Taming our Sentient Systems with Decision Management

Our systems are getting better at ‘sense and respond’, as they discover patterns in real-time data feeds. This big data gets generated by the social, mobile people;  and increasingly by ‘things’ like sensors and appliances – leading to the Internet of Things.

One of the core technologies that enable pattern-discovery is Complex Event Processing (CEP). The goal is to identify significant events in the environment and to respond to them appropriately. Chris Taylor on BPM for Real positions CEP as

The central nervous system that’s doing the heavy lifting for all of this change is a combination of technologies built on a platform of speed and fast cycles of change.


The interesting element in this conceptual model is the box in the middle labeled, ‘Decisions’ (highlighted in red by me). Even in Chris’ model, once the patterns have been detected, we need to decide what actions to take in order to exploit the opportunity or to counter the threat.

Opher Etzion tries to get a little bit deeper into this black box called, ‘Decisions’ and says

illustration follows the 4D: detect (channel), derive (pattern detection), decide (decision), do (actions).  The “decide” part is not necessarily “IF—THEN” rules, but can also be optimization or another event driven pattern.

While CEP is indeed a critical element for our new generation of sentient systems, the Decisions embedded within these systems need to be managed explicitly and aligned with organizational goals. We need to consider Decisions first.

Decision Management is an approach for automating and improving high-volume operational decisions. Focusing on operational decisions, it develops decision services using business rules to automate those decisions, adds analytic insight to these services using predictive analytics and allows for the ongoing improvement of decision-making through adaptive control and optimization.

A Decision Management Platform will bring together all the components of a sentient system as shown in the following excerpt from Decision Management Systems Technology Report.


Managing our sentient systems means managing the Decisions they can or they should make.




2 comments for “Taming our Sentient Systems with Decision Management

  1. April 23, 2013 at 7:06 pm

    The basic approach in OpenRules is to allow business users to manage rules directly in Excel, OpenOffice or Google Docs (allowing collaborative rules management). Rulebooks contain RuleSheets which contain different types of decision tables such as KPI Rule Families. There are special tables that allow a user to define decisions and sub-decisions. Other Excel sheets contain a glossary – a set of fact definitions – and each fact name is linked to a business concept and mapped to a technical attribute name to support implementation. To support testing, other blocks of cells in Excel can be used to define new data types and example records. Finally decision objects are defined that map business concepts to object definitions. All these are different tables managed within multiple Excel Rulebooks that can be located in a local file system, a web server, a database, or can be created dynamically from a custom GUI. Rulebooks can be managed in the OpenRules repository with check-in/check-out and versioning at the Rulebook level. The repository allows advanced searches supported by Excel and related tools but little or no impact analysis in terms of database changes and their impact on rules – users can obviously do a lot in Excel, however, as Excel functionality remains available.

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