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Intelligent Automation Exchange: 4 takeaways for transformation leaders

Intelligent Automation Exchange: 4 takeaways for transformation leaders

It was a great pleasure to join IQPC’s premier in-person event for intelligent automation and digital transformation leaders - Intelligent Automation Exchange. We took the stage with our customer Rushabh Shah, Deutsche Bank’s Program Director of RPA, and joined talks with the industry’s leading experts and implementers.

With so many intelligent automation leaders in one place, the event provided a rare snapshot of the intelligent automation landscape, its most important developments and emerging trends.

Here’s a summary of our key observations and the major digital transformation trends to follow from the event:

Hyperautomation means ‘putting data to work’

For enterprises, the pandemic was a time of disruption and adaptation. However, now that the technology foundations are in place, the top priority for transformation leaders is scale. Far from sustaining a long-term shrinkage of demand, the global easing of restrictions and re-opening of economies has seen demand skyrocket in many industries. As we have seen, the biggest obstacle to business now is a shortage of capacity.

But how do today’s businesses achieve scale? Serving more requests and customers often means scaling up operations and headcounts. Yet this is expensive in the short-term and unsustainable indefinitely. Intelligent automation leaders have been tasked to solve the puzzle of fast, cost-effective scaling, and most are turning to hyperautomation to do it. This is the programme of extending automation to every corner and process in the enterprise.

The challenge is that hyperautomation demands clean, structured data - and lots of it. Yet the vast majority of data in the enterprise is and always has been unstructured. Business conversations, emails, chats, calls; these are the data formats that hold services and the business together. But for the most part they remain outside of core IT systems - out of sight, out of mind.

As the event chairperson, and PepsiCo’s Head of Global Continuous Improvement, Anna Alechno put it: achieving scale in automation depends on putting unstructured data ‘to work’. Intelligent automation leaders are now laser-focussed on finding ways to improve data quality and turning this raw, unstructured data into business value. Machine learning and natural language processing (NLP) have therefore been added as important tools to the digital transformation arsenal.

Find out more about how NLP is contributing to the intelligent automation tech stack.

Email automation is a top priority

In terms of where these automations will be targeted, intelligent automation leaders are focusing on the high-volume, largely transactional workflows. Email is one of the most popular and important targets. Transformation leaders are coming to realise just how much time their people spend simply processing emails - mainly repetitive, transactional requests.

The leading enterprises are now investing in NLP capabilities, to free their employees from repetitive email requests. NLP is providing them with the interpretive layer needed to understand these messages en masse - transforming them into machine-readable data. As Rushabh Shah, Programme Director Intelligent Automation at Deutsche Bank, said of the Re:infer platform: ‘We’re using it to kill waste - you could see it as process mining for your email logs.’ Transformation leaders are then turning the extracted data over to automation tools for downstream processing.

However, intelligent automation leaders are also looking beyond email, to other communication types. Remote and hybrid working have seen chat and call volumes explode. There are now so many different channels for conversing with colleagues and customers that employees feel overwhelmed by communications. In this respect, strong translation capabilities are a must for large enterprises. NLP solutions that provide support for a wide range of languages and message types, are at a premium.

Learn more about how NLP is making end-to-end email automation a reality.

Employees are no longer afraid of automation

For some time ‘the bots are coming’ has been a source of anxiety for employees working in service-focused enterprises. However, as automation has become widespread and a key part of many employee workflows, there are strong signs that views are changing. During the pandemic, employees have experienced first-hand how automation can make them happier and more productive - and they want more.

It’s become clear that the point of automation isn’t full time equivalent (FTE) reduction, but capacity liberation. Automation only succeeds when it has employee support and makes employees more valuable and indispensable to the business. The benefit of a solution like Communications Mining is that it frees employees to focus on the work they like and the work that matters. It’s less manual, repetitive data processing and more customer care, innovation, collaboration and strategy.

This change is reflected in the shifting priorities of intelligent automation leaders. Delegates weren’t only talking about cost reduction - they were just as enthusiastic about improving the value and working experiences of their people. Process simplification was flagged as a major intelligent automation goal - with more simplified, satisfying experiences for customers and employees alike.

See how Communications Mining improves the outcomes and experiences of both internal and external customers.

Hybrid development is a stepping stone to decentralised development

Transformation leaders don’t want intelligent automation to happen to their people - they want their people to be its participants, drivers and collaborators.

There’s a widespread recognition that the old automation development model is stuck. The low-hanging fruits and opportunities are gone. The priority isn’t RPA, but much broader process automation. Yet the technical skills required by traditional development tools remain in short supply. Scaling automation throughout the enterprise, therefore, means empowering everyone, not just development teams.

No-code and low-code development tools are making this possible. This will be a big year for the citizen developer, as enterprises equip employees at all levels with the zero-code tools they need to build their own automated workstations. As SEG Automotive’s Vladmiro Ferreira pointed out, even employees with limited technical skill can play an invaluable role as ‘citizen designers’ - identifying problems and outlining the requirements of the automation solution.

The destination is clear, but the best deployment method is up for debate. Most intelligent automation leaders plan on moving towards a decentralised development model driven by citizen developers. Yet there have been teething issues. Without centralised control and with everyone making their own automations, process complexity and support costs can grow out of control.

That’s why many are finding success through a hybrid development culture. This is characterised by numerous local centres of excellence (CoE) for automation being overseen by a head CoE. The local CoEs have the autonomy to go out and drive automations in their department, but the head CoE has final project approval. It’s the head that coordinates with the support function, ensuring local automations are scalable and supportable before they are rolled out.

Decentralised development is regarded by many as the next level of process automation, but hybrid development is proving an invaluable stepping stone on that journey.

See our biggest intelligent automation predictions for 2022.

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