Question

Describe how Decision support systems /business intelligence technologies and tools can aid in each phase of decision making

Answer 1

Answer: Decision making is the process of developing and analyzing alternative data to make a decision – choose an option from the available alternatives. Most decisions are made in response to a problem – a difference between a desirable and an actual decision and involve judgment – the cognitive feature of the decision-making process. Decisions can be two types- programmed or non-programmed. Programmed decisions are routine and can be solved through clear-cut mechanical procedures, such as applying rules to find the best solution. Most management decisions are programmed. Non-programmed decisions are nonrecurring and they are often made under conditions that involve so much ambiguity that specific programs are not available. Although each group of decision’s domain is specific and time demandingness, we can find common tools and principles for making better decisions.

Decision Support System- Most computer systems support decision making because all software programs take automating steps of decision that people would take.

Data-Driven DSS- Data warehousing and analysis systems. Executive information systems and Geographic Information Systems, managing report System. Data-driven DSS stress access to and manipulation of a large number of databases of structured data and especially a time-series of internal data of the company and sometimes external data.

Knowledge-Driven DSS- This DSS can suggest or recommend actions to managers about what should he do. These DSS are personal-computer systems with specific problem-solving expertise. The “expertise” means knowledge about a specific domain, understanding of problems within that domain and “skill” at solving some of these types of problems. This concept is related to Data Mining. These are analytical applications that search for hidden patterns in a database. Data mining is the process of sifting through huge data to produce data content relationships. Data Mining tools can be used to create Knowledge-Driven and hybrid data-driven DSS.

Document driven DSS- These types of DSS integrates a variety of storage and processing technologies to provide complete document analysis and retrieval. A search engine is a powerful decision-aiding tool related to this type of DSS.

Model-Driven DSS- It includes user accounting, financial models, representational models, and optimization models. This type of DSS uses data and parameters provided by decision-making to aid them in analyzing a situation, but they are not usually data concentrated.

Communication Driven and group DSS- It includes communication, collaboration, and coordination and GDSS mainly focuses on supporting groups of decision-makers to analyze a problem and performing group decision making jobs.

BI-Business Intelligence- BI is a new term in IT, the meaning of this varies from context to context. BI describes a set of concepts and methods to improve business decision making by using the fact-based support system. There are different views that describe BI as a successor of DSS. It is the next generation of DSS considers in some articles. BI provides users with the ability to easily extract data from one or more different sources and subject matters. Format the data for a report or representation is also easier. Applications of BI provide users with the capability of multidimensional analysis. For example- users can drill down their income statement moving from net sales to sales by product and finally, to sales by customer/region. This capability provides users with the ability to answer questions such as: Which geographic regions did we sell the most and the least products? Who are the top customers by-product?