Intelligent Process Automation: Ultimate Guide

Automation Solutions

According to Allied Market Research, businesses are continuing to grow their use of intelligent process automation because it increases workplace productivity, supports faster decision-making, and industries around the globe are rapidly adopting the technology.  If you’re looking to understand intelligent process automation benefits, intelligent process automation use cases and intelligent automation vs robotic process automation, then you’re in the right place.

Continue reading!

Coming Up

1. What is Intelligent Process Automation?

2. How Does RPA and AI Work Together?

3. What Technologies Make Up Intelligent Process Automation Tools?

4. What are the Benefits of Intelligent Process Automation?

5. How to Implement Intelligence Process Automation?

6. What is an Example of Intelligent Automation?

7. Final Thoughts

What is Intelligent Process Automation?

Intelligent process automation (IPA) refers to a combination of technologies that bring together the benefits of robotic process automation (RPA) and machine learning. Intelligent process automation adds the intelligence to robotic process automation, which means that robots can learn on their own due to the aid of artificial intelligence and algorithms.

With robotic process automation, software is trained to mimic human actions to complete tasks. However, robotic process automation relies on the use of structured data only in order to work.

While it is useful for many cases, there still exist several business processes that utilize unstructured data (such as emails, texts, images, letters, and scanned documents). For this type of data, intelligent process automation can be of great help.

With cognitive abilities, thanks to machine learning, IPA is RPA’s smarter cousin. IPA boasts added flexibility and the necessary components to manage nuances and exemptions within processes that RPA can’t manage on its own.

How Does RPA and AI Work Together?

Robotic process automation and artificial intelligence work together in order for IPA to exist. As mentioned, robotic process automation only works with structured data and has its own limitations. It is best applied to simple, repetitive, and rule-based tasks. For example, an organisation can leverage a tool like SolveXia to carry out end-to-end process automation with an easy drag-and-drop interface to design business processes.

Through the addition of artificial intelligence and machine learning, IPA can be used to automate tasks that are complex, analytical, and require cognitive ability. IPA software leverages natural language processing (NLP) to work with semi-structured and unstructured data.

Additionally, with machine learning algorithms, businesses can choose IPA to optimise current and future processes by analysing historical data and creating forecasts. IPA provides a framework to totally reimagine business processes, whereas RPA allows businesses to automate existing processes easily.

What Technologies Make Up Intelligent Process Automation Tools?

To dig a little deeper into what makes intelligence process automation capable of all that it can do, it’s helpful to review the technologies that are involved.

Take a look:

RPA

Robotic process automation is a software tool that uses robots to execute tasks in place of a human. Robots are developed with a user ID, like that of a human, so they can access programs and data to complete rules-based tasks.

Some examples of what RPA can do includes: checking files, performing calculations, logging into systems, creating documents, and generating reports, to name a few.

Smart Workflow

Smart workflow is a process-management tool that aids RPA and humans to be able to understand the status of processes in real-time. The software is able to oversee handoffs between departments, provide data on bottlenecks, and track processes. It’s basically the link that ties together a human overseeing robotic execution.

Natural Language Generation

Natural language generation (NLG) is the technology that drives an understanding between humans and robots by way of turning data into prose. NLG is used across industries. One example is the way that financial institutions can utilise the software to replicate weekly management reports.

Machine Learning / Advanced Analytics

Machine learning uses algorithms that are able to learn through the recognition of patterns in structured data. There are two main types of learning, namely supervised and unsupervised.

Supervised algorithms rely on a set of structured data inputs and outputs and then learns from that moving forward. Unsupervised algorithms provide insights and pattern recognition by way of observing structured data.

Cognitive Agents

Cognitive agents are born from the combination of natural language generation and machine learning. This duo creates a virtual workforce that can take data sets, recognise patterns, learn from data, and execute tasks.

What are the Benefits of Intelligent Process Automation?

IPA has led to businesses being able to cut their process times in half, which has resulted in jaw-dropping ROIs.

These figures alone should be indicative intelligent process automation benefits, but to break down how these upsides are achieved, let’s review the major advantages of this technology:

  • Increased efficiency
  • Optimised productivity
  • Lowered costs
  • Less risks
  • Innovative processes
  • Better fraud detection and monitoring
  • Boosted customer experience
  • Increased employee satisfaction

With intelligent process automation, workforces have access to advanced analytics and insights from data in real-time. With end-to-end process automation that hastens workflows and reduces errors, organisations can optimise their productivity and achieve maximum efficiency.

How to Implement Intelligence Process Automation?

Intelligent process automation may sound complicated, but its deployment doesn’t have to be. IPA is a combination of technologies that can easily integrate with existing systems, so your organisation does not have to reconfigure its entire IT to implement and get going.

Here’s an overview of how you can implement intelligent process automation:

1. Understand business goals

Begin by outlining business goals and ensuring that IPA is the solution to help you achieve your business goals. IPA is a dominant force in driving forward change, and as such, business leaders must have utmost clarity of the outcomes they wish to accomplish before they get going.

2. Take a holistic approach

Although it is possible to use automation software within silos in an organisation, it’s best to approach automation on the whole for the entire organisation. While you can start deploying a software within a small test case scenario, you’ll want to choose a solution that can be used and adopted by every department.

To do so, it’s a good starting point if you can outline the processes by which IPA will aid and test IPA’s feasibility on certain use cases. Then, assign a team who can be responsible for ensuring that the rest of the organisation is on board and aligned.

3. Build a MVP

Select a certain process to create a minimum viable product. In the case of IPA, this means that you’ll want to redesign an existing process with the help of IPA in its most simplistic form that will still accomplish the intended outcome. With the results, you can showcase the value of IPA to stakeholders and be on the way to digital transformation.

4. Focus on value

IPA will surely allow you to realise quick and immediate gains, but it should also be considered in terms of long-term impact. You can weigh the degree of standardisation necessary to achieve a process alongside the impact through automation to decide which processes are of highest value (highly standardised plus high impact from automation).

5. Change management and assignment of responsibility

When transforming any organisation with automation, you’ll need to ensure that the right people and processes are in place. To do so, you can create a Center of Excellence (CoE), which is a group dedicated to supporting automation’s deployment throughout the organisation. They will be responsible for vendor management, creating a solutions library, capability building and more.

Importantly, when you include intelligent process automation, or automation of any kind, within an organisation, every person needs to be on board. This comes along with change management and the transparent communication of the value added from the new technology.

By leveraging change management, you can align the culture of the organisation with the new set of practices and a sense of willingness to utilise the technology as instructed.

What is an Example of Intelligent Automation?

Examples of intelligent automation can be found in virtually every industry. Within industries with a high volume of transactions and big data, IPA is increasingly useful, as is an automation solution like SolveXia’s finance-focused software.

For example, companies within the financial services sector have a lot of customers with different needs and issues. It is paramount to be able to support these customers in a timely manner to be able to retain them.

With IPA, all customer support data can be pulled from various sources, even unstructured sources like phone calls, emails, and online chats. By doing so, employees cut the time it takes to resolve issues as they don’t have to manually go through every customer support ticket to provide resolutions.

In similar fashion, insurance companies often spend too much time being bogged down with data entry and claims. With IPA, all necessary data from claims forms can automatically be transferred into a CRM so that employees can service customers swiftly.

Final Thoughts

Intelligent process automation provides invaluable benefits to organisations across industries.

With increased capabilities over robotic process automation, intelligent process automation can accomplish tasks using structured or unstructured data and help you to completely reimagine and automate your business processes. If you’re looking to automate business processes, try out a free demo like SolveXia’s and see how the tool can supplement your IPA endeavours.