Defn: The systematic discovery, definition, deployment, and execution of computerised decision making.
Decisioning fits naturally into an automated systems framework. External events occur that require business responses. Where the business has a selection of possible responses, decisions are required to determine the most beneficial response. The business usually has a strategy for making these decisions based on prior learning experiences; if it does not, a new learning experience is required. In a healthy organisation, these learned experiences are captured as policy, which can then be automated using decisioning.
In legacy systems the decision maker is often human, so the process must be interrupted to acquire the decision. Modern systems seek responses that are 'zero touch'. To achieve zero touch, we must automate the decision-making that was performed by human 'actors' within the process, replacing them with automated proxies that immediately return accurate, regulated and auditable decisions.
It is necessary but not sufficient to incorporate decision-making know-how into the system code-base. We must also change how we build systems to take advantage of this powerful new paradigm. The decision-making knowledge results in a different class of system component to the data and processes that define the rest of the system. Events, data, and processes are generic by industry - they are relatively stable and generally do not differentiate individual businesses. Therefore we can build support for these elements on a generic, industry-wide basis. For example, all insurers have customers and risks - both of which exist completely and independently of any particular insurer. Similarly, all insurers have processes to issue policies. But all insurers will use different decisions to determine how to accept customers and risks, and how to price and qualify the policies.
So decisioning demands a new development and architectural approach to leverage the automation of decision making. When implemented as plug and play components within a comparatively static application framework, decisioning can allow the system to respond rapidly to business changes without affecting the underlying code base. The decisions driving business behaviour can adapt as fast as the business can learn.
For business management, decisioning implements business policy and practice, as well as providing the ability to experiment with, test, and audit this policy throughout the life of the business. The business focus is on developing and managing the decisions that implement corporate policy.
For the developer, the decisioning components must integrate easily, execute quickly and predictably, and not otherwise constrain architectural options. The development focus is on providing a robust, well-engineered application infrastructure to service and respond to the business decision making.
For systems vendors, this plug and play approach also allows 'mass customisation' by mixing and matching bespoke decisioning components within a common application. The Vendor focus is on mass customization.