The Rise of Deep Process Automation

Welcome to Part II of our 3-part series on the Rise of Deep Process Automation!

Deep process automation is the automation, execution and monitoring of complex processes, where a complex process can be defined as a process that has between 50-5000 logical rules and between 20-1000 tasks. This is distinct from Deep Process Automation’s counterparts which are Robotic Process Automation and Workflow Automation as they are more suited for tackling simpler repeating tasks and workflows with far fewer tasks and logical rules.

WHAT LED TO THE RISE OF DEEP PROCESS AUTOMATION

The culmination of several trends in the past few years has resulted in the conditions being ready for Deep Process Automation to gain widespread adoption in enterprise process automation.

Widespread imperative of digital transformation and automation of enterprise processes:
1. Recent widespread use of automation techniques for different enterprise process complexity levels
The limitations in automating complex enterprise processes via existing architectures and techniques:
1. Robotic Process Automation and Workflow Automation are automating simpler enterprise processes and their limitation in automating complex processes,
2. Bespoke enterprise software is used for the development of highly complex processes, and their limitations in automating complex processes,
3. Limitations of today's enterprise architecture in automating complex enterprise processes (in particular, microservices, the leading edge architecture of choice for modern enterprises)
Widespread use of blockchain architecture in enterprises:
1. The execution of complex enterprise processes are naturally distributed among a number of separate entities (functions, teams, systems)
2. The Blockchain architectures distributed execution platform is a natural solution for the automation of complex enterprise processes with separate entities (functions, teams, systems)
Increased need and requirement for compliance and regulation enforcement for complex processes

Now let’s take a deeper look into these different factors which have led to the rise of Deep Process Automation.

1. Widespread imperative of digital transformation and automation of enterprise processes
Digital automation and transformation has accelerated in the past few years with more and more enterprises rushing to automate and digitize their processes and systems. In 2020 there has been a considerable increase in the urgency of accelerating digital automation and transformations in enterprise.

2. The limitations in automating complex enterprise processes via existing architectures and techniques:

For a detailed explanation of Robotic Process Automation, Workflow Automation and Deep Process Automation, please refer to our blogpost on the landscape of process automation. https://www.luthersystems.com/blog/2020/9/4/luthers-approach-to-enterprise-processes

Limitations of today's enterprise architecture in automating complex enterprise processes (in particular, microservices, the leading edge architecture of choice for modern enterprises)

Microservice architecture limitations

Microservice architectures are increasingly being adopted today across large enterprises, and have grown considerably in their utilization across enterprises since their early adoption in 2010. This adoption often aims to upgrade legacy systems and to obtain the developer agility benefits promised by microservice architectures. Despite their advantages for some enterprise applications, microservice architectures face 3 core limitations, particularly for automating complex enterprise processes.

Limited Scalability

introduce more data silos,
more fragmentation across processes, and
requires multi-group change management coordination, which is slow, complex and expensive.

Data Security concerns

do not provide built-in data integrity, auditability, data durability “out-of-the-box”.
security requires additional add-on systems, often with bespoke & non-standard integrations.

Bespoke development

do not have a widely adopted implementation, which results in numerous varying implementations and developments which increases IT operations complexity.3.

3. Widespread use of blockchain architecture in enterprises:

3.1 The execution of complex enterprise processes are naturally distributed among a number of separate entities (functions, teams, systems)

Complex enterprise processes involve multiple tasks. Generally these tasks are executed and performed by a number of different teams and functions and systems. These teams have separate, dedicated operational and technological governance and governance (logical) rules. This results in the overall process having distributed execution and governance, i,e., each part of the process is run via different teams/functions with their own set of logical rules that they follow, which are ideally meant to be in sync and consistent with one another. However, in practice, the separation of governance results in inconsistencies in the logical rules governing the execution of the overall process, which in turn results in the need for reconciliation and rectification of errors across the process.

3.2 The Blockchain architecture’s distributed execution platform is a natural solution for the automation of complex enterprise processes with separate entities (functions, teams, systems)

Blockchain Technology has matured considerably since 2014, where the technology gained general recognition as an architecture beyond peer to peer payments. In 2017 the architecture is used in simple enterprise applications, and has expanded in its reach, scope and use in 2018 and 2019 within multiple enterprises.

At Luther, we believe that Deep Process Automation is uniquely suited for tackling complex enterprise processes. And under the business process automation umbrella, it is the only solution that is able to automate end-to-end processes that feature a large number of tasks and logical rules without being extremely costly. Our product is based on smart contracts which we believe are uniquely suited as the best operating system for Deep Process Automation for complex enterprise processes.

In our next blogpost, we will discuss why blockchain technology is the best architecture for Deep Process Automation.

4. Increased need and requirement for compliance and regulation enforcement for complex processes

Compliance and regulatory requirements have become increasingly strict, enforced and monitored since the 2008 financial crisis, particularly in the highly regulated financial and insurance industries.

Further increasingly potent cyber attacks and data breaches since 2013 have made enterprises far more cautious and security aware. With stricter regulations, including the imposition of data residency and sovereignty restrictions, culminating in the 2019 GDPR data protection regulations. Enterprises increasingly understand the central role automation plays in the reliable and verifiable enforcement of compliance rules and regulation.

Stay tuned for our final blogpost from our mini-series where we discuss why blockchain technology is the best architecture for Deep Process Automation!