Mind The Gap - Refinements to DMN 1.1 Suggested by Real-World Experience
•
1 gostou•3,304 visualizações
DMN is a great standard and we’ve both achieve considerable successes with it: its help to improve the transparency, accuracy and agility of many business decisions and helped us to deliver better decisions and decision services to our clients. However, like any released product, DMN 1.1 can benefit from usage suggested refinements.
Recomendados
Recomendados
Mais conteúdo relacionado
Mais procurados
Mais procurados (20)
Semelhante a Mind The Gap - Refinements to DMN 1.1 Suggested by Real-World Experience
Semelhante a Mind The Gap - Refinements to DMN 1.1 Suggested by Real-World Experience (20)
Mais de Decision Management Solutions
Último
Último (20)
Mind The Gap - Refinements to DMN 1.1 Suggested by Real-World Experience
- 1. @jamet123 @janpurchase #decisionmgt © 2017 Decision Management Solutions, Lux Magi Ltd. Jan Purchase James TaylorRefinements to DMN 1.1 Suggested by Real-World Experience
- 2. @jamet123 @janpurchase #decisionmgt © 2017 Decision Management Solutions, Lux Magi Ltd. 2 Presenters ▶ We work with clients to improve their business by applying business rules and analytic technology to automate and improve decisions. ▶ Vendor-neutral ▶ Original DMN submitter ▶ Using decision modeling since 2011 ▶ I have spent 14 years focused on analytic applications and Decision Management ▶ We enable investment banks to automate demanding financial compliance regulations, against challenging deadlines, through the application of business rules, business decision modeling and business decision management systems. ▶ 13 years’ experience applying Decision Modeling and Business Rules in finance
- 3. @jamet123 @janpurchase #decisionmgt © 2017 Decision Management Solutions, Lux Magi Ltd. 3 Agenda ▶ Motivation ▶ Decision Modelling business case is compelling ▶ DMN 1.1 has been very effective ▶ Benefits from ‘in the field’ feedback and refinements ▶ We Discuss ‘Gaps’ Revealed by Demanding Projects ▶ Large, volatile models or model complexes ▶ Complex business logic requiring transparency ▶ Representing varied interests of different stakeholders ▶ Navigating complex, managed data
- 4. @jamet123 @janpurchase #decisionmgt © 2017 Decision Management Solutions, Lux Magi Ltd. 4 Our Approach ▶ Transparency and Collaboration ▶ Business, Operations, Analytics and IT ▶ To Each Stakeholder one or more Views ▶ Manage complexity with multiple views ▶ Model Decision-Making not just Automation ▶ All decision-making can be modelled ▶ Automation is not necessary for value ▶ Decisions as First Class Objects ▶ Not just something to support a process
- 5. @jamet123 @janpurchase #decisionmgt © 2017 Decision Management Solutions, Lux Magi Ltd. 5 Multiple Views ▶ Even Moderately Complex Real-World Models Create Messy Diagrams if a Single View is Used Branch Action Selection Call Center Cross-Sell Script Outbound Marketing Campaign Qualification Rank Actions Risk of Action Action Availability Customer Service Actions Add-on ProductsMarketing Campaigns Customer Value Probability of Action Customer Information Campaign Schedule Customer Preferences Customer Product Portfolio Product Catalog Product Profitability Data Product Cost Product Propensity Customer Lifetime Value Model Product Profitability Guidelines Product Risk Models Challenger Risk Models Branch Expertise Customer Service Expertise Campaign Schedule Call Center Notes Incremental NPV of Action Value of Action
- 6. @jamet123 @janpurchase #decisionmgt © 2017 Decision Management Solutions, Lux Magi Ltd. 6 Rank Actions Risk of Action Action Availability Probability of Action Customer Information Product Profitability Data Product Cost Product Propensity Product Profitability Guidelines Product Risk Models Incremental NPV of Action Value of Action Multiple Views What’s Omitted? ▶ Multiple Views Help a Lot But it’s not Always Clear That Information is Being Omitted Show objects with requirements that are not displayed Questions: Treat all requirements equally or only show missing Information Requirements? Show missing “requires” differently from missing “required by”? … or +?
- 7. @jamet123 @janpurchase #decisionmgt © 2017 Decision Management Solutions, Lux Magi Ltd. 7 Branch Action Selection Call Center Cross-Sell Script Outbound Marketing Campaign Qualification Rank Actions Customer Information Campaign Schedule Customer Preferences Branch Expertise Customer Service Expertise Campaign Schedule Call Center Notes Multiple Views Implicit Links Often Matter ▶ Sometimes Helpful to See Links Implied by Omitted Elements It might be really important to show the SME that the Rank Actions decision is impacted by these analytic knowledge sources Questions: How to show an implicit link? How to interchange it?Product Propensity Customer Lifetime Value Model Product Profitability Guidelines Product Risk Models
- 8. @jamet123 @janpurchase #decisionmgt © 2017 Decision Management Solutions, Lux Magi Ltd. 8 Branch Action Selection Call Center Cross-Sell Script Outbound Marketing Campaign Qualification Rank Actions Risk of Action Action Availability Customer Service Actions Add-on ProductsMarketing Campaigns Customer Value Probability of Action Customer Information Campaign Schedule Customer Preferences Customer Product Portfolio Product Catalog Product Profitability Data Product Cost Product Propensity Customer Lifetime Value Model Product Profitability Guidelines Product Risk Models Challenger Risk Models Branch Expertise Customer Service Expertise Campaign Schedule Call Center Notes Incremental NPV of Action Value of Action Multiple Views Ubiquitous Inputs ▶ Some Input Data is Widely Used Showing all the links to a single Input Data results in a cats-cradle Questions: Allow multiple nodes representing the same object? How to display? Faint colors? Render on demand?
- 9. @jamet123 @janpurchase #decisionmgt © 2017 Decision Management Solutions, Lux Magi Ltd. 9 Cardinality and Multiplicity ▶ Most Real-World Decision Models ▶ Require or generate collections: sequences, lists, sets ▷ Iterate through collections applying the same logic to every item ▷ Test the content of collections ▷ Perform key based transformations: aggregation, sort, group, filter ▶ But DRDs Don’t Directly Support these Concepts ▶ This Leads to Confusion: ‘Cardinality Blindness’
- 10. @jamet123 @janpurchase #decisionmgt © 2017 Decision Management Solutions, Lux Magi Ltd. 10 Explicit Data Multiplicity ▶ Data Inputs, BKMs and Decisions in DRD ▶ Distinguish single item vs collection output ▶ Representation Must ▶ Require minimal change ▶ Not rely exclusively on language specifics ▶ Suggestion: Use ‘*’ to Document a Collection ▶ Not New Information: It can be Derived from the DLD
- 11. @jamet123 @janpurchase #decisionmgt © 2017 Decision Management Solutions, Lux Magi Ltd. 11 Decision Cardinality ▶ Real-World Decision Models Need to Explain How Decisions Are Related - How Many Decision ‘Instances’ are Involved? ▶ Fan Neutral: one provider feeds one consumer ▶ Fan Out: single provider, multiple consumers (iteration) ▶ Fan In: multiple providers, single consumer (aggregation) ▶ Fan Complex: many-to-many relation (cross partition) Questions: Should keys be added by the ||| marker to show dimensions of fan-out, fan-in? Should boxes reinforce ‘zones of different cardinality’? Note: Cardinality and Multiplicity are separate concepts Can be combined in several ways
- 12. @jamet123 @janpurchase #decisionmgt © 2017 Decision Management Solutions, Lux Magi Ltd. 12 Expressive Decision Tables ▶ Most Real-World Decision Models Need to Test Condition Inputs ▶ Without Non-scalable Use of Context Entries Issuer Type EMG Issue FE Issue AP Issue US Issue Failsafe Rating <Issuer Type> true, false true, false true, false true, false AA-, A, AA, AAA, UNKNOWN 1 US MORTGAGE SECURITIES - - - - AAA 2 true - - - AA- 3 true - - A 4 true - AA 5 true AAA 6 false UNKNOWN US Issue list contains(Instrument Classes, US AGENCY) or list contains(Instrument Classes, US TBILL) P Determine Failsafe Rating EMG Issue FE Issue list contains(Instrument Classes, FAR EAST AGENCY ) list contains(Instrument Classes, AP AGENCY) list contains(Instrument Classes, GOVT EMERGING) AP Issue not (US MORTGAGE SECURITIES ) false false false
- 13. @jamet123 @janpurchase #decisionmgt © 2017 Decision Management Solutions, Lux Magi Ltd. 13 Expressive Decision Tables ▶ Most Real-World Decision Models require input entries more powerful than Unary Tests ▶ Use of expressions ‘>Start Date + Expiry Period’ ▶ Use of functions ‘>=max(Expiry Date, Month End)’ ▶ Direct handling of collections ‘list contains(GOLD, SILVER)’ ▶ Need ‘lower ceremony’ iteration, aggregation, filters ▶ Without these: ▶ Decision tables become larger, less readable, less scalable ▶ Forced to resort to boilerplate FEEL more often ▶ Does this lose the advantage of static analysis?
- 14. @jamet123 @janpurchase #decisionmgt © 2017 Decision Management Solutions, Lux Magi Ltd. 14 Expressive Decision Tables Questions: What best practices are needed to stop decision tables becoming too opaque as a result of this additional expressive power? Issuer Type EMG Issue FE Issue AP Issue US Issue Failsafe Rating <Issuer Type> true, false true, false true, false true, false AA-, A, AA, AAA, UNKNOWN 1 US MORTGAGE SECURITIES - - - - AAA 2 true - - - AA- 3 true - - A 4 true - AA 5 true AAA 6 false UNKNOWN US Issue list contains(Instrument Classes, US AGENCY) or list contains(Instrument Classes, US TBILL) P Determine Failsafe Rating EMG Issue FE Issue list contains(Instrument Classes, FAR EAST AGENCY ) list contains(Instrument Classes, AP AGENCY) list contains(Instrument Classes, GOVT EMERGING) AP Issue not (US MORTGAGE SECURITIES ) false false false Determine Failsafe Rating Issuer Type Instrument Classes Failsafe Rating <Issuer Type> <Instrument Class> AA-, A, AA, AAA, UNKNOWN 1 US MORTGAGE SECURITIES - AAA 2 list contains(US AGENCY) AAA 3 list contains(US TBILL) AAA 4 list contains(AP AGENCY) AA 5 list contains(FAR EAST AGENCY) A 6 list contains(GOVT EMERGING) AA- not(US MORTGAGE SECURITIES ) P
- 15. @jamet123 @janpurchase #decisionmgt © 2017 Decision Management Solutions, Lux Magi Ltd. 15 Expressive Decision Tables ▶ Most Real-World Decision Models Benefit from Rule Level Annotations ▶ With Knowledge Source traceability ▶ Able to evaluate expressions like TDM ‘Messages’ ▶ Can be merged to depict shared purpose ▶ Need Explicit Default Consistent with Other Outputs U Asset Category Instrument is Convertible Issuer Class Asset Class Annotation 1 OTHER - - OTHER "IAS 3.3.1 misc; undeterminable" 2 INDEX - - INDEX "IAS 5.10.4 and 5.10.6; index derivatives (" + Instrument.Index+")" 3 EQUITY - - EQUITY "IAS 5.10.4; equity derivatives" 4 true - CVTPFD 5 false - OTHER 6 SUPRA SUPRA "IAS 3.2.1 supernational debt" 7 not(SUPRA) OTHER "IAS 3.3.6 misc; non-convertible debt" 8 true - CONVERTIBLE "IAS 3.1.10 convertible stock" EXCEPTIONAL "IAS 7.1 exceptional circumstances" "IAS 3.3.1, 3.5.5 preferred vs non-convertible preferreds" Asset Class PREFERRED DEBT false DEFAULT
- 16. @jamet123 @janpurchase #decisionmgt © 2017 Decision Management Solutions, Lux Magi Ltd. 16 Glossary, Data Management ▶ Real-World Decision Models Need Glossaries ▶ DMN keeps its Glossary Approach Open ▶ But We Need: ▶ Multiple references to value lists across models ▶ Enumerations to be symbolic constants, not strings ▶ Enumerations to have sort orders ▶ Ways to manage enumerations – functions to: ▷ Return a list of allowed values ▷ Check if a value is an allowed value ▷ Compare values in the context of the list
- 17. @jamet123 @janpurchase #decisionmgt © 2017 Decision Management Solutions, Lux Magi Ltd. 17 ‘And Another Thing…’ ▶ Real-World Experience Suggests a Need for ▶ Better integration with analytics, optimization, cognitive ▶ Decision tree notation ▶ ‘-’ conclusion ▶ Additional FEEL functions ▶ Need the ability to aggregate with any function ▶ Some Features Cause Trouble in the Real World ▶ Null handling ▶ Use of italics, bold, underline for ‘special meanings’ ▶ Hit Policies output order, rule order ▶ Ranges using ‘(‘, ‘)’
- 18. @jamet123 @janpurchase #decisionmgt © 2017 Decision Management Solutions, Lux Magi Ltd. 18 Next Steps / Q&A ▶ Contact Us ▶ purchase@luxmagi.com @janpurchase ▶ james@decisonmanagementsolutions.com @jamet123 ▶ More Information ▷ www.decisionmanagementsolutions.com ▷ www.luxmagi.com ▶ Book ▶ Free chapter: http://bit.ly/RWDMFree ▶ http://www.mkpress.com/DMN/ ▶ Any Questions?
Notas do Editor
- James and Jan Chatty
- Just as with any new device or services, refinements are driven by use in real projects. Specifically those projects that really test the status quo by being demanding: large, complex, volatile
- Most Models need to Correlate the use of iterated items And Yet Sequences, Sets, Lists not distinguished from each other, or from simple values in DRD Decision Requirements Can’t Represent Collection Activity Cannot Test Collections Without Resorting to FEEL Boilerplate If your solution consistently yields the same boilerplate, you’ve failed to ‘capture the idiom’ FEEL Boilerplate not appropriate for non-executable models.
- The UTR demands that decision table conditions can only be mixtures of (see section 8.2.3.1 of our book): Equalities and Inequalities with literal or variable quantities (e.g., >6.5, GOOD, <Maturity Date) Ranges (e.g., [15..maxAge]) disjunctions (e.g., GOOD, BAD, UGLY) negations of the above (e.g., not(BAD)) UT may make DTs simple but it can increase their size and increase the frequency of FEEL context boxed expressions. Examples Available.