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Smart automation, the evolution needed to reach operational excellence

By Rosa Megía, Enrique Sahún — September 15, 2020

Business processes can be sped with these technologies


The first article of this series on operational excellence highlighted the importance of the initial analysis and discovery phase in order to objectively quantify corporate operations, evaluate processes, identify key inefficiencies and measure their impact on the business so as to subsequently prioritize how they are addressed.

Following that initial phase, we can then decide whether (and how) a process should be redefined so it may be optimized, and whether it can be partially or fully automated. At this point, and when applicable, we can begin to consider using robotic process automation (RPA) techniques.

This article does not aim to repeat the benefits of RPA techniques or the features of the processes that can best be automated since plenty has already been written about these topics. However, we believe it is important to discuss the two main types of robots we can develop, attended and unattended, depending primarily on whether they are front office processes, in which human intervention may be required, or back office processes, which tend to take place in the background, respectively.

In the first category, robots will offer high productivity and short response times for front desk services, such as a help desk or a call center.

In the case of back office processes, however, there are robots that operate with no human intervention and will make it possible to optimize performance, thereby lowering the cost of virtually any activity. Delving further, we can come across a number of hybrid scenarios in which both types of robots are combined, even with individuals, who can also participate in the process.

However, on this occasion, we want to focus on how this automation can be elevated to another level of intelligence by combining RPA with other solutions or technologies, resulting in what is known as IPA (intelligent process automation). These techniques will enable us to create a 100% automated process by covering those aspects that a robot on its own is unable to execute and that require human intervention (leading to some of the hybrid scenarios we mentioned earlier).

By combining RPA with artificial intelligence, the possibilities for optimization can grow exponentially by making robotics more flexible and able to manage exceptions. This approach makes it possible to undertake complex automations that up until now required human reasoning in certain parts of the process, or were simply impossible to automate because the scenarios did not have perfectly defined rules.

The idea is to combine RPA with artificial intelligence techniques, such as machine learning, to automate decision making through predictive models. For example, this type of automation can be applied to complaint or customer registration procedures for companies that use a scoring process. In these cases, the model will recommend the action of approving or dismissing a complaint, or accepting a new customer, before continuing with the subsequent back office process. This enables autonomous process execution, from beginning to end, without human intervention.

Cognitive intelligence capabilities can also be leveraged to extract information and understand natural language texts in those parts of processes that require the semantic comprehension of a document. This technology is particularly important when automatically interpreting the interactions of a customer who is communicating with the company via any of the available channels. As a result, it will be possible to speed up that process and make it more objective, reducing costs significantly and even eliminating potential human errors.

On the other hand, to optimize a customer onboarding process, we will integrate biometric solutions so as to automatically and reliably identify and verify individuals. This will improve the customer experience from the initial interaction with the brand, while reducing the operating costs of that process.

These are just some examples of how we can automate processes to the next level of operational excellence we strive for. Additionally, these concepts can be applied to any sector or industry. There are many examples in industries such as finance, insurance and telecommunications where processes that were only 30-50% automated reached automation levels of 90-100% thanks to IPA.

According to Forrester in 2019, intelligent process automation could reduce global labor costs by €120 billion between now and 2022. In addition to the cost savings, the combined application of these technologies speeds up business processes, resulting in higher returns on investment. Therefore, it seems that this will be the trend for RPA and the foundation for the next generation of optimized operations.

Would you like to learn more about operational transformation? Download our report: Transformation plan: The first step to operational excellence

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