PRESENTED BY Carl Lehmann – Principal Analyst, 451 Research Denis Gagne – CEO and CTO, Trisotech DESCRIPTION When business processes must execute complex decisions across the enterprise, most process automation platforms and rules management engines fall short. While competent in rules-based process modeling and automation they’re unable to model, automate and orchestrate complex decision-making processes, for example, in areas such as in clinical contexts, insurance risk management, and structured financial services, among others. 451 Research is tracking an emerging class of automation and orchestration technology that is becoming competent in both. Join us to explore the industry trends driving the need for joint process and decision automation. The benefits derived from a unified approach to both. The technical apparatus needed to automate and orchestrate process and decision models.

1. © 2023 S&P Global.
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Automating and Orchestrating
Processes and Decisions
Across the Enterprise
Carl Lehmann
Senior Research Analyst
S&P Global | Market Intelligence
September 14, 2023
© 2023 S&P Global.
Permission to reprint or distribute any content from this presentation requires the prior written approval of S&P Global.

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Today’s speakers
Denis Gagne
CEO/CTO
Trisotech
dgagne@trisotech.com
Carl Lehmann
Senior Research Analyst
451 Research | S&P Global Market Intelligence
carl.lehmann@spglobal.com
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Process and decision orchestration
• Needs and challenges
• A new approach
451 Research findings
• Processes, decisions, events and data
Orchestrating processes and decisions
• Intelligent process automation
• Intelligent decision automation
• A unified platform
Business impact
Agenda
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Process and decision
orchestration

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The need to orchestrate process and
decision automation
Process automation is a high priority among the formal digital
transformation strategies of many enterprises
Serious investments made in next generation
– Digital automation platforms
– Low-code application development environments
– Robotic process automation technology
– Process discovery tools
Decision management is often an afterthought
– When included, it uses dated rules management technology
Decision-making must go beyond simple rules management
– Means to assimilate and understand complex relationships
– Harness the predictive capabilities of AI/ML to automate, rather than
manage, decision-making processes
Decision and process automation are different and disparate
platforms
Decision automation is becoming a priority and a
differentiator
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Needs and challenges
Must remain in control
and competitive.
Business Objectives
• Profits
• Cost control
• Return on assets
• Risk management
• Resource optimization
• Competitive differentiation
• Opportunity cost
management

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Needs and challenges
Must execute with speed & accuracy,
efficiently & consistently.
Business Objectives
• Profits
• Cost control
• Return on assets
• Risk management
• Resource optimization
• Competitive differentiation
• Opportunity cost
management
• Customer experience
• Order management
• Accounts payable/receivable
• Production management
• Supply Chain management
• Financial management
• Operations, scheduling
Process Execution

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Must simplify, reduce variability,
understand constraints.
• Number and type of variables
• Rules, policies, constraints
• Weights and measures
• Limits, capacities
• Roads, routes
• Regulations
• Climate
• Privacy
• Skills
• Time
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Needs and challenges
Sources of complexity
• Customer experience
• Order management
• Accounts payable/receivable
• Production management
• Supply Chain management
• Financial management
• Operations, scheduling
Process Execution
Business Objectives
• Profits
• Cost control
• Return on assets
• Risk management
• Resource optimization
• Competitive differentiation
• Opportunity cost
management

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Needs and challenges
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Need a better way to orchestrate
decisions & processes during execution.
• Number and type of variables
• Rules, policies, constraints
• Weights and measures
• Limits, capacities
• Roads, routes
• Regulations
• Climate
• Privacy
• Skills
• Time
Sources of complexity
Decision-making processes
• Experience
• Data analysis
• Guesses/hunches
• Metaheuristic algorithms
• Heuristic algorithms
• Predictive modeling
• Decision modeling
• Customer experience
• Order management
• Accounts payable/receivable
• Production management
• Supply Chain management
• Financial management
• Operations, scheduling
Process Execution
Business Objectives
• Profits
• Cost control
• Return on assets
• Risk management
• Resource optimization
• Competitive differentiation
• Opportunity cost
management

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A new approach
Orchestrated process
and decision automation!
• Number and type of variables
• Rules, policies, constraints
• Weights and measures
• Limits, capacities
• Roads, routes
• Regulations
• Climate
• Privacy
• Skills
• Time
Sources of complexity
Decision-making processes
• Experience
• Data analysis
• Guesses/hunches
• Metaheuristic algorithms
• Heuristic algorithms
• Predictive modeling
• Decision modeling
• Customer experience
• Order management
• Accounts payable/receivable
• Production management
• Supply Chain management
• Financial management
• Operations, scheduling
Process Execution
Business Objectives
• Profits
• Cost control
• Return on assets
• Risk management
• Resource optimization
• Competitive differentiation
• Opportunity cost
management

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451 Research findings

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Drivers of digital transformation strategies
Q. Beyond traditional revenue and cost-saving metrics, what are the primary drivers to adopt a digital transformation
strategy at your organization?
Q. Beyond traditional revenue and cost-saving metrics, what are the primary drivers to adopt a digital transformation strategy at your organization? (Check all that apply).
Base: Respondents whose organizations have a formal or are developing digital transformation strategy (n=222).
Source: 451 Research's Voice of the Customer: Macroeconomic Outlook, Business Trends, Digital Transformation.
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Decision intelligence platform adoption
Q. Which of the following best describes your organization's adoption plans for a decision intelligence platform?
Q. Which of the following best describes your organization's adoption plans for a decision intelligence platform?
Base: Respondents who are familiar with analytical products and services in use at their organization (n=397).
Source: 451 Research's Voice of the Enterprise: Data & Analytics, Data Science and Decision Intelligence Platforms 2023.
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Digital transformation technology priorities
Q. Which of the following software technologies are a part of your organization's current digital transformation efforts?
Q. Which of the following software technologies are a part of your organization's current digital transformation efforts? (Check all that apply).
Base: Respondents whose organizations have a formal or are developing digital transformation strategy (n=222).
Source: 451 Research's Voice of the Customer: Macroeconomic Outlook, Business Trends, Digital Transformation.
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Real-time decisions through event-stream processing
Q. Event stream processing technologies allow decision-makers to harness streams of event data from devices and
applications and make decisions in real time. Which of the following best describes your organization's event stream
processing adoption plans?
Q. Event stream processing technologies allow decision-makers to harness streams of event data from devices and applications and make decisions in real time. Which of the following best describes your organization's event stream processing adoption plans?
Base: All respondents (n=382).
Source: 451 Research's Voice of the Enterprise: Data & Analytics, Data Platforms, 2022.
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Benefits of being data-driven
Q. What are the most significant benefits your organization would expect from being more data-driven?
Q. What are the most significant benefits your organization would expect from being more data-driven? Please select all that apply.
Base: All respondents (n=477).
Source: 451 Research's Voice of the Enterprise: Data & Analytics, Data-Driven Practices 2022.
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Orchestrating
processes and
decisions

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A data-driven action-oriented approach
• Uses execution data and AI to intelligently
design and redesign processes
• Makes processes smarter as they execute
• Can expose and make recommendations,
predictions and decisions
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Intelligent process automation
Intelligently guides developers,
users, systems in process design,
improvement and proper execution.

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A real-time data graph relationship
approach
• Designed to narrow the field of
analytic complexity
• Reduces guess work and
compute resources
• Minimizes the need for scarce
data science skills
• Decisions made within context
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Intelligent decision automation
Intelligently guides decision-
making processes to improve
speed, accuracy and
consistency.

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Digital automation platform capabilities
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Production Marketing Sales Service Operations Fulfillment Finance
Digital Automation Platform – Capabilities
Intelligent Process Automation
Recipes,
Templates
Event
Processing
Modeling,
Process
Engine
UI, Low-/
No-Code
Libraries,
Forms,
Docs
AI
Policies,
Rules,
KPIs
Analytics

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Decision intelligence platform capabilities
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Enterprise Resource
Planning
Supply Chain
Management
Customer Relationship
Management
Business
Applications
Intelligent Decision Automation
Event
Processing
UI, Low-/
No-Code
Algorithms
Policies,
Rules,
KPIs
Decision
Modeling
AI
Predictive
Modeling
Graph
Repository
Constraint
Planning
Decision Intelligence Platform – Capabilities

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Together creates a unified process and decision automation platform
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Enterprise Resource
Planning
Supply Chain
Management
Customer Relationship
Management
Business
Applications
Decision Intelligence Platform – Capabilities
Event
Processing
UI, Low-/
No-Code
Algorithms
Policies,
Rules,
KPIs
Decision
Modeling
AI
Predictive
Modeling
Graph
Repository
Intelligent Decision Automation
Constraint
Planning
Production Marketing Sales Service Operations Fulfillment Finance
Recipes,
Templates
Event
Processing
Modeling,
Process
Engine
UI, Low-/
No-Code
Libraries,
Forms,
Docs
AI
Policies,
Rules,
KPIs
Analytics
Digital Automation Platform – Capabilities
Intelligent Process Automation
Interoperable
capabilities

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Business impact

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Automating and orchestrating processes and
decisions across the enterprise
Business impact
• On the IT organization: A unified platform for process
and decision automation reduces complexity by providing
a single environment for designing, developing and
managing both automated processes and decision logic.
Developers need not switch between different platforms.
• On the enterprise: A unified approach can provide data-
driven insights that can collect and analyze data from both
processes and decisions, providing valuable insights that
can inform strategic decisions and process optimizations.
• On business outcomes: Business processes and
decisions can be aligned with strategic goals. Speeds
decision-making to provide quick responses to customer
inquiries and market changes can result in a competitive
advantage.
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25. Automating and
Orchestrating Processes
and Decisions Across
the Enterprise

26. Trisotech.com
Automation helps eliminate repetitive manual tasks
and improve local efficiency
… doing more with less, but
[…]

27. Trisotech.com
We are going to explore why these
technologies are not enough by
themselves…
▪Pointwise Task Automation
▪Traditional Rule Automation
▪Generative AI

28. Trisotech.com
…and explore some key lesson learned
▪ Orchestrating Business Activities with Business
Decisions
▪ Scaffolding not shackling Knowledge Workers
▪ The importance of:
oContext (Situational Awareness)
oKnowledge Graph
oIntegration, Connectivity and Interoperability

29. Pointwise Task Automation
alone is not enough
When automating in isolation, there's a risk of losing the broader context in which
decisions are made or actions are taken.

30. Rule Automation
alone is not enough
As a traditional rule systems grows and evolves, the number of rules can
become unwieldy. Maintaining, updating, and ensuring there are no conflicts or
side effects among rules can become a major challenge.

31. Generative AI
alone is not enough
Generative AI excels in producing a range of outputs based on learned patterns, but it
might not always be precise. Answers provided are fundamentally unexplainable.

32. Automating Business Decisions
is key
Making the right decision at the right time is vital to organizations.
Automating business decisions is key for organizations looking to scale,
boost efficiency, adapt to market shifts, and stay competitive.

33. Explainable
Decisions
• Explainable AI is required if not mandatory
• A Black Box solution will not cut it
• Transparency, Provability and Explainability
are mandatory requirements of today’s business
decisions automation
Various legislation require that companies be able to explain to
their customers how machine decisions are made.

34. Decision Automation
What you model is what you execute!
Decisions as first-class citizen
Visual representation of decisions
Completely explainable decision automation
There is a standard for that: the Decision Model and Notation (DMN)

35. Decision Automation
needs situational awareness
Decision automation can enhance efficiency, consistency, and speed, it should
ideally complement human judgment and expertise, contextual
understanding, and holistic strategy.

36. Orchestrating Business Activities
with Business Decisions is Key
The coordination and synchronization of business activities with decisions
is more than just a good-to-have feature; it's an essential aspect of modern
business strategy.

37. Trisotech.com
Combining efficient Doers with
effective Thinkers
Orchestrating Business Activities
with Business Decisions
Leading the Decision Automation Revolution

38. Scaffolding not shackling
Knowledge Workers is key
The goal of integrating automation in the workplace should be to elevate the
capabilities and roles of knowledge workers. Automation should serve as a
robust scaffold that allows them to best contribute to the organization
success, rather than as chains that limit their potential.

39. Context
(situational awareness)
is key
While automation offers numerous benefits in terms of efficiency,
productivity, and scalability, it's crucial to ensure that it's contextualized
to the specific needs, challenges, and nuances of the environment in
which it's applied.

40. Trisotech.com
Process Management
Process
Management
and Case
Management
provide context
to Decision
Management
Case Management
Decision Management

41. Variable
Every work effort instance
looks slightly different
Unpredictable The exact course of action
is unknown and highly
situation specific
Emergent
The exact course of action
only emerges during
process execution when
more information becomes
available
Trisotech does it all using standards

42. Knowledge Graph is key, not Data
Knowledge Graphs provide context to data, connecting disparate
pieces of information and showing how they relate to each other.

43. Trisotech.com
Digital
Enterprise
Graph
Semantical layer
powering
the intelligence fabric
A semantic model of your organization

44. Integration, Connectivity and
Interoperability are Key
More than just buzzwords; they are essential paradigms that underpin the
seamless functioning of the digital ecosystem. Organizations that prioritize these
aspects are better positioned to thrive, innovate, and stay competitive.

45. Cloud First Strategy
Public Cloud
On Premise
Private Cloud
It’s a
Hybrid World
We have reached the cloud tipping point
Internal APIs
B2B APIs
Public APIs
API
API
API API
API
API API
API
API
API
API
API
API
API
API
API
API
API

46. Trisotech.com
IoT
AP
I
AP
I AP
I
AP
I
AP
I
All logos, trademarks and registered trademarks are the property of their respective owners.
Integration and
connectivity
from Trisotech

47. Becoming an Adaptable Digital
Enterprise is the Ultimate Goal
To quickly and effectively respond to shifts in the market, technological
innovations, and changing customer behaviors by leveraging digital
tools, methodologies, and mindsets.

48. Trisotech.com
Trisotech is Model Driven

49. What you model is what you execute !
The Model is the Decision Requirements
The Model is the Decision Logic
The Model is the Decision Documentation
The Model is the Decision Code
The Model is Verifiable

50. Orchestrating Everything
across the Enterprise is Key
Order2Cash
Marketing2Lead
Opportunity2Order
Procure2Pay
Hire2Retire
Procure2Pay
Concept2Launch
Recruit2Hire
Strategy2Operations
Inside-out2Outside-in

51. Trisotech.com
Trisotech brings it all together

52. Let Trisotech help you become an
Adaptable Digital Enterprise

53. Trisotech.com
▪ Financial Industry examples:
o One of the largest provider of Mortgage Automation software uses the Trisotech platform to create its
mortgage automation applications.
o A large Bank uses the Trisotech platform for onboarding, Credit Card and Incentive programs, fraud
detection, credit scoring, …
▪ Healthcare industry examples:
o A world-renowned Cancer Treatment Center creates cancer treatment side effects management
application(s).
o Intermountain Health Case Study: They created their ePneumonia application using the Trisotech
platform. https://www.trisotech.com/intermountain-health-case-study/
Concrete Examples of Value Added

54. Trisotech.com
To be an Adaptable Digital Enterprise
▪ Pointwise Task Automation alone is not enough
▪ Rule Automation alone is not enough
▪ Generative AI alone is not enough
▪ Automating Business Decisions is Key
▪ Orchestrating Business Activities with Business Decisions is Key
▪ Scaffolding not shackling Knowledge Workers is key
▪ Context (Situational Awareness) is Key
▪ Knowledge Graph is Key, not Data
▪ Integration, Connectivity and Interoperability are Key
▪ Orchestrating Everything across the Enterprise is key
▪ Becoming an Adaptable Digital Enterprise is the Ultimate Goal

55. Generative AI also need to be
Orchestrated
While generative AI models possess impressive capabilities, their true potential can be
harnessed only with effective orchestration. Prompt engineering plays a pivotal role in this
orchestration, guiding the AI to produce relevant, accurate, and valuable content that
aligns with specific objectives.

56. Any questions?
THANKS!