BRMS Developer (WebSphere ILOG JRules)

You will have proven experience as a BRMS Developer within a Java/JEE environment using IBM‘s WebSphere ILOG JRules platform. You will have implementation experience using integration technologies (e.g. Web Services, JMS) and have the ability to liaise with and engage key stakeholders.  Ideally you will also have knowledge and/or exposure to IBM‘s WebSphere integration suite (including the MQ Series).

This got a reaction out of me since we’re looking for people (although emphasizing logic, semantics, and English rather than any particular engine).  At first, I thought it must be a Java job, but stakeholder engagement indicates this is a full-fledged knowledge engineering position.

$100k for anyone with strong, specific experience seems low.  For someone that can understand objectives and translate requirements into operational business logic, it seems lower.

I’m surprised there isn’t more of an Ilog premium, too.  JBoss Drools consultants can make more than this.

• the bulk of revenues and all the growth was in pre-configured Decision Management applications
• FICO score revenues were half as much, w/ B2B growing as B2C (myFICO) waned
• tools revenues were less than half again as much and flat
  • optimization (XPress) was up
  • Blaze Advisor was down

This is in sharp contrast to the success that Ilog has enjoyed under the IBM umbrella.

Blaze Advisor doesn’t seem to make sense as a stand-alone tool any more.   Applications are great, and so are combinations of BI/optimization/rules, but if the BRMS tool will survive independently it needs to find more traction, perhaps outside of Fair Isaac.

the innovative Decision Graph visual metaphor, a decision tree management solution that makes even the most complex rule sets easier to manage and explain

Of course, a decision tree is really more like a root system (i.e., the tree is upside down).  So, what this capability is particularly good for explaining how some pretty structured logic gets wherever it lands up, which FICO touts:

The new capability is especially valuable to businesses that need to be able to explain their decision logic to external auditors and regulators, or to internal parties such as senior management.

Unfortunately, this capability is only good for business logic that has been heavily analyzed and transformed from more natural forms of knowledge that stakeholders and regulators understand or communicate about.

FICO’s suggestion is that after operational guidelines and regulations have been laboriously translated (literally and, hopefully, appropriately) into if-then-else logic (i.e., decision trees) that viewing the path through the “code” will be informative to stakeholders and suitable for regulators.  That seems like quite a stretch given the immediately following sentence, which indicates the complexity of using the metaphor in the first place:

Decision Graph gives business analysts a more intuitive way to view and navigate decision trees, which can reach 10,000 nodes or more.

Lots of people are attracted to such “visual programming” metaphors, but they are extremely limited in their logical expressiveness and, therefore, in their utility.  Still, if you are using induction technology (such as FICO’s)  to produce very large decision trees (independent of governing policies or regulations) such a tool can be useful, if only to understand what the machine “discovered” or to explain “how” it reached a decision, albeit post facto, which may or may not be compliant with governing doctrine.

The press release also talks about using this structure to experiment or optimize certain decisions by simulation, which is good stuff.  FICO has long led in this area, especially in the markets it focuses on (i.e., B2C financial).  This would have been a better central point, imo.

Overall, I agree with the following quote embedded within the release:

“Business rules management provides a shared platform for CIOs and business managers to help their enterprises stay competitive, and making business logic clearer to all parties is an essential part of that collaboration,” said Jim Sinur, a vice president at Gartner Research specializing in business rules management systems. “Better visualization of business logic can provide a huge uplift for companies that are looking for ways to improve business decisions.”

Showing thousands of nodes in a tree or cells in a table does not accomplish the appropriate goal (i.e., effective collaboration) of the first clause, however.  And Jim did not say that decision trees provide effective visualization.

My take: the best approach is to guarantee that the statements of business policy and regulation are unambiguously understood by machine intelligence that automatically translates them into completely reliable systems.

That is, the best visualization for general purposes may be plain English.

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.

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.

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.

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).

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

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):

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 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.

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).