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Haley / ART syntax lives on in open-source Java rules

The ART syntax lives on in yet another product! 

JBOSS Rules (formerly Drools) just described its imminent support for rules expressed in the CLIPS syntax here.

NASA derived CLIPS from the syntax of Inference Corporation’s Automated Reasoning Tool (ART) in the mid-80s.  I designed and implemented the ART syntax with Chuck Williams on a team with Brad Allen and Mark Wright. 

CLIPS didn’t have many of the features of ART (including an ATMS or backward chaining, for example), but it Continue reading “Haley / ART syntax lives on in open-source Java rules”

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Understanding events and processes takes time

We have been teaching a computer to answer questions like, “How much did IBM’s earnings change last quarter?”  It takes a fair bit of knowledge, including how to understand English, to answer this question.  But teaching it what a “quarter” is brought back memories of debates with some former CMU colleagues about what units are and how to model time.  Since quite a few people ask me for help with knowledge engineering and ontological matters, I thought some might be interested in parts of those debates.As you will see, a strong upper ontology of common knowledge is required to understand common business knowledge.  Leveraging such an ontology is the only way to deliver business rules for under $50.

Sentences like “do something if more than a number of possibly related things have happened within a timeframe of something else happening” or “do something if nothing happens within a timeframe following something happening” are extremely common in business process management (BPM), complex event processing (CEP), and workflow.  With a sense of time, a business rules management system (BRMS) can support BPM, CEP, and workflow applications almost trivially.  Without a sense of time, most BRMS force users to perform computations.

For example, without a sense of time and an infrastructure that supports it, the sentence “call a customer if no response is received within 30 days of notifying the customer of a delinquency” has to be transformed into something like “if a notice is mailed on a date and the notice is a delinquency and the date of notification has a day number then compute the date for checking by adding 30 to the day number and check for a response to the delinquency notice on the date for checking”.  The checking on a date for a response to a notice must also be implemented as a database (or persistent queue) of events to be polled or triggered by application code.  Then a second rule is required to implement the check, as in “if checking whether a response has been received to a notice and the notice was given on a date of notice and the notice was given to a customer and there exists no record of communication with the customer since the date of notice then call the customer”.  (Note that this is actually how most BRMS products would implement this.  The natural language approach I prefer handles the original sentence.)

The discussion here reflects the general structure and content that a usable ontology for business process management requires.  Most users of business rules management tools will find the need to understand and engineer this discussion in their tool of choice.  As my Haley Systems customers know, much of this is reflected in Authority’s built-in ontology and English vocabulary, but quite a few of the points discussed here reflect improvements, especially concerning the confusion between units and amounts.

As you will see the discussion takes careful thinking.  Some readers may find it onerous.  If at any time you have had enough (or if you simply cannot take anymore!), please skip to the end and decide whether to fill in the conclusions by revisiting the body.

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The $50 Business Rule

Work on acquiring knowledge about science has estimated the cost of encoding knowledge in question answering or problem solving systems at $10,000 per page of relevant textbooks. Regrettably, such estimates are also consistent with the commercial experience of many business rules adopters. The cost of capturing and automating hundreds or thousands of business rules is typically several hundred dollars per rule. The labor costs alone for a implementing several hundred rules too often exceed $100,000.

The fact that most rule adopters face costs exceeding $200 per rule is even more discouraging when this cost does not include the cost of eliciting or harvesting functional requirements or policies but is just the cost of translating such content into the more technical expressions understood by business rules management systems (BRMS) or business rule engines (BRE).

I recommend against adopting any business rule approach that cannot limit the cost of automating elicited or harvested content to less than $100 per rule given a few hundred rules. In fact, Automata provides fixed price services consistent with the following graph using an approach similar to the one I developed at Haley Systems.

Cost per Harvested or Elicited Rule

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Elicitation and Management of Rules, Requirements and Decisions

A manager of an enterprise architecture group recently asked me how to train business analysts to elicit or harvest rules effectively. We talked for a bit about the similarities in skills between rules and requirements and agreed that analysts will fail to understand rules as they fail to understand requirements.

For example, just substitute rules in the historical distribution of requirements failures:[1]

  • 34% Incorrect requirements
  • 24% Inadequate requirements
  • 22% Ambiguous requirements
  • 9% Inconsistent requirements
  • 4% Poor scoping of requirements
  • 4% Transcription errors in requirements
  • 3% New or changing requirements

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When Rules Meet Requirements

I am working on some tutorial material for business analysts tasked with eliciting and harvesting rules using some commercial business rules management systems (BRMS). The knowledgeable consumers of this material intuitively agree that capturing business rules should be performed by business analysts who also capture requirements. They understand that the clarity of rules is just as critical to successful application of BRMS as the clarity of requirements is to “whirlpool” development.[1]  But they are frustrated by the distinct training for requirements versus rules. They believe, and I agree, that unification of requirements and rules management is needed.

Consider these words from Forrester:

One might argue that Word documents, email, phone calls, and stakeholder meetings alone are adequate for managing rules. In fact, that is the methodology currently used for most projects in a large number of IT shops. However, this informal, ad hoc approach doesn’t ensure rigorous rules definition that is communicated and understood by all parties. More importantly, it doesn’t lend itself to managing the inevitable rules changes that will occur throughout the life of the project. The goal must be to embrace and manage change, not to prevent it. [2]

But note that Forrester used the word “requirements” everywhere I used “rules” above!

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Missing Goals and Requirements in Business Rules

Both of the following statements are true, but the first is more informative:

  1. Business Rules Management Systems (BRMS) typically produce forward chaining production rules that are interpreted by[1] a business rules engine (BRE) based on the Rete Algorithm.
  2. BRMS typically generate rules that are interpreted by a BRE.

First, dropping the word “production” before “rules” loses information. BRMS do not typically generate rules that are not production rules. Consider, for example, the BRMS vendors involved in the OMG effort produced the Production Rule Representation (PRR) standard. The obvious question is:

  • What is different about production rules?

Second, dropping the words “based on the Rete Algorithm” loses information. The dominant rules vendors and open-source engines are all based on the Rete Algorithm.

  • Why does the Rete Algorithm matter?

Third, dropping the word “chaining” before “rules” loses information. Chaining refers to the sequential application of rules, as in a chain where each link is the application of one rule and links are tied together by their interaction. But:

  • Why does chaining matter?

Fourth, dropping the word “forward” before “chaining” loses information. Forward chaining reacts to information without requiring goals. This begs the question:

  • Don’t goals matter?

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Business Rules Process Management

Some strategy folks in an enterprise architecture group recently asked for help making rules more relevant to their organization. Their concerns ranged from when to embed rules in their middle tier versus encapsulate them within services to identifying ideal use cases and reference implementations. They were specifically interested in coupling rules with BPM and BI.

Such questions occur every time a group or enterprise considers adopting rules technology for more than a specific application. They are looking for guidelines, blueprints, or patterns that will help them disseminate understanding about when and how to use rules. They have adopted a BPM vendor which will be integrated with their selected rule vendor, each as enterprise standards, so they are particularly interested in the integration requirements between the two.

Two high level understandings are critical for success in furthering adoption of rules technology.

  1. abstract activities for which rules technology well-suited and
  2. when and why rules technology is better than familiar alternatives

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Business Rules Market Maturity

Some recent correspondence with clients and prospective adopters of business rules technology indicates interested mainstream has become increasing concerned and confused by consolidation in the business rules market.

On the analyst front, they read advice such as the following from Gartner:[1]

As Gartner has stated, the BRE market is a volatile technology sector, and market trends point to increased consolidation. In recent research, we stated that some consolidation will come from rules-to-rules acquisitions. Recent examples of this include Trilogy/Versata buying Gensym and now, RuleBurst purchasing Haley Systems.

Another form this consolidation will take is application vendors or business process management suite vendors buying much-needed rule technology, as seen in SAP’s recently announced intention to purchase Yasu Technologies. In either case, rule technology will persist, but the vendors selling the technology will often be different.

I agree with Gartner, enterprise app and BPM vendors desperately need rules technology. I also agree with the following analysis from Forrester:[2]

SAP’s decision to purchase Hyderabad, India-based Yasu Technologies greatly improves its business rules management capabilities. Other large vendors would be wise to follow SAP’s lead in the business rules market. If you look at the big vendors, they’re all going to need this technology. SAP’s competitors are going to have to step up to these requirements also.

It’s encouraging that SAP bought Business Objects and is now buying Yasu. We’re seeing requirements to link business rules and business intelligence or analytics. SAP has told us they have seen these requests, and we’re encouraged that SAP is now acting.”

Unfortunately, Gartner’s concluding advice could have been more constructive:

Prospective BRE customers: Buyer beware – the rule engine market is a volatile sector. Choose your vendors carefully and be prepared to see more BRE acquisitions.

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Managing Semantics, Vocabulary and Business Rules as Knowledge

A client recently asked me for guidance in establishing a center of excellence concerning business rules within their organization. Their objectives included:

  1. Accumulate requisite skills for productive success.
  2. Establish methodologies for productive, reliable and repeatable success.
  3. Accumulate and reuse content (e.g., definitions, requirements, regulations, and policies) across implementations, departments or divisions.
  4. Establish multiple tutorial and reusable reference implementations, including application development, tooling, and integration aspects.
  5. Establish centralized or transferable infrastructure, including architectural aspects, tools and repositories that reflect and support established methodologies, reusable content, and reference implementations.
  6. Establish criteria, best practices and rationale for various administrative matters, especially change management concerning the life cycles of content (e.g., regulations or policies) and applications (e.g., releases and patches).

I was quickly surprised to find myself struggling to write down recommendations for the skill set required to seed the core staff.  My recommendations were less technical than the client may have expected.   After further consideration, it became clear than any discrepancy in expectations arose from differences in our unvoiced strategic assumptions.  Objectives, such as those listed above, are no substitute for a clearly articulated mission and strategy.  

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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.