Cause-and-effect mapping

Five Whys

Five Whys analysis attempts to probe beyond the immediate causes of an event to expose underlying causes.

You start by asking why the event happened. When you come up with a causal factor, you ask "And, why did that happen?" You repeat that process, going further back along the causal chain of events.

The choice of five is somewhat arbitrary. It's mainly to encourage you to keep going further than you would normally.

A similar technique for exploring potential future consequences is the Five Hows or Five So Whats. In this case, the Event could be a choice you make and you could produce different future-focused causal maps for each option.

Root cause analysis

RCA is a more detailed approach to exploring causal factors for a problem.  The basic components are:

• Define the problem and list the observable symptoms (Representation)

• Generate a sequence of events leading up to the problem  to identify possible causal factors (Causation - correlating)

• Differentiate between the possible causal factors to identify the extent to which they contributed to the problem (Comparison)

RCA can involve the use of things called Fishbone diagrams. These are like the left-hand side of a bow-tie diagram but separates different types of causal factor and differentiates between primary and secondary causes. 

The technique usually involves brainstorming the possible causes and then sorting them into categories. Some commonly used categories include:

• Environment - factors related to the context of the event (conditions, timing, etc.)

• People - factors related to individuals or groups involved (skills, knowledge, motivations, personality, etc.)

• Process - factors related to the methods used (procedures, standards, technology, monitoring, etc.)

• Resources - factors related to the inputs (time, money, energy, raw materials, etc.)

• Communication - factors related to the interaction between people (cooperation, information, understanding, etc.)

A variation of the Fishbone diagram is the Lovebug diagram. This adds branches on the right-hand side categorising all the factors that might act as barriers to prevent something from happening.

A similar approach can be applied to exploring the potential future consequences and implications in different categories. This ought to be called Tip Effect Analysis.

Pre-mortem

In a pre-mortem you start with the assumption that something is going to fail. You mentally project yourself into the future after the failure and conduct a post-mortem to explore why it failed. So it's like conducting a root cause analysis in advance so that you can adjust your future plans to reduce the risk of failure.

Decision trees

A decision tree is a way of mapping out future possible pathways where there are a number of choices or potential chance events that could lead to different outcomes.

A decision tree starts with a 'decision node' (usually represented by a square) from which the various available choices branch out. You then follow each branch and identify any subsequent branching nodes representing future options that may become available as the result of the initial choice until you reach an end node (usually a triangle), which could be a specific outcome or just the limits of your ability to predict.

As well as decision nodes, you could include 'chance nodes' (usually circles) which represent factors outside your control that generate different pathways depending on what happens.

A binary decision tree attempts to convert all decision and chance nodes into closed questions that can be answered 'yes' or 'no', leading to only two branches ('Will I do A?' 'Will Z happen?'). Non-binary decision trees allow for multiple outcomes from each node ('Will I do A, B or C?' 'Will X, Y or Z happen?').

You can start with a chance node. In which, case you are, effectively, scenario planning.