The Benefits of Data Strategy Applications in the Airline Industry

Posted: August 25th, 2021

The Benefits of Data Strategy Applications in the Airline Industry

Student’s Name

Institutional Affiliation

Table of Contents

Introduction. 3

Creating Competitive Advantages from a Data Strategy. 6

Developing and Maintaining Customer Relationships. 6

Improving CRM through increased Knowledge: British Airways’ “Know Me”. 8

Handling Overbooked Flights. 10

Using strategic data management to reduce overbookings: United Airlines. 12

Strategic Management of Flight Disruptions. 13

Managing disruptions through a data-driven resilience program: EasyJet 14

Conclusion. 17

References. 18

The Benefits of Data Strategy Applications in the Airline Industry

Introduction

With thousands of airlines around the globe, each offering highly competitive products, today’s passengers have a broad range of options. Besides, in the current digitalized business environment, potential consumers have easy access to the information they need to rate different sellers. In the presence of numerous alternatives and readily available information, today’s consumers have a measure of control over the services and products that they expect from providers. In such a state, customer retention becomes an essential predictor of profitability and survival (Climis, 2017; Jiang & Zhang, 2016). Effective retention programs allow airlines to keep as many loyal customers as possible. However, realizing such a goal is not an easy task. Companies must endeavor to develop and maintain excellent delivery platforms that exceed customer expectations if they are to deliver value to their clients. They must strive to build long-lasting provider-client bonds and focus on solving the problems experienced by the buyer as they interact with the products.

As companies expand their operations, they become increasingly complex and in need of integrated systems to manage new and intricate business demands. Building a reliable data strategy enhancesits capacity to meet such requirements. A data strategy can be viewed as a set of decisions and choices that are designed to provide a high-level set of actions for accomplishing high-level goals (Chiang, Grover, Liang, & Zhang, 2018). Central to an organization’s data strategy is the plans for harnessing information to support business goals and create a competitive advantage. A well-designed strategy provides a firm with the relevant information needed to develop and market products that are customized to meet the unique needs of its customers and, hence, improve their consumption experiences. Building such a plan requires an organization to understand its individual needs, which are inherent to its overall business model and strategic objectives. In contrast, the absence of a dependable data plan implies that an organization relies mainly on people and its information technology system to access the data needed to run its operations.

A data strategy offers airlines with competitive advantages in several ways.For example, companies with efficient data strategy have enhanced decision-making capabilities. A reliable data strategy supports the re-imaging of organizational decisions at nearly all levels. Given the increased volume, depth, and accessibility of data made possible by such a plan, firms can develop a decision-making framework for creating sustainable competitive advantage (Chiang et al., 2018). The information obtained from a properly maintained data warehouse can provide firms with essential insights into the business environment and real-time metrics needed to measure market variables.

A data strategy also helps in identifying and mitigating risks. The airline business environment is characterized by many uncertainties that occur in varied forms and magnitudes. While many contingencies are unforeseeable and, hence, nearly impossible to manage, the effects of many others, such as fluctuations in passenger flows, changes in currency rates, or some weather patterns,can be prevented or minimized by an efficient risk mitigation plan. A well-panned data strategy can help a firm to identify and characterize potential risks and their impacts, as well as develop strategies for mitigating them.

Risk management is a critical component of safety. Every flight presents airlines and their crew with unique conditions, some of which may lead to stressful situations and jeopardize safety (Bai, Tao & Yang, 2014). Flight safety is dependent on various internal and external variables, including the status of an aircraft, the flight environment (such as weather), and the human factor (such as crew experience). Authorities in the aviation industry have developed several risk controls for enhancing safety. Such controls provide a measure of protection against preventable occurrences (Bai et al., 2014). Still, even the controls are limited by several uncertainties and human factors. A data strategy may provide airlines with analytic techniques for identifying and eliminating situations that may lower the safety of an aircraft.

Companies can also use their data strategy to analyze consumer trends and develop customer-centered products. Consumers characterize the air travel business with highly dynamic behaviors and constantly changing segmentation boundaries (Cho & Min, 2018). Although such fluctuations present providers with unique business opportunities, managing them can be challenging. An efficient reporting system built on data analytics foundation and having a reliable information delivery framework can provide a basis for tracking changes in consumer behavior. In the end, it also turns them into opportunities for improving their experiences and, consequently, their loyalty.

Generally, data strategies offer airlines with a range of benefits and opportunities for increasing their competitiveness, including improved decision-making, risk management, safety, and customer experience. The nature of the operations of these companies exposes them to vast and diverse information, allowing them to build large data warehouses. Still, the extent to which a company gains the benefits is contingent on their ability to turn its data repositories into innovative ideas. In the next section, three benefits of data strategies (maintaining customer relations, handling overbooked flights, and managing flight disruptions) are illustrated with specific examples from British Airways, United Airlines, and EasyJet. Each case highlights various ways in which a reliable data strategy can be utilized to create competitive advantages.

Creating Competitive Advantages from a Data Strategy

Developing and Maintaining Customer Relationships

Over the years, there has been increasing growth in customer-oriented strategies that focus on meeting the needs of individual customers. Retaining today’s highly informed and sensitive customers require business entities to develop excellent relationships with their clients. Accordingly, many companies are investing heavily in tools and techniques for building and maintaining organization-customer relationships. Marketing strategies are progressively changing from entirely product-centric to consumer-centric. In a customer-centered approach, the consumer has is seen as the critical reason for organizational existence (Banihashemi, Jahanshahi, Khaksar, & Yaghoubi 2011). The goal of this approach is to enhance the maximum retention of customers.

A notable trend in this direction is the development of customer relationship management (CRM) systems. Croteau and Li (2009) define CRM as the strategies involved in creating unique products for different individuals. Meeting this goal requires a firm to identify and classify its clients based on their needs. Theoretically, the groups should be as small as possible to allow a firm to design exclusive products for individual customers. Research shows that companies that build and maintain efficient CRM systems have increased opportunities for attracting and retaining customers. In Bin-Nashwan and Hassan (2017), CRM enhances customer satisfaction in at least three domains, improved service quality, handling complaints, and service access. In that case, CRM provides a platform for improving satisfaction and loyalty.

The implementation of an efficient CRM requires to affirm to acquire, document, and analyze data on individual customers. According to Kim, Hwang, and Suh (2003) CRM has four dimensions, customer knowledge, interaction, satisfaction, and value. Customer knowledge refers to the extent to which an organization understands its clients (Kim et al., 2003). In this regard, a firm must collect and analyze sufficient and appropriate information about their current and potential consumers. Some of the relevant consumer data that an organization can receive include their tastes and preferences, location, time of purchases, or hobbies. Since consumers are dynamic, these variables are ever-changing. Companies must implement mechanisms for tracking shifts in consumer characteristics. Indeed, research shows significant links between knowledge management and CRM (Banihashemi et al., 2011; Cabras, Rodrigues, & Tckhakaia, 2015). A reliable data strategy enables a company to develop an efficient knowledge management system and, thus, enhance its CRM strategies.

Knowledge management is particularly critical for companies in the airline industry. A longitudinal study by Cho and Min (2018) across U.S. low-cost and legacy carriers highlights the need for airlines to maintain current knowledge management systems. Studies on the characteristics of airline consumers have segmented passengers along different traditional lines, such as time and purpose of travel (Chen & Liu, 2017; Banihashemi et al., 2011). While such an approach to segmentation hasallowed companies to meet the needs of different consumers, they do not always account for the unpredictable nature of today’s customers. According to Cho and Min (2018), although there are some shared characteristics among passengers, market segments are highly dynamic, and the segmentation boundaries are constantly shifting. The introduction of ultra-low-cost carriers has escalated the fluidity. Under such uncertainties, providers need to assume a cautious approach to segmentation. They should ensure that they understand and keep proper tracks of any movement in consumer preferences. A data strategy based on informed customer knowledge is fundamental for realizing this objective.

As noted previously, airline passenger characteristics, including their tastes and preferences, are continually changing, a state that requires companies to continually re-draw their segmentation lines (Cho & Min, 2018). A reliable knowledge management platform allows a company to stay up-to-date with such shifts. Organizations usually collect and store large volumes of information, much of which may not be relevant for their objectives or may not apply to customer relations. Navigating through such data mass to obtain data for specific customers can be time-consuming and frustrating to both employees and clients. An efficient KM system should focus on identifying, collecting, organizing, storing, and sharing critical information among users to enhance a company’s understanding of its customers. 

Improving CRM through increased Knowledge: British Airways’ “Know Me.”

The case of British Airlines (BA) offers an excellent example of the importance of applying data strategy in developing and maintaining good customer relations. The company has made essential milestones in CRM with its focus on knowledge management. Knowledge management (KM) can be described as the act of exploiting different types of knowledge from varied sources to solve an identified problem (Cabras et al., 2015). Such an integrated approach plays essential roles in maintaining customer relations and permits a firm to gain unique competitive advantages, especially concerning customer management. BA has repeatedly highlighted the need for an efficient KM strategy.

Like most international providers, BA operates hundreds of aircraft and thousands of domestic and cross-border flights daily. In an attempt to enhance its competitiveness and maintain its relevance, BA resorted to improving its knowledge management system. For years, BA has relied on data management and analytics to develop a complicated and extensive database that keeps information on nearly all aspects of customer interactions. The firm’s reliance on knowledge management has been instrumental in minimizing some of its customer-related issues, including forecasting demand and managing complaints (Xue, 2016). Through the knowledge of its consumers, BA can develop products and deliver its services based on customer-specific needs.

In 2012, the company took KM to a higher notch by launching a “Know Me” feature to help improve the way its staff interacts with clients. The new platform collects data from multiple service channels, including inside the planes, within the airports, BA’s website, its call center, and customer emails into a single warehouse for improved mining and manipulation (Allchin, 2012; Xue, 2017). Know Me provides customer relations employees with a unique view of each of BA’s customers along with their history with the firm.

The program offers BA staff with a mobile platform for accessing client information in a bid to enhance passenger experiences. For instance, in a video shown to Marketing Week Live, a BA employee responds to a call from a customer attempting to access the executive lounge. Based on the information retrieved by Know Me, the staff recognized that the passenger had experienced similar problems in the past and. Hence, he was allowed to use the facility, although it is reserved for BA staff (Allchin, 2012). Such incidences highlight the value of a well-managed data strategy in improving a company’s CRM strategies. Such a plan allows a firm with the relevant knowledge needed to provide customer-customized service delivery. 

A unique feature of Know Me is its ability to trace and identify regular customers as soon as they enter specific locations. The program employs images from Google’s public domain to locate specific passengers as soon as they enter the airport or its premises. The idea is to provide the passengers with the impression that their presence is acknowledged and appreciated. The application also tracks customers’ purchase patterns, frequently ordered menu, seat preferences, loyalty status, complaint history, travel routes, and other relevant client details (Cabras et al., 2015). The program is intended to allow the firm’s employees to recognize customers and give them personalized attention. Passengers are given relevant directions to enhance their experiences, including where they should sit. In response to criticism related to consumer privacy, BA added a feature that prompt users to provide their details voluntarily (Xue, 2017). According to Cabras et al. (2015), the introduction of “Know Me” allowed BA to increase the speed at which it analyzed customer data. This was in besides improving the efficiency of other business operations, such as mechanical maintenance.

Handling Overbooked Flights

On a Sunday evening, Flight 3411, belonging to a branch of the Chicago-based United Airlines, was ready to take off for Louisville from Chicago’s O’Hare International Airport. However, the journey would not begin until some passengers were removed to allow the plane to accommodate four crew members who were initially scheduled for Flight 4448 earlier that day. Flight 4448 experienced mechanical failures and was possibly canceled. The management offered travel vouchers to willing passengers aboard Flight 3411, but none of them was willing to volunteer his seat. By about 20 minutes before the scheduled departure for Flight 3411, the four crew members had not been rebooked, forcing the management to select four passengers for involuntary removal (Lartey, 2017).  When one of the selected passengers declined to comply, a security officer wrestled and dragged him down the aisle. As a result, the incident created a scene that went viral in the social media and threatened United’s reputation.

The incidence is an extreme case of an involuntarily denied boarding (IDB) and overbooking. Although United later stated that Flight 3411 was not overbooked, the scene created at the plane highlighted the danger of IDBs. Many customers fail to honor their bookings, either unintentionally or voluntarily, a situation that exposes airlines to significant risks. A commonly used strategy formanaging the effects of non-arrivals is overbooking. Airlines usually sell more tickets than the available seats to account for possible non-arrivals. When the honoring rates are high, positions can be overbooked. Additionally, unpredictable weather, problems with traffic control, mechanical failures, or other occurrences can lead to flight rescheduling and, consequently, overbookings.

According to the U.S. Department of Transport, in 2016, there were 106,723 denied boardings due to oversold tickets, representing about 0.005% of the total annual traffic. Out of the 106,723, 8,955 (8.39% of denied boardings) were IDBs (OAEP, 2017). The numbers exclude passenger aircraft with less than 30 seats and airlines with less than 1% of their revenues obtained from domestic travels, indicating that the actual figure is slightly higher than those reported by the authority. The figure suggests that only a small fraction of passengers are affected by IDBs. Still, as highlighted by the above case, it may take only a single incidence to damage a company’s reputation.

Overbooking and the resulting IDBs and can create unpleasant experiences for both customers, gate agents, and the entire staff. When an overbooked flight occurs, a commonly used resolution strategy is to offer rewards, such as travel vouchers, to customers who are willing to be rescheduled. Although this arrangement can provide lucrative opportunities to flexible clients, many passengers travel under tight schedules and can be highly inconvenienced if they have to be rescheduled. Consequently, overbooking can be a cause of low customer satisfaction. Strategies aimed at keeping such occurrences at low levels can provide airlines with some competitive advantages. Companies with a competent data strategy can maximize the opportunities presented by such resources to minimize the frequency of overbookings, as illustrated by the case of United Airlines.   

Using strategic data management to reduce overbookings: United Airlines

As an attempt to reduce the instances of overbooking across all its branches, in 2017, the Chicago-based United Airlines launched the Volunteer Solicitation Program. In the initial version of the program, in case of an overbooked flight, the airline would notify the passengers, either through its website, airport kiosks, or mobile app, and offer them travel vouchers in exchange for their seats. Through the program, gate agents could generate data on potential volunteers and use the information to enhance the booking process (“United Airlines,” 2019). The original idea was that with early notifications, passengers had increased flexibility in addition to the vouchers. Data obtained by the company showed that many customers approved the innovation (“United Airlines,” 2019). Consequently, United began developing strategies for expanding the functionality of the program.

In December 2018, the company introduced a revamped version of the program that leverages data analytics, game-based marketing, and automation to monitor the thousands of daily United flights across the globe. The fully automated platform allows clients to volunteer their seats, receive compensation, and self-rebook new flights without having to go through tedious processes at the gate. Using a data analytic-built configurable engine, the program determines the best flights and offers available to customers. The gamification element gives passengers a measure of control by allowing them to base their bidding on their expectations. The information generated by the program enables United to the best decisions for both the airline and passengers. 

The innovative technology at United highlights the value of an efficient data strategy in improving customer satisfaction. Today, airlines are in a unique position that allows them to gather much information about their passengers. They can capitalize onthe richly available data to develop customer-orient products aimed at enriching flight experiences for customers and employees. Through Volunteer Solicitation, United has streamlined the booking process leading to reduced frustrations for employees and customers. According to the company, the program has resulted in notable declines in the number of IDBs (“United Airlines,” 2019). Overbooking of flights and the resulting IDBs are frequent occurrences in the airline industry and their effects can be disastrous. It may not be easy for airlines to avoid overbookings. Still, as illustrated by the case of United, strategic data management presents companies with excellent opportunities for reducing them to manageable levels, and hence, minimize the number of IDBs and enhance customer experiences.

Strategic Management of Flight Disruptions

Excellent service delivery is a fundamental objective for all service providers and, especially, in the airline industry. Air travel is associated with some elements of pride and prestige and consumers expect highly of their providers. When such expectations are not met, passengers can be highly dissatisfied. However, excellent service delivery is limited by the many uncertainties in the business environment. Airlines must contend with multiple sources of uncertainties, including political factors, unpredictable weather elements, changing consumer preferences. The recent years have seen notable advancements and adoption in predictive analytics in the industry, which have revolutionized the marketing landscape. Such techniques help not only amassing large volumes of data but also predicting possible changes in the flight environment with increased accuracy.

A significant proportion of flight uncertainties occur in the form of disruptions. Disruptions of scheduled business operations constitute one of the significant challenges experienced by airlines across the world.The Airport Council International (2013) defines disruption as an occurrence that leads to the canceling or at least a 2-hour delay within 48 hours of a scheduled departure. When they occur, disruptions can result in high levels of customer and employee dissatisfaction as well as significant financial losses. Globally, it is estimated that disruptions cost airlines and their passengers up to billions of dollars annually and a substantial proportion of the industry’s revenues (Kazda & Serrano, 2017). Airlines operate under tight error margins and any interruption in flight schedules can have far-reaching effects. Hence, an efficient system for managing disruptions is critical to the streamlining of the industry.

Disruptions can also attract significant financial costs resulting from direct and indirect losses. Such losses have undesirable impacts on individual consumers, companies, and the region’s economy (Kazda & Serrano, 2017). Delays and flight cancellations can drive operating costs too high levels as customers seek refunds or compensations. Much of flight disruptions result from external factors, such as weather elements, changes in the political landscape, and problems with the management of airports. However, a significant proportion of the disturbances emerge from organizational variables, including employee strikes, mismanagement of passenger traffic and issues with communication. A reliable data management strategy can help keep the effects of such disruptions to manageable levels. The case of the London-based EasyJet illustrates this point.

Managing disruptions through a data-driven resilience program: EasyJet

According to its statements,EasyJet aims to be a global leader in the industry’s data-driven innovations (EasyJet, 2018). The low-cost carrier has taken essential steps in becoming a data-driven organization, especially with its accelerated use of big data. For instance, it has built a dedicated team of data scientists and analysts focused on building a data-oriented culture across the institution. The company’s data-driven strategy has also been instrumental in saving and improving its efficiency and revenues. In 2019, EasyJet experienced an ancillary revenue growth of 13.7% attributed mainly to its emphasis on data-driven programs and products that are designed to enhance the efficiency of operations (EasyJet, 2019). The company is expected to increase its investment in this direction.

EasyJet also employs its data management strategy to enhance customer experiences and improve customer value. For instance, using artificial intelligence platforms, the company’s employees can predict the foods and drinks preferred by passengers in a given flight to allow the match the supplies with demand (EasyJet, 2018). Improved matching ensures that the flights do not experience shortages or excesses in particular food brands. Such an approach is instrumental in improving customer experiences and minimizing food wastages, all of which contribute to improved profitability. EasyJet also uses advanced data analytic techniques to analyze the billions of searches made by customers through its website to optimize flight durations and destinations (EasyJet, 2019). Besides, by optimizing flight destinations, the company can reduce the number of stand-by planes and, thus, eliminate substantial overhead costs.

Like other airlines across the world, EasyJet must contend with the inconveniences resulting from disruptions. Each year, the company reports numerous instances of delays and cancellations, all of which increase its liabilitiesand operation costs. In 2019, it had a £50 million provision for customer claims related to disruptions. Increased expenditures are particularly critical for EasyJet since the company uses low costs as its critical competitive strategy. Strategies aimed at minimizing the occurrence and effects of disruptions present the firm with opportunities for gaining a competitive edge. In this regard, the company acknowledges the importance of data analytics.

In 2018, the company took a significant step to tackle the problem. Under the Operational Resilience (OR) program, one of the most considerable data strategy initiatives in the company’s history, EasyJet uses data and other resources across its facilities to manage the uncertainties in the business environment(EasyJet, 2018). For example, OR employs a range of data management tools to predict component failures and facilitate replacements. Improved failure management reduces the frequency and duration of flight delays.Also, OR has allowed the company to increase the number of parameters used in its operation planning, such as extended turn times for large aircraft and buffers for crew-constrained ports. The program also implements an on-time performance (OTP) stimulator for predicting events that can cause disruptions allowing the company to take advanced precautions.

OR enables the company’s staff to foresee potential sources of preventable customer disruptions and implement appropriate mitigation strategies. The systematic application of OR has made it possible for the airline to minimize the potential adverse outcomes of such occurrences. For instance, despite the harsh weather conditions during the fourth quarter of 2019, EasyJet management to maintain a flat year OTP of 75%. Overall, in the 2019 financial year, EasyJet reported a 30% drop in total disruption events, including a 46% reduction in flight cancellations and a 24% decline in delays of at least three hours. The company recorded a drop in disruption costs for the first time in four years (EasyJet, 2019). In the same year, actual headline costs per seat increased by about 1.5%, mainly due to changes in fuel prices and foreign exchange rates. Still, at constant currency rates, OR allowed EasyJet to lower the costs by 0.8% (EasyJet, 2019). The decline was mainly due to the ability of the program to cut down yearly disruption expenditures. The case of EasyJet highlights the transformative role thatan effective data strategy based on predictive analytics and artificial intelligence can assume in improving the efficiency of the industry.

Conclusion

The flight environment presents airlines with a wide range of situations that limit their ability to deliver excellent services to their clients. Mechanical failures, weather elements, changes in customer behavior, and other factors may make the air travel business highly challenging. Having reliable data strategy can help the companies to minimize the effects of some of the uncertainties. Data strategies offer airlines with several benefits, including improved decision-making, risk management, safety, and customer experience. The case of BA, United, and EasyJet also demonstrates the problems encountered by also present them with opportunities to improve their competitive advantages. A reliable data strategy allows them to turn the uncertainties for their gain. These companies have relied on their data warehouses to develop strategies for solving specific problems, such as those related to customer relations, overbooking, and flight disruptions, which are frequent occurrences in the industry.

References

Airport Council International (ACI) (March 2013). Passenger protection under cases of flight disruption. Montreal, Canada: Worldwide Air Transport Conference.

Allchin, J. (2012). Know your customers: Case studies from BA, the Guardian, and Milka. Retrieved from https://www.marketingweek.com/know-your-customers-case-studies-from-ba-the-guardian-and-milka/.

Bai, J., Tao, L., & Yang, K. (2014). Assessment of flight crew errors based on THERP’, Procedia Engineering, 80, 49-58.

Banihashemi, S., Jahanshahi, A., Khaksar, S. & Yaghoubi, N. (2011). The impact of knowledge management on customer relationship management. European Journal of Economics, Finance and Administrative Sciences, 34, 76-86.

Bin-Nashwan, S., & Hassan, H. (2017). Impact of customer relationship management (CRM) on customer satisfaction and loyalty: A systematic review. Journal of Advanced Research in Business and Management, 6(1), 86-107.

Cabras, I., Rodrigues, & Tckhakaia, E. (2015). Knowledge management in the airline industry: A case study from British Airways. International Conference e-Society. Funchal, Portugal.

Chen, C., & Liu, H. (2017). Exploring the impact of airline service quality on customer loyalty: Evidence from Taiwan. International Journal of Business and Management, 12(5), 36-49. DOI: 10.5539/ijbm.v12n5p36.

Chiang, R., Grover, V., Liang, T., & Zhang, D. (2018). The strategic value of big data and business analytics. Journal of Management Information Systems, 35(2), 383-7.

Cho, W., & Min, D. (2018). A longitudinal examination of passenger characteristics among airline types in the US. Journal of Air Transport Management, 72, 11-19. DOI: 10.1016/j.jairtraman.2018.06.004.

Climis, R. (2017). Factors affecting customer retention in the airline industry. Journal of Management and Business Administration, 24(4), 49-69.

Croteau, A. M., & Li, P. (2009). Critical success factors of CRM technological initiatives. Canadian Journal of Administrative Sciences, 21(1), 21-34. DOI: 10.1111/j.1936-4490.2003.tb00303.x.

EasyJet. (2019). Annual report and accounts, 2018. London, UK: EasyJet plc.

EasyJet. (2019). Results for the year ending 30 September 2019. London, UK: EasyJet plc.

Jiang, H., & Zhang, Y. (2016). An investigation of service quality, customer satisfaction, and loyalty in China’s airline market. Journal of Air Transport Management, 57(2), 80-88.

Kim, J., Hwang, H., & Suh, E. (2003) A Model for evaluating the effectiveness of CRM Using the balanced scorecard. Journal of Interactive Marketing, 17(2), 5-19. DOI: 10.1002/dir.10051

Lartey, J. (11 April 2017). United Airlines passenger violently dragged from the seat on an overbooked flight. Retrieved from https://www.theguardian.com/us-news/2017/apr/10/united-airlines-video-passenger-removed-overbooked-flight.

OAEP. (2017). Air travel consumer report. Washington, DC: U.S. Department of Transportation. Retrieved from https://www.transportation.gov/sites/dot.gov/files/docs/resources/individuals/aviation-consumer-protection/2017MarchATCR.pdf.

United airlines take home the CIO 100 award for the innovative customer volunteer program. (2 May 2029). Retrieved from https://hub.united.com/united-cio-100-award-volunteer-2636113029.html.

Xue, C. (2017). An examination and critique of the use of knowledge management in achieving and sustaining a competitive advantage in business. Research in Business and Management, 4(1), 14-28. DOI:10.5296/rbm.v4i1.10785.

Appendices

Appendix 1: Expected Financial Performance for EasyJet Case after adopting Data Driven system

Appendix 2: EasyJet Financial Performance