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Thursday, 02 December 2021 11:56

Why intelligent automation fails

By Andy Mellor, Kofax

GUEST OPINION: While most organisations have been migrating towards digital transformation for some time, the events of the past few years propelled them further down the path at breakneck speed. With the challenges that lie ahead, intelligent automation (IA) is an increasingly attractive option, but to use it to build a competitive advantage, you need to back it up with the right approach.

As we start navigating the post pandemic landscape, many organisations are eyeing how they will handle the next set of challenges. Remote working is increasingly being viewed as key part of the employment mix, rather than a stop gap measure, requiring a rethink of systems built for office life.

Changing legislation such as the Consumer Data Right gives consumers more control over their data, including the right to withdraw consent, meaning organisations need to have command of all their data.

Labour shortages are making it more difficult to attract and keep the right people, especially in the tech sector. Meanwhile, global supply chain issues causing business disruption, requiring maximum insights to make the best decisions.

These make taking a digital-first approach the obvious choice, which is probably why 88% organisations surveyed for Kofax’s 2022 Intelligent Automation Benchmark Study believe that automating business workflows post-Covid will ensure business continuity.

Organisations know that they need Intelligent Automation (IA) but many have not made much progress in executing it, still largely relying on manual or partially manual processes.

Given that none of the respondents have fully automated any of the high-value workflows, such as accounts payable automation or invoicing process, which they report as being critical to their digital transformations, we are now in a unique position to do it right.

Without the correct change management, roll-out automation projects can create a divide between vision and reality. After all, no matter how transformative technology is, it won’t be much help if it is not implemented without big picture approach. How many horror stories have you heard of cloud roll outs that brought bill shock, as capacity or services were dialled up during busy periods but never dialled down again?

Just as these tales of cloud-gone-wild aren’t creating a rush to abandon cloud, the potential pitfalls don’t mean that you should let your IA dreams fall by the wayside. But it does mean that before you get started, you need to avoid the missteps.

Taking a piecemeal approach
Many organisations have spent the last several years accumulating point solutions for automation to support business operations as they needed them. Then one day, they wake up to realise they’ve built fragmented and siloed automation projects.

Unfortunately, a piecemeal approach won’t cut it anymore. When asked about the challenges created by these one-off approaches, the top responses in a survey of 450 IT and automation decision-makers nominated technical debt (46%), delays in successful outcomes (35%), and problems of scale (34%). Add in a need for qualified talent to manage and scale these myriad solutions, and that they are hard to find now, and it’s easy to see why many businesses find themselves in a pickle.
One platform puts an end to automation silos.

There’s only one solution to manage and maintain, and everything can be implemented with a minimal required skill set. An integrated platform also lightens the workload when it comes to solving large business and operational challenges.

Not using IA to guide decisions
Organisations are awash with data waiting to be collected, analysed, and applied. Data pulled from the web, internal systems, and documents are key to the processes driving the business, so embracing advanced analytics are important for unlocking the true value in the information coming in, and ensuring decisions are based on actionable insight.

But it’s not just this deep analysis that IA can assist with. It can be something as simple as ensuring that invoices, contracts, sales orders, and more are routed to the right people and departments. Seamless collaboration between human and digital workers makes it easy to execute and automate workflows across high-value business processes. When correctly executed, employee productivity increases, and workers can spend more time on value-added, strategic work and less time on manual, error-prone tasks.

Not have C-suite buy in
IA is a key part of an organisation’s digital transformation. It also can touch every aspect of the business. With stakes this high, it means that a successful IA implementation needs to be closely aligned to an organisation’s strategic vision and accompanied by an appetite for change management. And this can’t just come from one department.

Getting buy-in doesn’t just mean making the business case for IA. It also means highlighting what it means for the workforce. Yes, it can help to plug the skills gap, but the last thing you want is to scare off any employees who worry that a software robot may replace them. In fact, 33% of respondents to a KPMG survey indicated that management concerns over IA’s impact on employees was the biggest obstacle to rolling it out. Building the case that it’s an escape from drudgery to and a path to more satisfying work is a crucial step.

Not empowering people to use AI
A key component of employee buy-in is to get it into their hands so they can realise the benefits. That’s why an IA platform with a low-code philosophy is a must.

“Easy to learn” and “easy to use” are features many business line managers look for in a platform, with more than 70% of respondents to one survey listing both qualities as requirements for helping them do their jobs more efficiently. A low-code platform lets citizen developers (i.e., the people who do the work, not IT developers) put their business knowledge to work on automation initiatives with minimal training, while still providing more advanced features for skilled coders and developers.

The landscape is complicated enough. Implementing siloed, disparate projects without the right cultural buy-in is more likely to be a hindrance, not a relief.

 


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