What is the Decision Model?
Barbara von Halle and Larry Goldberg
The Decision Model is an intellectual template for perceiving, organizing, and
managing the business logic behind a business decision. 1 An informal definition of business logic is it is a set of business rules represented as
atomic elements of conditions leading to conclusions. A more formal definition of
business logic is “a means by which a business derives a conclusion from facts.” So,
business logic is a prescription for the way business experts want to evaluate facts
in order to arrive at a conclusion where the conclusion has both meaning and
value to the business. Therefore, a business decision is defined as a conclusion that
a business arrives at through business logic and which the business is interested
It follows then that business logic itself is intellectual in nature because,
it represents business thinking about the way important
decisions are to be made.
To make business logic tangible, common practice is to translate the business
thinking into a visible, communicable form, which often is a set of business rules
or business statements. These vary in format: free-form text, fill-in-the-blank templates,
decision tables, decision trees, or sentences adhering to specific syntax or
grammar. Regardless, it is these business rules or statements (more accurately, their
intended logic) that are modeled in a Decision Model structure adhering to the
Decision Model principles.
First, it is important to understand what it means for the Decision Model to be
an intellectual template.
The Decision Model as an Intellectual Template
As an intellectual template, the Decision Model is a logical representation of business
logic. It is, by deliberate intent, not a physical model of how that business
logic is to be implemented in specific technology. It is not even a model for how
that business logic is to be communicated through procedure manuals or training
materials. Instead, it is an intellectual template for the full and rigorous specification
of that logic. From this full and rigorous specification, if the goal is to automate
it, a Decision Model can be translated into one or more target technologies
through appropriate design methodologies. If the goal is for humans to follow it,
a Decision Model can be translated into whatever format is most easily referenced
It is also important to understand that the Decision Model is a model and not
just a list.
The Decision Model as a Model
The Decision Model is not simply a list of business rules or business statements.
Rather, it is a model representing a structural design of the logic embodied by those
statements. (See Figure 1.)
Figure 1. A Decision Model
As a model of business logic, the Decision Model is a unique representation of
business logic, unlike other representations. For example, it is, by deliberate intent,
not a model of how that business logic relates to processes, use cases, information,
or software models. It is not a notation added to data models, fact models, process
models, or any other kind of model. Instead, it is an independent representation of
business logic based on the premise that business logic has its own existence, independent
of how it is executed, where in the business it is executed, and whether or
not its execution is implemented in automated systems. The Decision Model can
be anchored to any and all other kinds of models, but maintained independently
Having its own existence implies that a model of business logic has a recognizable
structure that is not the same as the structure of other kinds of models.2 Not
only that, the Decision Model is distinct in its representation of business logic
because a Decision Model aims to be:
- Simple to interpret and manage
- Declarative so as to be independent of technology or processing requirements
- Optimal in integrity, meaning that its business logic is consistent within itself
and aligns with business direction
As a separate model with these characteristics, the Decision Model elevates business
logic to the status of a valuable organizational asset that would remain elusive
without such a representation.
Examples of Business Logic
Earlier, this chapter defined business logic as a means by which a business derives
conclusions from facts. The following are statements by which conclusions can be
reached from facts:
- A person who has not had any jobs in the past five years is considered to have
a poor job history.
- A person with more than ten jobs in the past five years is considered to have
a poor job history.
- A person with a poor job history, a large mortgage, and a significant number
of miscellaneous loans is considered very likely to default on a loan.
- A person with a low credit rating must not be granted an unsecured loan.
- A person’s credit rating is computed according to proprietary formula A154.
First of all, each of these statements is expressed in the way that a business person
might express it. None is stated in terse, forced, unnatural, or pseudocode format.
The expressions are business-friendly and serve as a starting point. The goal is to
discover the intended business logic behind the statements and translate it into a
more rigorous form in a Decision Model. In fact, a natural language statement can
be generated from the Decision Model that is more precise than the raw material
from which it started.
For now, each of the foregoing statements is, simply, one business conclusion.
That is, each statement comes to a simple or complex conclusion (e.g., a loan applicant
is considered to have a poor job history) based on facts (e.g., how many jobs a
person has held in the past five years).
The first two statements come to a conclusion about a person’s job history. The
third one arrives at a conclusion regarding a person’s likelihood of defaulting on a
loan. The fourth comes to a conclusion about granting an unsecured loan. And, the
fifth comes to a conclusion about the value assigned to a person’s credit rating.
In the fourth statement, the conclusion seems like an unconditional constraint
because it defines a situation that must never be true. In the fifth statement, the
conclusion is the result of a computation because it provides a specific formula.
Regardless, each of these statements still arrives at a conclusion using certain facts
as input (i.e., conditions) specified by business leaders.
Capturing business logic, from conditions to conclusions, and refining it until
it is atomic, precise, unambiguous, and aligned with business objectives is what the
Decision Model and its principles are all about. A Decision Model is a prescription
for how the business arrives at fact-based conclusions that collectively represent the
intended business logic behind a business decision.
These individual conclusions and their representation in a Decision Model
are independent of whether they support complex custom software, purchased
software packages, or processes carried out by humans. In fact, a Decision Model
conforms to all Decision Model principles regardless of type of automation or lack
thereof. In practice, it is best to develop a Decision Model up front and then determine
whether the Decision Model is best carried out by technology or by humans.
If technology is most appropriate, the Decision Model can assist in selecting the
technology that best fits the characteristics of the business logic behind the business
1The concept of a business decision is discussed later in this chapter and covered in more detail
in the next chapter. For now, it is sufficient to recognize that a Decision Model is the business
logic behind one business decision, and hence has very specific boundaries
2Examples of other kinds of models include process models, data models, object models, and
other kinds of architectural models (e.g., enterprise architecture, system architecture, and
technology architecture models).
3One characteristic of business logic, for example, is whether it is very computation-oriented or
more inference-oriented. Therefore, the characteristics of the business logic behind a business
decision, its complexity, and its political sensitivity should be understood up front so that the
most appropriate technology for its automation can be selected.
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