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Four pillars that distinguish a fully automated company


The main difference between a fully automated business and a traditional enterprise is their approaches to automation. While the former takes a proactive approach to automation, a traditional enterprise takes a reactive one.

A fully automated enterprise thinks ‘automation first’, applies automation where it makes the most sense and can have the greatest impact, finds the right balance between what software robots do and what humans are freed up to focus on.

The reasons for automating are broad. However, UiPath has consolidated them into three data-backed categories: performance, ROI and competitiveness.

Performance: According to a report from Capgemini, the top-performing 20% of companies in their survey about automation are getting “considerably more” business returns than the bottom 20%.

ROI: Fully automated enterprises reap significant ROI. Simply put, the dollars you put into automation create more dollars coming out. SMBC, for instance, one of Japan’s leading financial institutions, has achieved $450 million in ROI from their automation investments.

Fully automated enterprises perform better. While many organizations now recognize the value of individual automation technologies, fully automated enterprises are reaping compounding benefits by combining them. Harvard Business Review found, for instance, that businesses that combine RPA and AI had a 9% average increase in revenue, whereas businesses that didn’t combine them saw only a 3% increase.

Further, IDC found that organizations using RPA provided shorter response times and improved overall process efficiency (79%), made fewer errors, reducing time spent in rework (79%) and Increased work without hiring more headcount (74%).

And what makes a fully automated business work? According to UiPath, there are basically four pillars

Assign automatable work to robots

In a fully automated enterprise, human employees can focus on the work they want to do and never have to do what a robot could do better.

We’re talking about the repetitive tasks that have come to dominate knowledge work: data entry, data consolidation, and data processing. For decades, companies have relegated this kind of work to the back office, tasking humans with the unengaging, error-prone work of moving information from one system to another.

A McKinsey study found that, in the United States alone, about 2.6 trillion hours of work a year is automatable. The 30% of automatable activities that McKinsey cites are then automated, leaving humans to do work they’re suited for—work that’s creative, fulfilling, and valuable. A fully automated enterprise implements robots that can take over existing back-office work.

Provide a robot for every person in the company

In the IDC report “A Robot for Every Worker,” 71% of employees reported feeling optimistic about how automation would affect their daily work. Additionally, 80% of decision makers who adopted automation offered their employees the tools to help them automate their work—likely fueling that optimism.

A fully automated enterprise recognizes the desire employees have for automation and enables them to leverage the capabilities of robot assistants right from their desktops. Employees can then focus on their jobs instead of wrestling with technology.

Contact centers provide the perfect example of this pillar in action. A fully automated enterprise contact center will have a robot that looks up information and manages data entry while an agent talks to customers and focus on relationship-building.

Democratize development
A fully automated enterprise provides low-code tools that enable all workers to quickly bring new application ideas to life from the bottom up. With that, employees become citizen developers who can build their own ideas.

Traditional enterprises tend to underestimate their employees’ potential. A McKinsey study found that successful organizations were more likely to put the responsibility of delivering automation efforts into the hands of their functions or business units. Less successful organizations, however, were “more than twice as likely” to make a central team entirely responsible for automation delivery. In summary, employees want to learn, and companies that give employees automation responsibilities succeed.

Unleash AI across every facet of work
With process mining, AI can discover opportunities for automation that humans might have missed, helping inform a continuous system of observation and ideation.

AI adds cognitive automations that require judgments normal robots can’t provide. Robots use machine learning models or skills in real time to automate increasingly sophisticated processes, expanding the universe of automation. In a fully automated enterprise, data scientists can use real-world data to inform their models and deploy those models more quickly than they could in traditional enterprises.

With four concrete outcomes in mind, it is possible to explore the automation potential of any company, says UiPath.

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