Decision making is of fundamental importance to any organization. Decisions are the critical mechanisms within processes which create value by changing the state of an entity[1] that represents value for the organization in question.

Decisioning focuses us on the very core of the business[2]. Some unique and identifiable entity must be traded, managed, leveraged, used, built, or sold in order to achieve the objectives of the business – for a commercial enterprise, these objectives are likely to be revenue based; other organizations might use different criteria to measure value, for instance lives saved for a clinical screening program, or constituents served for a charity.

Regardless of the measure, until something happens to the entity, the purpose cannot be achieved and no value can be derived; therefore, in order to generate value, we must have a permanent change to the entity (we will call this a state change). Note that we are interested primarily in the entities that are the basis of value and which are fundamental to the purpose of the business. Changing state implies that there is activity against the entity, and this observation gives rise to the traditional process (activity) and data (entity) systems analysis approaches.

But if we look closely at any process causing state change, we will see that the change is always the result of a decision within the process rather than the process itself. Many processes can execute against an entity, but a change in value is only derived when a state change occurs. Whenever state change occurs, the process can be shown to be a container for decisioning – the state change is a result of the decisions rather than an inherent characteristic of the process.

Definition: A Decision is a proprietary datum derived by interpreting relevant facts according to structured business knowledge.

A decision is ‘made’ when we resolve the available facts into a single definitive outcome; a decision cannot be multi-valued, ambiguous or tentative. A decision results from applying discipline, knowledge and experience to the facts that describe the subject entity. This application of discipline, knowledge and experience within decision-making is the characteristic that most closely defines the unique character of any business.

The power of automated decisions to regulate and control system responses in a zero touch processing environment is driving increasing interest in decisioning.

Decisions are clearly identifiable at the heart of any automated systems response, giving purpose to the data and direction to the process. If decision centric analysis is used to rigorously identify and describe decision-making behavior prior to systems development, then it can be used to drive the discovery of data and its relevance to the business – it is the decision requirement that is the primary driver of the need for the data. Decision analysis is therefore a primary data analysis tool, and can be used as a precursor to formal data modelling. When data analysis is driven by decision modelling, it gives rise to concise and provably relevant data models. And because decisions also predicate process responses, decision analysis also implicitly drives process definition.

Decisions are also drivers for the discovery of other decisions. For example, the decision to accept insurance business depends on precursor decisions regarding the acceptability of the customer, the insured risk, pricing calculations, etc. Each additional decision can also depend on further decisions until a tree structured model of inter-dependent decisions is formed – the ‘decision model’.  

Definition: A Decision Model is an ordered assembly of decisions that creates new and proprietary information to definitively determine an optimal and ultimately more valuable course of action for the business.

It is the Decision Model that is the highest order analysis artifact and the only one which can be tied directly to the operational strategy of the business. The concept of a model that defines order and context for decisions is a critical differentiator between the disciplines of decisioning and those of ‘business rules’. A ‘decision’ is atomic, and like its data counterpart, is only given meaning by its context. Like the data model, the decision model is the critical concept in decisioning that provides this context. Further, it is only a complete assembly of decisions within the context of the model that can drive the business response – such that the decision model must operate as a single unit of work in order to transition a business entity from one valid state to the next. The decision model representation of this transition is the only artifact in the system design world that directly describes the act of value creation for the business. It is this definition of value creation that defines each business in a way that is different from every other business – the decisions by which it conditionally accepts, values, and responds to business events. We liken this knowledge to the business DNA, given that the complete business operation can be cloned if its core decision making IP can be replicated.

[2] Note: we use the term “business” in its widest context – an organization that delivers value to its stakeholders, so that business can be considered to be synonymous with organization.