COMP8016 - BUSINESS DATA ENGINEERING - T7283 – INDIVIDUAL ASSIGNMENT I

Name : Wachyu Danyanto NIM : 1701533915 Class : LTA2-LEC

BUSINESS DATA ENGINEERING – INDIVIDUAL ASSIGNMENT I Questions and Answer: 1.

What were the problems faced by Continental Airlines? Ten years ago Continental Airlines have major problems in their services such as: on-time performance, mishandled luggage, many complaints from customers and overbooking because they lacked of infrastructure and real-time information they need to have insight about their airlines businesses, we summarized it as data latency (delayed data) caused analysis latency (delayed information) that have major impact on decision latency (delayed action), so it caused major losses in revenue and value of the businesses (Anderson-Lehman, Watson, Wixom, & Hoffer, 2004; Watson, Wixom, Hoffer, Anderson-Lehman, & Reynolds, 2006).

2.

What was the strategy (business and technology) taken by Continental Airlines to resolve the problem? The first business strategy they made to resolve the problem was to built and develop an enterprise data warehouse (EDW) system to provide an accurate and integrated data for revenue management with three data warehouse applications (Anderson-Lehman et al., 2004) : 

Demand-driven dispatch Combining forecast information from revenue management data mart with flight schedule data to identify opportunities for maximizing aircraft usage which will give estimated $5 million a year of incremental revenue.

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Goodwill letters Building customer loyalty with regular written communication which will increase additional $6 million revenues and giving top 10 percent information of Continental Airlines’s customers.

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Group Snoop Enhancement in group booking and reservation, by using booking and agency data, this application can identify and assess seat inventory accurately and estimated $2 million of annual savings. The second business strategy was to built Real-time Business Intelligence Applications using real-time

data in minutes to hourly and integrating within the Data Warehouse system (Anderson-Lehman et al., 2004) and divided into five categories (Watson et al., 2006): 

Revenue management and accounting.

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Customer relationship management.

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Crew operations and payroll.

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Security and fraud.

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Flight operations.

Name : Wachyu Danyanto NIM : 1701533915 Class : LTA2-LEC

Figure 1 Data Warehouse Architecture (Anderson-Lehman et al., 2004)

Technology used by Continental Airlines: 

Hardware: 3 GHz, 10 node NCR 5380 server.

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Software: Teradata Warehouse, Teradata QueryMan, Microsoft Excel, Microsoft Access, Hyperion Intelligence, SAS Clementine for data mining, Teradata CRM for campaign management, and custom built application.

3.

How was the solution justified? What were the key investment consideration? Solution justified by involvement and sponsorship of top and senior management, strategies alignment between business and IT, selection of best technologies, clear vision, mission and business roadmap and let the technology follows the business. Key investment divided into $20 million invested for Hardware and Software and $10 million invested in personnel, so the total investment has reach around $30 million, with estimation $500 million increased in revenues and cost saving, and achieved ROI over 1000 percent in the six years of period (Anderson-Lehman et al., 2004).

4.

What are the key takeaways for you personally? Development and investment in Real-time Business Intelligence and Data Warehouse Application which include DSS, OLAP, EIS, and Data Mining for supporting business strategy will have major benefit in business decision making on increasing business value and generating more business profit and revenue.

References: Anderson-Lehman, R., Watson, H. J., Wixom, B. H., & Hoffer, J. A. (2004). Continental Airlines Flies High With Real-Time Business Intelligence. MIS Quarterly Executive, 3(4), 163–176. Watson, H. J., Wixom, B. H., Hoffer, J. a., Anderson-Lehman, R., & Reynolds, A. M. (2006). Real-Time Business Intelligence: Best Practices at Continental Airlines. Information Systems Management, 23(1), 7–18. http://doi.org/10.1201/1078.10580530/45769.23.1.20061201/91768.2