Introduction to Decision Making
Decision Making Title
Decision Making Options
Decision Making Criteria
Decision Making Risk
Decision Making Analysis
Decision Making Reporting
Introduction To Decision Making
Sound decision making is the cornerstone of organisational success and informs how, as individuals, we perform our work and plot the course of our lives. Decisions can
range from the simple to the highly complex, where complexity depends on many factors. Such factors include the number of options to consider in the decision,
the consequences of the decision, the volume of information involved, the number of constraints encapsulated in the decision, and the risks inherent in the outcome.
While some decisions may be almost reflex, made easily and quickly without significant formal analysis, other decisions may require significant effort to collate
relevant information, identify constraints and remediate risks. In some cases, it may take a team to assemble all relevant data, apply robust decision making processes,
and ultimately take a judgement call on the correct outcome.
When making decisions, there are times when the amount of information to collect and the need to "get it right the first time" can be overwhelming. It is at times like
these when we may benefit from tools or systems that can help us to organise our decision making process, keep all information in one place and allow us to return to
it at any time with all of the key characteristics of the decision available for review. The need for a tool or system is magnified when many decisions need to be made
simultaneously. Decision Making Modelling provides the process that allows the complexities of multiple decisions (whether simple or complex) to be considered while
collating all decision information and criteria in the right place at the right time.
There are a number of tools that can be used when considering decision making including:
These can also be used in conjunction with other quality tools or techniques and other business requirements including:
- Affinity Diagrams
- Analytic Hierarchy Process
- Conjoint Analysis
- Cost Benefit Analysis
- Decision Making Trees
- Game Theory
- Heuristic Methods
- Influence Diagrams Approach
- Linear Programming and Operations Research
- Multiple Criteria Decision Analysis
- Net Present Value and Present Value
- Paired Comparisons
- Pros and Cons Technique
- Hypothesis Analysis
- Trail and Error
- Failure Risk Analysis and/or Fault Tree Analysis and/or FMEA
- Continuous Improvement
- Personnel Management
- Process Improvement
- Project Management
- Product Design
- Risk Management
- Supply Chain Management
- Training Management
What is decision making modelling?
Taking the multiple criteria decision analysis as a focus, as it allows for individual and/or group decisions while considering elements of the other decision tools, put
simply, Decision Making Modelling facilitates the definition and allocation of all decision options. That is all of the alternatives we are deciding between.
As a simple example consider a visit to a restaurant where we ask ourselves "What’s for lunch?" All choices on the menu are alternatives (options) to choose from.
One of these options will be the outcome – the item we decide to eat. To decide it is needed to list and assess the criteria that will inform our decision.
The criteria for a decision can be split into things that must be addressed (Givens) and things that are nice to have (Wants). Givens (or given criteria) are mandatory
criteria, and must be delivered by the option we choose when making the decision. If an option cannot address all of the Givens, it should be excluded. Wants are
“nice to haves” and each option can be ranked by how well it addresses each want. For example, in our restaurant, for lunch let’s get something that is a food that we
like and that none of our lunch guests are allergic to. Both these requirements are givens – lunch will not be eaten unless they are met. However, what about our
preferences for food. If we meet the givens, we can choose from items we like on the menu and there is no allergy. Is the preference pasta, beef, chicken, vegetarian,
fish. Each possible selection (or want criteria) will likely have a different weight based on the preferences of our group of guests. Once we establish these
weightings, then each options can be rated against its ability to deliver that want.
In Decision Making Modelling, we use options, givens and wants to score a decision and identify an ordered set of options, ranked from most to least appropriate. Using
the options, wants and given criteria, we can assess which of the options meet all our mandatory (given) requirements. Once we have a set of viable options (where all
givens are met), we can then determine the most appropriate option by ranking each want in terms of its relative importance, and scoring each option on how well it
meets the want criteria. Once the decision scores are revealed, a qualified and informed decision can be made. To see this process scroll down to the
Decision Making Title and read through each of the decision
However, there is still a risk the decision can be invalid or wrong. An additional set of criteria should be considered – that is, the risk that the chosen option
will cause undersirable flow on effects or consequences. For this reason, a robust decision making model allows each option to be assessed against one or more risks.
A risk is an outcome we do not want to happen because of the decision. For example, at lunch, a risk may be that we do not like the meal and it will not be eaten.
While we remediate this risk by choosing from options that meet all of our mandatory given requirements, and score highly against our “nice to have” wants, we may wish
to consider an additional risk that some of the food will be wasted, and therefore what is the likelihood that some portion of the group will not eat the option we choose?
The addition of risk allows us to consider undesirable consequences of our decision, and lets us inform and qualify the decision by assessing the risks and thus reducing
the likelihood of choosing an unpalatable option.
The option that meets all of the givens, with the lowest risk and highest want score, is typically the best option to select. However, it is not always that simple.
If the scores for each option are close, additional options, more given, want or risk criteria may be needed to clarify the way forward. Running the decision making model
will allow the decision to made without emotion and no matter the outcome, it provides clarity and a clearly documented data-based and robust process for making the decision.
What is required from a robust Decision Making Modelling system?
A Decision Making Modelling system should provide a number of key attributes and capabilities.
What are the limitations of decision making modelling processes?
Decision making modelling processes allow you to collate options, criteria and assessment outcomes for a decision, and use this data to assess and inform your decision
making process. By using the data, rather than emotion, you can make repeatable, explainable, quantifiable decisions.
- The ability to name our decision.
- The ability add and track options.
- The ability to add, track and compare decision criteria for givens (mandatory) and wants (optional) criterion.
- The ability to add, track and compare risk factors.
- The ability to allocate outcomes and ratings to all of the decision attributes:
- Givens – either met or not met.
- Wants – the relative importance of each want and how well an option delivers on the want.
- Risk Severity/Consequence – the level of consequence if the chosen option fails to address a specific risk.
- Risk Probability/Occurrence – how likely is it the risk to occur for a specific option.
- The ability to see all options, their criteria and ratings side by side
- The ability to report on decision outcomes.
- The ability to add more data to the decision model as and when required.
A decision making tool provides a framework as well as assessment and reporting capabilities around your decision model. However, the decision making model is only as
good as the information and the accuracy of assessment provided to it. This requires human input, taking a robust view of the problem and considering all relevant
options, criteria and all flow consequences once the decision is made.
No matter the capabilities of the decision making tool, though, the one thing the decision making modelling process does not do is make the decision for you. The decision
making process will provide you with a powerful and advanced guide to making your decisions in a robust and repeatable manner – but ultimately the selected option
belongs to the decision maker.
While giving your decision a title may seem innocuous and superfluous it does have organisational advantages when in an environment of making many decisions at the same time
and needing to track the history of decisions. The decision title allows the user or organisation to label and track each decision and identify the decision for future
editing, reference and reporting.
The title identifies the decision to be made and allows the data from that decicsion to be separated from other decision data within the Decision Making Model.
For example, Buying a New Home. Once the title and the type of decision has been identified
options for the decision can be collected.
Decision Options can be added to the Decision Making Model at any point in the process. Options are the alternatives that will deliver the result for the decision.
Examples of decision options would be:
- Different types of cars when buying a car
- The menu when deciding what to eat a restaurant
- Types of trees when deciding what to plant in a garden
- Differnt methods when deciding what process to use in the manufacture of a product
- Improvement ideas for a process in a process improvment program
- Problem solving proposals in a discovered failure in a product design or manufacture
- A list of houses when buying a new home
Each option identified needs to be assessed against the decision criteria
and decision risk.
Decision criteria are the elements within the decision that make up all the requirements the decision needs to meet. Some of requirements will be mandatory, or givens, and
if not met immediately remove any option from the filtered list that creates viable options for the decisiion. Each decision that is made will have its own unique set of
requirements some mandatory (givens) and some nice to haves (wants).
Givens are all the mandatory requirements or must haves in the decision
Wants are the nice to haves in the decision. Each want is rated or ranked in the order of its importance to the overall decision.
Givens and Wants once established are measured against each option.
Risks can be written in relation to not being able to meet wants and/or givens (although
if the given cannot be met there is minimal need to analyse the risk as it will not be considered) along with any other risk associated with the decision.
The risk in decision making is based around the risk that the option we choose will be the wrong one. The risk is a score measure that rates each viable option in terms of
how bad the risk item (Severity) and the likelihood that it will occur (Probability). In decision making we are looking to minimise risk. The options with the lower risks
will be more appetising as the best option but this needs to be balance how well the option meets all the wants.
Risk needs to be defined, usually from not meeting givens and wants, but additionally against any other activity or circumstance which may lead to any of the givens or wants
not being met. The root causes of each given or want not being able to be delivered. The risk criteria needs to be given a severity rating on how bad the result would be if it
where to eventuate then each option needs to address the level of probability that the risk would escape for that option for the total risk for each option to be calculated.
Once givens, wants and risks are in place the options can be assessed and analysed
against each other.
When all the required criteria are in place - givens, wants, risk and their associated level of importance and severity respectively - options can be analysed (scored)
against the criteria.
Each option needs to be assessed against all the given criteria. Any option that does not meet the given criteria should not be considered as a viable option.
It still may be worth scoring the failed given options in the wants. If there is a standout amongst them that does not meet the givens there may be a discussion to have
about the particular given. Remember the criteria is always up for discussion but needs to be set for the decision to be made.
Each option should then be assessed against each of the want criteria and be given a score how well the option delivers the criteria. This is a relative measurement across
the options. There are a number of approaches to scoring:
Let's use a 1 to 10 scale with 10 being best and 1 being worst. Each option must have a score for each want criteria.
In each option for each want criteria simply rate what you think each score is out of 10. This has the advantage of asking a simple question of each option and can be done
quickly but will have the disadvantage of potentially miss identifying the relative importance of each of the options to the criteria.
Best Options First
In deciding the score for the criteria for the option choose the best option for that criteria first and give it a score and then score each of the other options against the
score of best option. Continue through all other options with each criteria but first choose the best option for each criteria then score the other options.
Maximum Criteria Score Best Options First
In each want criteria select the option that best fits the criteria and give it the maximum score - in this case a 10. Scoring wants is a relative measure and the baseline
is which option is best. If it the best of all options available then it is a 10. Score all the other options against the criteria using 10 and the top option as a starting point.
If the option is only half as good as the baseline then it scores a 5 and so on through all the options for that criteria and then all the other criteria.
Each option should be assessed against risk criteria. Each option will have a probability that the risk will escape. A high probability will result in a higher risk score.
In decision making modelling the decision maker is looking for the risk to be lower - which is different to the decision makers apetite for risk. It does not necessarily
automatically mean the option with the lowest risk should be taken.
Once all the data for criteria givens and wants and risk severity and probability has been entered a decision on the best option can be made.
Making a Decision
Choosing the best options can be dependant on a number of factors based on:
The data should be able to represented in a clear and precise fashion in order for the decision maker to be clear on the data available, the decision to be made and
ultimately the decision itself. A simple method is to sort the options in maximum criteria result order then by minimum risk values.
- The decision makers apetite for risk
- How close each of the options are in terms of criteria score
- How close each of the options are in terms of risk score
- How balanced the outcomes of the criteria and risk scores are
- Whether there is a standout option above all the other options
- How many options fail to meet givens
- Whether further criteria or risk options are needed to separate the options further
The data can also be represented by the decision making model chart below. The lower the risk line the better, the higher the criteria line the better.
Decision Making Model systems should be able to produce a report on the decision with a breakdown on the data - this allows for reporting of the decision method where
Decision Making Modelling New Home Report