1. Semantic Business Management November 5, 2009 Paul Haley Automata, Inc. paul@haleyAI.com (412) 716-6420

2. Copyright © 2009, Automata, Inc. Forecasting beyond rules for… Model-driven architecture Service-oriented architecture Complex event processing Business process modeling Business activity monitoring Predictive analytics Business intelligence Corporate performance management 2

3. The ontology is the model Copyright © 2009, Automata, Inc.3

4. Business rule realities Derived from artificial intelligence Primarily based on production rules Substantially limited to forward chaining –Backward chaining avoids combinatoric deduction Goals rarely explicit; no automatic sub-goaling –Lacking deductive capability, authors bear the burden No ability to solve problems or optimize solutions –No search to achieve goals or evaluate alternatives Not enough AI or operations research 4

5. Copyright © 2009, Automata, Inc. Business needs more AI Natural logic: –Only full page color ads may run on the last page of the Times. Some business rules to enforce constraints: –If an ad that is not full page is to be run on the last page of the Times then refuse the run. –If an ad that is not color is to be run on the last page of the Times then refuse the run. Business rules for user interfaces: –If asking for the size of an ad that is to be run on the last page of the Times then the only choice should be full page. –If asking for the type of an ad that is to be run on the last page of the Times then full page should not be a choice. More general business rules (without if): –Ads run on the last page of the Times must be full page. –Ads run on the last page of the Times must be color. 5

6. Copyright © 2009, Automata, Inc. Semantic technology: the next step Semantics – focus on meaning (not structure) Resource Description Format (RDF) –Graphs are the universal data structure –Metadata is just more data in the graph –World-wide identification of nodes, links More powerful, logical deduction –Description logic (e.g., OWL-DL) –Logic programming (e.g., Prolog) –Predicate calculus (i.e., first-order logic) –HiLog (higher-order syntax for FOL) More powerful ontology (OWL) 6

7. Incremental steps forward Copyright © 2009, Automata, Inc.7 Production Rule Representation –no functional advance –may be adequate for some interchange Two very quick slides on: –Semantics of Business Vocabulary & Rules –World-wide web Rule Interchange Format Then back to the big picture

8. OMG SBVR Copyright © 2009, Automata, Inc.8 Semantics –Business Rules –Vocabulary logical aspects are a huge step forward but no ontology – no meanings and no runtime options needs more linguistic competence

9. W3C RIF Copyright © 2009, Automata, Inc.9 Think of RIF as first-order logic in XML a dumb version covers production rules SBVR and RIF overlap on logic SBVR textual, RIF formal syntax Weak vocabulary in SBVR, none in RIF Weak ontology in SBVR, strong in W3C

10. Copyright © 2009, Automata, Inc. Forecasting beyond rules for… Model-driven architecture Service-oriented architecture Complex event processing Business process modeling Business activity monitoring Predictive analytics Business intelligence Corporate performance management 10

11. Copyright © 2009, Automata, Inc. BI, BPM & CEP realities Flowchart metaphor dominates Events are second class citizens Asynchronous activity is awkward State within the business is poorly defined Policies enforced only at certain points Policy-based decisions are context free Governance is not part of the process Business transformation is like coding 11

12. Copyright © 2009, Automata, Inc. BAM, PA, BI, and CPM realities Activities have to be modeled (again?) –How long does it take or how much does it cost X to do Y? Decisions have to be represented. –How else can we audit or learn from what we have done? Predictive analytics doesnt know what to look for –will remain a skilled art until the meaning of data is clear Business intelligence is doesnt know what matters –will display the intelligence of analyst, not its own, until… Corporate performance management has no intelligence –will remain insight-free BI until the goals and objectives of business are clear 12

13. Ontology needed for BPMN –events and processes BMM –goals and objectives With ontology of rules, the process, and motivation: –Predictive analytics can automate intelligent investigation understanding data produces better variables understanding data produces better hypotheses understanding objectives produces better KPIs –BI produces more pertinent dashboards and reports –CPM becomes more insightful and pertinent PA & BI identify variance that is relevant Sharing ontology across the business stack is key Copyright © 2009, Automata, Inc.13

14. Events are primitive Events occur. –They happen. –They are temporal. –Processes are a kind of event. –Actions are processes. Its all about the verbs. –Tense is context for BPM & CEP –De-verbal nouns are not just objects! See the blog for all the details An SOA request is an action, process, and event. Semantic SOA is coming Copyright © 2009, Automata, Inc.14

15. Service-oriented architecture Why was it in the abstract? An SOA request –is an action –is a process –is an event Semantic SOA is coming –the externalization of IT will continue so are intelligent web agents Copyright © 2009, Automata, Inc.15

16. The ontology is the model Copyright © 2009, Automata, Inc.16 and the process definition the rest is the logic including requirements and policies and other rules