MG413 Data Insights For Business Decisions Assignment Sample

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Introduction

• The UK hospitality industry contributes £91 billion annually to the economy (UK Hospitality, 2024).
• Employs approximately 330,000 people across diverse sectors.
• Critical for enhancing customer experiences and operational efficiency.

The UK hospitality sector is a significant factor in the UK economy. It currently contributes £91 billion to the economy and directly supports up to 330,000 people. The substantial sub-sectors of this industry group are food and beverage, accommodation, travel and tourism, and entertainment and recreation. The substantial sub-sectors of this industry group are food and beverage, accommodation, travel and tourism, entertainment, recreation, and these areas are frequently explored in depth using academic support resources such as a uk assignment writing service for study guidance. All these sectors depend on data and information to compete in what is rapidly becoming a digitized economy. This presentation will describe these sectors, focusing on the role of data and information in these sectors and their strategic relevance. Organizations can transform, boost and sustain better customer relations and operations using contemporary technologies and efficient data strategies.

MG413 Data Insights For Business Decisions Assignment Sample

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Task 1: Types of Data Collected and Usage

• Organizations gather and use various forms of data in the hospitality industry to boost customer satisfaction and organizational performance( Elshaer et al., 2024).
• Customer information, including previous bookings, likes and dislikes, and feedback, is critical in customizing services.
• For instance, what hotels may use this data to adapt the rooms' settings or suggest the proper type of cuisine for a guest. Data insights For Business Decisions additionally help hotels refine guest-experience models. Inventory details, employee timetables, and transactions are some of the most vital aspects in running the day-to-day activities smoothly.
• Companies can sustain a competitive advantage through market data in which firms analyse competitor plans and cost structures (Bhardwaj and Kalia, 2021).

Further, the information system includes environmental data like weather forecast information and information about local events to help the companies to change the services and offerings accordingly.

Depending on the collection source, the data can be grouped as first-party, second-party, and third-party data. First-party data is collected from the consumers by the business directly without the involvement of third parties, for instance, by using the customers’ feedback, loyalty cards, or questionnaires. Second-party data is collected from partners and may include interaction with the customers by partners such as travel agencies or event organizers; this generated knowledge about the consumer’s behaviour widens a business. It is collected from outside the firm through surveys, case studies, questionnaires, census, and other samples derived from population statistics, market surveys, and other comparatively extensive sources.

Task 2: Traditional Market Research vs. Big Data

• Standard industry research in the hospitality industry presents itself through questionnaires, focus group discussions, and interviews (Tomasella, Ali and Gill, 2023).
• These methods provide data in qualitative form and help firms gain insights into customers’ preferences, satisfaction levels, and buying behaviour.
• On the other hand, traditional research has shortcomings such as the small number of cases, data collection time bearing and time taken to analyze results (Richard et al., 2020). Data insights For Business Decisions enable hotels to compensate for these limitations by using real-time analytical models.

On the other hand, Big Data references significant volumes and numbers of consistent data feeds from numerous digital assets.

• Live streaming from the number of customers in the restaurant, bookings from the online portal, and interaction with customers on different social media platforms
• Reviews generated by the customers back the decision-making of the restaurants.
• Unlike conventional scholarly study and investigation, Big Data can allow for instantaneous choices and forecasts (Jabbar, Akhtar and Dani, 2020).

For instance, the price of rooms can be varied in line with demand signals obtained online through dynamic pricing strategies. Although CAT is deep and contextual, Big Data is fast, wide and solutions-focused, which is why it is an essential tool in the hospitality industry.

Task 3: Data Capture, Storage, and Management Systems

• The hospitality sector collects data from various digital and hard-copy sources.
• POS systems capture transactional details, reservation platforms harvest consumers’ data, and connected machines, including the thermostat and keycards, capture guests’ preferences (Kholod, Celani and Ciaramella, 2024).
• At the same time, customers’ replies to the surveys and presentations on social networks can provide information about the overall experience and expectations.

Data collected then is stored in structured and unstructured forms. While there are relational to organize the data into a structured model with examples such as SQL, there are non-relational databases that are even newer, such as MongoDB, that fit unstructured data in the forms of posts on social media.

• Modern cloud-based solutions such as Amazon AWS or Microsoft Azure are often used to guarantee scalability and availability (Bello et al., 2020).
• Decision-makers receive information processed, analyzed and presented through management information systems (MIS).
• Some of these are Oracle Hospitality and Amadeus, which combine disparate pieces of information to provide intelligence (John et al., 2025).

For instance, these systems can estimate the demand for booking, manage the staff shift and increase customer personalized care. All these are testaments to the need for data acquisition and storage efficiency.

Task 4: Impact of Technological Developments

• Over the recent past, technological developments have comprehensively revolutionized how data is applied in the hospitality industry (Iranmanesh et al., 2022).
• AI is now used to determine the spending pattern of the customer and to offer customised products and services, which enhances customer satisfaction and the company's revenue.
• For instance, conversational AI in customer care presents real-time responses to customers specifications and requests and machine learning identification of customers needs from previous interactions (Gidumal et al., 2023).

The IoT has made it possible for companies to gather data that is relevant to their activities within an organization, including energy consumption or room availability. The data assist in properly distributing resources, cutting costs and, above all, creating the best image for the guests. For example, when it comes to lighting and HVAC systems, these two controls work depending on the guest’s preferences to create comfort and, at the same time keep energy costs down.

• There have also been significant advancements in payment systems security and a general increase in data openness through blockchain technology (Javaid et al., 2022).
• On the same note, blockchain makes transactions secure by proving that no one can alter data on the ledger, hence dealing with fraud and data breach issues.
• These technological advancements have placed data at the centre of decision-making.

Some organizations independently analyse the results of the work and can predict the needs of consumers, the optimal price level, and the required amount of goods. Thus, organisational changes in the fast-growing and highly competitive hospitality industry can be managed effectively and quickly in case of new features in a given market milieu.

Task 5: Operational and Strategic Use of Data

• Data is central to the hospitality industry's tactical day-to-day and organizational strategic management (Lamest and Brady, 2019).
• On a strategic level, data improves service delivery, and on an operational level data brings organizational efficiency and guest satisfaction. Data insights For Business Decisions help organizations adjust pricing, staff levels, and service models dynamically.
• For instance, raw data from POS and booking platforms help control inventory, schedule human resources, and set the correct price rates in real-time (Wynn and Jones, 2022).

In other instances, the hotel uses customer feedback obtained from surveys or other forms of response in cases of service delivery to solve problems that may promptly lead to poor customer experience. Further, it provides data from smart devices, including keycards and IoT, to track room occupancy and energy usage, reduce operation costs, and enhance sustainability.

• Informational processes guide the selection of business strategies that affect the organization (Farida and Setiawan, 2022).
• With the help of analytics, one can discern trends and cyclicality and calculate the market interest in particular products.
• For instance, through the patterns of the customers who book in hotels, the former can improve their marketing techniques to suit the latter.
• It also assists strategic use of data in diversifying services that address diverse customer needs (Sinnaiah, Adam and Mahadi, 2023).

For instance a resort chain may use a trend analysis to determine whether to include spa or adventure tourism services because of the trend in the guests. Data also helps in strategic forecasting, where an organization forecasts operations based on seasonal changes, or entry into new markets. In addition, the data helps to identify frequent consumers in loyalty programs and adjust incentives for maintaining a strong connection with the targeted audience. Thus, overall data is essential not only for functionalism but also as the basis for creating innovation, competitive advantage, and industry longevity.

Task 6: Research Plan

• Thus, to improve data gathering and utilization in the hospitality industry, a well-defined research proposal must address the need for better technology solutions and data processing facilities.
• The plan starts with an industry benchmarking analysis to determine the relevant industry practices about data acquisition and storage (Dash et al., 2019).
• This includes evaluating the leading organizations within the industry practice about information utilization and deriving findings on practical strategies (Sun and Gu, 2021).

Subsequently, proof of concepts should be conducted in specific strategized organizations to validate new data collection instruments. For example, mobile applications or IoT objects can monitor customers’ activity and operations indicators in real-time. These pilots will also focus on how other forms of advanced analytics, including artificial intelligence and machine learning algorithms, can also be used to deliver insights efficiently.

Conclusion

• For the last decades, information and data have played significant roles in developing the hospitality industry since they assist industries in offering specific services to users while ensuring maximum productivity and constant adaptability to the modern market.
• Classic quantitative information gathering is still in use but is now backed up by big data, which is more accurate because it gives real-time results.

The use of artificial intelligence, IoT, and blockchain has extended much further to influence decision-making as well as customer satisfaction. Thus, possessing strong frameworks for data collection, storage, and management, one can harness information to solve contending operational issues and grasp opportunities for strategic development.

References

• Bello, S.A., Oyedele, L.O., Akinade, O.O., Bilal, M., Davila Delgado, J.M., Akanbi, L.A., Ajayi, A.O. and Owolabi, H.A. (2020). Cloud computing in construction industry: Use cases, benefits and challenges. Automation in Construction, [online] 122(1), p.103441. doi:https://doi.org/10.1016/j.autcon.2020.103441.
• Bhardwaj, B. and Kalia, N. (2021). Contextual and task performance: role of employee engagement and organizational culture in hospitality industry. Vilakshan - XIMB Journal of Management, [online] ahead-of-print(ahead-of-print). doi:https://doi.org/10.1108/xjm-08-2020-0089.
• Dash, S., Shakyawar, S.K., Sharma, M. and Kaushik, S. (2019). Big data in healthcare: Management, analysis and future prospects. Journal of Big Data, [online] 6(1), pp.1–25. doi:https://doi.org/10.1186/s40537-019-0217-0.
• Elshaer, I.A., Alaa M. S. Azazz, Sameh Fayyad, Mohamed, S.A., Fouad, A.M. and Fathy, E.A. (2024). From Data to Delight: Leveraging Social Customer Relationship Management to Elevate Customer Satisfaction and Market Effectiveness. Information, [online] 16(1), pp.9.9. doi:https://doi.org/10.3390/info16010009.
• Farida, I. and Setiawan, D. (2022). Business Strategies and Competitive advantage: the Role of Performance and Innovation. Journal of Open Innovation: Technology, Market, and Complexity, 8(3). doi:https://doi.org/10.3390/joitmc8030163.
• Gidumal, J.B., Secin, E.W., O’Connor, P. and Buhalis, D. (2023). Artificial Intelligence’s Impact on Hospitality and Tourism marketing: Exploring Key Themes and Addressing Challenges. Current Issues in Tourism, [online] 27(14), pp.1–18. doi:https://doi.org/10.1080/13683500.2023.2229480.
• Iranmanesh, M., Ghobakhloo, M., Nilashi, M., Tseng, M.-L., Yadegaridehkordi, E. and Leung, N. (2022). Applications of disruptive digital technologies in hotel industry: A systematic review. International Journal of Hospitality Management, [online] 107(1), p.103304. doi:https://doi.org/10.1016/j.ijhm.2022.103304.
• Jabbar, A., Akhtar, P. and Dani, S. (2020). Real-time big data processing for instantaneous marketing decisions: A problematization approach. Industrial Marketing Management, [online] 90. doi:https://doi.org/10.1016/j.indmarman.2019.09.001.
• Javaid, M., Haleem, A., Singh, R.P., Suman, R. and Khan, S. (2022). A review of Blockchain Technology applications for financial services. BenchCouncil Transactions on Benchmarks, Standards and Evaluations, [online] 2(3). doi:https://doi.org/10.1016/j.tbench.2022.100073.
• John, Beekers, I., Verkouter, I., Richards, L.B., Vegelien, A., Bloemsma, L.D., Vera, Cloos, J., Erkens, F., Gradowska, P., Hort, S., Hudecek, M., Juan, M., Anke, Navarro-Velázquez, S., Ngai, L.L., Rafiq, Q.A., Sanges, C., Tettero, J. and Os, van (2025). A data management system for precision medicine. PLOS Digital Health, 4(1), pp.e0000464–e0000464. doi:https://doi.org/10.1371/journal.pdig.0000464.
• Kholod, M., Celani, A. and Ciaramella, G. (2024). The Analysis of Customers’ Transactions Based on POS and RFID Data Using Big Data Analytics Tools in the Retail Space of the Future. Applied Sciences, [online] 14(24), pp.11567–11567. doi:https://doi.org/10.3390/app142411567.
• Lamest, M. and Brady, M. (2019). Data-focused managerial challenges within the hotel sector. Tourism Review, 74(1), pp.104–115. doi:https://doi.org/10.1108/tr-03-2017-0064.
• Richard, B., Sivo, S.A., Orlowski, M., Ford, R.C., Murphy, J., Boote, D.N. and Witta, E.L. (2020). Qualitative Research via Focus Groups: Will Going Online Affect the Diversity of Your Findings? Cornell Hospitality Quarterly, [online] 62(1), pp.32–45. doi:https://doi.org/10.1177/1938965520967769.
• Sinnaiah, T., Adam, S. and Mahadi, B. (2023). A Strategic Management process: the Role of decision-making Style and Organisational Performance. Journal of Work-Applied Management, [online] 15(1), pp.37–50. doi:https://doi.org/10.1108/jwam-10-2022-0074.
• Sun, P. and Gu, L. (2021). Energy big data acquisition and application based on service portfolio quality. Sustainable Energy Technologies and Assessments, 45, p.101134. doi:https://doi.org/10.1016/j.seta.2021.101134.
• Tomasella, B., Ali, A. and Gill, D. (2023). Hospitality that cares: a qualitative investigation into small foodservice businesses’ social responsibility. Current Issues in Tourism, pp.1–17. doi:https://doi.org/10.1080/13683500.2023.2214849.
• UK Hospitality (2024). Facts and stats. [online] UKHospitality. Available at: https://www.ukhospitality.org.uk/media-centre/facts-and-stats/ [Accessed 15 Jan. 2025].
• Wynn, M. and Jones, P. (2022). IT strategy in the hotel industry in the digital era. Sustainability, 14(17), p.10705. doi:https://doi.org/10.3390/su141710705.