ICTSCC 2015 - 19th International Conference on System Theory, Control and Computing
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Merging business processes for a common workflow in an organizational
collaborative scenario
Maria Laura SEBUHoria CIOCÂRLIE
Computer and Software Engineering DepartmentPolitehnica University of Timisoara
ICTSCC 2015 - 19th International Conference on System Theory, Control and Computing
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Business contextHigh competition on the market for better products and services → organizations start collaborations
• Successful collaboration– Products and operational– Internal tools– Market opportunities– Audience
• Failed collaboration– Credibility – Customer satisfaction– Bad results in portofolio– Wasted resources
• Root cause - differences in approaches, methods, processes and tools used
• Half of outsourcing projects are doomed to fail !
ICTSCC 2015 - 19th International Conference on System Theory, Control and Computing
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Business context• Process-based solution to support multi organizational
collaboration• Identify if a collaboration is feasible (higher compatibility →
reduced costs and less effort for setup)– compute the similarity between business processes
• Same domain, standardized processes OR different domains• Different level of information for business process representation• Considering a modular design
• Collaborative solution based on merging business processes• Validation of the solution (in synch with business objectives)• Monitor the execution• Increase the transparency and structuring of cooperation
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Business process management
• Business result = output of repetitive actions → process definition– Intra-organizational ↓ good compatibility– Inter-organizational = ∑ intra-organizational business
process• Process mining - extract process definition – Data mining on mining event process logs– Enhance– Correct– Improve
ICTSCC 2015 - 19th International Conference on System Theory, Control and Computing
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Business Process Merge• Assumption– Collaborations = ∑ input from all parties →
common acceptance of a process → positive context → successful outcome
• Preprocessing– Business process representations• Event driven Process Chains (EPC)• Business Process Modeling Notation (BPMN)
– Abstract: reduce to directed graph format
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Business Process Merge - Preprocessing
• BPMN: a function that maps nodes to types– Activities (BPMN) → Node (Directed graph) Activity:Activity
Type:Activity Name– Events (BPMN) → Node (Directed graph) Event:Event Type:Event Name
• Start Event• End event• Intermediate event
– Gateway (BPMN) → Node (Directed Graph) Gateway:Gateway Type:Condition • Data based exclusive gateway• Inclusive gateway• Parallel gateway• Event-based gateway
ICTSCC 2015 - 19th International Conference on System Theory, Control and Computing
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Business Process Merge - Preprocessing
Translate Activity in Node Translate Gateway in Node
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Business process merge - Algorithm• Defined over a pair of directed graphs• Initialize common graph with the set of maximum common
regions– Maximum common region = maximum connected sub-graph composed
only of matched nodes and substituted edges• Compute added nodes (nodes present in one or more of the input
graphs and not included in one of the maximum common sub-graphs)
• Compute added edges and assign weights– Weight = number of graphs which contain the edge
• Apply transitive reduction = extract the graph with as few edges as possible that has the same reachability level as the original graph
ICTSCC 2015 - 19th International Conference on System Theory, Control and Computing
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Business process merge - Algorithm
• Match nodes – semantic similarity (SEMILAR API)– Wordnet Lesk Tanim (Greedy and Optimum)• relatedness of two words is equal to the overlaps
counted in the dictionary definition– Wordnet Lin (Greedy and Optimum)• ratio between the amount of information describing
the common parts and the information needed to describe in particular what strings represent
ICTSCC 2015 - 19th International Conference on System Theory, Control and Computing
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Business Process Merge - AlgorithmFunction MergeBusinessProcess (Graph G1, Graph G2)BeginSet{Graph} MCR ← MaximumCommonRegion(G1, G2)Graph CG ← (NCG = {n € MCR}; ECG = {e € ECR})Set{Node} AddedNodes = ComputeAddedNodes(G1) ComputeAddedNodes(G2)∪Set{Node} AddedEdges = ComputeAddedEdges(G1) ComputeAddedEdges(G2)∪Foreach (Node node : AddedNodes)
If {node} ∩ NCG = ØNCG = NCG {node}∪
Foreach (Edge edge : AddedEdges)If {edge} ∩ ECG = ØECG = ECG {edge}∪
Else w(edge)++
Graph TR ← ApplyTransitiveReduction(CG)Return TREnd
ICTSCC 2015 - 19th International Conference on System Theory, Control and Computing
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Business process merge - Algorithm
Function ApplyTransitiveReduction (Graph MCG)BeginForeach (Edge edge : GetEdges(MCG))
List<DirectedPath> dirPaths = getListDirectedPath(edge.getNodeStart(), edge.getNodeEnd());Foreach (DirectedPath path:directedPaths)
If (weight(path)>weight(edge))deleteEdge(MCG, edge);break;
End;
ICTSCC 2015 - 19th International Conference on System Theory, Control and Computing
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Business Process Merge – Post-processing
• Convert merged directed graph into a business process– Map node to business process
element by analyzing the label• Calculate similarity with input
business process– Graph comparison algorithms
• Name of the activities composing a process (labels)
• Topology of the process models
• Validate– Structural: conformance checking
techniques on the event log dataset (fitness, precision, structure)
– Functional: compliance of the process model with the process requirements
ICTSCC 2015 - 19th International Conference on System Theory, Control and Computing
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Business Process Merge Algorithm – Case Study
ICTSCC 2015 - 19th International Conference on System Theory, Control and Computing
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Business Process Merge Algorithm – Case Study
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Business Process Merge Algorithm – Case Study
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Business Process Merge Algorithm – Case Study
Removed Edge Path Coverage[C, F] [ [C, E], [E, F]] and [ [C, P], [P, F] ]
[D, G] [ [D, C], [C, E] [E, G] ]
[P, R] [ [P, F], [F, M], [M, R] ]
[A, B] [ [A, X], [X, B] ]
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Related WorkOur approach Other solutions
Semantic evaluation of label content→ merge business processes from different domains →flexibility
Labels are evaluated in a syntactic context
Nodes are compared only with nodes of the same type (activities, control)
Nodes are compared with any nodes by computing a context similarityRisky !
Transitive reduction of common graph Merge control elements (consecutive splits and joins)Trivial connectors are removed
Maximum Common Region (MCR)Compute added nodes and edgesTransitive Reduction
Construct process model such as the sum of distance between each process and the generic is minimal
Fully automatedBPMN exemplification
NOT fully automatedBackward tracebility
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Conclusions
• Input: set of business process models• Output: business process collaborative solution• Implementation is– Directed graph based– Independent of process model representation
(directed graph)• Business process = ∑ business processes easy to
set up
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Thank you for your attention !