Comparing Three Decision-Making Techniques in BABoK
BABoK V3 places significant emphasis on decision making by
business analysts. Making correct decisions is important as the organizations
can avoid waste by choosing the right options.
However, BABoK provides 3 techniques which one can use to make
decisions. There seems to be quite a bit of overlap among them as well.
They are
- Evaluation
criteria (aka Selection criteria)
- Decision
model
- Decision
analysis
When should we use which approach?
Let’s explore.
Before we compare the 3 techniques, let’s pick the descriptions
provided for the 3 techniques from BABoK.
Evaluation Criteria
Evaluation criteria define a set of measures to rank multiple
options based on their value to stakeholders, thus allowing a range of scores.
Value attributes can be performance, applicability, scalability, reliability
etc. Evaluation criteria must be able to measure values features provide to
stakeholders.
Decision modeling
Show how repeatable business
decisions are made using data and knowledge.
Decision tables
A
tabular representation of a set of rules. Each row/column is a rule and each
column/row represent one of the conditions of that rule.
https://docs.google.com/document/d/1Y81NjF07QeTTbHLHj6QDyGF82bvNy2w-q7-ngf1USU4/edit?usp=sharing
Decision trees
Each path on a decision tree leaf node is a single rule. Each
level in the tree represents a specific data element; downstream branches
represent different conditions that must be true to continue down that branch.
Decision trees include Decision
nodes – Different strategies, Chance nodes – Define
uncertain outcomes, Terminator or end nodes – Identify final
outcomes.
Decision Analysis
Understand:
- Values,
goals, and objectives relevant to the decision problem,
- Nature
of decision to be made,
- Areas
of uncertainty that affect the decision,
- Consequences of each possible decision.
2 types of decision matrices:
Simple
decision matrix:
Each alternate is checked against each criterion. Tally the
number of criteria matched for each of the alternates. Choose one with the
maximum tally.
Weighted
decision matrix:
0ptions are assessed against weighted criterions. Weights are
assigned based on their importance. The higher weighting, more important
criterion. The formula is the Sum of (Weight i * Rating i)
Decision
trees
Decision analysis also uses Decision Trees as well.
Comparing
and contrasting the 3 techniques
Now let’s observe the contradictions for Decision analysis
technique. Don’t simple and complex decision matrices look exactly like
Evaluation criteria?
In my humble opinion, these 2 decision matrices should have been
part of Evaluation criteria.
Now decision tree appears in both decision model and decision
analysis?
Will we be using decision tree in repeatable processes?
Unlikely. Hence, the decision tree should be placed only in Decision analysis,
not in Decision Modeling.
One can argue that a decision tree is indeed a diagram, hence
should be part of the decision model. Since the decision model deals with
simple and repeatable decisions, wouldn’t a flow chart not suffice for decision
model?
From the examination point of view, let’s summarize the 3 techniques as below:
Evaluation
criteria |
Decision model |
Decision
analysis |
|
Purpose |
To select one
option among multiple options |
Provide
decisions to common business situations |
Provide
decisions to uncommon business situations |
Applicable
situation |
Simple and one
time |
Simple and
repeatable |
Complex and
uncertain |
Techniques |
Decision
matrices |
Decision table Flowchart |
Decision tree |
Usage frequency |
One time |
Multiple |
One time |
We
would love to seek the opinion of other business analysts on these 3
decision-making techniques.
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