Theme 3 - 3.3.3 - Decision Trees

Question 1

Whats a decision tree ?

Answer 1

A business can’t afford to follow every option ( for investment or business venture ) so it may use a decision tree to analyse the probability of a success in a choice of strategies for e.g:
- a new product launch
- A new marketing campaign
- Relocation to a new building

These are the different startageies to make money but you can make a decision tree to analyse the probability of success in these 3 strategies

Question 2

How do the decision trees work ?

Answer 2

A decision tree traces an alternate outcome of a decision, the results can be compared and the business can decide which option would be the most profitable

This is a quantitative approach (numbers) and it is pictorial as its in the shape of a tree and it predicts the best outcome so a business knows what to spend its money on

The data is usually based on historical data from the business - for example they would know the probability of the success of launching a new product would be 20% based on previous product launches

Question 3

How to make a decision tree ?

Answer 3

Starts with a decision point:
- a square is a decision point
- this may be empty, have an A or 1
- they appear at the start

A decision needs to be made by the business at this point

Then add in 2 decisions:
- Now the business has to decide between courses of action, there will be more than one

Chance node:
- A chance node is a circle, and it comes after each decision
- Each decision that a business makes may result in a number of outcomes

Success or failure:
- so from the chance node (circle) you get outcomes and these are the probability of success or failure
- so branching off from the circle there is 2 things which are the success and failure probability ( which add up to 1 ) so for the 2 decisions there are 2 probabilities of success/failure

Question 4

What’s the expected value of each outcome ?

Answer 4

So if you have one decision and it has a probability of success and failure - you would do the success probability x the total money outcome + the failure probability x the failure outcome

Question 5

What are the limitations of decision trees ?

Answer 5

Decision trees are based on predicted data of the potential impact of a decision - so the predicted data is the success and failure of each decision —> these are predictions because you don’t actually know

Decision trees dont take into account unforeseen costs and circumstances

Probabilities and net outcomes are all estimates

Using decision trees might fit with the culture exhibited by the business but this is likely to be overridden by the need to act quickly, which would suggest the decision trees are not that useful in some situations - these might take too much time to make and by the time you make them the opportunity might be gone

Large degree of uncertainty about any situation that a decision tree might be used for, so the benefits of adding numbers to uncertainty e.g.
58% might not be correct