When it comes to making predictions for the year ahead, hyperautomation is a curious phenomenon.
On the one hand, it has been spoken about in aspirational terms for some time and has even been recognised in Gartner’s top 10 strategic technology trends for both 2020 and 2021. Gartner also believes that 85% of companies will increase or sustain hyperautomation investment strategies over the coming year, while Deloitte has termed the technology as “the next frontier for organisations globally” in a paper published at the turn of the year.
On the other hand, it’s a slow and complex process – and it’s still early days. While COVID-19 and the resulting push for digital transformation has kickstarted hyperautomation’s rapid rise to fame, the process can take years for organisations, all of which will digitise at their own speed.
So, for clarity’s sake: what is hyperautomation as we end 2021? How does it differ from the regular old automation that we’ve become accustomed to?
Hyperautomation can be defined as automation that is data-driven rather than process-driven, thanks to a combination of artificial intelligence (AI), machine learning (ML), natural language programming and predictive analytics technologies.
In this regard, it’s a ‘levelling up’ of automation. Enterprises have been using technologies like robotic process automation (RPA) to free employees from the monotony of repetitive tasks, like data logging. This frees them to concentrate on higher-value tasks that are both more stimulating and rewarding.
Hyperautomation is an introspective elevation of that concept, using data taken from every process and every piece of equipment. You are attempting to digitally recreate your entire organisation, integrating every process with one another, to capture the data you need to inform improvement across the board. If this sounds complex, that’s because it is!
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Hyperautomation has come to prominence as a trend for 2021 thanks to the maturity of digitalisation and of data management tools. The aforementioned digital upskilling that many organisations have committed to during the pandemic, combined with these tools, form the basis for hyperautomation to take place in the right environment.
But we’re only at the start of a long journey. The digital recreation of your business, warts and all, can prove a gruelling exercise in self-examination given the speed at which systems are recreated, and resultant insights are amalgamated.
Companies will need to invest a lot of time and energy in order to create long-term adoption of hyperautomation. Turning theory into action is a big challenge to take on, and preparation is key.
That means that the value of hyperautomation will only start to materialise for the pioneers that stay focused. Organisations need to stay on the ball and avoid slipping back into old, stagnant processes driven by more operational, tactical initiatives.
By taking the time to understand the necessary steps required before setting out on a hyperautomation journey, businesses will be able to achieve that focus and increase their chances of success.
Expectation and preparation
The flip side of that, of course, is that you will see some organisations who have started on their journey abandon the ‘hyper’ prefix in favour of plain automation. For those organisations that are less digitally sophisticated, or for those that bought in at the peak of the ‘hype cycle’, the gains that standard automation can offer them might represent enough short-term improvement to satisfy them.
While it would seem odd to include this in an article on hyperautomation predictions, it’s indicative of two things that are key ingredients to hyperautomation itself:
- The objectives for the hyperautomation journey. Is it just about reducing cost and claiming back time, or is it about something deeper? Many organisations don’t realise that they need to make an ideological shift to maximise their gains from the process, cultivating a better respect and understanding of data, and abandon it as a result. Indeed, Exasol research this year suggested that less than half of young people (just 43%), a significant proportion of the future workforce, consider themselves data-literate.
- The need for a sophisticated ‘digital culture.’ Following on from that, the organisation in question needs to be ready to respect data as a game-changing difference maker, and as a justification for strategic decisions. Whether that’s a department internally acting as a ‘Centre of Excellence’ for data, or a chief data officer advocating for data’s importance at the head of the business, the process needs a champion.
Ultimately, those that choose not to hyperautomate will do so because they lack – by choice or otherwise – some of the key building blocks needed for the process to succeed. 2022 will see some organisations choose to quit hyperautomation – but see many others, if Gartner’s 85% is correct, begin to address the building blocks they need to begin or continue their journey.
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For those that stick with it, what hyper-revelations will we see in 2022? Well for starters, instead of automating small tasks in isolation, digital native companies will start to understand how to automate entire end-to-end workflows. Take HR as an example. If you can digitise the whole process from selecting candidates, hiring, employee education and development, mentoring, churn prevention, and more, then you’ll be able to standardise best-practice, improve efficiency and eliminate bottlenecks.
We’ll also see the continued emergence of digital twins: the virtual representation of assets, systems and processes in a bid to improve performance and reliability, increase productivity and reduce risk. They allow us to understand whether a tweak in one department will create a bottleneck in another.
For example, by running hospital-wide simulations, healthcare leaders can work out the impact of tweaking staffing or changing the layout of a ward, for example. They can then understand whether the consequences of that tweak in one department will have the same impact on another without physically impacting on patients and workers.
While they won’t be widespread, these are the benefits that digital native organisations that retain a laser-focus on their hyperautomation strategy will begin to see in the future.
Written by Mathias Golombek, chief technology officer at Exasol