Automation isn’t new. From the Mayans automating water transportation down their aqueducts to Henry Ford’s assembly line, we have long made use of it to replace manual labour.
The 21st Century’s digital revolution and artificial intelligence (AI) simply ushered in the next phase of automation. But be in no doubt: as with the Industrial Revolution, those failing to adapt are falling into obscurity while start-ups embracing new technology become billion-dollar unicorns.
Already in 2020 IBM research revealed that executives were investing on average 59 percent of their IT budget on automation technologies, including AI, cloud computing, connected IoT, and robotics. In the most recent IBM report, The evolution of process automation, almost every organization – 91% of over 3,000 surveyed – is currently engaged in some level of intelligent business process automation, with nearly four out of ten employing AI-based capabilities.
Most organizations have therefore started their automation journey. If you haven’t, the good news is there is still time to get going. So, where do you start, and how do you scale it across your organization?
Analysing work activities is the best way to assess your potential for automation. Using the American Productivity and Quality Center (APQC) list of over 1,000 cross-industry activities, IBM examined the average effort needed for each activity to identify the most “automatable” enterprise activities.
It found that the most automatable business process categories are the most transactional, such as tasks that support managing financial resources, managing customer services and delivering physical products. The least automatable process categories tend to involve vision, setting strategy and managing external relationships.
The Gift of Time
Mike Gilfix, VP of IBM Automation and Chief Product Officer, likes to say that “automation is the gift of time”. It frees up people and processes. As increasingly complicated tasks are performed by process automation, humans are free to engage in higher-value tasks. Another survey found that more than 90% of C-level executives using intelligent automation say their organization performs above average in managing organizational change in response to emerging business trends. The value of automation primarily comes from the efficiencies it creates.
Ok, that all sounds fine in theory, but what does it look like in practice? One Fortune 75 global consumer goods organization used advanced automation to resolve workflow problems (known as “trouble tickets”) upward of 30 percent more quickly and improve employee productivity by upward of 50 percent. In another example, a European electricity supplier saw estimated savings of €6 million after only the first 8 of 50 planned bots – mostly customer service chatbots – went operational. They now anticipate double-digit percentage cost savings after the full roll-out.
How to start with process automation
So, how do you get started? The evolution of process automation report identified the following three steps:
But, this comes with a caveat. Process automation is not – yet, at least – a drag-and-drop activity. Once you have identified which process areas are best suited for automation, the most crucial step is to reimagine the process from end to end. Too often, as processes became digitized, each new component is just bolted onto or sliced into the existing inefficient processes. Dropping bots into a poorly designed process undermines the ability to create value.
Learn how to avoid pitfalls of Process Automation
To avoid such potential pitfalls and discuss the ways to improve your automation journey, CorporateLeaders and IBM are hosting an intimate and interactive peer-to-peer virtual roundtable on Thursday 27th May. This is an exclusive opportunity for up to 15 Finance, Operations, Digital, Automation and Transformation Leaders to hear from our keynote speakers Stijn Lenjou, Head of European Funds Unit, Federal Public Service Home Affairs of Belgium, (FOD Binnenlandse Zaken/ SPF Intérieur) and IBM experts. Where we will discuss:
The technologies underpinning the evolution of data automation into complex enterprise operations are readily available – but the path to take isn’t always clear.