Tendencies and purpose matter

The basic formal ontology (BFO) offers a simple, elegant process model.   It adds alethic and teleological semantics to the more procedural models, among which I would include NIST’s process specification language (PSL) along with BPMN.

Although alethic typically refers to necessary vs. possible, it clearly subsumes the probable or expected (albeit excluding deontics0).  For example, consider the notion of ‘disposition’ (shown below as rendered in Protege):

BFO's concept of 'disposition'

For example, cells might be disposed to undergo the cell cycle, which consists of interphase, mitosis, and cytokinesis.  Iron is disposed to rust.  Certain customers might be disposed to comment, complain, or inquire.

Disposition is nice because it reflects things that have an unexpected high probability of occurring1 but that may not be a necessary part of a process.   It seems, however, that disposition is lacking from most business process models.  It is prevalent in the soft and hard sciences, though.  And it is important in medicine.

Disposition is distinct from what should occur or be attempted next in a process.  Just because something is disposed to happen does not mean that it should or will.  Although disposition is clearly related to business events and processes, it seems surprisingly lacking from business models (and CEP/BPM tooling).2

A teleological aspect of BFO is the notion of purpose or intended ‘function’, as shown below:

Function according to the Basic Formal OntologyFunction is about what something is expected to do or what it is for.  For example, what is the function of an actuary?  Representing such functionality of individuals or departments within enterprises may be atypical today, but is clearly relevant to skills-based routing, human resource optimization and business modeling in general.

Understanding disposition and function is clearly relevant to business modeling (including organizational structure), planning and performance optimization.    Without an understanding of disposition, anticipation and foresight will be lacking.  Without an understanding of function, measurement, reporting, and performance improvement will be lacking.

0 SBVR does a nice job with alethic and deontic augmentation of first order logic (i.e., positive and negative necessity, possibility, permission, and preference).

1 Thanks to BG for “politicians are disposed to corruption” which indicates a population that is more likely than a larger population to be involved in certain situations.

2 Cyc’s notion of ‘disposition’ or ‘tendency’ is focused on properties rather than probabilities, as in the following citation from OpenCyc.  Such a notion is similarly lacking from most business models, probably because its utility requires more significant reasoning and business intelligence than is common within enterprises. 

The collection of all the different quantities of dispositional properties; e.g. a particular degree of thermal conductivity. The various specializations of this collection are the collections of all the degrees of a particular dispositional property. For example, ThermalConductivity is a specialization of this collection and its instances are usually denoted with the generic value functions as in (HighAmountFn ThermalConductivity).

Time for the next generation of knowledge automation

In preparing for my workshop at the Business Rules Forum in Las Vegas on November 5th, I have focused on the following needs in reasoning about processes, about events, and about or over time:

  1. Reasoning at a point within a [business] process
  2. Reasoning about events that occur over time.
  3. Reasoning about a [business] process (as in deciding what comes next)
  4. Reasoning about and across different states (as in planning)

Enterprise decision management (EDM) addresses the first.  Complex event processing (CEP) is concerned with the second.  In theory, EDM could address the third but it does not in practice.  This third item includes  the issue of governing and defining workflow or event-driven business processes rather than point decisions within such business processes. 

Business applications of rules have not advanced to include the fourth item.  That is to say, business has yet to significantly leverage reasoning or problem solving techniques that are common in artificial intelligence.  For example, artificially intelligent question and answer systems, which are being developed for  the semantic web,  can do more than retrieve data – they perform inference.  Commercial database and business intelligence queries are typically much less intelligent, which presents a number of opportunities that I don’t want to go into here but would happy to discuss with interested parties.  The point here is that business does not use reasoning much at all, let alone to search across the potential ramifications of alternative decisions or courses of action before making or taking one.  Think of playing chess or a soccer-playing robot planning how to advance the ball on goal.  Why shouldn’t business strategies or tactical business decisions benefit from a little simulated look-ahead along with a lot of inference and evaluation?

Even though I have recently become more interested in the fourth of these areas, I expect the audience at the business rules forum to be most interested in the first two points above.  There will also be some who have enough experience with complex business processes, which are common in larger enterprises.  These folks will be interested in the third item.  Only the most advanced applications, such as in biochemical process planning, will be interested in the fourth.  I don’t expect many of them to attend!

The notion of enterprise decision management (EDM) is focused on point decision making within a business process.  For enterprises that are concerned with governing business processes, a model of the process itself must be available to the business rules that govern its operation.  I’ve written elsewhere about the need for an ontology of events and processes in order to effectively integrate business process management (BPM) with business rules.  Here, and in the workshop, I intend to get a little more specific about the requirements, what is lacking in current standards and offerings, and what we’re trying to do about it. Continue reading “Time for the next generation of knowledge automation”

Process vs. Decisions

In comments to a recent post concerning the acquisition of Haley Systems by Ruleburst, James Taylor suggested that a “decision-centric” perspective is necessary for business rules to become mainstream.  In subsequent correspondence, I questioned whether fixating on decisions would achieve his objectives for enterprise decision management.   EDM hopes to integrate business intelligence (e.g., predictive analytics) with point decision making so as to improve decision making over time.  This is a natural step beyond the typical point decision making application of business rules, such as in a stateless web service that returns a simple decision, such as a score, price or simple yes/no.  But it is a narrow perspective on the broader confusion between business rules and business process that has been holding back the mainstream.

For years, smart people have been searching for a razor to determine what logic they should “code” in process versus as rules (e.g., using a BRMS versus their BPM platform).  At first glance, the decision-centric approach seems to have the answer.  Simply put a decision node in your business process diagram and let the BPM tool orchestrate the decision implemented as a stateless web service! 

Unfortunately, this alluring answer is all too often inadequate or impractical.  The business rule vendor has effectively transfered responsibility for managing state (i.e., information collection and provisioning) into the business process diagram and orchestration tools – or code.  The result is implementation complexity, limited user communities, cost overruns and failures.  That will certainly hold back mainstreaming a bit!

A better answer is coming.  Complex event processing anticipates that business processes and decision making can be stateful, as Paul Vincent explains briefly but well here.  When CEP is supported by knowledge capture, management and automation tools such as the better BRMSystems provide, the lines between process specification and decision specification will further blur beyond the adequacy of the decision-centric advisory.   Expect this to happen in 2008.