1. Information Retrieval:

Information retrieval in DSS environment refers to the act of extracting information from a database for the purpose of making decisions. Usually, the sequence of retrievals made by the user is unanticipated. For example, the manager may see a few startling pieces of information on the display and, as a result of these, suddenly produce a report that provides more detail about the situation.

2. Data Reconfiguration:

Often managers using a DSS want information in a form other that that in which the data are logically represented within the computer system. The ability to reconfigure data makes it possible for managers and other decision makers to look at existing data from alternative perspectives are, sorting, exchanging fields, joining, and presentation graphics.

a. Sorting:

Sorting data Involves rearranging records in a file or a subset of a file so that they appear in a specific order.

b. Exchanging Fields:

Exchanging fields or columns is another method available for reconfiguring data. You can hide or replace the position of the column so that they can appear in the order which you think is useful.

c. Joining:

Joining enables users to cut and paste data from different existing logical files to form a new logical file.

d. Presentation Graphics:

Presentation graphic tools allow users to put data into a graphical form that can be easily understood. When working with graphics, users will typically have a choice of several types of graphs or charts, as well as coloring and pattern designs for each graphic element.

3. Calculator Activities:

Calculator activities refer to the set of tasks that normally can be done with a calculator. These activities are generally implemented either by heaving the user write out a complete formula, specifying all the variables involved and how arithmetic operations should be performed on them, or by having the set of functions resident in the DSS or DSS tools the DSS or DSS tools.

Arithmetic & Statistical Functions:

Arithmetic & Statistical Functions
SUM	Calculate the sum of several numbers
MAX	Finds the highest value among several numbers
MIN	Finds the lowest value among several numbers
COUNT	Counts the number of cells
AVERAGE	Calculate the average of several numbers
STD	Calculate the standard deviation of several numbers
SQRT	Calculate the square root
ABS	Calculate the absolute value of a cell
LOG	Calculate base 10 log of constant or variable
	Financial Functions
PV	Calculate the present value
NPV	Calculates the net present value of an Investment by using a discount rate and a series of future payments
FV	Returns the future value of an investment based on periodic, constant payments and a constant interest rate.
PMT	Calculates the payment for a loan based on constant payments and a constant Interest rate.
	Conditional Functions
IF	Selects an alternative based on whether the condition is true or false
COUNTIF	Counts the number of cells within a range that meet the given criteria.
HLOOKUP	Searches for a value In the top row of a table or an array of values, and then returns a value In the same column from a row you specify In the table or array
	Date Functions
TODAY	Returns the serial number of the current date. The serial number is the date-time code used by Microsoft Excel for date and time calculations.
NOW	Returns the serial number of the current date and time.
DATE	Returns the sequential serial number that represents a particular date

a. Functions:

Functions are pre-stored formulas that enable a user to perform a calculator type task as soon as the function is invoked, using a function, for instance, the user can add numbers in a column, calculate average, standard deviation, net present value, minimum & maximum values, square root, log, etc.

b. Analysis:

Analysis refer to using a decision support system (DSS) to review a set of facts and to assist in drawing conclusions based on there facts. Because the decision support environment is semi-structured, both the user and machine interact in this process. Four widely used types of decision support system (DSS) analysis tools, or techniques brought by users to the decision support system (DSS) environment are statistical tools, optimizing tools, what if analysis, and artificial intelligence routines.

c. Statistical Tools:

Statistical tools enable users to perform a variety of statistical operations on data on well as to do a number of other data handling tasks, such as, distributing data information categories of the user's own choice. Statistical analysis normally include regression analysis (make predictions from a set of data), correlation analysis (tools used to find the strength of association among data), and a variety of statistical inference methodologies (procedures such as analysis of variance, tests, and confidence limits; they can be used to determine whether a conclusion drawn from data is statistically significant).

Statistical methods are usually descriptive or predictive in nature; i.e. is they describe patterns among data or forecast events based on present or past happenings. Some of the most widely used statistical tools in business are the variety of regression routines used for forecasting purpose. These are particularly valuable when strategic plans are being formulated.

d. Optimizing Tools:

Optimizing tools are useful for deriving the best solution in certain structured decisions usually at tactical and operational levels. At the operational level, many decisions are structured and are frequently incorporated into computer based systems. Because the circumstances are well defined, optimizing techniques (Linear programming) are frequently used. Optimizing tools are used where it is required to optimize the value of a single objective (e.g. maximize contribution) where the factors .invoked (e.g. labor hours, machine capacity etc.) are subject to some constraints or limitation. It can be used to solve problems which:

Can be stated in numerical terms.

All factors have linear relationships.

Permit a choice between alternatives.

Have one or more restrictions on the factors involved.

A lot of manufacturing activities involves finding the "best" or "optimum" way to allocate resources. Some example include finding the cheapest way to mix sun flowers to achieve a finished oil that meets certain restrictions and determining the best way to allocate or schedule workers on assembly line to minimize production costs. These types of problems are solved by optimizing tools.

e. What-if analysis: (Sensitivity Analysis)

Asses risk with the help of DSS tools is known as sensitivity analysis. At its simplest this means, holding all the variables, bar one, constant and altering that one variable step and noting the effect on the result. One object of sensitivity analysis is to identify the "Critical" or "Sensitive" variables, which are those variables which have a more than proportionate effect on the result.

For example, a simulation of an investment program might include factors such as; cost per unit, price per unit, volume sold, amount of investment and as on.

It might be useful for a bank manager to know how much change should be expected in the profitability of a project if mortgage rates are changed by 1/2% in the next month or a chemical producer might want to know that $60,000/- per month could be saved in production costs if only the availability of a raw material could be increased by 10 percent.

In short, sensitivity analysis or what it analysis is to find out how sensitive a solution suggested by a model, is to changes in the model parameters.

What if analysis

Automatic recalculation has several advantages. For example, If a mistake is made in entering a number In a spreadsheet, and that number is used to calculate other numbers, then the result of all the calculations will be incorrect. In an electronic spreadsheet, when the one erroneous number is corrected, all resulting calculations will be automatically corrected of the same time. Similarly, if a number is changed, not because it is incorrect but because a user wants to see different results, related calculations will also be charged at the same time. This ability to change a number and have the change automatically reflected throughout the spreadsheet is the foundation of what if analysis, the process of changing one or more spreadsheet values and observing the resulting calculated effect.

A great number of such "what if" questions can be asked and answered by DSS models quickly as:

What if sales growth per month is nil, 1/2%, 1 & 1/2%, 2% or minus 1% etc.

What if the debt-to-capital ratio is 10% or high?

What happens if sales projections are 10% or low?

What if bank borrowing rates increase by 2%?

What if product development is delayed by a year?

Refiguring calculations on the basis of all these what ifs can take weeks to do by hand, but they are standard in the decision support system (DSS) world. For each what-if query, all the manger need is to change an underlying assumption or the value of a parameter and re-run the model. At the end of the interactive session several of these runs can be used to make decisions and, perhaps, convince other management members of the appropriateness of the chosen action.