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Event-centricity driving TIBCO

The call transcript from TIBCO’s Dec 21 review of Q4 results is great reading.  Starting from a simple Rete Algorithm and the insightful acquisition of Spotfire, TIBCO has transformed itself from a technical middleware vendor to a promising enterprise platform.

TIBCO has a long way to go in making its business optimization offerings less technical, but for those that can tolerate less alignment between IT and the business than may be ideal, TIBCO is leading the way in integrating technical agility with business visibility.

It will be tough for Oracle or IBM or SAP to close the gap with what TIBCO has.  Don’t be surprised if rule-based event-driven business processing drives the acquisition of TIBCO by one of these over the next two years.  The growth rate certainly justifies it!  And it won’t stop.

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Event-centric BPM and goal-driven processing

The slides for my Business Rules Forum presentation on event semantics and focusing on events in order to simplify process definition and to facilitate more robust governance and compliance are at Event-centric BPM.

After the talk I spoke with Jan Verbeek and Gartjan Grijzen of Be Informed and reviewed their software, which is excellent.  They have been quite successful with various government agencies in applying  the event-centric methodology to produce goal-driven processing.  Their approach is elegant and effective.  It clearly demonstrates the merits of an event-centric approach and the power that emerges from understanding event-dependencies.  Also, it is very semantic, ontological, and logic-programming oriented in its approach (e.g., they use OWL and a backward-chaining inference engine).

They do not have the top-down knowledge management approach that I advocate nor do they provide the logical verification of governing policies and compliance (i.e., using theorem provers) that I mention in the talk (see Guido Governatori‘s 2010 publications and Travis Breaux‘s research at CMU, for example) but theirs is the best commercially deployed work in separating business process description from procedural implementation that comes to mind. (Note that Ed Barkmeyer of NIST reports some use of SBVR descriptions of manufacturing processes with theorem provers.  Some in automotive and aerospace industries have been interested in this approach for quality purposes, too.)

BeInformed is now expanding into the United States with the assistance of Mills Davis and others.  Their software is definitely worth consideration and, in my opinion, is more elegant and effective than the generic BPMN approach.

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RulesFest 2011 keynote

The slides for my keynote at RuleFest 2011 are here.

Excellent presentations on complex event processing by Paul Vincent of TIBCO and Mauricio Salatano who showed simple, effective integration of events and rules using Drools.  Mauricio’s was a good demo and Paul’s slides are worth perusing once they go on-line.  (Some comments from Carlos about Paul’s, Mauricio’s,  and my presentations are here, here and here, FYI.)

Christian St. Marie and Hugues Citeau each of Ilog (IBM) on improving RIF support in JRules and the worthy ONTORULE project, respectively.  Both presentations confirm the gulf between production rules and sufficient logical expressiveness to support natural language or natural logic knowledge management, but IBM is clearly aware of  and trying to address the challenges raised in my presentation.

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Simple problems with the semantic web

The standard for defining ontologies these days is OWL and Protege.  Unfortunately, OWL lacks any notion of exceptions in inheritance or any other notion of defeasibility.

So, although you may want to say that birds fly, you’re ontology will be broken (or become much more complicated) when you realize there are birds that can’t fly, such as penguins or ostriches, or even sick or injured birds.

Practically speaking, you need something like courteous logic or the defeasibility in SILK to handle this (or any 1980s expert system shell or even earlier frame system).  OWL is very hard on mortal man (e.g., mainstream IT) in this regard.

How can I tell OWL that a pronoun is a noun but that pronouns are a closed class of words, unlike nouns, verbs, adjectives, and adverbs (in general).  Well, I’ll have to tell it about open-class nouns versus closed class nouns.  What a pain!

This is why we use Protege primarily as a drafting tool and, for example, SILK, to do reasoning.   Non-defeasible description logic and first-order reasoners are difficult to get along with, in practice (and make sustainable knowledge repositories too difficult – which inhibits adoption, obviously).

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Rules vs. applications of knowledge

I was just asked for some background on business rules and the major players, preferably in the form of videos. The request came in by email, so I didn’t have the opportunity to immediately ask “why”.   Below I give some specific and direct responses, but first a few thoughts about clarifying objectives.

I don’t know of any video that is particularly good from an executive overview standpoint concerning “business rules” or even “decision management” let alone “management of active knowledge”.    My recommendation is to clarify the objective before drilling into “business rules”, which is a technical perspective.  What is it that you are trying to accomplish?  Most abstractly, it could be to manage and improve performance of an activity or an organization.  That kind of answer or focus is the right place to start and then work backwards to the technical approach rather than start with an inadequately conceived technical need.  This is one of the major problems with business rules as an independent market or product line.

Learning from Enterprise Decision Management

While at Fair Isaac, James Taylor saw this clearly.  He articulated the enterprise decision management (EDM) and positioned the business rules capability Fair Isaac acquired with Blaze Software in that space.  That is, more as a strategic objective than as a tool or technology.  This is an example of the proper way to think about business rules.

The decision management perspective was also narrowly focused on point decision making (e.g., using rules) but James and others (e.g., John Lucker of Deloitte) have appropriately expanded the strategy of decision management to include analytics, which produce and inform decision making (i.e., business rules), into a continuous process not of point decision making, but more closed-loop, continuous process improvement.  Over recent years, this has evolved into the broader market of performance management, which also includes performance optimization.

The key thing to consider when considering inquiries about “the applications and market for business rules” is the applications of knowledge.  The “knowledge engineering” community is often too focused on the sources of knowledge.  Focusing on sources rather than opportunities and benefits is a big part of why the business rules market has been subsumed into the business process management market, which is small in comparison to the business intelligence market, the fastest growing segment of which is performance management.

Semantic enterprise performance optimization checklist:

Here’s a checklist to consider when framing your considerations of strategies and tactics that might involve business rules technology:

  1. What knowledge (including policies, regulations, objectives, goals) is involved?
  2. What knowledge is superficial (i.e., derived from or approximations of) versus deeper knowledge?
  3. Will you capture the motivation for a decision rather than how that decision is made using rules?
  4. How will the performance  of your decision management or governance system be evaluated?
  5. Is the knowledge involved in evaluating such performance part of the knowledge that you will capture and management?
  6. How does the manner of evaluation relate to goals and objectives and over what time frames?
  7. Is the knowledge about goals and objectives time frames part of the knowledge to be managed?
  8. Are your decisions rigidly governed in every aspect or do you need the business process to include experimentation and optimization?

Most business rules efforts are focused on contexts so narrow that they are reduced to technical buying criteria without much or any consideration of the above.  That is, most business rule efforts do not even cover point 1 above.  Few reach bullet 2 and only strategic thinkers get to the third.

Specific recommendations for the naive question:

So I went off looking for videos…  You can find some on technical matters involving IBM/Ilog but I didn’t find any good videos from IBM at the business strategy level which concerned knowledge-based process/decision management/governance, which surprised.

A video from the vendors of Visual Rules touches on many of the traditional buying points that IT people typically formulate before evaluating vendors (here).

Although it did not respond to the inquiry, I sent along this video of James’ since it touches on so many of the aspects beyond business rules that are increasingly in vogue, even if it does not go far enough towards things like the business motivation model and the market for performance management, imo.

And for a very thorough background in the form of an analyst presentation that is consistent with all of the above, John Rymer of Forrester is most thorough in the two longer presentations that are here and there.

Please send me any other content that you would recommend!

Paul

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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).

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What is has always been going to be

I’ve been working for a while now on an ontology for representing events (which includes process, of course).  One of the requirements of a system that is to monitor, govern, implement, or reason about processes is that it consider “situations”, which are things that happen or occur, including events and states.  (See, for example, the perdurants of the DOLCE ontology, BFO‘s occurents, or OpenCyc’s situations.)  This requires the representation of time-variant information at various points or during various intervals of time (more than just the Allen relations or OWL Time).   If you’re interested in such things, I’d recommend Parsons‘ “Events in the Semantics of English” or Pustejovsky‘s “Syntax of Event Structure“, both of which look at the subject from a linguistic rather than inferential perspective.  When you pursue this to the point that you implement the axioms that an artificial intelligence needs to provide assistance in defining or governing a business process (or answering questions about molecular biological processes) you land up in some pretty abstract stuff, including the Stanford Encyclopedia of Philosophy.  I found the title of this post entertaining within the page on temporal logic.

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IBM Ilog JRules for business modeling and rule authoring

If you are considering the use of any of the following business rules management systems (BRMS):

  • IBM Ilog JRules
  • Red Hat JBoss Rules
  • Fair Isaac Blaze Advisor
  • Oracle Policy Automation (i.e., Haley in Siebel, PeopleSoft, etc.)
  • Oracle Business Rules (i.e., a derivative of JESS in Fusion)

you can learn a lot by carefully examining this video on decisions using scoring in Ilog.  (The video is also worth considering with respect to Corticon since it authors and renders conditions, actions, and if-then rules within a table format.)

This article is a detailed walk through that stands completely independently of the video (I recommend skipping the first 50 seconds and watching for 3 minutes or so).  You will find detailed commentary and insights here, sometimes fairly critical but in places complimentary.  JRules is a mature and successful product.  (This is not to say to a CIO that it is an appropriate or low risk alternative, however. I would hold on that assessment pending an understanding of strategy.)

The video starts by creating a decision table using this dialog:

Note that the decision reached by the resulting table is labeled but not defined, nor is the information needed to consult the table specified.  As it turns out, this table will take an action rather than make a decision.  As we will see it will “set the score of result to a number”. As we will also see, it references an application.  Given an application, it follows references to related concepts, such as borrowers (which it errantly considers synonomous with applicants), concerning which it further pursues employment information.

Continue reading “IBM Ilog JRules for business modeling and rule authoring”

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Progress towards Knowledge-based Enterprises

I couldn’t agree more with these points from Giles Nelson’s article in CIO on BPM and event processing (as highlighted by TIBCO’s Paul Vincent): 

…we need to take a different view of BPM technology and try to see how it can be used to make knowledge-based business more ‘operationally responsive’… …the potential for creating real business value by bringing together the two disciplines of event processing and BPM is substantial…

As Paul notes, this follows Progress’ acquisition of Savvion (i.e., CEP vendor buying BPM vendor). 

I am glad to see other leaders pursuing the vision of knowledge-based enterprise.  As I discussed, IBM is getting there (but SAP seems out of the picture).  Will Oracle take the lead?

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Google vs. Facebook and Bing (again)

Almost a year ago, I wrote about semantics and social networking as threats to Google.  In that post, I referenced a prior article on investments in natural language processing, such as Microsoft’s acquisition of Powerset, which is now part of Bing.

Today, there are two articles I recommend.  The first addresses the extent to which Google’s Superbowl ad is a response to the threat from Bing.  The second addresses Facebook overtaking Google.