Enabling Operational Excellence
Enabling Operational Excellence
Enabling Operational Excellence
Enabling Operational Excellence

TURNING OPERATIONAL KNOWLEDGE & COMPLIANCE INTO A COMPETITIVE EDGE

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Calling everything a decision? That does no more good than calling everything ‘thing’!

A decision management tool vendor recently wrote:

“The relation between business rules and decisions is I think pretty well agreed by all – it’s just that some focus on 1 or the other, and some both – any “disagreement” is more on the value in the different approaches.”

I respectfully disagree (strongly).  There are fundamental differences between decision rules and behavioral rules including these: 1. Behavioral rules are usually one of a kind. They don’t fit in decision tables. Some might appear in decision models if you are concerned about such things as integrity (will the DMN standard be?), but the large majority don’t. 2. Decisions are generally single point of determination for any given real-world case. Most behavioral rules are multi point of determination, meaning they could be violated under quite different circumstances. 3. The detection of violations of behavioral rules should be automatic and event-based. There’s no “decision” involved in the detection … it should be automatic. (This is where the current generation of rule engines … mostly based on 1980s expert-system thinking … fall woefully short. It’s also probably one reason they haven’t become more mainstream in industry mindshare.) 4. Behavioral rules generally have a different source than decision rules … laws, regulations, contracts, agreements, deals, certifications, warranties … and business policies. Decision rules sometimes arise from those sources, but if so, have limited coverage. Decision rules in contrast often arise from the heads of knowledge workers and inspection of big data and event streams. (Behavioral rules do too, but likewise don’t begin to cover everything.) So the issue is by no means simply a “matter of approach”. Spinning it that way might be useful for vendors, but it won’t be helpful to business analysts. We need to think soberly about the true range of business rules and the fundamental distinctions that exist. If not people will end up very frustrated on the other side of the DMN hype cycle. We can do better than that, and for the sake of the DMN standard, we should. P.S. For discussion and examples of the fundamental distinction between behavioral rules and decision rules see Appendix 3 in the DecisionSpeak Primer … available for free download on http://www.brsolutions.com/b_ipspeakprimers.php.  By the way, DecisionSpeak and its companion TableSpeak are *quite* concerned about integrity in decision models.

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Open Letter re: Decision Models

written in response to Jacob Feldman: http://www.brsolutions.com/2013/05/07/response-to-decisionspeak-tablespeak-annnouncement/ Jacob, Thanks! And I agree with you about the ‘executable’ part. Our emphasis is on business-friendly, business-driven models. I believe DecisionSpeak and TableSpeak move things forward significantly in that regard. There’s no reason why decision models have to be oriented to IT development. If they are robust, they will nonetheless be executable. I would sound a note of caution. Decision models are no silver bullet. There are issues of semantics (vocabulary) and integrity (restrictions) to be addressed. And they don’t cover even the majority of all business rules – especially behavioral rules. If you throw everything you (should) know about business rules out the window when you use decision models, you will be in for a very rude awaking. I’m glad we did not rush to the market. We’ve taken our time to do our homework with respect to theory (which has been out there for a great many years) and to hone our approach in real-life consulting work. I think the results speak for themselves!

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Response to DecisionSpeak / TableSpeak Announcement

guest post by Jacob Feldman First of all, congratulations on your new Primers that provide very detailed convention sets for the decision management domain. I quote from your documents: * DecisionSpeak™, a set of conventions for expressing the meaning of operational business decisions. * TableSpeak™ is a set of conventions for business-friendly representation of decision tables and their meaning (semantics) in declarative fashion. Naturally, my first thought is: can we make these conventions EXECUTABLE? More precisely: Can we help subject matter experts (not programmers) to: – create documents that follow these conventions? – automatically validate (enforce) compliance to these conventions? – execute the compliant documents? After a quick walking through the documents, I think the answers are YES. We, at OpenRules, should be able to build OpenRules templates (in Excel) that supports these conventions and to direct users how to apply these templates to create, validate, and execute concrete decisions, decision tables, and other types of rules. There are certainly many details how better to address certain constructions described in TableSpeak™, but they all look solvable to me. Previously, we provided a similar implementation as soon as another decision modeling methodology (TDM) was published. Now we are working with James Taylor making business requirements created by his newest DecisionFirst Modeler executable. As you know, OpenRules is also working on a reference implementation for the DMN as this standard comes to the age. It would be only natural to provide support for the IPSpeak™ methodology. Based on our previous positive experience working with you, Gladys, and other experts from BRS, I am looking forward to making IPSpeak™ executable. http://openrules.com

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Looking to Find Out What Decision Analysis is About? Make Business Processes & Business Architectures Smart? Design Business-Friendly Decision Tables? Write Business-Friendly Business Rules? >>> Free downloads …

As part of the April announcement of the new 4th edition of my book Business Rule Concepts: Getting to the Point of Knowledge, I’m pleased to make available some additional complementary (and complimentary!) downloads: Decision Analysis – A Primer: How to Use DecisionSpeak and Question Charts (Q-Charts) – 49pp http://www.brsolutions.com/IPSpeakPrimers (free) Decision Tables – A Primer: How to Use TableSpeak – 121pp http://www.brsolutions.com/IPSpeakPrimers (free) Tabulation of Lists in Rulespeak®: A Primer Using “The Following” Clause – 16pp http://www.brsolutions.com/IPSpeakPrimers (free) We’ve comprehensively written-up state-of-the-art experience and insight in these important areas. I hope you will make the most of them! P.S. Do have a look at other items of interest: http://goo.gl/WPV7O  

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Announcing New Online Interactive Training: Decision Analysis & Decision Tables: All About Modeling Decisions

Location: Online Interactive Training Why Attend … Working on developing requirements? Wrestling with complex business process models? Harvesting business rules to implement in a rules engine? Many professionals are finding there are big gaps in their current approaches:
  • Their requirements methodology fails to capture and specify decision logic.
  • Their business process models mangle the logic for making decisions.
  • Their decision management platforms support implementation but don’t connect to the business.
This training provides proven, pragmatic solutions. It provides 8 easy steps so you can think clearly before you implement. More info:  http://www.attainingedge.com/online-training-decision-analysis-and-decision-tables.php

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Omissions? My Cumulative List of *Desktop, Internet and Personal-Device* Problems for which Business Rules, Decision Management, and Related Technologies are Suited

Find your desktop, internet or personal-device application in this list? If not, please let me know! ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Authorization … identity, certification, software licensing Collaboration … routing, RFI/RFP work management, document development, software specifications Data Access … consistency checking, content management, customized displays Data Distribution … pocket PCs, smart phones, network planning, design and management e-Business … self-service, dynamic pricing, configuration, fulfillment, billing Enrollment … sign-up criteria, evaluation Filtering … message management Point of Sale … optimizing customer experience, touch-point management Personalization … personal preferences, customized ‘smart’ dialogs, work personalizaton Recommendations … stock purchases, investment options, problem diagnosis, rating

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Omissions? My Cumulative List of *Business Problems* for which Business Rules, Decision Management, and Related Technologies are Suited

Find your targeted business problem in this list? If not, please let me know! ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Customer Relationship Management (CRM) … customer care, personalization, complaint management Distribution … scheduling, routing, dispatching Financial … settlement, disbursements, allocation, billing, account management, credit worthiness, procurement, audit Fulfillment … eligibility, configuration, inventory management, order management, certification, supply chain Governance … regulatory compliance, adjudication, reportability, scenario gaming Human Resources … qualification, task matching, union restrictions Management … resource optimization, supervision and control, workflow scheduling and management Marketing … customer base segmentation, supply chain, brand management, loyalty programs, closed loop Marketplaces and Trading Exchanges … bids and offers, trades, reconciliation Planning … business intelligence, trending, capacity planning, risk assessment, production scheduling, optimization Sales … pricing, discount schemes, contextual product packaging, incentive programs, repeat business, campaigning, cross-selling, lead qualification, consultative sales Security … monitoring, alerts, risk profiling, detection, privacy breach  

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Omissions? My Cumulative List of *Industries* Having Applied Business Rules, Decision Management, and Related Technologies Successfully

Find your industry in this list? If not, please let me know! ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Banking, Credit, Financial Services, and Securities and Capital Markets … portfolio management, investment planning, loan origination, online banking, defined benefits, pension management, anti-money laundering Education … scheduling, certification, evaluation, scoring Entertainment and Gaming … royalties, casting, distributions Government, Taxation, Regulation and Safety … targeted inspections, entitlements, citizen empowerment, licensing Health Care … benefit administration, care management, consumer-directed health Insurance and Underwriting … customized plans, risk management, scoring, claims, fraud Manufacturing … product configuration, warranty management, quality assurance, lab procedures Media … promotions, advertising, scheduling Retail … buying trends, discount schemes, deals Telecommunications … provisioning, smart packaging Transportation and Travel … logistics, scheduling, load optimization Utilities … resource allocation, consumption analysis, real-time markets

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Why Business Rules Will Always Remain in Structured Natural Language

I was reading a fascinating article in The Economist about how robots, including military drones and driverless automobiles, increasingly need ethical guidance[1]. What does that have to do with business rules, you ask? Read on … In the next five years, software systems will begin to appear that bypass programming going more or less straight from regulations, contracts, agreements, deals, certifications, warranties, etc. (written in English or other natural language) to executing code. Think about the economics of the equation! If for no other reason (and there are many others), you’ll quickly see the why a snowballing migration to such platforms is inevitable. And these tools will do the same for business rules based on business policies. I said more or ‘more or less’ above because the tool will have to make certain assumptions about the meaning of what it ‘reads’. For example, if I say, “a person must not be married to more than one other person” most of us would probably assume that means “at a given point in time”. But automated tools could easily be held responsible for making the wrong interpretation. It should therefore err on the safe side, and at the very least, log all its reasoning. That’s where the article comes in. Concerning robots that make liability-laden decisions, it contends that principles are needed …

“… to determine whether the designer, the programmer, the manufacturer or the operator is at fault if an autonomous drone strike goes wrong or a driverless car had an accident. In order to allocate responsibility, autonomous systems must keep detailed logs so that they can explain the reasoning behind their decisions when necessary.” [emphasis added]

That explanation better be in a form that humans (and lawyers too) can actually read. That means structured natural language. The article went on to make the following astute observation …

“This has implications for system design: it may, for example, rule out the use of artificial neural networks … decision-making systems that learn from example rather than obeying predefined rules.”

Right! Where there is social liability, there will always be natural language. P.S. To vendors: If your meaning of ‘business rule’ doesn’t compel you toward this debate, then you’re simply not really doing ‘business rules’(!).


[1] “Morals and the Machine”, The Economist, June 2, 2012, p. 15

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The Debate Continues: Expert Systems vs. Business Rules … Yet Another Response

guest post by Jan Purchase, Director of Lux Magi Ltd ~~~~~~~~~~~~~~~~~~~~~ I do see value in distinguishing ‘policy’ rules from ‘expert’ rules. It’s also clear that, at their extremes, these rule types are poles apart. Still I fear that this distinction may be a continuum rather than a discrete dichotomy. Policy rules might be exemplified as the constraints of business operational practice – the rules that dictate what a company should and should not do. They might be mined from the boundary conditions of the fact model of the company’s business capability – as you suggest in your excellent book on this subject[1]. An example policy rule might assert, for example, “A company agent may be assigned to a high-value customer only if the agent is assigned to at most five other clients”. Expert rules, on the other hand, are often seen as more complex – for example, using heuristics to determine the best, anti-cancer drug to apply in a given situation, or forecasting regional sales opportunities. Often these expert rule bases use expert experience, genetic algorithms, fuzzy logic and feedback loops to reach a decision. They seek to augment, or even supplant, the wisdom of a small population of subject matter experts. But isn’t there a middle ground too? Consider an insurance policy decision rule that bin-sorts clients into good, bad and medium risk (the latter to be referred to a human underwriting expert). If this were a simple four-row, decision table based on the value of the policy and the risk profile of a client, you would probably consider it a ‘policy rule’. But if I add scorecarding, heuristics and analytics, at what point does it become an ‘expert rule’? Would you consider all decision rules (as opposed to constraint rules) to be ‘expert rules’? Or do they need to be complex or directly represent the experience of SMEs? Don’t all rules, to some extent, represent the wisdom of experts? Don’t many of them constitute and inform policy? In short: Is there a simple question we can ask (concerning a rule) to determine if it is a ‘policy’ or ‘expert’ rule? ~~~~~~~~~~~~~~~~~~~~~~~~ See my reply to Jan: http://www.brsolutions.com/2012/05/29/the-debate-continues-expert-systems-vs-business-rules/ Answer to Jan’s Question: The question to ask of every rule is whether the end-point is enforcement or is it a decision. An enforcement rule never becomes a decision rule, and a decision rule never becomes an enforcement rule. Once an enforcement rule, always an enforcement rule (assuming you don’t retire it). You can adjust thresholds (e.g., the mph of the speed limit), you can change the enforcement level (e.g., from ‘strictly enforced’ to ‘override with explanation’), you can change the sanctions (or eliminate them), etc., etc. And you can and should use analytics to measure and improve the rate of success in achieving underlying business goals. But it’s black and white. Enforcement is enforcement and decisions are decisions.

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