Time/place Framework pg 441

The effectiveness of collaborative computing technology depends on the location of the group members and on the time that shared info is sent and recieved.

When information is sent and recieved almost simultaneously, the communication is said to be synchronous (real-time): Telephones,IM and face to face meetings are egs.

Asynchronous communication occurs when the reciever gets the information at a different time than it was sent: email

pro's/cons for working in groups pg 437

Group decision making process pg 436

characteristsics of groupwork page 436

• performs a task
• may be located in different locations
• may work at different times
• work for the same of different orgs
• groups is remporary or permanent
• can span several managerial levels
• may be synergy or conflict
• creates gains/or losses in productivity
• may have t be done quickly
• may be impossible or too expensive for all team members to meet in one location face to face
• needed data may come from many different sources, including external ones
• expertise of non team members maybe required
• should concerntrate on decision making

Internal Data page 98

The term “internal data” is used here to denote any information useful to the decision-making process found within the company.

http://www.gestiondesarts.com/index.php?id=783

Levels of DSS models - Strategic, Tactical, Operational page 105

http://www.smallbusinesshq.com.au/factsheet/20305-Tips-on-Strategic-Tactical-and-Operational-Decision-Making.htm

Strategic Decisions - 'What?'

Strategic decisions deal with the big picture of your business. The focus of strategic decisions is typically external to the business and usually future oriented. Strategic decision-making creates the forward thrust in the business.

It includes decisions about:

• What business are you in?
• What is your vision for the business?
• What's your business' identity?
• What do you stand for?
• Which direction is the business headed?
• How will the business compete?

Corporations often capture their overall business strategy in a "Statement of Intent" and it's an excellent term for describing what strategic decision-making is. Too often people confuse strategic decisions with tactical decisions and fail to really examine the big picture. It can lead to stagnation in the business and an inability to move forward.

Top managers

Tactical Decisions - 'How?'

Tactical decisions involve the establishment of key initiatives to achieve the overall strategy. For example, if you have decided to be the Number 1 provider in your market (a strategic decision) then you will develop tactics (e.g. implement a marketing system, increase number of therapists) to achieve that outcome. In a small business you may have 4 or 5 key tactics that you are going to use to achieve your overall strategy.

Again this layer of decision-making can sometimes be overlooked yet it is the glue that creates a strong connection between your long-term vision and your day-to-day activities. Tactical decision-making is the domain of 'mission' statements.

Think in terms of the battlefields from which the term has emerged. The overall strategy, that is, what the army is there to do, is to win the war. Then you have a number of 'missions' you send troops on, preferably diplomatic ones, the cumulative effect of which is intended to win the war.

Operational Decisions - 'How will we deploy resources?'

Operational decisions determine how activities actually get done. They are the 'grass roots' decisions about who is going to do what and when. It includes:

• How will we spend our money this month?
• How will we service that client?
• What is our procedure for delivering an order?
• Who will be doing quality control?

If you are making decisions involving processes and procedures they are usually operational decisions. Operational decisions are often made in 'real time' and are the result of needing to make quick adjustments or change to achieve the desired outcome.

http://www.enotes.com/business-finance-encyclopedia/decision-making

STRATEGIC, TACTICAL, AND OPERATIONAL DECISIONS

People at different levels in a company have different types of decision-making responsibilities.

Strategic decisions, which affect the long-term direction of the entire company, are typically made by top managers. Examples of strategic decisions might be to focus efforts on a newproduct or to increase production output. These types of decisions are often complex and the outcomes uncertain, because available information is often limited. Managers at this level must often depend on past experiences and their instincts when making strategic decisions.

Tactical decisions, which focus on more intermediate-term issues, are typically made by middle managers. The purpose of decisions made at this level is to help move the company closer to reaching the strategic goal. Examples of tactical decisions might be to pick an advertising agency to promote a newproduct or to provide an incentive plan to employees to encourage increased production.

Operational decisions focus on day-to-day activities within the company and are typically made by lower-level managers. Decisions made at this level help to ensure that daily activities proceed smoothly and therefore help to move the company toward reaching the strategic goal. Examples of operational decisions include scheduling employees, handling employee conflicts, and purchasing rawmaterials needed for production.

It should be noted that in many "flatter" organizations, where the middle management level has been eliminated, both tactical and operational decisions are made by lower-level management and/or teams of employees.

Semi structured problems page 14

Fall between structured and unstructured problems, having some structured elements and some unstructured elements.

eg's

• Trading bonds
• setting marketing budgets
• capital aquisition analysis

see chart

The components of DSS Mathematical problems PART 2 page 92

Data management subsystem

• inlcudes a database that contains relevenat data, managed by DBMS. CAn be interconnected with DW.

1. DSS database

• internal data: from orgs Transaction Processing System (TPS). Monthly payroll, operational data from functional areas of the business, machine maintenance scheduling. future hiring pans. Included in DW.
• external data: industry data, market research consensus data, govt regs, tax rate schedules, national economic data.
• private data: guidlines used by specific decision makers as assesments of specific data and or situations.
  

1. DBMS
2. Data query
3. Query facility
   

Model management subsytem

software package: financial, statictsical, management science, quantitive models that provide analytical capabilities and software mgt. Often call model base management system MBMS. Can be connected to external storage.

• Model base

1. Strategic models: used by top managers for strategic planning responsibilities.
2. Tactical models: used by middel managers for allocation and controlling orgs resources.
3. Operational models: support day to day working activities.
4. Analytical models: used to perform analysis on data.
   

• MBMS
• Modeling langugae
• Model directory
• Model execution, integration, command processor.
  

User interface subsytem

User commiunicated with and comand the DSS. User is considered part of the system.

Knowledge based management subsytem

can support any of the other components or act as independant component. Augments system/ decision maker with intelligence.

Differenc between DSS and BI page 90

DSS generaly built to solve a specific problem and contains its on databases.

BI apps focus on reporting and identify problems by scanning data extracted from the DW (Date Warehouse)

DSS Characteristics and capabilities page 90

Simulation types page 167

Probalistic Simulation: One or more of the dependant variables are probalistic

• Discrete distributions: limited number of events or variables, finite number of values
• Continuous distributions: unlimited number of possible events

Time Dependant Vs Time Independant Simulation:
Time Independant refers to a situation where it is not important to know exactly when the event occured
eg. Important to know that 3 units were sold in 1 day but not important to know when.

Time dependant, precise details of when the event happened are important.
eg. waiting lines in a que

Object Oriented Simulation: Using UML

Visual Simulation: Graphical display of computerised results and may include animation

Simulation page 165

Simulation is the appearance of reality

A technique for conducting experiments (eg. what-if analysis) with a computer on a model of a management system.

One of the most commonly used methods DSS methods

Problem solving search methods page 162

Analaytical techniques: Use a mathematical formula to derive an optimal solution directly or to predict a certain result. Used primarily for solving structured problems, usually of a tactical or operational nature. areas such as resources allocation, inventory mgt

Algorithms: Step-by-step process for obtaining an optimal solution. Solutions generated and tested for possible improvements. The process continues until no further improvment is possible.

Blind Searching: In conducting a search, a description of a desired outcome may be given. This is called a goal. A set of possible steps leading from the initial consitions to the goal is called the search steps. Problem solving is odne by searching through possible solutions.

Heuristic Searching: Via knowledge, common sense, rule of thumb. Heuristics are the informal, judgemental kowl,edge of an application area that constitute the rules of good judgement in the feild. Domain KNowledge.

Goal Seeking page 161

What-if analysis page 160

Sensitivity analysis page 159

Methods of handling multiple goals page 159

With some methods, the decision maker needs to search the solution space for an alternative that provides the required attainmemt of all goals while searching for an efficient solution.

Utility theory : Utility theory is an attempt to infer subjective value, or utility, from choices. Utility theory can be used in both decision making under risk (where the probabilities are explicitly given) and in decision making under uncertainty (where the probabilities are not explicitly given). More...

Goal programming : It can be thought of as an extension or generalisation of linear programming to handle multiple, normally conflicting objective measures. Each of these measures is given a goal or target value to be achieved. More...

Expression of goals as constraints

A points system

Multiple goals page 158

Managers want to attain simultaneous goals, some of which may conflict.

Difficulties of analysing multiple goals:

• Difficult to obtain explicit of the orgs goals
• Decision mkaer may change importance of assigned to specific goals over time or for different decision scenarios
• goals viewed differently at different levels of the org
• goals change in response to change in the org and environment
• relationships between alternatives and their role in determinning goals may be difficult to quantify
• complex probs are solved by groups of decision mkaers, each of whom has a personal agenda
• participants view the importance / priorities of goals differently

Linear Programming pge 154

Every LP problem is composed of:

• decision variables (who's values are unknown and are searched for),
• an objective function (a linear mathematical function that relates the decision variables to the goal, measures goal attainment, and is to be optimised),
• objective function coefficients (unit profit or cost coefficients indicating the contribution to the objective of one unit of a decision variable),
• constraints (expressed in the form of linear inequalities or equalities),
• capacities (upper, lower limits of variables), and
• input/output coefficients.

The components of DSS Mathematical problems page 151

All models are made up of four basic components. Mathematical relationships links these components together.

Result (outcome) variables

• Reflect the level of effectiveness of a system, ho well the system attains its goals. These variables are outputs.
• Considered dependant

Decision variable (pg 58, 152)

• Describes alternative courses of action. The decision mkaer controls the decision variables.

uncontrollable variables (or parameters)

• Factors that affect result varibales but are not under the control of the decision maker.
• Some of these variables limit the decion maker and therefore form what are called constraints of the problem.

intermediate result variables

• Reflect intermediate outcomes in mathematical models. eg. determining machine maintenance scheduling, spoilage, total profit, employee satisfaction