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Home » Understand what hyper-automation is and how it can optimize your business processes

Understand what hyper-automation is and how it can optimize your business processes

With the advancement of technologies, companies find several allies to increase productivity and make teams more satisfied. One of the concepts arising from these transformations is hyper-automation, an evolution of standard automation, but which allows more knowledge about the company’s processes and optimization of strategies.

If you need security in your operations and intend to invest your time and money in activities that really demand human attention, understanding and applying hyper-automation is crucial. With it, you and your team are freed from merely bureaucratic tasks and can dedicate themselves to intellectual and planning strategies.

In this article, you will understand the main differences between automation and hyper-automation, as well as the advantages that this feature can bring to your daily life and how to implement it as quickly as possible. Good reading!

After all, what is Hyper automation?

Hyper automation starts from the premise that isolated tools are not capable of replacing the so-called “human capabilities”. However, by combining and integrating these tools – such as RPA (Robotic Process Automation) , AI (Artificial Intelligence) and iBPMS (Intelligent Business Management) – this replacement becomes possible.

But you must be wondering what the “human capabilities” are, after all, right? One of the most difficult activities to be reproduced by machines, but which is gradually gaining space in the routines of companies.

The term “hyper automation”, therefore, refers to the combination of tools to replace humans in addition to operational tasks. Yes, the machines themselves would be able to handle more complex issues, reducing the chances of errors and providing greater freedom to sectors that deal with bureaucracy.  

Here are the main differences between hyper automation and automation. 

Understanding the Differences Between Hyper automation and Automation

Common automation aims to combine several technologies, with rules to create a beginning, middle and end process for your chain of activities within the company. Using data, this automation is done in routine actions to increase productivity, tie jobs, eliminate errors, etc. Typically, standard automation is restricted to replacing operational processes that require brute force, for example. 

Hyper automation, on the other hand, works with the same resources, but in a high way, in order to use intelligence and breadth to generate more solid and lasting results in the company. Hyper-automation provides the strengthening of your team, letting the robots work and your employees to focus on the strategic parts. In other words, hyper-automation seeks to replace not only physical strength, but also the intellectual strength of various sectors where this is possible. 

How did Automation become Hyper automation?

As we talked about earlier, hyper automation is an evolved version of machine learning. To be more specific, machine learning is a branch of artificial intelligence based on the concept that systems can learn from data to identify patterns and make decisions. This with little or no human intervention. 

The interaction made its application more advanced and faster. In practice, machine learning is already among us in some situations and can facilitate (and much) the day to day of managers. That’s because some decisions can be made only based on data, because they are something frequent and customary in the company, or because they are not ethical or human decisions.

What are the benefits of hyper automation?

See how important hyper-automation is to improve the performance of companies in any market segment? See now the main advantages you should expect from this type of resource.

Increased productivity

The benefit that stands out refers to increased productivity. This becomes even clearer when you think of machines that solve problems around the clock.

Imagine, for example, a chatbot. He can transmit information and perform various calls on any day or time. This represents a great increase in productivity in the face of all kinds of support provided by employees.

Thus, you can outsource simple and direct issues to technology, and pass on to the team only problems that are complex and require more steps to solve.

Scenario analysis with data

Data analysis is directly linked to business intelligence. As markets become increasingly competitive, there is a lower tolerance for errors, mainly related to the creation of products and services to meet demand. Therefore, bringing information to decision making is a necessity.

When it comes to the audience, using the data collected from customers to draw an ideal profile, perform demand estimates and develop better solutions for the audience, allows the corporation to remain competitive and strong.

In addition, creating scenarios that offer certain predictability about income and expenses is essential for good strategic planning. However, analyzes with such a degree of complexity can only be implemented with adequate technological resources such as Machine Learning, Big Data and AI .

Integration of disruptive technologies

Through hyper-automation, it is possible to connect various technological resources, regardless of your sector of activity and the activities carried out in it. By integrating various parts of the institution, you can centralize data, automate tasks and improve the productivity of the entire team.

In this way, the company becomes even more competitive and also creates the necessary foundations for an expansion model. This contributes to the transition from a small business format to a structure with gains of scale.

Projection for the future

All sectors have undergone transformations due to the emergence of technologies, software and the access that the internet offers. Denying this reality represents a great risk for the corporation and threatens its full development.

Therefore, it is worth getting ahead and starting the business projection for the future earlier. If a company starts collecting customer data just a year after its competitors, for example, it takes time to be able to use the information in a strategic way, as other corporations are already implementing.

Soon, digital resources will be part of everyone’s routine, just as cell phones and smartphones are now. So, why not start this process of adjusting the company and the entire team sooner?

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