Our recent research, Today’s State of Work: At the Breaking Point set out to examine exactly how far organisations are on the road to adopting intelligent automation. The research indicated that adding machines to everyday work drives revenue growth, creates new job opportunities and connects employees back to the work they want to do.
There is a certain leap of faith to overcome here i.e. the notion that automating our lives actually create jobs can appear paradoxical. After all, 87% of executives surveyed by ServiceNow say employees are worried that automation will eliminate jobs.
The leap in understanding we must make is clarified by applied futurist Tom Cheesewright, who in supporting us with the research, and explains that intelligent automation is as much about augmenting the human worker as it is about replacing them. Cheesewright explains:
To date the automation conversation has always been about doing more with less. But whether the tasks are physical or mental, there’s a really exciting prospect of extending human capability. Intelligent automation can mean the time, scope and tools to just do more.
The technology model now presenting itself to us is therefore one where we can engineer business process efficiencies into the fabric of new data-driven business models. So how do we achieve this progression? Cheesewright adds:
Friction starts fires. The natural starting point for the application of intelligent automation is to focus on clear areas of business friction: administration, data entry, manual manipulation of information. Very often we find that back-office areas have seen years of stagnation and underinvestment. Addressing this can save resources and reduce risk, but, most importantly, it can create the platform for more transformative change.
Machines making human decisions
Our aforementioned survey of 1,850 corporate leaders validates this need to move to a new tier of business operations. We found that 94% agree that intelligent automation could increase productivity, through the use of Artificial Intelligence or Machine Learning, to streamline decision making and to improve the speed and accuracy of business processes.
Further findings from the survey found:
- By 2018, almost half of all companies (46%) say they will need greater automation to handle the volume of tasks being generated. By 2020, nearly nine out of 10 companies (86%) will hit that breaking point.
- More than three quarters (78%) say data from mobile devices and the Internet of Things contribute to the overload.
Despite a very tangible level of automation in many areas of our lives, is the world of business keeping pace? In a world of smart homes, smart cars, smart commerce and smartphones, has the workplace itself been holding back against the benefits of smart automation intelligence?
In my experience, businesses have been dissuaded from starting intelligent automation projects due to the up-front investment costs and a certain nervousness about inflexibility. Automating many workplace tasks has long been possible, but doing so meant expensive and rigid hard-coding of processes, while the operational status quo – people – remained relatively cheap and highly adaptable.
As with all areas of technology, progress has brought lower cost and greater robustness, but it has also brought more flexibility to workplace automation. Leaders are gaining confidence that the investment will deliver returns and not lock them in.
Cross the intelligent automation chasm
The automation opportunity is huge, but this does also mean that there’s a learning curve, an adoption leap and (for some organisations at least) a perceived chasm between where they operate today and where they could be operating with task and service automation in place. Cheesewright says:
There is a natural apprehension about making fundamental changes to the complex house of cards that is many organisations. The first step is to compartmentalize risk inside clear functions. When processes, inputs and outputs are understood, then experimentation – which is cheaper now in the age of cloud computing than ever before – can begin.
The most forward-thinking organisations have recognized that there is an overhead to this compartmentalization, but that is the price of rapid adaptability in an age of accelerated change.
Where do we start?
So how do we ‘get’ automation? How do we start our implementation path to automated enhancement? Do we simply call an IT consultant or Systems Integrator, or both? Which department should we start the automation process in, or should it be a company-wide initiative?
Our survey pointed out that IT support is the best at business process efficiency, while Human Resources (HR) is the worst. So, while HR can be named the department “most in need of a reboot”, does that mean we shouldn’t ever start outside of HR?
The truth may be more cerebral than a one department at a time approach — the application of automation actually comes down to a people issue.
The 3-Cs of Intelligent Automation
Cheesewright believes that tomorrow’s workplace is indeed populated by more machines than people. He is also adamant that intelligent automation is set to transform every industry. He explains:
It’s increasingly clear that the workers worthy of a bionic boost will exhibit three skills that are hard for the machines to replicate: the abilities to curate, create, and communicate.
It is these 3-Cs people (and their abilities to exhibit these skills and characteristics) that firms should identify when looking for where to apply the automation advantage. Where the 3-Cs flourish, humans outstrip machines. But it is these precise areas that can now be enhanced by automation.
- Curation is about the discovery and qualification of information. Recognizing gaps and knowing where to look in order to fill them, whether in knowledge or markets. Machines can be programmed to sift huge amounts of data, they can be trained to spot patterns and given enough sources, search for truths amongst the fake news. But human beings have evolved these integrated capabilities over millions of years, to the point that machines will find it hard to match the best in anything but the narrowest environments.
- Creation is about the synthesis of something new and original. While machines can ‘create’ within defined boundaries – for example writing simple sports or stock reports – their more original creative efforts are still identifiable by most humans at a hundred paces. Making something that is unique, original and appealing will remain a human skill for some time, whether the creation is in code, paint, language or any other media.
- Communication is about telling compelling stories, selling your ideas to colleagues and customers, partners and investors. Machines already help us to optimize our communications, analyzing billions of digital interactions each day. But they can’t replicate the emotion, passion or narrative skill of a human author and orator.
Intelligently automated future harmony
In the automation-powered future, some machine power will exist as a direct replacement for its human counterparts. These machines and automation controls will work faster, cheaper and, very often, better. But many automation layers (and automated machines) will augment their human partners, expanding their innate skills and boosting productivity. Cheesewright says:
Even without the neural interfaces of science fiction, the gap between humans and machines is narrowing all the time. Multiple sensor inputs combined with machine learning can dramatically increase the apparent bandwidth of communication between us and our tools. The next twenty years will see us create augmented super-humans of creativity, insight and communication.
Working out our new ‘living relationship’ with automation may be daunting for some, but it is a positive inevitability with a beneficial long-term outcome. It’s time to learn to love our machines.
Image credit - Robot and human connecting through electricity bolts © Pixelbliss - Fotolia.com
Disclosure - ServiceNow is a diginomica premier partner at time of writing.