Hamid Motahari

1. © 2014 IBM Corporation
Towards Cognitive BPM
as a Platform for Smart
Process Support over
Unstructured Big Data
Hamid R. Motahari Nezhad
IBM Research, USA
Leveraging information and analytics for smarter process decisions

2. © 2013 IBM Corporation
Processes in our life
 A process refers to how work gets done
 Processes can be personal, or business processes
 Processes can be repetitively performed (are programmable), or unique
 They cane formally defined, prescribed, described or simply done
 They can be apriori designed, or created on the fly
 People may converse about processes (over many communication channels)
2 Ref: Motahar-Nezhad, Swanson, 2013
Spectrum of Work

3. © 2013 IBM Corporation
Outline
 Business Process Management
– Historical Perspective
– Business Process Analytics
 Cognitive Systems
– Data generation
 Cognitive BPM
– Vision
– Example Use Case
– Initial Work in Support of Cognitive BPM Vision
– Research Questions and Directions
 Conclusions and Discussion
3

4. © 2013 IBM Corporation
BPM: Historical Perspective
4
Databases
BackendSystems
Layer
Self-Generating Integration
SAP using
java
API
Web
Service
API
Excel using
com
API
MSMQ using
com or java
API
Databases using
jdbc
API
Business
Rules
Layer
Production
Business Level
Objects
Business Level Objects
Inv oices
Business Lev el
Obj ects
AFE’s
Business Level
Objects
Anything
Business Level
Objects
Process
Layer
Any Process
General Workflow System and UserInteractionsCalculation
Interface
Layer
Web
Service
Presentation Presentation
XML
API
BackendSystems
Layer
Self-Generating Integration
SAP using
java
API
SAP using
java
API
Web
Service
API
Web
Service
API
Excel using
com
API
Excel using
com
API
MSMQ using
com or java
API
MSMQ using
com or java
API
Databases using
jdbc
API
Databases using
jdbc
API
Business
Rules
Layer
Production
Business Level
Objects
Business Level Objects
Inv oices
Business Lev el
Obj ects
AFE’s
Business Level
Objects
Anything
Business Level
Objects
Process
Layer
Any Process
General Workflow System and UserInteractionsCalculation
Interface
Layer
Web
Service
PresentationPresentation PresentationPresentation
XML
API
XML
API
BPMS
TQM
General Workflow
BPR
BPM
time
ERP
WFM
EAI
‘85 ‘90 ‘95 ‘05‘00‘98
IT Innovations
Management Concepts
DatabasesDatabases
BackendSystems
Layer
Self-Generating Integration
SAP using
java
API
Web
Service
API
Excel using
com
API
MSMQ using
com or java
API
Databases using
jdbc
API
Business
Rules
Layer
Production
Business Level
Objects
Business Level Objects
Inv oices
Business Lev el
Obj ects
AFE’s
Business Level
Objects
Anything
Business Level
Objects
Process
Layer
Any Process
General Workflow System and UserInteractionsCalculation
Interface
Layer
Web
Service
Presentation Presentation
XML
API
BackendSystems
Layer
Self-Generating Integration
SAP using
java
API
SAP using
java
API
Web
Service
API
Web
Service
API
Excel using
com
API
Excel using
com
API
MSMQ using
com or java
API
MSMQ using
com or java
API
Databases using
jdbc
API
Databases using
jdbc
API
Business
Rules
Layer
Production
Business Level
Objects
Business Level Objects
Inv oices
Business Lev el
Obj ects
AFE’s
Business Level
Objects
Anything
Business Level
Objects
Process
Layer
Any Process
General Workflow System and UserInteractionsCalculation
Interface
Layer
Web
Service
PresentationPresentation PresentationPresentation
XML
API
XML
API
BPMS
BackendSystems
Layer
Self-Generating Integration
SAP using
java
API
Web
Service
API
Excel using
com
API
MSMQ using
com or java
API
Databases using
jdbc
API
Business
Rules
Layer
Production
Business Level
Objects
Business Level Objects
Inv oices
Business Lev el
Obj ects
AFE’s
Business Level
Objects
Anything
Business Level
Objects
Process
Layer
Any Process
General Workflow System and UserInteractionsCalculation
Interface
Layer
Web
Service
Presentation Presentation
XML
API
BackendSystems
Layer
Self-Generating Integration
SAP using
java
API
SAP using
java
API
Web
Service
API
Web
Service
API
Excel using
com
API
Excel using
com
API
MSMQ using
com or java
API
MSMQ using
com or java
API
Databases using
jdbc
API
Databases using
jdbc
API
Business
Rules
Layer
Production
Business Level
Objects
Business Level Objects
Inv oices
Business Lev el
Obj ects
AFE’s
Business Level
Objects
Anything
Business Level
Objects
Process
Layer
Any Process
General Workflow System and UserInteractionsCalculation
Interface
Layer
Web
Service
PresentationPresentation PresentationPresentation
XML
API
XML
API
BPMS
TQMTQM
General Workflow
BPRGeneral Workflow
BPR
BPMBPMBPM
time
ERPERP
WFMWFM
EAIEAI
‘85 ‘90 ‘95 ‘05‘00‘98
IT Innovations
Management Concepts
Adapted from Ravesteyn, 2007 and graphics from K. Swenson
‘15
Social BPM
Business Process Analytics

5. © 2013 IBM Corporation
Business Process Analytics (BPA)
 All activities that are performed on process data (logs, events, social network, metadata, etc)
to deliver process insights, monitor and optimize processes and recommend actions
 Technically involves the application of machine learning, data mining, optimization and
automation techniques on process(-related) data
5
Ref: Muehlen, 2009Ref: Forrester, 2010

6. © 2013 IBM Corporation
Different Types of Analytics
Existing BPA need to be designed, defined and programmed
for a specific analytical result
Mostly reactive: not autonomous/learning, and proactive
6
Discovery
Analytics
Ref: Gartner

7. © 2013 IBM Corporation
COGNITIVE SYSTEMS
7

8. © 2012 International Business Machines Corporation8
Businesses are “dying of thirst in an ocean of data”
1 in 2
business leaders
don’t have access
to data they need
83%
of CIOs cited BI and
analytics as part of
their visionary plan
2.2X
more likely that top
performers use
business analytics
80%
of the world’s data
today is
unstructured
90%
of the world’s data
was created in the
last two years
1 Trillion
connected devices
generate 2.5
quintillion bytes
data / day

9. © 2012 International Business Machines Corporation9
Understands
natural language
and human
communication
Adapts and learns
from user
selections and
responses
Generates and
evaluates
evidence-based
hypothesis
Cognitive System
1
2
3 Cognitive Systems do actively
discover, learn and act
A Cognitive System offers computational capabilities typically based on Natural
Language Processing (NLP), Machine Learning (ML), and reasoning chains, on
large amount of data, which provides cognition powers that augment and scale
human expertise
Watson

10. © 2013 IBM Corporation
COGNITIVE BPM
10

11. © 2013 IBM Corporation
Cognitive BPM: supporting process over unstructured information, a
bottom-up approach
 Traditional BPM and workflow systems define structured processes over structured
information
 Case management support human-guided flexible processes (top-down)
 Cognitive BPM supports processes over flex-structured (big) data based on intelligent
analytics (bottom up inherently, learning/directing makes it work both directions)
 Understanding the (unstructured) information, people (worker/individual) and the
environment in a process context
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Users
Assistant/
Agents
CustomersEmployees/
Colleagues
Plansworkflows
Rules
Policies
Regulations
Templates
Instructions/
Procedures
ApplicationsSchedules
Conversations over Email,
chat, social media, etc.
Organization
Cog. BPM
Agent
Unstructured Linked Information

12. © 2013 IBM Corporation
Cognitive BPM Systems
 A Cognitive BPM system offers the computational capability of a cognitive
system to provide analytical support for processes over structured and
unstructured information sources, and continuously discovers, learns and
acts to achieve a process outcome
– Meets two pressing needs: supporting complex process decisions,
and processing large amount of data
–Analytics-driven and integrated process (model) definition, reasoning
and adaptation
• Process is not assumed apriori defined; discovered, learned and
customized based on accumulated knowledge and experience
–Analytics supporting the execution of process
• When, What action (how) and whom to contact
–The need for revisiting some basic abstractions of BPM
• Real-world course of actions
• New information availability changes course of actions in a plan
• Fluid tasks, notion of task completion, and process/plan adaptation
12

13. © 2013 IBM Corporation
Process Definition,
Discovery, Learning
Process
Enactment
Process/
Environment
Sensing
Process
Analytics
Proactive/ Reactive
Process
Response/Adaptation
Cognitive BPM Lifecycle
13
Environment
Sensing
Data
sources
Data Processing/
Analytics
Process
Composition /
Enactment Update
Process
Monitoring/Analytics
IoT

14. © 2013 IBM Corporation
Use Case 1: Knowledge-intensive Enterprise Processes
 Human-Centric, knowledge-instensive Processes in IT Services Provider
Environments (Sales Management Processes)
– Reference, descriptive processes are available, no (WFM) system supporting
the process
– The need for a business-aware automation solution for human-centric
processes
– Conversational, multiple interactions and facts impacting process decisions
– Inbox used a work management system, in addition to phone, chat and records
in databases
– Changes to process guidelines and templates are commonplace and
communicated through email
 Cognitive BPM
– Providing automation support, and analytics over process
– Ability to process and link process information from unstructured sources over
multiple channels
– Putting the business first (outcome), not the process
• Process should support more sales, through employing all analytics type:
diagnostic, predictive, prescriptive
14

15. © 2013 IBM Corporation
Research Supporting Cognitive BPM in Enterprise Processes
15
Health Identification and Outcome Prediction for Outsourcing Services Based on Textual Comments
Hamid R. Motahari Nezhad, Daniel B Green ia, Taiga Nakamura, and Rama Akkiraju, IEEE SCC 2014
A Win Prediction Model for IT Outsourcing Bids
Daniel Greenia, Rama Akkiraju, and Mu Qiao, IEEE SRII Global Conference 2014.

16. © 2013 IBM Corporation
Use case 2: Cognitive Assistant/Agents
 Systems that reason, learn from experience, and accept guidance in order to
provide effective, personalized assistance (DARPA PAL)
 IBM’s Watson, Apple’s SIRI, SRI’s CALO, … .
 Open Source
– Cougaar (http://www.cougaar.org/)
– Open Cog (http://opencog.org/)
– Open Advancement of Question Answering Systems (http://oaqa.github.io/)
– SolrSherlock (http://debategraph.org/SolrSherlock)
16
$3B
Cognea

17. © 2013 IBM Corporation
Cognitive BPM in Cognitive Assistants/Agents
 Goals
– Increasing worker’s productivity, efficiency, and creativity (serendipity)
 Current cognitive assistants are focused on personal space or virtual conversational agents
 Cognitive Work Agent
– Is process and work aware
– Monitors worker’s input channels and interactions (emails, chats, social connections,
external and internal environment, knows rules, policies and processes)
– Proactively acts on worker’s behalf and reacts to requests: becomes a copy of you in
work environment
• Commands/requests - Responds to simple requests intelligently
• Situational awareness – monitors the environments to overcome information
overloading (selective).
• Deep QA: process questions, how-tos, previous successful process experience
– Organizes and assists your work
• Extract tasks/commitments, promises, commitments
• Managed to-dos: status updates, over-dues, plans
• Manages calendar, schedules, social contacts
• Finds and present prior related interactions to a particular conversation
17

18. © 2013 IBM Corporation
Use Case 3: Work Assistant Example
 Assume an executive admin is managing an event organization process for their
department
– Step 1: sending invite to an event to employees in their department, through
email and requests for RSVP
• Cognitive BPM (1): Q&A ability for the admin: How many have confirmed,
how many pending, how many not answered
• Cognitive BPM (2): Predictive analytics: how many will eventually RSVP?
• Cognitive BPM (3): Diagnostic analytics: why some not accepted
(customers in case of marketing case)?
– Step 2: Ordering place, food, transportation, etc
• Cognitive BPM (1): tracking of the process steps, which vendor have
replied, which ones pending, have questions, etc.
• Cognitive BPM (2): keeping track of synchronization and consistency
(dates, amounts, numbers, etc.) among different steps
– Step 3: Pre-event steps
• Reminding people who have RSVPed
• Compiling and sending logistic information (from different steps)
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19. © 2013 IBM Corporation
Research in Support of Cognitive BPM in Work Assistant Space
 Task, commitment and process extraction from workers interactions over
email and chat
19
Anup K. Kalia, Hamid R. Motahari Nezhad, Claudio Bartolini, Munindar P. Singh: Monitoring
Commitments in People-Driven Service Engagements. IEEE SCC 2013: 160-167

20. © 2013 IBM Corporation
Research Directions
 Abstractions and models for Cognitive Processes
 Cognitive Process Management System
–Analytics on unstructured information to support process
understanding
–Analytics to support process adaptation, customization and
configuration
–Proactive process adaptation
 Cognitive Work Assistants
–Cognitive augmentation of workers in work environments, and in
process management
 Teaching processes to cognitive agents
–Interactive learning where cognitive agents ask process questions
–Gradual learning through experience, and process improvement
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21. © 2013 IBM Corporation
Conclusions and Discussions
We are in the beginning of a profound transformation of BPM
field due to advances in AI and Cognitive Computing
Major advances in business process analytics work so far,
however, systems need prescriptions by humans
The vision of Cognitive BPM supports a self-learning,
adaptive and analytics BPM systems that focuses on process
outcome
–Analytics-driven, learning, and proactive adaptation
–Enabling systems and human work together to achieve
better results
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22. © 2013 IBM Corporation
QUESTIONS?
Thank You!
22
COGNITIVE BPM: PROCESS SUPPORT OVER
UNSTRUCTURED BIG DATA