#76 Competitive Advantage, Better Processes w/ Intelligent Automation vs. Hyper Automation

Hallo und willkommen back to another episode of the Process and Automation Podcast. I'm Sascha Cutura, and with me as always is Arno van Rooyen, and together we are the Automation Guys. Yeah, all our listeners out there know we are extremely passionate about all things process, workflow, and automation. So yeah, and that's, that's the reason why we can't stop recording new episodes. So that's why we are back here today. And yeah, businesses today know that operational efficiency, effectiveness, and productivity are key to competitive advantage. And yeah, process automation tools are being adopted more and more. Because they help IT and business leaders turn those goals into reality. And if you have spent time researching ways to boost efficiency in your business by taking advantage of several automation opportunities, you most likely come across the term Hyperautomation. And the other term, intelligent automation. And yeah, we are talking on those topics here on the podcast a lot and have done several episodes. But yeah, so the community is asking for clear differentiation and this is what we deliver today. So yeah, these two things are critical concepts. And should be understood by everyone who is involved in the automation space really. So today we will discuss hyperautomation versus intelligent automation so you can decide which approach will be the best fit for your company and for your specific automation journey. So Arno, do you like to kick this off?

Yeah, sure. Thanks, Sascha. Thanks for that intro and welcome to all our listeners. This is a topic that we have touched on in the past and the question is, you know, what is the difference between hyperautomation and intelligent automation? You might have seen these terms being thrown around, analysts are talking about it. But when it comes to automation, you can think of the concept as comprising of three levels. So each level really builds on the complexity and also the power of the previous one. So the first concept really, uh, that I want to get started with is the concept of simple automation. So simple automation really refers to the use of one automation technology to solve a simple automation problem. So for example, You could use robotic process automation, or RPA, to collect data from a web page, or, you know, you want to interact with an application where there's no application programming interface, or API. Intelligent automation is the next step, whereby it refers to blending of RPA technologies which is robotic process automation technologies and concepts of artificial intelligence or AI. So you might have heard that term before. So RPA will handle simple tasks with the procedural steps while AI can handle cognitive tasks based on pre-trained models. And these models are typically, for example, things you see in invoice processing. So that might use an AI-driven intelligent document process— intelligent document processing methodology, or IDP. And that would extract data from an invoice. Once that data is extracted and it is in a structured format, then you would use an RPA bot to enter that information into a specific software program that might lack an API, or you might do something else with that data. But at that point, it is in a structured format.

Yeah, and then the next topic there is also, yeah, it's then hyperautomation. And the concept of hyperautomation goes one step further than to what Arno just mentioned. Yeah. It really refers to the use of all the automation tools, including the capabilities used to orchestrate tasks between these tools, between human and digital workers. So yeah, hyperautomation includes AI, RPA, and also it's wider range of tools, decision rules, workflow orchestration, intelligent business process management. So all that stuff we have been doing for a while separately. So it combines it all together under that term. So all your teams will be able to streamline and automate complete end-to-end processes. So, and as you can see, intelligent automation versus hyperautomation isn't an either-or proposition. It's actually a progression. And the next level of automation. So, I don't know, what, what do you think? How is Hyperautomation different from the so-called regular automation?

Yeah, it's also a good question. And I think that, you know, if you look at both Simple Automation and Intelligent Automation, they operate at an individual task level. So there's something you want to achieve that's very simple. They can work wonders for repetitive tasks like data entry. And, you know, for more complex, yet still isolated mundane tasks, you know, such as, you know, using natural language processing or NLP in chatbots, you know, this can be used to improve customer experience, for example. But if you look at complex processes, you know, sort of bigger processes or real end-to-end business processes, hyperautomation initiatives are really the way to go because obviously the orchestration capabilities of hyperautomation that you, you, that you touched on earlier allows for very complex interactions between the various automation tools and of course the human workers. And you know, they enable this at a, end-to-end level for, for all of your core business processes. So this orchestration layer lets you reap the full benefits of HyperAutomation, not just task-specific benefits. So, um, let's, let's consider an example, um, and I'll, I'll choose order processing. So the steps for orchestrating this full process might include a purchase requisition comes in either digitally or, you know, it can even be by physical mail or email. Then the AI comes into play. So AI-driven intelligent document processing, or IDP, uses OCR, which is optical character recognition, to classify the document as a purchase order. It recognizes that. Then it extracts the relevant information, like the order volume, perhaps the address details, or the account numbers from the document, you know, without requiring any manual intervention or manual entry. Next, the orchestration layer will then use predefined business rules to either validate the information or pass it off to a human to look for errors or any discrepancies. If the purchase order looks good, then the RPA bot enters information into the appropriate finance system, for example. If not, the orchestration layer routes information to an employee or to a human operative for intervention. So again, once all of this information has been entered into the required systems, the AI might then generate several emails. First, it perhaps generates an email to be sent to the appropriate departments to fulfill the order. Then it could generate an email and send that to the purchase requester with some tracking information. And then finally, the orchestration layer sends requests to use RPA or RPA bot to print of shipping labels for the fulfillment department. So, so again, this is a very simple and abbreviated example. You know, there are other elements of this process that can be automated as well. You know, I'm thinking about checking inventory levels, ordering more inventory as needed as Sascha fulfill orders. Things like sending billing requests, verifying and reconciling payments, you know, and many more. So there's obviously a lot of additional kind of scenarios that you can bring into, into the fold. The point here that I'm trying to make is that intelligent automation can automate a small portion, but to fully automate the process and, and grow that automation, you need the essential orchestration components And these are only found in hyperautomation technology. So that's the big differentiator.

So what to look for in a hyperautomation platform, that might be the question you now ask. So yeah, when you think about the hyperautomation versus intelligent automation, as Arno mentioned, yeah, both are really important. So it's not like like we discussed before, either or. So if you want to get really the full benefit of automation, you have to find that platform, or a platform which covers the whole multiple automation tools in one platform. So, or you buy lots of different ones, of course. But when you look out for one platform, you have to make sure it covers the AI aspects, the RPA aspects, the workflow aspects all in one. And yeah, so that's what we are discussing here often on the podcast as well. So we talk about, for example, Forrester and Gartner, and they independently look at different vendors in the industry and will rate these platforms, hyperautomation platforms, based on the different areas, how good they are and where they have their strengths and weaknesses. So yeah, we had a couple of episodes in the past. Feel free to listen back to those or just reach out to us and ask us for our opinion, or feel free to just share what your thoughts are on certain platforms. You can do that directly, either on, yeah, directly on LinkedIn or you join our, theautomationguys.net community. There you can just share all your, yeah, questions with other like-minded people. Yeah, we will be back next week again, and until then, let's automate it. Unfortunately, that's it again with this episode of the Process in Automation Podcast. If you like this episode, please give us a 5-star rating and don't forget to subscribe to this podcast so you don't miss any upcoming episode. We hope you will tune in next time, and until then, let's automate it!