Hyper automation isn’t just another iteration of robotic process automation (RPA).
It’s not something you can buy. And if you think it’s hype — then you don’t know what you don’t know.
Hyper automation is a culmination of experience, strategy, analysis, and technology adoption that is focused solely on automating deeper business outcomes.
It is industry and technology agnostic. It reflects the maturity of an organization’s automation center of excellence.
Why Hyper Automation Represents a Massive Change
Far too many vendors have attempted to be all things to their customers – resulting in failures and stunted growth for customers.
However, this strategy is not for the weak-of-heart or brand-new automation journeys. Architecting “Gen 2” automation strategy is challenging and requires both time in the automation trenches and a deep understanding of business models and processes.
The pivot happens when there is practical experience in the limitations of RPA, and the understanding that further investment must be made in both human capital, and complementary technologies.
How Automation Begins at Most Places
Successful first-generation automation strategy is focused on the low-hanging fruit of simple, well-defined, and highly repetitive tasks.
These are easily handled by a purpose-built RPA tool. By starting with these types of use-cases, organizations will see value in building automation teams that combine the technical, subject-matter, and people-expertise needed for success.
Moving Past the Low-Hanging Fruit to The Real Prizes
Moving past simpler automation tasks is the hallmark of an organization moving into Generation 2 automation – hyper automation.
These organizations are ready to tackle complex, subject matter intensive processes that often involve a high degree of decision-making and experience-based judgement.
And the good news for smaller players in the industry? Automation demands results, so vendors able to effectively deliver on niche value propositions have a seat at the table.
Mainstream RPA vendors will never be able to provide the level of sophistication provided by adjacent technology dedicated to solving very specific and challenging automation requirements.
The Need to Solve Difficult Business Problems Will Not Go Away
Business leaders will demand more out of automation investments. As early wins create new budgets and funding, increasing pressure will be applied to solve challenging human-centric processes.
The good news – the funding is there.
The bad news – hyper automation is pretty complex.
You will be judged on your ability to understand, apply, and use an architecture of complementary technologies – and not just disparate coding languages and open-source machine learning tools.
You don’t have the luxury of time to build robust and scalable platforms to support enterprise automation projects with looming deadlines and scalability requirements.
In order to create excellent experiences for both business users and especially customers, automation designers, architects, and developers need to understand how to combine the tools of:
- Process mining
- Integrated business process management
- Decision modeling
- Intelligent document processing
- Cognitive automation
- Machine learning