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Information Management System Essay

1. What does the database information reveal about the current business situation? The hotel reservation system database takes into account the various room types which are most preferred by the customers. The full exploitation of the information system database is done at this stage. It is found that using database queries and aggregation, the “Ocean room” type is the most occupied rooms in all seasons whereas the “bay window” room type is the least occupied. The database takes into account the business data which is evaluated for a series of records.

2. Which specific business strategies might be pursued to increase room occupancy and revenue? Room occupancy is an aspect which needs to be studied over a period of time and then devise a strategy to tackle it. The information system must be made more analytical to tap the various customer preferences and analyze the dynamic behavior with respect to price and season. Such analysis is done using multi-dimensional database system which would analyze customer preference trend with respect to the various parameters taken into picture.

Business Intelligence software’s can be used for such purposes. Upon analysis of the various factors it is decided that the price and season are some of

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the dynamic parameters which must be strategized for a better occupancy of prices. Revenue can be increased by way of promotions and special occasions which can be made available to the favorite customers or frequent customers. Such privileges would ensure better grooming of customer for their acquiring, retention and innovation.

The hotel can use supply chain management (SCM) software to address the needs of the customers and the external entities to effectively manage the data transfer among the departments like Room Service, kitchen, Musical floor, Dining, Bar, Booth and office. The CRM software would ensure better handling the customers’ requests (Cooper, 2003). The hotel would be able to seamlessly interconnect its departments for enabling the reduction of cost and effort of the resources. It would not only foster better relationship among departments but would enhance communication and ability to manage conflict and change in the organization.

3. How could the database be improved to provide better information for strategic decisions? Effective data collection of the customer’s preferences, hotels sales, and marketing and promotion factors can even out a strategy for framing a better correlation among the various variables which impact their growth and customer service. The online analytical processing (OLAP) capabilities in a database, like that of Oracle Warehouse Builder or SQL Query Analyzer or Pentaho (open source) can be used for better data analysis.

The customer data and hotel sales data must perform trend analysis to know the shifting preferences of the customers and the hotel’s initiative towards customer reference (Levinson, 2007). Strategic decisions towards spending out can be decided well only if enough analysis is done on the stored data. The hotel would be able to expose what prices the customers prefer, what season is best for promotion, which customers would be given a priority, what extra facilities which it may imbibe to fetch more customers and work for their retention.

Such decisions enable better market and competitive advantage for the hotel. The primary objective is kept clear when it comes to fetching data. Large database collection with irrelevant data does not make sense. Knowing what is required by the top level managers would bring enough specificity in approach towards data collection and cleansing. Appropriate focus on right methods would reduce effort and time to invest in other avenues which brings forth better results and performance for data collection and analysis.


Cooper, M. C (2003). Characteristics of Supply Chain Management and the Implications for Purchasing and Logistics Strategy. The International Journal of Logistics Management, 4, 2, 13-24. Cummins, FA (2002). Enterprise Integration: An Architecture for Enterprise Application and Systems Integration. John Wiley & Sons, Inc. New York, NY, USA. Levinson, Meridith (2007). Retrieved 1, March 2009 from http://www. cio. com/article/109454/The_Brain_Behind_the_Big_Bad_Burger_and_Other_Tales_of_Business_Intelligence.

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