs and increase customer retention. Enterprises can leverage a variety of customer data sources. As technology continues to advance, data is accessible to all organizations at all times. Technically, it’s reasonable to say that the organization already has data available. It’s up to the associations to make sure that they implement a suitable data analysis system to manage the massive amounts of data.

References
[1]G. Pal, G. Li and K. Atkinson, "Multi-Agent Big-Data Lambda Architecture Model for E-Commerce Analytics", Data, vol. 3, no. 4, p. 58, 2018. Available: 10.3390/data3040058.

[2]S. Phillips, "Going Beyond the Data as the Patching (Sheaving) of Local Knowledge", Frontiers in Psychology, vol. 9, 2018. Tesco big data case study Available: 10.3389/fpsyg.2018.01926.

[3]H. Liu, "Beyond the Scale of Big Data", Frontiers in Big Data, vol. 1, 2018. Available: 10.3389/fdata.2018.00001.

[4]E. Kuiler, "From Big Data to Knowledge: An Ontological Approach to Big Data Analytics", Review of Policy Research, vol. 31, no. 4, pp. 311-318, 2014. Available: 10.1111/ropr.12077.

[5]"Supply Chain Brain - Supply Chain News, Analysis, Videos, Podcasts", Supplychainbrain.com, 2020. [Online]. Available: https://www.supplychainbrain.com/. [Accessed: 28- Mar- 2020].

[6]"U.S. Companies to Increase Investment Across Broader Range of Emerging Markets, Study Finds", Supplychainbrain.com, 2020. [Online]. Available: https://www.supplychainbrain.com/content/general-scm/business-strategy-alignment/single-article-page/article/us-companies-to-increase-investment-across-broader-range-of-emerging-markets-study-finds/. [Accessed: 28- Mar- 2020].

[7]"Supply Chain Brain - Supply Chain News, Analysis, Videos, Podcasts", Supplychainbrain.com, 2020. [Online]. Tesco big data case study Available: https://www.supplychainbrain.com/. [Accessed: 28- Mar- 2020].

[8]D. Rijmenam, "How Big Data Can Help The Developing World Beat Poverty", Datafloq.com, 2013. [Online]. Available: https://datafloq.com/read/big-data-developing-world-beat-poverty/168. [Accessed: 28- Mar- 2020].

[9]B. Marr, "Big Data At Tesco: Real Time Analytics At The UK Grocery Retail Giant", Forbes, 2020. [Online]. Available: https://www.forbes.com/sites/bernardmarr/2016/11/17/big-data-at-tesco-real-time-analytics-at-the-uk-grocery-retail-giant/#564fdc3a61cf. [Accessed: 28- Mar- 2020].

[10]R. Patil et al., "Supermarket Tesco pioneers Big Data - Dataconomy", Dataconomy, 2020. [Online]. Available: https://dataconomy.com/2014/02/tesco-pioneers-big-data/. [Accessed: 28- Mar- 2020].

[11]B. Hjørland, "Data (with Big Data and Database Semantics)", KNOWLEDGE ORGANIZATION, vol. 45, no. 8, pp. 685-708, 2018. Available: 10.5771/0943-7444-2018-8-685.

[12]J. Korhonen, "Big Data – Big Deal for Organization Design?", Journal of Organization Design, vol. 3, no. 1, p. 31, 2014. Tesco big data case study Available: 10.7146/jod.13261.

[13]A. Shiri, "Linked Data Meets Big Data: A Knowledge Organization Systems Perspective", Advances in Classification Research Online, vol. 24, no. 1, p. 16, 2014. Available: 10.7152/acro.v24i1.14672.

[14]G. Slinger and R. Morrison, "Will Organization Design Be Affected By Big Data?", Journal of Organization Design, vol. 3, no. 3, 2014. Available: 10.7146/jod.9729.