Decision Making, Systems, Modeling, and Support
2.1 DECISION MODELING AT HP USING SPREADSHEETS
- HP works with Olavson and Fry to develop spread sheet tools for decision making at HP
- A Tool is “reusable business problem.
- HP develop tools through three phases
- Problem framing
- Design and develop
- Hand off
- Problem framing:
- Will analytics tools solve the problem?
- Can the existing solution be leveraged?
- Is a tool needed?
- Design and develop
- Develop prototype no quickly on possible
- Build insight, not black boxes
- Remove unneeded complexity before handed off
- Partner with end user in discovery and design
- Develop Operation(OR)champion
- Who will use the tool?
- Who owns the decisions that the tool will support?
- Who else must be involved?
- Who is responsible for maintenance and enhancement of the tool?
- When will the tool be used?
- How will the use of the tool fit in with other processes?
- Does it change the processes?
- Does it generate input into those processes?
- How will the tool impact business performance?
- Are the existing metrics sufficient to reward this aspect of performance?
- How should the metrics and incentives be changed to maximize impact to the business from the tool and process?
Decision Making: Introduction and Definition
- Characteristics of Decision Making
- Definition of Decision Making
- Decision Making and Problem Solving
- Decision-Making Disciplines
- Decision Style and Decision makers
Characteristics of Decision Making
- Groupthink (i.e., group members accept the solution without thinking for themselves) can lead to bad decisions.
- Decision makers are interested in evaluating what-if scenarios.
- Experimentation with a real system (e.g., develop a schedule, try it , and see how well it works)may result in failure.
- Experimentation with a real system is possible only for one set of conditions at a time and can be disastrous.
- Changes in the decision-making environment may occur continuously, leading to invalidating assumptions about situation (e.g., deliveries around holiday times may increase, requiring a different view of the problem).
- Collecting information and analyzing a problem take time and can be expensive. It is difficult to determine when it stop and make an intelligent decision.
- There may not be sufficient information to male an intelligent decision.
- Too much information may be available(i.e., information overload).
- Decision making is a process of choosing among two or more alternative courses of action for the purpose of attaining one or more goals.
- Managerial decision making is synonymous with the entire management process.
-Planning involves a series of decision: what should be done? When? Where? Why? How? By Whom?
- Managers set goals, or plan ; hence, planning implies decision making. Other managerial functions , such as organizing and controlling, also involve decision making.
Decision Making and Problem Solving
- A problem occurs when a system does not meet its established goals, dose not yield the predicted results, or does not work as planned.
- Problem solving may also deal with identifying new opportunities.
- Differentiating the terms decision making and problem solving can be confusing.
- Here , we use the terms decision making and problem solving inter change.
Decision-Making Disciplines
- Decision marking is influenced by several major disciplines, some of which are behavioral and some of which are scientific in nature.
- We much be aware of how their philosophies can affect our ability to make decision and provide support.
- Behavioral disciplines include anthropology, law, philosophy, political sciences, psychology, social psychology, and sociology. Scientific disciplines include computer science, decision analysis, economics, engineering, the hard sciences(e.g., biology, chemistry, physics),management sciences/operations research, mathematics, and statistics.
Decision Style and Decision makers
- Decision style is the manner by which decision to problems. This includes the way they perceive a problem a problem, their cognitive responses, and how values and beliefs vary from individual to individual and from situation to situation.
- Researchers have identified a number of decision-making styles. These include heuristic and analytic styles. One can also distinguish between autocratic versus democratic styles. Another styles is consultative (with individuals or groups).
- Of course, there are many combinations and variations of styles .
- A person can be analytic and autocratic , or consultative (with individuals)and heuristic.
- Decision are often made by individuals, especially at lower managerial levels and in small organizations.
- Most major decisions in medium-sized and large organizations are made by groups.
- Obviously, there are often conflicting objective in a group decision-making setting.
- Therefore, the process of decision making by a group can be very complicated. Computerized support can greatly enhance group decision making.
- Computer support can be provided at a broad level, enabling members of whole departments, divisions, or even entire organizations to collaborate online. Such support has evolved over the past few years into enterprise information systems (EIS) and includes group support systems (GSS), enterprise resource management (ERM)/ enterprise resource planning (ERP), supply chain management (SCM), knowledge management system (KMS), and customer relationship management (CRM) systems.
2.3 Models
- A major characteristic of a DSS and many BI tools(notably those of business analytics) is the inclusion of at least one model.
- The basic idea is to perform the DSS analysis on a model of reality rather than on the real system.
- A model is a simplified representation or abstraction of reality. It is usually simplified because reality is too complex to describe exactly and because much of the complexity is actually irrelevant in solving a specific problem .
- Model can represent system or problem with various degrees of abstraction .
- They are classified, based on their degree of abstraction, as icon, analog, or mathematical.
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Models
- Iconic(Scale)Models
- Analog Models
- Mental Models
- Mathematical(Quantitative)Models
- The Benefits of Models
Iconic(Scale)Models
- An iconic model, also called the scale model-the least abstract type of model-is physical replica of a system, usually on a different scale from the original.
- An iconic model may be three-dimensional, such as a model of an airplane, a car, a bridged, or a production line. photographs are two-dimensional iconic models.
Analog Models
- An analog model behaves like the real system but dose not look like it.
- It is more abstract than an iconic model and is a symbolic representation od reality.
- Model of this type are usually two-dimensional charts or diagrams.
- Organization charts that depict structure, authority, and responsibility, and relationships
- Map on which different colors represent objects, such as bodies of water or mountains
- Stock marker charts that represent the price movement of stocks
- Animations, video, and movies
Mental Models
- Mental models are descriptive representations of decision-making situations that people form in their head and think about.
- Their thought process work through scenarios to consider the utility of and risks involved in each potential alternative.
- Typically, mental models are used when there are mostly qualitative factors in the decision-marking problem.
- Mental models help frame the decision –making situation, a topic of cognition theory.
Mathematical (Quantitative Models)
- The complexity of relationships in many organizational system cannot be represented by icons or analogically because such representation would soon become cumbersome and using them would be time-consuming.
- Therefore, more abstract models are described mathematically.
- Most DSS analyses are performed numerically with mathematical or other quantitative models.
The Benefits of Models
- Manipulating a model (changing decision variables or the environment) is much easier than manipulating a real system. Experimentation is easier and does not interfere with the organization’s daily operations.
- Models enable the compression of time. Years of operations can be simulated in minutes or seconds of computer time.
- The cost of modeling analysis is much lower than the cost of a similar experiment conducted on a real system.
- The cost of making mistakes during a trial-error experiment is much lower when models are used than with real system.
- The business environment involves considerable uncertainty. With modeling, a manager can estimate the risks resulting from specific actions.
- Mathematical models enable the analysis of very large, sometimes infinite, number of possible solutions. Even in simple problems, managers often have a large number of alternatives from which to choose.
- Models enhance and reinforce learning and training.
- Models and solution methods are readily available on the Web.
- Many Java applets (and other Web programs) are available to readily solve models.
- The existence of a problem can be determined by monitoring and analyzing the organization’s productivity level
- The measurement of productivity and the construction of a model are based on real data
- The collection of data and the estimation of future data are among the most difficult steps in the analysis
2.4 Phases of Decision Making Process
TABLE 2.1 Simon’s Four Phases of Decision Making and the Web
Intelligence
Design
Choice
Implementation
2.5 DECISION MAKING:THE INTELLIGENCE PHASE
- Problem(or Opportunity) Identification
- Problem Classification
- Problem Decomposition
- Problem Ownership
Problem(or Opportunity) Identification
- The intelligence phase begins with the identification of organizational goals an