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Decision Support Systems Introduction Information Technology Essay

Paper Type: Free Essay Subject: Information Technology
Wordcount: 3236 words Published: 1st Jan 2015

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There are a lot of different kinds of systems needed to run big businesses. The one management uses the most is, A decision support system is a computer program application that analyzes business data and presents it so that users can make business decisions more easily.” (Rose 1) DSS is receives data and processes it into information. To make decisions quickly and efficiently based upon facts rather than instinct.

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Decision support systems are essential in today’s business world. DSS is important because it lessens the time it takes for repetitive tasks. For example, weekly reports and formats them graphically and outlines if a person has succeeded or failed in their goals. This can quickly let the user know the when, where, how, why, and what of a situation. There are many types Decision Support Systems. They are 5 main types of Decision support systems Communication, Data Driven, Document-Driven, Knowledge driven and Model Driven. (Power 1)

Communication-Driven DSS

The easiest concept is Communication Driven DSS, “Most communications-driven DSSs are targeted at internal teams, including partners. Its purpose are to help conduct a meeting, or for users to collaborate. The most common technology used to deploy the DSS is a web or client server.” (Power 1) They are several ways to use a Communication-Driven DSS but they contain key characteristics:

Communications-Driven DSS software has at least one of the following characteristics:

Enables communication between groups of people

Facilitates the sharing of information

Supports collaboration and coordination between people

Supports group decision tasks (Communications-Driven DSS 1)

They are cheaper options for new or small companies. Most people do this kind of DSS and not know it. Every business conducts “Voice Interaction” just by picking on the phone or standing next to a person and communicating the plan of action. Skype a popular program can be used for many of Communication-Driven DSS mediums. Skype has the ability to do Video Interaction, Chat or Text interaction just to name a couple. Each can be used to generate collaboration and agenda creation. The ever popular Facebook can be a very effective Communication-Driven DSS with its ability to poll questions, Meeting Management and use its forum like structure for collaboration. All a person has to do a just create a private group and use its features. One can put events for meetings and get responses if able to attend. A company’s employees can see view comments and poll question for group decisions.

Data-Driven DSS

The most common DSS is Data-Driven DSS because, “Most data-driven DSSs are targeted at managers, staff and also product/service suppliers. It is used to query a database or data warehouse to seek specific answers for specific purposes. It is deployed via a main frame system, client/server link, or via the web.”(Power 1) C:Documents and SettingsOwnerDesktop13_1_4_g3a.jpg

What are Data-Driven DSS? 29 Nov 2007. Web. 21 Feb 2013.

The Data-Driven DSS starts with data which are raw facts and then proceeds to go through the DSS system. Where it manipulates the data provides information from the raw data. Information is the structured form of data. This simply puts it into context. The data can be red, leather, Size 10, man, and the data can go on. Information then provides the context of shoes. Then it is understandable information then one can manipulate sales of said shoe broken down into sizes and color or anything. Then within the system one can see shoes are selling from sizes 10 down. Knowing this information one could then can stock more of the smaller sizes to improve floor space. This is done by queries large amount of from several resources. Like sales and inventory for our shoe example. This one is had multiple types:

There are two sub-types of data-driven DSS:

The first sub-type OLAP provides the means for interactive ad-hoc exploration of huge amounts of data to gather the information necessary for the decision.

The second one, Data-mining, provides the means for automatically find structure in the form of relations and/or patterns in large databases. (What are Data-Driven DSS 1)

OLAP (Online Analytical Processing) this is the actual software tools that manipulates the data being queried. That will give presentable and understandable information base upon the items queried. This is where one can make a decision like the shoe example by increasing shoe purchases of shoe sizes smaller than ten and decreasing purchases of shoes sizes greater than 10.

Data-Mining on the other hand finds patterns and pre-conceived connections. They find keywords with the data. For the shoe example is would match the pattern of size 10 and sales together and bring that to someone’s attention. Then one bases a decision on the results. Basic difference is that OLAP displays queried data while Data-mining is automatic displays data. They are presented in the same why but the process is different.

Document-driven DSS

Business can use this DSS to search of news about their company in other words, “Document-driven DSSs are more common, targeted at a broad base of user groups. The purpose of such a DSS is to search web pages and find documents on a specific set of keywords or search terms.” (Power 1) They are several types of Document-Driven DSS but, “They are 3 main types of Document Driven DDS: oral type or transcribed conversations, video type or news reports and television commercials and written type such as memos, reports, and emails”. (Hopkins 1)

How Google Works. n.d. Web. 21 Feb 2013.C:Documents and SettingsOwnerDesktopHow Google Works1.jpg

Any search engine uses Document-Driven DSS for searching. Search engines enable the user find key words sifting through a vast amount of data. Google has bots searching the internet for article or any piece of information added to the web. Google then estimates the reliability of the site. Then checked and penalized are applied. This is done with seconds of the site being searched. When a person searches Google its uses synonyms to look for similar words then the initial result is created. After that Google then removes duplicate pages and sorts them by page rank. User’s filters are applied and results are displayed. (Learn How Google Works: In Gory Detail 1)

Knowledge-driven DSS

The all purpose DSS is, “Knowledge-driven DSSs or ‘knowledgebase’ are they are known, are a catch-all category covering a broad range of systems covering users within the organization setting it up, but may also include others interacting with the organization – for example, consumers of a business. It is essentially used to provide management advice or to choose products/services. The typical deployment technology used to set up such systems could be silent/server systems, the web, or software running on stand-alone PCs.” (Power 1)

Knowledge Driven DSS basically gives knowledge and expertise where there is none or lacking. Turbo Tax is a kind of knowledge driven DSS. Turbo Tax gives any user the effectiveness that of an accountant would have doing taxes. One doesn’t need any prior knowledge or experience because its all with the Knowledge- Driven DSS. C:Documents and SettingsOwnerDesktop111502_sarkar_1.gif

Sarkar, Pushpak. Information Quality in the Knowledge-Driven Enterprise. 1 Nov 2002. Web. 21 Feb 2013.

From a users standpoint they can asks the DSS questions and it will give the user actions they can persue. Those actions contain the pobability of said action. Also show why and how a they arrived at a particular action. Assisting those actions they can initiate said actions within the DSS. Then users can update the KDSS with there outcomes and paths they chose. (Power 1)

This can be applied to any business related decisions. The DSS would have prior knowledge of outcomes and actions to take on any given task. Could be used from when to sell stocks to how to deal with discipline employees to buying company would benefit the business. Some Knowledge Driven DSS can train users the information contains within a particular KDSS. Company can plan complete business strategies: Long Term, Short, and Companies overall vision.

Model-driven DSS

This DSS uses semi-structured and unstructured decisions, “Model-driven DSSs are complex systems that help analyze decisions or choose between different options … These DSSs can be deployed via software/hardware in stand-alone PCs, client/server systems, or the web.”(Power 1)

Model Driven DSS uses the tools to run a system:

Decision Analysis tools – DA tools help decision makers decompose and structure problems. The aim of these tools is to help a user apply models like decision trees, multi-attribute utility models, Bayesian models, Analytical Hierarchy Process (AHP), and related models.

Forecasting Support System – A computer-based system that supports users in making and evaluating forecasts. Users can analyze a time series of data.

Linear Programming – A mathematical model for optimal solution of resource allocation problems.

Simulation – A technique for conducting one or more experiments that test various outcomes resulting from a quantitative model of a system. (Power 1)

Each plays about in developing a Model DSS System. This DSS deal with Unstructured to semi-unstructured means it’s not clear cut. Every situation is different. This is where a model DSS System comes in to play. Bank takes into account all the necessary to inform them to decide if they will loan the person the money. They also what terms and condition if they do loan them money. All this is decided in simulation, linear programming, forecasting, and decision Analysis tools.

DSS Effectiveness

Having a DSS system doesn’t improve outcomes, “The distinction between effectiveness of decision-making and efficiency in decision-making helps DSS analysts understand the impact of DSS on decision behavior.”(Power 1) A bad DSS meaning ineffective design can actually hurt the user’s decisions. DSS has to be used and improve effectively to work as desired. Also the design has to affect the company’s views.

If the DSS is design required for profit first and customer second could hurt the company in the long run. The decision of how it ranks decision choices is important. DSS has some information but needs to be updated on current procedures and outcomes. In other words, in the past it might have worked firing people to make a bigger profit. This improves the company’s short term but having to retrain and loss of progress will hurt the company in the long run.

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This goes for any outdated decision also each decision tried needs to be reviewed. When firing people starts heading into an unfavorable outcome it needs to be revalued. The DSS needs to be nurtured into an effective system. Not all decision work flawlessly and need to have more than one solution for each question. A fully capable DSS can make effective use out of anyone. It will have the combined knowledge of the management staff. So any inexperienced manager can still make effective decisions. It is only as effective as the logic behind it and the information being put in the system.

Decision Impacts

Decision can impact a company’s financial future. Current business decision practice takes into account a wide range of information and statistics. Failure to account and use all the available tools in the company’s arsenal can hinder effective business decisions:

Poor assumptions can be traced back to any of the following

Failure to properly account for changes in input or energy costs

Not fully understanding how marginal pricing and marketing projections for growth impact profitability

Not fully understanding how fixed costs vary with the volume of different product groups

Assuming or neglecting to evaluate impact on working capital

Ignoring important constraints (e.g., Wall Street expectations, emission credit requirements, tax rates, etc.) : (Power 1)

A DSS designed effectively can take into account all necessary information. This won’t let the user forget anything that might affect any particular decision. A DSS can take everything into account. Then let the user weight or take out pieces that shouldn’t be included in the decision making process. This goes into the tools that Managers can use:

Managers can understand the best choices from a universe of choices.

More insight through: what-if analysis; simulation/sensitivity analysis; optimization to any variable or objective function; infeasibility and “next best alternative”

More impact through: full set of metrics and KPIs; resource allocation guidelines; alignment of targets and incentives

More flexibility through: fast structuring and analysis of scenarios with multiple variables; easy to store, retrieve, analyze, and share (Centurion)

A functional DSS system lets the user accomplish these takes faster and more efficiently. This also reduces errors in calculation. This way of decision making greatly speeds up the decision making process. C:Documents and SettingsOwnerDesktopchart.jpg

Centurion, Carlos. Impacts of Business Planning Technology. 31 August 2009. Web. 25 Feb 2013.

Pros of a DSS System

The benefits of a DSS system:

Saving of human time due to computational speed.


Providing the expertise of many medical professionals at the user’s fingertips without the cost.


Helping inexperienced staff make decisions and hence increasing their confidence.


Helping experienced staff in situations / decisions that are too complex for them to handle alone.


Providing an invaluable learning resource to medical students, incorporating the elements of realism and so giving them experience.


Enabling medical evidence to be found quickly.


Alerting staff when something occurs even if they did not explicitly ask to do so and so act as a supervisor to prevent them from making a wrong decision. (PROS AND CONS OF DECISION SUPPORT SYSTEMS 1)

C:Documents and SettingsOwnerDesktopIN4_clip_image002.jpg


DSS system free up employees for other tasks. Provides expertise without having to hire one to train or teach employees. A DSS can supply sound decisions to inexperience personnel. Can be used in lieu of a decision making team. A Warning can be triggered to prevent mistakes.

Summary – Conclusion

Decision Support Systems puts data into information this helps the user make an effective decision. This is shown in many ways. It formats data into understandable information so anyone is able to make a decision. They can have multiple paths for any decision. This can be useful in determining who path is best for which decision. All DSS are the same because of they are intended to help the user make effective decisions, regardless of experience. DSS are different because of how they gather the information. They make time consuming decisions in a matter of seconds because all the information can but computed as fast as a computer can process it.

Communication Driven DDS (CDDS) are used in the business world on daily basis. It is even used in not business instances. They are many free effective CDDS they might not encompass all mediums but are effective. Skype is a cheap why to communicate between teams using voice, chat, and browsing. Combined with Facebook and its utilities for events, schedules and forums like ability. People use this method of DSS when they are playing games online. The fast past game require fast and effective decisions making that a CDDS provides.

The most common DSS in the business world is Data Driven DSS. This DSS searches gathered information stored in a database or data warehouse for the data. The data is gathered from as many databases or data warehouses as needed for the decision. It can be used for performance in sales over cost. Meaning the user can determine its worth of keeping an item valued at 20$ that can be sold for $100 but is takes 2 months to sell it. Over an item that’s valued 35$ but be sold for $50 but the turnover is one a week. Going with the latter will net the company 20$ more with higher foot traffic in the company’s store. It also depends on several other factors which choice the company will pick. The DSS will show the company the comparison and they can make a decision about it.

As stated before a Document Driven DSS can be used for searching within documents for keywords. Search engine is the best example of this DSS in action. They scour the web for any added content for one’s search. They rate it by usefulness, Accuracy, and reliability of the information. Then they rank those results after they apply personal filters for user’s search. This can be used to place ads within user’s mailbox and even place them on one’s Facebook. The ethical aspect of the DSS in based on design and use.

A Knowledge Driven DSS is a multi-purpose DSS. This is based on experience this combines knowledge of passed outcomes. This DSS is able to teach management and employees alike. Allows people to see passed decisions and how they turn out. Shows how the company does business with other businesses. It can encompass anything the business has a procedure or desired outcome of many situations. The knowledge databases needs to be constantly containing current information to be effective.

Module Driven DSS are for what if situations. It has a lot of math behind its decision making process. Decision Analysis tools, Forecasting Support System, and Linear Programming Simulation are the components of a Model Driven DDS. It deals with a lot of what could happen in the future based upon past statistics. They can manipulate the information and see how it plays out. In graphical display that a user can see if the user’s decision is going to improve or not and what is the cause of the result.

The effectiveness of a DSS is based on design. If they gather the necessary information needed the how, what, when, where, why, and who of the system to be designed. It also has to implement the company’s views such as customer stance, political stance, and if there is a bias stance of the decision. The overall effectiveness is based on the design of the system and the information it uses to process decisions.

DSS is a faster more efficient way to make decisions, especially for the company’s future. One can manipulate the information where one can set plans if they succeed. They can push their success. If they fail one can mitigate their losses. This can be a very effective planning tool.


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