Unit 2.2 business

 Unit 2.2 - Understanding management decision making

Overview of key concepts - 

Managers need to make decisions

They need to maximise rewards and minimise risk

A way of minimising risk is to use the scientific method of decision making

Part of the analysing of data in the scientific method is using decision trees

Decision trees use a diagram and probability to calculate the likelihood of an event occurring

However, managers use a mixture to aid decision making - scientific methods, hunches, past experience. This should help to take in most factors.

There should be a balance between quantitative and qualitative information to aid decision making.

Management and decisions -

Managing is all about making decisions - making the right decision about resources such as:

People, money, materials needed and machinery

Decisions making is complex - 

Its for managers to minimise risk but maximise rewards

Decision making for managers - 

Risk:

Finances - could lose money or not make as much money as anticipated

Reputation - could damage reputation of business/manager

People - could lose good staff if they are not successful , demotivate staff

Future - could influence future decisions

Resources - resources not used effectively (either over or under utilised)

Rewards:

Finances - could make more money than anticipated

Reputation - could enhance reputation of business/manager

People - could attract good staff in future, motivate staff

Future - could get future business from potential customers

Decisions to be made - 

Strategic:

Normally long term

Involve a lot of resources

Difficult to reverse

Taken by senior managers and leaders

'setting overall plan'

Tactical:

Normally short term

Fewer resources involved

Easier to reverse

Taken by middle and junior management

'Day to day decisions'

Decision making -

It can be based on three assumptions - Experience, data, hunch or gut feeling

Scientific decision making - 

Set objectives: 

Determine what you want to achieve

Ensure objectives are SMART

Gather data:

Market research

Break even analysis: ratio analysis, investment appraisal

Analyse data:

Filter and analyse the data to aid decision making

Ensure the quality of the data, reliability and validity are important

Select a plan:

Develop a corporate plan from the information gathered

Select the most appropriate strategy to choose

Implementation:

Designate resources and people to plan

Implement the plan - put into action

Review:

Check to see if the plan is being implemented correctly

Is the plan within budget and timescales?

Benefits of using scientific approach - 

Clear direction by emphasising objectives and getting people involved in the decision making process

Decisions based on logic and rational thinking

More people are involved in the decision making process

Flexible because at any stage the decision can be reviewed and altered accordingly

Easier to defend a decision based on logic

Intuition and experience - 

Used by smaller business owners or smaller groups

The more experienced the individual the greater use of intuition

Can lead to creative solutions

But decisions are not always evidence based, could be biased or subjective

Hunches or gut feeling -

Used because of problems with scientific method:

Too much data to be collected

Time consuming

Data could be flawed, unreliable or invalid

This means managers frequently go with their hunches rather than relying just on the scientific approach

Opportunity cost -

It measures the cost in terms of the next best alternative forgone

Decision trees - 

They are a mathematical and graphic model to aid managers in making the right decisions

Shows different outcomes and their options, numerical data is then added to make it more useful

First the probability is either 'high' or 'low' the value can then range from 0 to 1

Values of decision trees - 

Decision trees are a part of the scientific decision making process

They analyse the data, making it easier to make decisions

The visual nature of the diagram makes it easier to understand complex information

Used as a tool but should not be used exclusively - qualitative information should also be considered

Makes managers think about different options and their possible consequences

They force managers to quantify the impact of each decision 

Helps to establish a logic order to options

Limitations of decisions trees -

Only uses estimates of the probability of different outcomes and the financial consequences of each outcome

The value of a decision tree analysis depends heavily upon how accurate these estimates are

Only includes financial and quantifiable data - they do not utilise qualitative data and this is sometimes more important

Possible qualitative information - 

The possible qualitative information which could affect decisions may include:

Risk adversity of management/owner - linked to leadership style

External environment (PESTLE)

Business's ability to change

Competition

Summary - 

Decision making is complex and every manager approaches it differently

The level of adversity to risk is a large factor - the higher the adversity to risk the more scientific the approach. The more risk a manager is willing to take the greater chance of using hunches or experience

The approach also depends upon different industries and the size of the organisation. Smaller entrepreneurial businesses tend to go more on hunches - possibly because they do not have the resources or skills to be able to analyse too deeply.


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