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Dagstuhl Workshop on Fresh Approaches for Business Process Modeling Working group on: KiP meets CWA Achim Brucker, Alexander Herwix, Rick Hull, Hamid Motawari, Flavia Santoro, William Wong 12 May 2016. Overview.
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Dagstuhl Workshop on Fresh Approaches for Business Process ModelingWorking group on: KiP meets CWAAchim Brucker, Alexander Herwix, Rick Hull, Hamid Motawari, Flavia Santoro, William Wong12 May 2016
Overview • On Tues/Wed we created a framework to understand Knowledge-Intensive Processes (KiP’s) • On Wed/Thur we asked: --- Does our KiP framework work well with CWA ??? ------ • Three ways that KiP’s interact with “knowledge” • Create a knowledge artifact, e.g., a CWA model • Maintain a knowledge artifact • Use a knowledge artifact • This lead to 3 general observations • We need to understand how practitioners perform Knowledge-Intensive Work • There are different kinds of knowledge, which will affect the shape of KiP’s • Low hanging fruit: Annotate nodes in models with semantically related documents, images, etc • Can we make intricate models, e.g., CWA models, “living”?
Many different kinds of “knowledge” that KiP’s might focus on • Spectrum, kind of • Lots and lots of data – e.g., • Intricate, structured models, e.g., CWA, ITOM, BPMN schemas, … • Info/knowledge gathered during an accident investigation • Amorphous knowledge a CEO thinks about when making a big decision • Some “knowledge” is being captured in a machine-readable format • Often based on abstractions and abstraction hierarchies • Often with visualizations and tools • Often these are fairly mature, with a fairly mature & active community • Other “knowledge” may never be capture in machine-readable format • In that case, the role of KiP is to enable the humans as much as possible • The boundary of “machine-readable” is shifting, as new text analytics capabilities are being developed, e.g., “cognitive computing”
Making models “alive” (using CWA as example) • In general, including CWA, the model is created and used by one group… … but the actual operations are being performed by other groups • As a result, the CWA model gets out of date • There are few incentives to keep it up to date • How can we set up processes, incentives, fresh approaches so that these kinds of models can be kept up to date • Examples of success from other fields • Entity-Relationship data modeling – tools arose for mapping from ER diagrams into Relational DDL … • Empowerment of the end-user – eg, spreadsheets designed by, and then used by, same person • Example: shifting spreadsheet users to using GoogleDoc spreadsheets
Directions to explore for keeping models alive Some general principles • Give to all users the “knowledge-enhanced” CWA model • If the see value, they will help maintain accuracy • Change detection in procedures, conditions/rules and instructions that impacts the correctness or the logic of a model • Instrument the operational model so that it sends update to CWA model • And, at the highest level, change recommendation techniques for keeping the models in sync with the latest changes in enterprise/environment guidelines, actors, rules/regulations, etc. • Incentivize the operations-level users to maintain accuracy of the CWA model
Directions to explore for keeping models alive An example we might try to imitate . . .
Business Artifacts for “Visibility” across silosBusiness Entity paradigm provides end-to-end view of multiple silos and their interactions Business Artifacts (with Lifecycles) • Provide an end-to-end view of operations • Cut across operational and infrastructure silo’s • Unify data and process • Provide structure for other BPM aspects • Can “wrap” app’s to bring them into model • Provide skeleton for specifying variations Business Artifact Type: Lifecycle Model . . . Engineering Change Eng. WO . . . Part Info Model Eng. Purch. Manu. ... Visibility work led by Prabir Nandi (IBM)
Is there an analog of Business Artifactsthat would work similarly for hierarchical models?
CEO/strategy • Increase Profit Increaseenvironmentalsustainability Increase ManuProductivity Reduce airpollution Priorities/Values SupplyChain AssemblyLine PhysicalPlant Operational Functions Shipping Ware-housing Ordering InventoryMgmt ObjectProcesses
CEO/strategy • Increase Profit Increaseenvironmentalsustainability Increase ManuProductivity Reduce airpollution Priorities/Values SupplyChain AssemblyLine PhysicalPlant Operational Functions Shipping Ware-housing Ordering InventoryMgmt ObjectProcesses Textdoc ProcessDescrips CMMNbased BPMNspce Ad hoc,spreadsheetbased ProcessSpecs
Creation and Maintenance of CWA diagrams • This activity has probably been studied heavily by the Enterprise Architecture community ?? • Historically these diagrams have been static – can we make them “alive”, and thereby give them a bigger purpose and life, so that they
Fundamental characteristics and “centricities” Centricity Characteristics Workforce Pyramid • Coordination/Collaboration • Decisions on Knowledge • Very ad hoc, intuitive Knowledge-centric Design & Strategy Support Judgement- Intensive Processes • Long-running • Many kinds of activities • Best practices hidden • Spreadsheets Goals-centric Transaction- Intensive Processes • Care & feeding of ERP • Variation, Evolution • Spreadsheets • Text-based process descriptions Data-centric However, all three aspects are relevant to all three levels
Fundamental characteristics and “centricities” Centricity Characteristics Workforce Pyramid • Coordination/Collaboration • Decisions on Knowledge • Very ad hoc, intuitive Knowledge-centric Design & Strategy Support Judgement- Intensive Processes • Long-running • Many kinds of activities • Best practices hidden • Spreadsheets Goals-centric Transaction- Intensive Processes • Care & feeding of ERP • Variation, Evolution • Spreadsheets • Text-based process descriptions Data-centric However, all three aspects are relevant to all three levels
What is building on/coming after Data Science? “Cognitive Computing” – combining Big Data Analytics with Text/Image Processing, Learning, … Tata Consultancy “The world’s first neural automation system for the enterprise” • A cognitive system has the following capabilities • Monitor/Alert: Discovers patterns in data even if they are weak signals (“whispers”) • Analyze: Assesses relative value of alternative paths, using statistical evaluations • Decide/act: Advises on the optimal action to take • Adapts and learns from training and experiences • Important Cognitive System attributes • Ability to incorporate relevant contextual information, including new data • Deep natural language analysis, for info ingestion and human interaction • Learning in real time as data arrives • Can identify similar/related past experiences and learn from them • Explain/justify recommendations to humans IPSoft’s Amelia
Opportunities for “Cognitive Computing” Workforce Pyramid • Rapid exploration/ingestion of broad corpora of relevant (unstructured) information • Decision-making based on learned knowledge • Goals-based dynamic planning • (Enable guided collaboration of numerous autonomous agents) Design & Strategy Support Judgement- Intensive Processes Transaction- Intensive Processes • “Read” regulations and policies … … and map into processes Govt Reg’sCorp. Policies Define Processes • Capture “Digital Exhaust” … … and learn processes Care & Feeding of ERP System • Move from Spreadsheets to Case Mgmt and Business Rules … … so that humans can examine and tune auto-learned process • ERP System
Three (approximate) Levels of Business Operations & Processes Workforce Pyramid Examples • Build vs. Buy decisions • Merger & Acquisition decisions • Launch of a new kind of product • Large IBM deals that transform a company Design & Strategy Support Judgement- Intensive Processes • Fraud investigations in a Bank • Execution of Data Center Outsourcing deals Transaction- Intensive Processes • Back-office processing (e.g., payroll, F&A, …) • Supply Chain Management • Business Process Outsourcing (BPO), e.g., IBM GPS
Characteristics of the different levels Workforce Pyramid Characteristics Characteristics • Coordination/Collaboration • Decisions on Knowledge • Very ad hoc, intuitive Design & Strategy Support Judgement- Intensive Processes • Long-running • Many kinds of activities • Best practices hidden • Spreadsheets Transaction- Intensive Processes • Care & feeding of ERP • Variation, Evolution • Spreadsheets • Text-based process descriptions
Opportunities for “Cognitive Computing” Workforce Pyramid • Rapid exploration/ingestion of broad corpora of relevant (unstructured) information • Decision-making based on learned knowledge • Goals-based dynamic planning • (Enable guided collaboration of numerous autonomous agents) Design & Strategy Support Judgement- Intensive Processes Transaction- Intensive Processes • “Read” regulations and policies … … and map into processes Govt Reg’sCorp. Policies Define Processes • Capture “Digital Exhaust” … … and learn & enact processes Care & Feeding of ERP System • Move from Spreadsheets to Case Mgmt and Business Rules … … so that humans can examine and tune auto-learned process • ERP System
Opportunities for “Cognitive Computing” Cognitive Computing is …. Workforce Pyramid Centricity Characteristics Design & Strategy Support • Coordination/Collaboration • Decisions on Knowledge • Very ad hoc, intuitive Knowledge-centric Judgement- Intensive Processes • Long-running • Many kinds of activities • Best practices hidden • Spreadsheets Transaction- Intensive Processes Goals-centric • Care & feeding of ERP • Variation, Evolution • Spreadsheets • Text-based process descriptions Data-centric
Opportunities for “Cognitive Computing” Cognitive Computing is …. Workforce Pyramid Design & Strategy Support Judgement- Intensive Processes Transaction- Intensive Processes
Challenges of the different levels Workforce Pyramid Characteristics • Coordinating open-ended, highly collaborative processes • Both humans and “cognitive agents” • Decisions made over time, based on extensive acquisition of knowledge • Some best practices but lots of intuition guiding activity Design & Strategy Support Judgement- Intensive Processes • Long-running activity (weeks to months to years) • Many kinds of activity that MAY be relevant • Best practices & patterns available, but buried Transaction- Intensive Processes • Mainly based on ERP systems, but … … many manual processes surrounding them • Lots of variation, evolution over time • In many companies – ad hoc, spreadsheet based
Opportunities for “Cognitive Computing” Workforce Pyramid Challenge Problems Characteristics • Coordination/Collaboration • Decisions on Knowledge • Very ad hoc, intuitive Design & Strategy Support Judgement- Intensive Processes • Long-running • Many kinds of activities • Best practices hidden • Spreadsheets Transaction- Intensive Processes • Care & feeding of ERP • Variation, Evolution • Spreadsheets • Text-based process descriptions
Automating the Pipeline from Knowledge Harvesting to Executable Logic in an Agile, Incremental Fashion Near-term focus of “Ops Accelerator” Long-term focus of “Ops Accelerator” Current Mode of Operation Client policies, Govt. regulations Client policies, Govt. regulations Client policies, Govt. regulations + Automatic Knowledge Harvesting Coarse-grained English process descriptions Coarse-grained English process descriptions Coarse-grained English process descriptions “Crowd Sourcing” + DesktopProcedures ExecutableLogic ExecutableLogic SAP code SAP code SAP code • Coordination by machine: • Monthly runs • Ancillary processes (new hire, …) • Coordination by machine: • Monthly runs • Ancillary processes (new hire, …) • Coordination by hand: • Monthly runs • Ancillary processes (new hire, …)
First model – A is and B is Power of a Good Model << animated slide >> Good models go beyond description – they support action • Selecting the right model for the job matters Example: “Game of 15” Winner: First one to reach exactly 15 with any 3 chips 1 1 2 2 2 3 3 3 4 4 4 5 5 5 6 6 7 7 8 8 8 9 9 – what is B’s move? Second model – – B’s move is 6!