What is Hyperautomation and How is it the Future of Digital Transformation?
There’s a word that’s been getting a lot of attention this past year. That word is hyperautomation. If you type the word ‘hyperautomation’ into Google Trends you’ll see that from 2004 to present the word’s popularity takes a huge spike upward in November 2019.
The recent surge in popularity can be strongly linked to Gartner’s recent report on the Top 10 Strategic Technology Trends for 2020. The spike in searches for hyperautomation comes coincidentally after Gartner’s research report was published on October 21, 2019.
- What is Hyperautomation?
- Hyperautomation Benefits
- Why is Hyperautomation Suddenly in the Spotlight?
- Revitalized Interest in RPA
- Advancement in Tools
- Perfect Timing
- I'm Not Ready for Hyperautomation
- Hyperautomation Mistakes to Avoid
- The Conclusion
What is Hyperautomation?
According to Gartner, hyperautomation focuses on two aspects of business operations: The first is to automate whatever can be automated within an organization. The second is to transition from RPA used for simple, rule-based task automation with structured data to RPA combined with AI for intelligent automation that can automate complex processes with unstructured data and a significant level of ambiguity. The data generated from intelligent automation can then be interpreted by humans for strategic business-oriented decision-making.
There are many immediate benefits from adopting hyperautomation.
Optimized productivity - automation performs faster than humans and is error-free.
Improved analysis and insights - automation creates more data that can be analyzed to better understand process performance.
End-to-end process automation - automation alone can complete single, simple tasks. Intelligent automation can focus on entire processes that contain both structured and unstructured data.
Better customer experience - streamlined processes, personalized customer support and data-driven process changes tailored to client expectations are all enabled by automation.
Increased ROI - adding automation to the right processes lowers lead time, eliminates inefficiencies, and never gets distracted with other activities.
Increased innovation - humans will spend less time on task-oriented work, freeing up their time to solve problems and innovate for higher business added-value.
Continuous improvement cycle - constantly increasing automation makes processes constantly more efficient and simultaneously provides ever more data for fact-based decisions on what to automate next.
Why is Hyperautomation Suddenly in the Spotlight?
RPA and AI predictions containing colossal numbers are overflowing on the internet.
According to a report by Forrester, the Robotic Process Automation market will reach 2.9 billion dollars by 2021.
An IDC spending guide predicts that by 2023, worldwide spending on AI systems will near $98 billion.
Across the board, various sources agree that these technologies are going to make a big, undeniable impact on market trends and business decisions.
The idea of combining automation and AI, however, isn’t a new concept. As long as AI has been around, there’s been a fascination with combining it with robots to aid humans. So why the sudden surge in interest?
Revitalized Interest in RPA
AI, usually in the form of Machine Learning which processes large amounts of data, was invented in the 1950s and has been widely used in business operations since the 2010s to predict consumer trends, improve customer relations, and detect fraud, to name a few of today’s commonplace applications.
RPA, on the other hand, has been around since the 2000s but it wasn’t until the last few years that it’s started to gain steady traction. Initial excitement over the technology in its early years led to quick adoption and created heightened expectations followed by a period of slow scaleup.
Two decades later, the technology has advanced, businesses have developed best practices for RPA implementation with great results, and adoption is on the rise. Businesses have figured out how to correctly implement RPA into business operations and the results are enticing.
Take a look at this 2018 headline:
Here’s an article from 2019:
And a recent survey from 2020:
Businesses have gotten the proof they need from early adopters and are convinced that RPA is a successful technology in getting the cost savings they’ve been reaching for.
Advancement in Tools
One of the biggest challenges businesses have faced in RPA initiatives is scaleup. In the past, businesses lacked transparency in their business processes which made it difficult to understand which activities were good candidates for automation and if the ROI was worth the effort.
Today there is growing adoption of process mining tools that help to rapidly increase process automation. Like RPA, the development of process mining technology over the years has played a large role in the emergence of hyperautomation.
A standard process mining software will use a business’s system data to discover and analyze business processes and identify process efficiencies and compliance issues.
Today, advanced process mining solutions are leveraged throughout an entire RPA initiative from planning to post-implementation. This is because advanced process mining will create a Digital Twin of an Organization (DTO), a virtual, digital copy of your current business process where you can safely test RPA before you implement it.
With a DTO you can test what-if scenarios limitlessly in a simulation environment, using your DTO as a way to understand which activities are best suited for automation based on lead time, costs, and estimated ROI.
Once the right automation has been implemented, process mining will constantly monitor the automation to see that it runs as expected. The data generated from automation can then be added into the process to create an ever clearer and more complete process.
Process mining is one of a handful of essential digital operations tools that can help bring the clarity needed to orchestrate hyperautomation. Other tools include intelligent Business Process Management Software, low-code development platforms, and Business Rules Engines.
During distressing circumstances surrounding the outbreak of Covid-19, it feels opportunistic to say that the pandemic’s resulting economic downturn has created the perfect storm of events to urge businesses to turn to automation.
Let’s look at it from a different perspective for a moment. Many businesses who need a solution to help them react to changing economic conditions and consumer behavior are finding automation a godsend, the key to surviving and even thriving amidst tumultuous times.
The almost immediate benefits of ROI, lowered operating costs, and increased productivity obtained from the hyperautomation approach are more than just a bandaid. The agility that intelligent automation brings to business processes means that companies can weather sudden and rapid changes thrust upon them, not just now, but continuously in the future.
Two examples of hyperautomation headlines surfacing during the worldwide pandemic
Hyperautomation was announced and already a buzzword at the end of 2019. Due to the course of events, it’s impossible to tell how the trend of hyperautomation would have become without the auspicious push given by world events (considering those market trend predictions, we can assume a similar trajectory) but considering the benefits businesses are getting from intelligent automation, it doesn’t really matter.
I'm Not Ready for Hyperautomation
The hyperautomation trend will be polarizing for some—it will likely depend on your experience with RPA. For many, the idea of ramping up automation sounds exciting and rewarding.
For others, especially if you’ve had failed RPA projects in the past, you probably aren’t chomping at the bit to add more bots to your crucial business operations.
If you’re in the latter group, you might recognize some of these common pitfalls from RPA projects. These problems will only be amplified for projects that contain multiple technologies automating cross-functional processes instead of a bot filling out a form.
Hyperatuomation Mistakes to Avoid
Starting hyperautomation without a strong business automation plan - your automation plan should be part of your organization’s overall business operations improvement strategy. You’ll need to assess the time, costs, and risks your automation initiatives will have on the entire organization. Part of this planning will involve choosing the right digital operations tools you’ll need to integrate, track, and analyze your automation.
Automating processes before they’re optimized - adding automation to inefficient processes will not suddenly produce efficient processes and the risk is performing inefficient processes faster and racking up costs.
Automating the wrong processes - just because you can automate a process doesn’t mean you should. Choosing the right processes to automate.
Automating unknown processes - no matter how well you think you know a process, you’ll never have full transparency on how the process actually performs without mapping your process and analyzing it. There’s a big difference between how a process should perform and how it actually does.
Hyperautomation is just still in its nascent stage and its future looks promising. Starting the hyperautomation journey will admittedly require some effort in planning an automation business strategy, finding the complete set of tools to support automation integration, and getting employees on board among the list of other preparatory actions. Once you get the initial work out of the way, you can expect to reap the benefits as soon as you implement intelligent automation.
Hyperautomation will doubtlessly experience a snowball effect. The more wins companies get with intelligent automation, the more they’ll implement it. The potential of intelligent automation is too strong to chalk up growing adoption to the “just because everyone else is doing it” mentality. Soon everyone will be using it and it will be a standard approach in the digital transformation journey.
Past experiences and hesitations aside, it’s advantageous to recognize that RPA and machine learning technologies are advancing at astounding rates. Those companies that decide to hold off on implementing these technologies will only be able to do so for a limited time before they start to feel the lag as other companies hyperautomate and advance.
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Stefano Pedrazzi has 15+ years of experience in the ICT and BPM field. He spent a significant part of his work life leading and managing Business Process Management and System Integration Projects for OT Consulting. Since 2017 he has been the VP of Sales & Marketing at myInvenio, helping his customers kick-start their Process Digital Transformation revolution using myInvenio’s process mining solution.