This blog, co-written with Keith Winn (Sr. Director of Intelligent Automation, Apexon), draws on their joint experience in the digital transformation and automation environments.
After years of being thought of as just a marketing buzzword, digital transformation has gone mainstream. No longer a new concept, it is now an accepted business optimization strategy and almost all large enterprises are engaged in moving themselves along the path to digital maturity. In many cases, the questions surrounding this decision are no longer whether and when to do it, but how to do it right.
The caveat is that the need to digitally transform is often overshadowed by confusion as to how to actually take advantage of the processes and solutions available. Throw in the disruption caused by the ongoing global health crisis and it becomes clear that there are defined steps to be followed. High on this list is the need for companies to take advantage of solutions such as intelligent or cognitive automation.
Taking that into account, this blog post will look at not only the potential of intelligent automation but also how it can be used to advance digital business goals.
Digital Maturity Leads to Automation
There are (at least) three defined stages of digital maturity that organizations pass through as they seek to digitally transform.
Salesforce defines digital transformation as “the process of using digital technologies to create new — or modify existing — business processes, culture, and customer experiences to meet changing business and market requirements” and cites the process as the reimagining of business in the digital age. This transcends traditional roles such as sales, marketing and customer service, replaced with how companies think about and engage with customers.
The first stage is often concerned with digital adoption. Companies looking to “go digital” need to quickly adopt a digital mindset, experimenting with and launching products that recognize the required digital transformation. Once this has been successfully integrated, they can move to a second stage – the creation of a digital infrastructure and foundation to support the ongoing requirements of “being digital.”
Provided that this proceeds in the expected manner, companies can evolve to a final stage, one where they make strategic decisions based on the both the level of digital maturity and the intelligent or autonomous solutions they have introduced.
Within each phase, organizations tend to have a high degree of autonomy in terms of how to initiate, drive and then scale their digital initiatives. Unsurprisingly, it is the final stage that we are interested in.
Gartner predicts that by 2022, 90 percent of large organizations will have adopted some kind of robotic process automation (RPA). In recent years, there has been increased adoption of automation technologies such as RPA because they help to minimize manual, repetitive processes, both speeding them up and improving accuracy. They can be customized easily and deployed rapidly, but are limited to narrow tasks.
In fact, RPA is within reach of almost all enterprises, even if they are in the earlier stages of their digital journey. The much greater challenge of joining these disparate processes up into a cohesive process is, for most enterprises, still a work in progress.
Putting RPA to Work
As we noted above, the integration of RPA automates routine, repetitive tasks carried out by skilled workers. Structured data is used to perform what would be monotonous tasks with greater precision and accuracy. RPA is a rule-based, easily programmable technology with almost immediate ROI. However, any exceptions that the RPA tool encounters need intervention from a human….or an intelligent automation tool.
Although RPA will eventually be seen as occupying the more basic end of the automation spectrum, the benefits they can achieve right now are impressive. Apexon has already demonstrated how customers have made significant cost and time savings, such as when this industrial manufacturer improved data accessibility or when a multinational modular space leasing company improved database accuracy and streamlined its invoicing processes.
Taking this into account, intelligent automation is the next level up on the continuum. With intelligent automation, RPA and AI combine to automate complex end-to-end business processes.
And while its acceptance into working processes is still nascent, intelligent automation can stitch together the many disparate, siloed automation initiatives enterprises currently host – in a recent Forrester report, cited by TechRepublic, the technology was referred as the “automation fabric” that will help to solve the piecemeal approach that companies are currently taking towards transformation goals.
Intelligent Automation – The Next Frontier?
As businesses assess which technologies to prioritize on their path to digital maturity, intelligent automation will be high on the list of potential solutions because of its ability to shift enterprise digital transformation into a higher gear. Whereas organizations currently have a high number of tactically deployed automation initiatives, intelligent automation can start to join those individual steps up to address wider, business-centric digital transformation goals.
As AI capabilities integrate with automation technologies like RPA, enterprises see a real opportunity to make a significant impact. Automation technologies have classically helped speed up processes and cut costs but, according to a recent Forrester survey, 37 percent of respondents said they are now investing in them to accelerate digital transformation.
Perhaps unsurprisingly given the demand from enterprises, intelligent automation software is booming.
Gartner predicts that market for the software that enables joined-up automation – AKA hyperautomation – to reach $600 billion by 2022. And this is not hyperbole; Gartner’s Fabrizio Biscotti describes this next wave of automation technologies as having gone from being “an option to a condition of survival.”
Understanding and Overcoming Barriers to Adoption
Intelligent automation promises a lot in terms of bridging the existing gaps between automation initiatives. While the demand is understandably high in enterprises, intelligent automation is not a quick fix and deploying it requires some groundwork. Much of this focus depends on where an enterprise already is on its digital transformation trajectory.
Creating smart workflows that deliver maximum ROI involves integrating different digital capabilities and has (until recently) been a complex, highly skilled endeavor knitting together existing automation solutions together with techniques such as OCR (Optical Character Recognition), NLP (Natural Language Processing), big data analytics, and more. In other words, some enterprises may need to be prepared to ready their systems before embarking on more automation implementations.
Intelligent automation presents non-technical challenges as well.
Culturally, businesses have a role to play in readying the workforce for what will undeniably, eventually, constitute a significant shift in the world of work. MIT, in its recent report, The Work of the Future: Building Better Jobs in An Age of Intelligent Machines, sees the increased adoption of advances machines and processes as inevitable and imminent.
However, far from being a source of anxiety, the authors of the report highlight that “the dynamic interplay among task automation, innovation and new work creation, while always disruptive, is a primary wellspring of rising productivity.” In their view, this rise in productivity is a force that will drive up living standards. This may well be the case, but it is worth noting that automation is always intended to augment and not replace a human workforce.
The Road Ahead for Automation
Highly regulated sectors such as healthcare and financial services are already beginning to implement intelligent automation solution, as illustrated by the fast-growing regulation technology (RegTech) sector. These solutions deliver improved regulatory compliance, while reducing costs.
On the spectrum of automation technologies, beyond intelligent automation lies what is sometimes referred to cognitive automation or intelligent process automation (IPA). Cognitive automation can, for instance, factor in both structured and unstructured data into its processes and will further push the boundaries of what we now know as automated systems.
When looking to implement advanced automation using external experts, enterprise leaders must assess providers based on both their automation expertise as well as their digital engineering credentials. The reason for this is quite straightforward; intelligent automation is a discipline that integrates many other enterprise technology components into the overarching intelligent automation “fabric,” rather than a standalone solution you can switch on and forget about.
Intelligent Automation – The Bottom Line
Intelligent automation is not only a highly promising technology but also one that enterprises should consider implementing to accelerate their digital maturity. When selecting an intelligent automation platform, factoring in the type of data, volume of tasks and desired outcomes is critical – think “right tool for the job” and you won’t go far wrong.
Ultimately, intelligent automation is going to bridge the gaps between the human and robotic workforces – augmenting and transforming, as opposed to pure replacement. Going far beyond piecemeal savings and efficiencies, intelligent automation will help organizations meet the demands of an increasingly connected, digital world.
Advanced automation will extend our expectations of what it means to be an agile, innovative business and how enterprises interact with customers. And while it is an integral step in the evolution towards digital maturity, enterprises that embrace it now can fast-track their digital transformation goals.
And that’s where Apexon comes in. If you’d like to discuss what’s next for your company, contact us today.