Decision Support Methodology

Match each of the quotations with the corresponding decision-making phase according to Simon's model, note that there may not be a one-to-one mapping. For each phase justify your selection in less than 200 words.

a) "The successful decision maker remains open to the full array of alternative solutions."


b) "Until a decision has degenerated into work and reaches the stage of actual execution, for all intents and purposes there is no decision."

c) "If you have no alternative to fall back on, you begin to drift if the decision doesn't work out."

d) "Organised tracking of progress, results and feedback are non-negotiable elements of any effective action program."

e) "Only by taking the time to investigate what the decision really needs to be about can the decision maker distinguish between the symptom and the ailment."

f) "One does not make unnecessary decisions any more than a good surgeon does unnecessary surgery."

Major purpose of models

Essentially, models are designed to help decision makers make optimal (or most satsfactory) decisions.

Planning a model should always be from the perspective of ensuring that correct decisions are made, and by utilising the most efficient methods.

Human Influence on modeling

Model planning, design and construction is often inadvertently influenced by the decision-maker’s own

• cognitive style
• decision style
• pre-existing biases and preferences

Modeling is a major tool of the Choice Phase

Choice is made by:

• Obtaining the outcomes from each ‘trial’ of the model,

• Checking these outcomes against the optimal (or satisfactory) criteria

• Confirming that these criteria have not changed!

• Selecting the ‘trial’ whose outcome best fulfills the criteria.

Modeling as a process

after the ‘Intelligence’ Phase (problem definition, information gathering, collating and analysing), models are …

• designed
• developed
• tested and amended
• Implemented
• User acceptance
• User training

Why use models?

• simplify exploration by allowing an emphasis on some aspects (of reality) while ignoring others.

• possible to compress years of data into a single model,

• help to better understand complex real situations,

• cheaper to play with and experiment with model than using the real thing,

• Experimenting with ‘reality’ may not be reversible,

• Simulation models are suited to ‘what-if?’ scenarios,

• can be re-run with different states and data,

• economical ‘trial and error’ testing is facilitated

Types of Models

Physical models

• Physical (touchable) representations.
• A smaller or larger physical copy of an object.

Abstract models

• Generalisations of reality that remove specific details in favour of general information which is relevant for the purpose.

Object models

• Represent, describe and simplify the appearance, structure, organisation and functioning of things (objects).

Process models

• Represent, describe and simplify the dynamic nature of processes.

Descriptive Models

• Describe the reality as it is or as it is believed to be.
• E.g. mathematical models (see below).
• Useful for satisficing.

Mathematical Models

• Describe reality using mathematical language and techniques, often variables and systems of equations that relate outputs to inputs.

Simulations

• Computerised models of dynamic processes.

What is Modeling? What is a model?

The use of a representation of something to explore the real thing.

• A simplification of the ‘reality’.
• A representation of the ‘reality’.

Choosing to do nothing!

One option that is always present, but often overlooked, is the choice to do nothing.

It should be placed on the list of ‘what-if’ scenarios, and evaluated along with the intentional alternatives as one possible choice.

The Knowledge-Based approach to decision-making

Is an extension of the classic approach, and may be:

• Descriptive knowledge (e.g. spreadsheet, balance sheet, etc.)
• Procedural Knowledge ( a series of steps, for example)

Decision-making

A problem-solving process that has been preceded by a problem-finding process

The means through which a manager seeks to achieve a desired result.

Finding and choosing between alternatives.

Alternatives
Where do they come from?
How many are sufficient?
How many are too many?

How much effort should be expended in finding more alternatives?
How to control them?
How to analyse them effectively?

How to select the optimum alternative?