Intelligent Process Automation (Quick Guide)

The world is experiencing a shift in technology and Intelligent Process Automation (IPA) is at the helm of this shift. We may not yet have reached the space-age era of The Jetsons, but several similar technologies are available today like driverless cars, intelligent robots, and virtual assistants.

Predictions for the period 2020 – 2025 indicate a market growth of 15.8 billion dollars as several companies look to adopt IPA as a strategy to minimize operational costs but maintain output quality. The impact of this technology will be felt everywhere, right from infrastructure to business models.

What is IPA?

With the impending shift in technologies, every CIO who has not yet gotten on board should be asking this question. So, what is it?

Intelligent Process Automation is a communion of different technologies coordinating together in the management of automated and integrated digital processes. The core technologies that form this collection are Artificial intelligence, Digital Process Automation, and Robotic Process Automation.

Intelligent Process Automation Benefits

Several companies have already seen the benefits even without automating all the processes within their company. With automation of less than 70% of their tasks, they are seeing as much as 35% more efficiency in the annual costs of operation. These efficiencies translate into the following benefits.

Humans are Freed from Mundane Tasks

Certain repetitive tasks within organizations can be very boring and labor-intensive, with the introduction of robotic process automation, humans can be released from doing such tasks and instead given tasks that make them more efficient and love their jobs even more. In the end, an organization may have more enthusiastic employees. But, that’s not all, the company can be sure that correct processes are being followed without corners being cut.

Enhanced End to End Visibility

When technology is applied individually, it is not easy to see the wider enterprise results. Deploying IPA, however, integrates all the technologies and creates a transparent process that easily identifies bottlenecks that might be affecting the customer journey. This facilitates solutions that smoothen out the customer journey and improve efficiency.

Minimizing Errors

There are various risks of errors within the various industries and many of them are tied to human involvement. It could be as a result of failing to adhere to set processes or just making mistakes like entering the wrong data. By integrating AI and RPA, the processes are easier to follow and areas that are prone to human error can be improved by the use of technology which will stick to guidelines and never get tired.

Enables Continuous Improvement of Processes

With the transparency increased, processes can be scrutinized better and areas for improvement identified. This means that businesses can constantly improve their processes. What’s more, when AI is included in the process, there is constant learning on the part of machines so eventually making adjustments to processes can be automated.

Compliance at all Levels

IPA makes it possible for compliance to be adhered to no matter the level. While humans would consider certain risks minimal and ignore guidelines, automated processes will stick to the regulations. Whether it is document privacy, legal regulations, or simple industry policies that may seem irrelevant, they will be adhered to all the time. For example, if air conditioning should be kept at a particular temperature, automation will ensure that regulation is adhered to, yet a human might think they can change it just for a few minutes because it is too hot or too cold and then forget to reset it. Such scenarios are avoided.

Better Customer Experience

When processes are working like clockwork, the customer will be much happier with the service they get. There will be shorter waiting time and quality is guaranteed since the product is produced according to a set standard and it will always be the same. Happy customers eventually translate into more money for the business because they get repeat business and recommendations.

Intelligent Process Automation Use Cases

There are many IPA use cases but let's focus on one that is more common. Customer support. With automation, customer inquiries can be attended to with auto-responses. This is great, but it is just involving the use of automation. This process can be improved if we add artificial intelligence.

If a business decides to use IPA for its customer support, they would expect it to handle different emails and messages from the website and determine the right response to give. This means that the machine needs to be able to perform natural language processing which entails deciphering:

• Sentiment
• Intent
• Speech
• Entity Classification

Emails will be grouped by the AI according to the content, it will decide which email can be given an automated response, which should be forwarded to a particular individual for resolving, which message is a compliment and which is a complaint.

Sorting through emails is a task that would take a lot of human hours but with IPA, the process is almost instant. Sales teams in many industries depend on this technology to improve customer support before and after the sale.

Another use case within customer support is the use of chatbots. Usually, all a chatbot can do is give responses to customers. This process can be made more efficient by introducing RPA. When the two combine, they can go a step further and perform actions.

If for example, a customer would like to make a purchase online, the chatbot will take down the order and receive payment, then transfer that order to the warehouse where a robot will package the item and have it ready for delivery. This is something Amazon is experimenting with.

IPA vs. RPA

Digital technologies have introduced us to IPA and RPA which are usually confused and sometimes used interchangeably. They however are 2 separate technological advancements although one may be superior to the other. When you consider them, you may realize that it is better to have the two working hand in hand. Let us understand the two.

• RPA: This is designed based on the abilities of software robots that make up a digital labor force that can efficiently carry out large volume manual tasks. Usually, these tasks need to be performed repeatedly. Intelligent robotic process automation works based on set guidelines to carry out mindless tasks that do not require analysis. For example, lifting an item, turning it upside-down, and then placing it onto another item and then repeating that action. This action is performed quickly and with precision based on the data fed to the machine. It can also be used for data entry and help desk tasks among others.
• IPA: This could be compared to providing a new brain for RPA. With this technology, the skill set of robotic automation can be expanded to take care of complex processes that involve analysis and decision making. IPA can accommodate structured data as well as unstructured data. It utilizes tools that provide advanced data management as well as analysis to mine structured data from complex sources.

When you introduce IPA to robotic process automation you add the following technology to the process:

• Machine Learning: This adds extra intelligence to the robot software that allows it to evaluate the performance of different tasks. So every time it performs a task it improves it with small adjustments based on performance data from the last time it performed the task. It will use set goals like cost reduction and time saving to measure performance. Eventually, the performance data can be transferred to other tasks as part of deep learning.
• Natural Language Processing: This is a tool that enables software to analyze human speech and retrieve useful content that can determine the next action of the system. This can be applied in voice-command searches for example using a virtual assistant to search for a particular document or retrieve data. It can also be used for chatbots that can chat with a user like a human would and even perform tasks based on chat analysis. A chatbot equipped with IPA can draw links between past interactions with a customer to determine what responses to give as well as provide suggestions.
• Optical Character Recognition: This enables the scanning of physical or digital text to create content. In this case, you can scan a document and the robot will identify the characters on the page to turn it into editable text in a particular format.

In essence, IPA provides more intelligence and added improvement in the execution of tasks in comparison to RPA which is more useful for execution of mindless tasks. Each of them has its advantages, but in the end, it is better to have them working together than individually if you want to achieve greater performance.  

Main Purpose of IPA

The main purpose of it is for automation of procedures that entail working with unstructured data. Document automation is among those procedures when you have to deal with text and images. This could be processing customer feedback, making reports, and taking action based on email communication. It enables organizations to give machines leeway to make decisions about certain processes.

A crucial capability of IPA is transfer learning which saves time that would have been spent learning particular skill sets to perform other processes within an enterprise. Instead of creating thousands of rules to deal with the various use cases, transfer learning enables duplication of experiences which improves performance with every execution of a task. This saves finances but gives impressive returns.

For enterprises that are already using automated processes, the IPA's purpose would be to improve the process efficiency through introducing artificial intelligence that will make the software they are using even smarter and able to perform more tasks within a shorter period.

Intelligent Process Automation Examples

IPA examples are visible in different industries. Some are very obvious and you may have interacted with them while others remain in the background. Here are some common examples.

Driverless Cars: If you have been following the news, you must have heard about different companies trying to develop driverless cars. These integrate robotic action to steer the car, while artificial intelligence determines the decisions made, for example recognizing a stoplight and the green one so that it will stop at the red light and go when the light is green. So many other decisions that a human makes while driving are being made by these cars with the help of IAP.

Financial Analysis: Financial officers have to go through a lot of financial data to find inconsistencies. These days, this can be left to intelligent automation to identify inconsistent data, this helps to create better financial analysis and can be used for financial forensics as well.

Processing Documents: A number of online surveys are taken and this data needs to be compiled into a report. Document automation software is now able to analyze thousands of survey forms and extract data from it to create reports. The process of research is becoming a lot easier and faster with better accuracy.

Human and Robot Collaboration: In the past, it was almost impossible for humans and robots to work in the same area at the same time because there was a risk of injury to humans. Today, IPA provides the needed intelligence for the robots to identify humans within the working environment and act in a particular way to ensure safety. This is already in use in car-making factories where humans and robots are sharing workspaces.

Warehouse Management: Robots have been designed to handle warehouses. These robots can take inventory, store goods as well as load and offload. They are capable of recognizing obstacles and move around without colliding with one another.

IPA Tools

For organizations to improve their efficiency, they need to adopt the right intelligent process automation tools. Making a choice may depend on various things including the kind of industry you are working in, what kind of automation you already have in place, how knowledgeable your staff is about IPA. There would be other questions you would also have to ask yourself but that is for a different guide. It would help however to know the different types of tools.

• General Process Automation Tools: As the name suggests, they can work in different industries performing general tasks
• RPA: These combined with cognitive automation tools are very flexible and add the abilities of robot technology to the process.
• Low Code Applications: They are easy to develop and do not require a lot of technical knowledge to use.
• Specialized Process Automation Tools: These are designed for specific needs within an industry. They are usually used by IT teams.
• Macros: They are the simplest tools and most users can find their way around using these tools. Excel is one example of macros tools.

Conclusion

The world of technology is developing faster than ever before and new solutions can be expected to enable enterprises to perform more efficiently. A lot of the technology that we envisioned for the future can be made possible with the improvement of IPA.

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