3.2.2 Understanding management decision making
The value of decision making based on data (scientific decision making) and on intuition
Scientific decision making:
- Set the objective
- Gather and interpret information (market research)
- Select the chosen option
- Implement the decision
- Review
Advantages of a scientific approach:
- Provides a clear sense of direction for all involved in the business
- Decisions are made and based on business logic
- It is flexible – at any stage in making a decision, it can be reviewed and changed if needed
Non-scientific decision making (intuition):
- The ability to understand something without the need for conscious reasoning; similar to a ‘hunch’
- Making decisions with a lack of evidence to prove it is the right thing to do
- This would be appropriate when a quick decision is necessary as it provides quick results when under a time scale
- It is mainly used by smaller businesses
The scientific approach vs intuition depends upon:
- Speed of decisions
- Information available
- Size of business
- Predictability of situation
- Character of person or culture
The use and value of decision trees in decision making
Characteristics of decision trees:
- They are good at choosing between several courses of action
- Provides a highly effective structure within which you can lay out options and investigate the possible outcomes of choosing these options
- It uses estimates and probabilities to calculate likely outcomes
- It helps to decide whether the net gain from a decision is worthwhile
Expected Value = the financial value of an outcome.
- = the estimated financial effect x its probability
Net Gain = the value to be gained from taking a decision.
- = the expected value of each outcome – the costs associated with the decision.
Advantages of decision trees:
- Gives you a decision
- Evidence to gain a source of finance
- Set out logically
- Easy to understand and results are tangible
- Likely costs considered as well as benefits
- Assesses risks
- Potential options and choices are considered at the same time – direct comparison
Disadvantages of decision trees:
- Always probe to arrow
- Calculating probability can be rad
- Could be inaccurate or unreliable as only estimates
- Doesn’t necessarily reduce the amount of risk
- Prone to bias
- Uses quantitative data only – ignores qualitative aspects such as effects on employee motivation and brand image
Influence on decision making
The influences on decision making:
- The business’ mission and objectives – do decisions match with the mission statement and current objectives of the firm?
- Ethics – this is the desire to act in a way that it morally correct ( these decisions are often not quantifiable and can attract negative publicity for the business
- The risk involved
- Non programmable = high risk – needs to be calculated and not taken on a hunch
- Programmable = low risk – can often be made using intuition or a hunch
- The external environment
- Demographics
- The environment
- Incomes
- Competition/market conditions
- Interest rates
- Resource constraints (e.g. information, time, labour, and materials)
- It may be costly to overcome these challenged associated with decision making
- Stakeholders – the different people who are an interest in the business