Analytics Magazine on OODA

While discussing the proposed OMG Decision Modelling standard with business rules specialist Ron Ross recently, Ron reminded me of the list of “roles” that “decisions” can provide:

Classification, Evaluation, Selection, Approval, Assessment, Assignment, Allocation, Diagnosis, Prediction

Curious as to what sources might refer to this list, I “googled” for these terms and one of the first relevant results was…

Threat evaluation and weapon assignment decision support: A review of the state of the art (2006-2007)

This is a fascinating paper that targets the military domain but nonetheless is very relevant to CEP (and indeed business) methodology:

1. “Threat evaluation” is also a business task: business threats are things like poor customer satisfaction, poorly managed product marketing, changing business conditions (locally or across the business), inability to predict business changes, regulatory compliance risks, and so on.
2. “Command and control” (a.k.a. business management) methodologies are also of interest: the paper refers to Boyd’s Orient-Observe-Decide-Act (OODA) cycle, Lawson’s Sense-Process-Compare-Decide-Act cycle, and a Monitor-Assess-Plan-Execute cycle.
   • Orient means setting up measurements, or event sources
   • Observe, Sense-Process-Compare, and Monitor means event (including “complex event”) detection, and all the associated processes for complex event processing.
   • Decide means making some decision based on our observed events.
   • Act and Plan-Execute mean behaviors that in turn will likely affect the environment and future events.
3. The paper refers to the JDL Data Fusion model which may well be familiar to some CEP folk: this model describes (with a minor translation from the table in the paper) the use of and relationships between:
   • event assessment
   • complex event or entity assessment
   • situation or state assessment
   • impact or cost-benefit assessment
   • performance or goal assessment.

I would therefore claim that the relationship between events and decisions seems not only very clear, but also well recognised.

One of the interesting aspects of “complex event processing” is that “processing” typically encompasses MORE than just event pattern detection (in many use cases). For example:

• in algorithmic trading, you can detect a trade opportunity, but must decide whether to act on it immediately or refer to some risk management rules or process
• in airline operations, you can detect a solution to some passenger delay events, but you must decide whether to simply notify the gate manager or initiate some solution process
• in customer management / CRM, you can detect a customer “change in state” event pattern, but must decide whether to respond with an appropriate offer or simply update the customer record
• in smart grid systems, on detecting a potential transformer outage indicator event pattern, you must decide whether and how to reduce load on the system versus prioritising the maintenance team
• etc etc.

Of course, the process of detecting patterns, making decisions, and instigating appropriate reactions is rarely expressible in a simple orchestration or sequence diagram - event processing is continuous and decisions can simply affect the types of patterns we are looking for. This is why CEP tools often use declarative constructs for defining pattern and decision knowledge, and multiple paradigms / event processing element types or languages for event detection and event-based decisions.

Although I prefer to differentiate CEP-based analytics between event-driven (some complex events cause you to run some analytic function) and event-based (analytic operations working event-at-a-time or on the event stream directly), Seth Grimes has just published an interesting article titled “CEP+BI= Event Analytics” in Intelligent Enterprise.

Seth had some useful data to back up his comments from a survey on “data analysis software”: “Responses to the question, “What business value can you see in real-time, continuous analysis?” demonstrate not only that current and potential users see value in “faster decisions” (68%) and “more accurate and timely information” (61%) but also that these capabilities are directly linked to concrete business measures that affect the profitability such as “higher customer satisfaction” (42%), “lower personnel and operational costs” (32%), and “increased sales” (26%).”

PS: partly related and very insightful was Tony Baur’s related observation via Twitter: “So in essence, CEP makes BI literally actionable. IOW BI is embedded in execution.”