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Warehousing Book For An Airlines Essay

The results of this effort needs to be shared electronically online to ensure everyone is kept informed about its progress. Memo:

With the data warehouse project entering the requirements definition phase, it's important to start setting the foundation for users across the network of retail stores to begin having ownership of the new system. Getting them interested in the new data warehouse, and to take ownership of it will require getting their inputs early on during the requirements definition phase.

I'd like to suggest the following steps be taken to ensure their needs are captured as part of the requirements definition phase:

1. Create an online, protected portal and have a series of questions and applications on it to give each store user a chance to contribute to not only the content of the new data warehouse, but its usability as well. Use this data as a means to create bi-weekly conference calls to discuss the status of the data-warehousing project.

2. Enroll each store in Skype and get budget to make sure they can all participate on video conferences with regard to the user interface design and contents of the data warehouse. This will be critical for ensuring each person has an opportunity to contribute to the process as well.

3. Post the matrix of all user needs and show the date and revision fo the data warehouse when their needs were included in the design. Also be sure to recognize with praise and recognition those users in each retail store who work hard to provide feedback.

4. Give the stores an opportunity to work with early beta versions of the data warehouse software and the interfaces used for querying and using it. This will also provide a greater level of ownership as well.

5. Sponsor a contest to see which user in which store can create the best tutorial demo. Whoever wins gets to go around to all the stores and host training, at the company's expense and also gets a weekend in any city of their choice also on the company. This will drive up ownership of the data warehouse immediately and will also lead to competition to learn as much as possible.

Remember the challenge is to get the users in each store to change their behavior and support the new data warehouse initiative. Taking these steps will lead to much greater levels of ownership in the project.

Business Intelligence Text -- Cases.

Question 4-page 27 - What benefits are being derived from this initiative?

Vodaphone's many benefits of creating an enterprise data warehouse (EDW) include gaining greater accuracy and precision in the marketing, selling and customer churn reduction strategies, in addition to increasing profit margins over time. The company had also been facing a stagnating 56% market share, yet with the insights gained from the EDW and the business intelligence applications it supports, Vodaphone was able to determine the best possible message to deliver to the right customers at the right time. The formation of the customer knowledge and analysis department also served as a catalyst for more effective customer offer optimization, campaign effectiveness analysis, customer insights and the development of trigger-based marketing campaigns as well.

Question 5-page 78 - What strategic advantage can Continental derive from the real-time system as opposed to a traditional information system?

Continental was able to transform their entire business model based on the real-time systems they evolved their EDW into from their traditional information systems. The creation of the Go Forward plan and a data warehousing award presented in 2004 (Johnson, 2004) solidified the company's position as a leader in the area of BI and analytics for retaining and growing airline customers. The strategic advantage of real-time systems was most valuable...

The benefits of the real time system soon became significant with fraud detection saving the company $7M and greater accuracy in demand forecasting and tracking also serving as a catalyst of accelerated growth. In total, the real-time systems became an essential catalyst in the turn-around the Continental and saved them from having to file for bankruptcy a third time. It was the catalyst of the business model also focusing first on customers, trimming costs to serve them better instead of being only concerned with trimming expenses alone.
Question 6-page 127 - What can businesses learn from a government initiative like the CPR?

There are many lessons learned about how best to integrate analytics and BI into the daily workflows of businesses, in addition to normalizing and aggregating massive amounts of data so it can be effectively used. The CPR initiative provides insights into how metro-wide EDW and data marts can be created and maintained to fulfill the needs of a diverse user base. Included are performance management applications, analytics and dashboards configurable for specific reporting requirements, and data definition analysis of key variables and attributes as well. An excellent lesson learned is the metrics and key performance indicators (KPIs) only matter when they are in the context of promoting collaboration and knowledge transfer. As the case alludes to, when this happens the entire organization benefits and decision outcomes improve due to data accuracy. The need for creating data warehouses as a catalyst of collaboration and rewarding shared task ownership and accomplishment through the use of the data is also evident. The case shows how a government agency can cut through bureaucracy by being goal-centered in their approach to managing data.

References

Birkner, C.. (2008, September). Hedges in flight. Futures, 37(10), 68-69.

Colleen Cunningham, Il-Yeol Song, & Peter P. Chen. (2006). Data Warehouse Design to Support Customer Relationship Management Analyses. Journal of Database Management, 17(2), 62-84.

Phillip Britt. (2007, January). Analyzing Business Turnaround. Customer Relationship Management, 11(1), 14.

Dev, C., Buschman, J., & Bowen, J.. (2010). Hospitality Marketing: A Retrospective Analysis (1960-2010) and Predictions (2010-2020). Cornell Hospitality Quarterly, 51(4), 459.

Johnson, L.. (2004). Strategies for Data Warehousing. MIT Sloan Management Review, 45(3), 9-9.

Ku, E., & Fan, Y.. (2009). Knowledge sharing and customer relationship management in the travel service alliances. Total Quality Management & Business Excellence, 20(12), 1407.

Fay Cobb Payton, & Debra Zahay. (2005). Why doesn't marketing use the corporate data warehouse? The role of trust and quality in adoption of data-warehousing technology for CRM applications. The Journal of Business & Industrial Marketing, 20(4/5), 237-244.

Zhiguang Qian, Wei Jiang, & Kwok-Leung Tsul. (2006). Churn detection via customer profile modeling. International Journal of Production Research, 44(14), 2913-2933.

Yi Ming Tseng. (2007). The Impacts of Relationship Marketing Tactics on Relationship Quality in Service Industry. The Business Review, Cambridge, 7(2), 310-314.

Hugh J. Watson. (2005, July). Real Time: The Next Generation of Decision-Support Data Management. Business Intelligence Journal, 10(3), 4-6.

Hugh J. Watson, Barbara H. Wixom, Jeffrey a Hoffer, Ron Anderson-Lehman, & Anne Marie Reynolds. (2009, December). Real-Time Business Intelligence: Best practices at Continental Airlines. EDPACS, 40(6), 1-16

Wong, J., &…

Sources used in this document:
References

Birkner, C.. (2008, September). Hedges in flight. Futures, 37(10), 68-69.

Colleen Cunningham, Il-Yeol Song, & Peter P. Chen. (2006). Data Warehouse Design to Support Customer Relationship Management Analyses. Journal of Database Management, 17(2), 62-84.

Phillip Britt. (2007, January). Analyzing Business Turnaround. Customer Relationship Management, 11(1), 14.

Dev, C., Buschman, J., & Bowen, J.. (2010). Hospitality Marketing: A Retrospective Analysis (1960-2010) and Predictions (2010-2020). Cornell Hospitality Quarterly, 51(4), 459.
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