The Future of Process Automation

Saikat Ray, Senior Director, Gartner

Jakob Freund, CEO & Co-Founder, Camunda

22

What is Hyperautomation?

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Digital Business Platform is Tablestakes for Customers

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Different Approaches Needed at Each Level for Hyperautomation

Customer Experiences

Knowledge Work

Adaptive and Evolving

Cases and Content

Micro Processes

Dynamically Bound

Transactions

Outcomes

Dynamic Channel HoppingCustomers

Customer Journeys and Personas

ERP

CRM

HR

Integrate Across Systems of Record

Fixed and Static

Processes and Rules

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Building Blocks of Hyperautomation

Customer Experiences

Knowledge Work

Case Management

Document Management

iBPMS

Decision Modeling

Attended RPA

Chatbots

Machine Learning

DMN

Transactions

Web and Mobile Portal

Chatbots and Voice Assistants

Event-Driven iBPMS

Custom-Made Customer Apps

Hybrid Integration Platform (HIP)

Unattended RPA

iBPMS

Business Rules

Complex end-to-end processes often have multiple vendors and systems to

integrate, orchestrate, manage and analyze. How should automation teams

address this challenge?

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Hyperautomation in Real Life – RPA, OCR, ML and BPM

Case Received

• Intelligent BPM Suite (iBPMS) picks up case

• RPA gathers data from legacy systems

• OCR extracts request context from notes

Preparation

• Decision management tooling used to identify citizen request/needs

• Decision models assess relevant social services policies

• Prepares policy payload and supporting reasoning

• Calculates results and implications

Assessment

• iBPMS presents data to case worker (first touch by a human)

• Worker reviews and refines result

• Customizes response to citizen

• May refer case for fraud assessment

Action Changes

• iBPMS calls RPA to update legacy systems

• Communication to citizen

• Machine learning used to capture and refine policy selection

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Business Process Automation Spectrum

Fully

Automated

Intelligent

Autonomous

Human

Process

Routine

Process

Standardized

Rule Based

Dynamic

Adaptive

Structured

Data

Semistructured

Data

Unstructured

Data

Task

Automation

Robotic Process

Automation

Process Discovery,

Orchestration and Optimization

Intelligent Business Process

Management Suites

System Automation via API integration

Integration Platform as a Service

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Decision Path to Narrow Down Your Choices

Every organization could have its own decision paths depending on its unique process automation needs.

Application leaders will need to expand and modify their unique decision paths based on ever-changing organizational requirements.

Automation of Business Processes?

Integrate with disparate systems

to automate?

RPA RPA and IPaaS

Yes NoOrchestrate processes with task automation?

iBPMS and RPA

Requires multiple integrations?

Yes No

No YesRequires multiple integration faster?

Packaged systems (ERP, CRM)

iBPMSiBPMS and

iPaaS

NoYes

Satisfies RPA selection criteria?

No YesYes No

NoIs the priority to automate

routine human tasks faster?

Yes

Is the priority to discover, design and orchestrate

processes?NoYes

Is traditional integration faster

and cheaper?

iPaaSTraditional integration

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Plan the JOURNEY – Be Smart where You Start

RPA

Process Discovery

NLP

OCR

Process Mining

iPaaS

Machine Learning

Chatbots/Voice Bots

iBPMS

Low-Code

Choose

Automation Tools

3

Enhance

Assess/ Right-size

Industrialize and scale

Re-Design the

Process

2

Define the Desired

Business Outcome

1

Revenue

Costs

Risks

How has the Intelligent Business Process Management Software (iBPMS)

market evolved in the last few years?

Is a ‘plug and play’ orchestration approach to integration possible today?

14

Orchestration in a Future Composable Business

Questions?

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