Blog Posts Process Management

What is Hyperautomation?

Blog: AuraQuantic Blog

Gartner defines hyperautomation as an effective combination of
complementary sets of tools that can integrate functional and process silos to
automate and augment business processes.

These
technologies include the application of advanced technologies, such as
artificial intelligence (AI), machine learning (ML), RPA, BPM, and data mining.

IMPLICATIONS OF BUSINESS
PROCESS HYPERAUTOMATION 

When we implement
a hyperautomation project it is very important to understand the scope of
automation that we are going to address and have a clear plan.

Integration
between tools is now more critical than ever.

We must be
aware that all organizations generate much more unstructured information than
structured data: emails, messaging, etc.

Structured data vs no-structured or semistructured data

Therefore,
we require software that is easy to use, scalable, and that also has the
capacity to extract data from the different sources that make up our software
system.

KEY COMPONENTS OF BUSINESS
PROCESS HYPERAUTOMATION

The functionalities
of advanced low-code software can be key to putting the plan into action. These
tools offer features to start processes and have wizards to facilitate
integrations with other system elements. In addition, they offer a powerful capability
to obtain reports, and track the status of tasks. In short, they enable the
control of the organization.

But one
tool is not enough to get our hyper-automated system up and running. We need
other tools that take our processes one step further, that have capabilities to
eliminate repetitive tasks, or replace tasks that require cognitive skills.

These tools
are RPA and Artificial Intelligence. However, our work will always require the
combination of human abilities and those of machines. Machines are very
powerful for working with data, but they do not have the same decision-making
capacity as humans. Achieving the perfect harmony between the work of machine
and that of people is vital to guarantee company competitiveness.

Furthermore,
we will need to use process mining applications to discover, monitor and
improve our processes. There are no definitive solutions, and our system must
evolve as our users do.

RPA

RPA
emulates human behavior to manage computer systems. They communicate with
systems in a similar way to how people do: they move the mouse, press buttons,
and enter or read data from the screens and these skills allow them to execute
repetitive tasks faster and more efficiently than anyone would.

Artificial Intelligence and related categories (machine learning, NLP, etc.) / Inteligencia Artificial y sus principales ramas

Currently,
they are widely used to integrate with legacy systems that are generating
information silos in the system.

In general,
the processes that can be executed by an RPA should be based on rules and not
depend on human judgment. They can start in response to a preconfigured event,
involve a high volume of workload, require the coordination of various
functions or involve common activities.

RPA
integrated with a low-code tool will provide data or execute tasks
within the general flow of a broader process.

iBPMS

Intelligent
Business Process Management Suites (iBPMS) have a more global concept of
process automation than RPA. Unlike RPA, they do not focus on a specific task,
they cover the complete set of tasks involved in a process. That is, a task
managed by an RPA would be an automatic task that would be part of an iBPMS
process.

An iBPMS enables
companies to model, implement and execute sets of interrelated activities
(processes), applying business rules. These actions will be carried out at
departmental and interdepartmental levels, and if the process requires it, they
will include external agents: clients, suppliers, etc.

Una organización eficiente gracias a la automatización de procesos

Integration
with external systems is achieved through native connectors that facilitate
integrations with products such as Office, SAP, SharePoint, etc. And in some
cases, they also offer wizards to generate new connectors using web service
technologies.

They are
very useful to control the organization, since they support the entire life
cycle of business processes and decisions: discovery, analysis, design,
implementation, execution, monitoring and continuous optimization.

An iBPMS
links technology and people better than any other software. It facilitates
integration with other tools and naturalizes the insertion of new technologies
such as RPA and AI within the organization.

(DTO). DIGITAL TWIN OF AN
ORGANIZATION

According
to Gartner analysts Marc Kerremans and Joanne Kopcho, “A digital twin of an
organization is a dynamic software model of any organization that relies
on operational and/or other data
…”

In other
words, with a digital twin we have a virtual replica of the product, service or
process that it simulates, which serves as a test tool to combine different
technologies and test new business opportunities or plan future scenarios.

AI TECHNIQUES IN HYPERAUTOMATION OF BUSINESS PROCESSES

Machine learning, and natural language processing
(PLN), are rapidly expanding the potential for hyper automation.

On the
other hand, process mining is contributing very positively to improving the automatisms
of organizations and discovering other tasks that can be automated.

Robotic Process Automation and Artificial Intelligence

Machine learning

Machine
Learning is a branch of artificial intelligence that creates systems that
automatically learn.

Simply
speaking, Machine learning and data analysis make sense of a lot of data. They
search through large data sets to establish patterns and based on these
patterns they identify which components we must pay attention to make a
prediction.

NLP

Natural
language processing (NLP) is adding the capability to understand and interpret
human language the way it is written or spoken.

This
feature is allowing the introduction of chatbots and virtual personal
assistants (VPA), who are carrying out tasks that have traditionally been performed
by people.

But NLP and Machine Learning can also help us find information by searching large volumes of unstructured data: emails, social media posts, videos, etc.

Some other
uses that are increasingly being incorporated into the processes are the
following:

• Sentiment
Analysis: widely used in product reviews and recommendation automatisms. They
are able to differentiate whether a comment is positive or negative.

• Automatic
language translation.

• Automatic
classification of texts into categories.

Process mining

Process
mining is a process management technique that allows you to analyze business
processes according to an event log. Specifically, it applies data mining
algorithms to the data in this registry to identify patterns and trends.

Process Mining

The event
logs are already available in systems such as BPM, CRM or ERP and provide us
with data such as: task name, executor, activity start and end date, etc.

Process
mining is the perfect complement to process automation projects since they serve
to discover and identify repetitive tasks that could be automated.

The post What is Hyperautomation? appeared first on AuraPortal.

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