Decision Support System - Report Example

TABLE OF CONTENTS INTRODUCTION 2. SCOPE 3. DECISION SUPPORT SYSTEM RULE BASED SYSTEM 3. MODEL BASED SYSTEM 3. STATISTICS BASED SYSTEM 3. 4. REQUIREMENTS OF DSS 5. AN IDEAL DSS MODEL 6. PROPOSED DSS DEVELOPMENT CYCLE 7. ANALYSIS BASED ON SPREAD SHEETS AND BAR CHARTS. OLD RECORDS HOUSEKEEPING BAR DETAILS OF EXPENSES. 8. TESTING INTRODUCTION As the technology matures and as its implications are worked out we identify ways to implement and manage it. There a variety of categories and disciplines we could address. Our main focus is on implementing Decision Support System (DSS) technology in managing the Maurer Hotel. There are a number of tools developed but, what is important is how effectively we utilize them in the process of decision making, particularly where information is uncertain or incomplete. DSS is one such tool which has a number of approaches each of which assists the process in different ways. It was traditionally aimed at managers to assist in high level decision making. The present project focuses on implementation of one of the DSS techniques in running a group of Hotels or rather implementing this tool in effective management. The details of various entities that change everyday in the hotel have been collected. Mrs. Danver presented the parameters that need to manipulate or rather clearly needs observation and statistical analysis for taking further decisions. The data in hand is sorted and the steps laid according to DSS are followed such that data when put in Excel sheets and their linking bar charts help to take further decisions towards the benefit of the hotel. A different category of data that is collected at Hotel Maurer is also presented. As the management issues of a Hotel are large in number taking into consideration of all the entities would make it laborious so few categories like Finance, Housekeeping, Bar, Staff, Restaurant and Old records are focused mainly. SCOPE The project is in partial fulfillment of the Degree addressing everyone who is interested to use its application and also for those who are interested in studying its technical where about DECISION SUPPORT SYSTEM Decision Support System is a tool used to improve the process of decision making in complex systems, in particular where information is uncertain or incomplete.“It can range from a system to answer simple queries that allow a subsequent decision to be made, to a system that provides detailed querying across a spectrum of related datasets. It was traditionally aimed at managers to assist in high-level decision-making” (Tatnall,2002). Any given DSS can be tailored to provide features across a spectrum of users to ensure the system is accessible at the right level for different audiences and to provide only the information appropriate for confidentiality and security purposes. DSS has a number of generic stages: Gathering of data and collation. Storage of data, accessing and mining. Analysis of the data. Reporting of the data There are many ways in which these are implemented. Simple query tools can provide one level of support. The more complex systems employ some form of artificial intelligence. There are many approaches to this three of them are: 1. Rule based systems. 2. Model based systems. 3. Statistical/probabilistic based systems. RULE BASED SYSTEM This is often called as ‘expert systems’ or ‘knowledge based systems’. These systems contain a database of information with a semantic content, allowing relationships to be defined between the data. A ‘rules’ database is devised which encapsulates the semantic relationships. One of the areas where this could be used is Pharmaceutical Department. MODEL BASED SYSTEM This system derives answers to questions by taking input from the user, then combines this information in the data storage and then runs analytical model of the data. This model can be very simple, such as plotting a series of curves in Microsoft Excel and choosing the one with a fitted parameter above a particular threshold, or can be very complicated, such, such as solving differential equations in one, two or three dimensions, perhaps as a function of time. “The scope of any given system is closely defined; an analytical model has a predefined application area, but the questions range may still be complex because the model has a certain amount of freedom and many possible constraints” ( Burgess, 2005). This system is useful where empirical information is either not available or not appropriate to a particular application area. STATISTIC BASED SYSTEMS The system is based on ‘Bayesian Statistics’. This type of approach involves the development of ‘belief networks’ to model the system and its properties. Each of them is assigned likelihood probabilities and are linked through conditional probabilities which means what are the probabilities that property A will take particular values, given the value of property B. the resultant network is complex web of influences and conditional probabilities. The values of the probabilities are initially ‘guessed’, either based on historical data or professional and technical intuition. Bayesian Theory now allows refinement of the probabilities and the network as a whole, as more details of the system are obtained. The ‘answers’ to questions are then depend on a ‘most probable’ or ‘least probability basis. REQUIREMENTS OF DSS Data classification and gathering is the first essential stage in developing DSS. Depending on the particular nature of the project the approach to data gathering may vary which requires Clear definition of problem to be solved, its scope and bounds. Intricate knowledge of the business domain, facilitating identification of the data to be gathered. A process that identifies and defines the rules relating to the parameters of the data. Data acquisition can be used in different contexts with DSS: As part of the system process ‘pipeline’, continually feeding into the data gathering process for a DSS. As a part of the working of a DSS providing direct input into the model. AN IDEAL DSS DEVELOPMENT MODEL Figure1. An ideal DSS model when studied thoroughly can be understood as follows; regarding Model Analysis our model to manage a group of Hotels needs details collected and put in Excel Sheets to clearly illustrate How much? What questions are to be answered by Mrs. Danvers? Knowledge Document data includes the IT requirements of DSS, data acquisition methods and so on. User Interface is different for different applications but, in our model we have used MS Excel or spread sheet mode, it gives a crystal clear break down patterns of data which can be utilized in understanding a periodic or abrupt increase or decrease in trends which helps in taking proper decisions for the betterment of the business. Communication networks include through which way Mrs. Danver going to view her data of the present is running Hotels and other needed particulars of the Hotel. PROPOSED DSS DEVELOPMENT CYCLE Figure 2. When we scan through the figure above we find that to access connectivity and accessibility we have various options like CD ROM, Internet, Mobile phones, Television, Telephones and few more. But, we in the present scenario are using internet and mobile phones for our accessibility and connectivity. The web based connectivity allows access anywhere and everywhere access in the 21st century generation. The question arises how the target needs to be answered. First let us define who the target audience is? In our model its Mrs. Danver and any other Manager or an Administrator who wishes to use software which could help in intelligent decision making. For this decision making we are using a technology developed in 1960’s which would require designing of a module content, which is done immediately after collecting data from the visit of the Hotel and later collected the requirements of DSS though books and internet. The terminology is learnt and used properly wherever needed in its right sense. Basically the ease of navigation, consistency and uniformity are maintained. The format is based on Harvard style. The model shall be modified based on feed back. In general the requirements of the customer are studied and analyzed. The following figure guides in how to follow up in step by step procedure for a better conclusion on the task at hand Figure 3. Based on above mentioned methodologies putting into practice we devise the data into Excel sheets and based on the Bar charts or flow charts the proper decision making is assisted. There are many categories or departments of a hotel which are dealt by Mrs. Danver, including them all is out of scope of this module, we are concentrating in guiding her to take intelligent decisions for which we are developing a software Based on DSS which when applied in primary areas such as House Keeping, Bar, Restaurant, Finance have given the following details: OLD RECORDS SUMMER NAME OF THE CUSTOMER NO.OF DAYS ON STAY TYPE OF FOOD PREFERED FEEDBACK Mrs & Mr. T.J.Berndt. 7 GREEN SALAD GOOD Mrs & Mr.D.T.Wegener 4 FRIED FOOD BETTER Mr.R.E.Petty 7 GREEN SALAD BEST Mrs & Mr.M.H.Kernis 6 FRUITS BASED BEST Mr.D.P.Cornell 9 NON-VEG BEST Mrs & Mr.C.R.Sun 3 GREEN SALAD GOOD Mrs & Mr.A. Berry 7 GREEN SALAD BEST Mr.T.Harlow 9 FRIED FOOD BEST TOTAL NO.OF STAY IN SUMMER(AVERAGE) 52 WINTER Mr.M.Harris 3 NON-VEG GOOD Mrs.&Mr.E.Karper 2 FRIED FOOD GOOD Mrs.&Mr.G. Stacks 5 FRIED FOOD GOOD Mr.D.Hoffman 4 FRIED FOOD BETTER Mr.R.DeNiro 6 GREEN SALAD BETTER Mrs.&Mr.P.Cruz 2 NON-VEG GOOD Mr.K.Keefe 3 NON-VEG BETTER TOTAL NO.OF STAY IN WINTER (AVERAGE) 25 SPRING Wegener, D. T 5 FRIED FOOD GOOD Kerr, N. L 3 FRIED FOOD BETTER Fleming, M. A 6 NON VEG BETTER Petty, R. E. 3 NON VEG GOOD Klein, D. J 1 FRIED FOOD BETTER Harlow, H. F. 2 GREEN SALAD BETTER Scruton, R. 4 FRIED FOOD BETTER TOTAL NO.OF STAY IN WINTER (AVERAGE) 24 OLD RECORDS: Regular polishing of metals like silver and brass makes them glow and last forever. Similarly regular reviewing of the records in a business and rectifying loopholes if any will make business grow without any haphazard. The old records give a view over the season to more concentrate on. We found summer season is more preferred by the customers as the Hotel is near seashore which gives them a serene view from the room itself and easy accessible to any other tourism spot. Winter and spring were preferred less. During summer fresh salads are in vogue so, Mrs. Danver would make a right choice of hiring in few more good chefs who are experts in this particular type of food. Salads are usually boring to kids, any new food festival arranged during summer especially for kids for example make a Mickey Model from all kinds of vegetables, arranging eating contests for salads which not only imbibes good eating habits in kids but also increases the reputation of the Hotel which might draw good sponsors so that the revenue could increase. This will fill the crest in revenue during the other two seasons. Monitoring the progress for every week will give a view of the dents and stake holders to rectify and be cautious for any unavoidable situations. The feedback of each customer is very essential in retaining the customer’s good will. The feedback given should be thoroughly read and communicated if needed by the customer and appropriate changes be made. For example if a complaints about the neatness check with the housekeeping department, if a customer complaints about the food quality immediately check with the kitchen and chef on duty because this department is the heart of the business. HOUSE KEEPING Date Day Staff working(num) Absent staff Num_of rooms checked out Num_of_rooms_cleaned Total_left_uncleaned 1/1/2001 Monday 70 2 65 63 2 2/1/2001 Tuesday 71 1 81 80 1 3/1/2001 Wednesday 70 2 99 90 9 4/1/2001 Thursday 64 8 76 66 10 5/1/2001 Friday 72 0 53 53 0 6/1/2001 Saturday 62 10 32 31 1 7/1/2001 Sunday 61 11 97 77 1 8/1/2001 Monday 69 3 33 30 3 9/1/2001 Tuesday 68 4 64 61 3 Presentation is one such tool which will surpass some of the minute defaults if occur. House keeping comes under this category. The above data is for a span of a week which shows that Friday, Saturday and Sunday needs attention as the staff is deficient these days. This might cause inconvenience to the customers and to the reputation of the Hotel. BAR BAR DETAILS DATE NAME OF BRAND NO.OF TIMES SERVED AMOUNT TENDERED($) AMOUNT RECEIVED($) 1/1/2001 WHISKY 5 800 800 2/1/2001 VODKA 1 200 200 3/1/2001 BEER 4 100 100 4/1/2001 WHISKY 1 700 700 5/1/2001 FRENCH WINE 8 1000 1000 6/1/2001 FRENCH WINE 9 1100 1100 7/1/2001 FRENCH WINE 5 1500 1500 8/1/2001 WHISKY 6 900 900 9/1/2001 WHISKY 2 200 200 The above formatted data shows that the French wine is in demand for the week so getting ready for any emergency or for next week stocks it is to be ordered more in number. As Mrs.Danver left it to the staff to decide on Menu this analysis makes it eas for them to order particular drink next week. DETAILS OF EXPENSES DETAILS OF EXPENSES The above data gives us a clear information that the Salaries and wages occupy the major share in companies expenses so she would better control in this area. Reducing wages would not be the solution rather changing the salary format to salary based performance would benefit both the company and the employee. TESTING The complexity of the project is more in finding the entities than developing it. So, Testing is done manually possing various values to the entities in the spread sheets. The report presented is based on implementation of DSS in managing the Hotel Business by Mrs. Danver. Suggestions are given after every chart to benefit the growth of the business. REFERENCE Hanna, M.M., Ahuja, R, K. & Winston, W. L. (2003). Developing spread sheet based decision support system using VBA for Excel. Gainesville, USA: Innovation Centre. Holsapple, C. W. & Whinston, A.B. (2005). Decision support systems – A knowledge based approach. Retrieved Feb 2005, from http://www.uk.edu/businessEconomics/dssakba/instmat.htm Monash University. (2005). Monash DSS lab. Retrieved Feb 2005, from http://dsslab.sims.monash .edu.au Palocsay, S.W. & Markham, I. S. 92002. Teaching spread sheet based Decision Support systems with Visual Basic for applications. Information Technology, Learning and performance Journal, 20(1), 27-35. Power. D. J. (2003, 31 May). A brief history of Decision support systems (Version 2.8). Retrieved Feb 2005, from http:// DSSResources.com/history/dsshistory.html Power. D, J. & Kaparthi, S.(20020.Building Web based decision support systems. Studies in informatics and control, 11(4), 291-303. Ragsdale, C. T. (2001). Teaching management science with spread sheets: from decision models to decision support. INFORMS Transactions on Education, 1(2). Tatnall, A., Ed. (2005). Web portals: The new gateways for internet information services. Hershey, PA, Idea group Publishing. Tatnall, A., Davey, B., Burgess, S., Davison, A. & Wenn, A. (2002). Management Information systems-concepts, issues, tools and applications. Melbourne: Data Publishing. Read More