Many businesses and enterprises already use robotic process automation (RPA) to automate highly repetitive tasks, such as form scanning, invoice processing, price comparisons and so on, with one RPA for each task.
Intelligent automation (IA) moves the bar forward through the power of AI and modern IT/cloud features. It allows businesses to automate tasks that require linking multiple processes together and applying increasingly sophisticated machine learning intelligence to automate decision-making.
The technologies that form IA allow a business to automate tasks more broadly and deeply across the company, delivering benefits beyond the usual accuracy, time and cost savings, audit trails and accountability. Delivering the ability to grow as a smarter organization, as demonstrated by these use cases and practical examples.
1. Handling unstructured data
RPA tools are brilliant for tasks involving structured data, account numbers, balances, part codes or addresses. But they’re useless when it comes to unstructured data such as free-form emails, customer reviews, transcripts or non-text formats such as phone-call bookings, photos or video streams.
Intelligent automation can use machine learning to scan these messages or documents, using speech-to-text AI where needed, and use text parsing to understand if something is a priority issue. For example, if someone has a serious complaint, is angry on the phone or if there’s a key supplier problem. Whatever the issue, IA can alert the right person to it, and move on to the next batch of notes, saving a person from scanning each one manually, and having to pass them on to various departments or workers.
Use cases: IF and Zurich
Nordic insurer IF ran a recent webinar on how it selects and ranks processes for automation, develops the right metrics and the challenges they faced.
Global insurer Zurich uses intelligent automation technologies in its Swift Insurance Platform providing coverage for small and medium cargo quickly. The platform relies on automation technologies to help brokers manage policy lifecycles for annual cargo insurance and single shipments.
2. Predictive analytics and maintenance
Predictive analytics is nothing new. Airplane makers to oil rig operators know the mean time between failure (MTBF) rate of every part, while jet engine makers can watch every turbine in flight for emerging maintenance issues. These technologies have filtered down from aviation to general manufacturing and everyday business use.
They combine analytics and intelligent automation with Internet of Things devices and smart production and monitoring platforms to provide advanced warning of outages, product or production failures and can alert maintenance to a problem in advance.
Use cases: GE’s Predix and the IIoT
With giants like GE’s Predix providing analytics for anomaly detection and predictive maintenance, there are a range of services in operation around global businesses, while smaller firms can automate workflows and processes using the industrial Internet of Things (IIoT) and IA can allow smaller factories to outperform larger traditional ones.
3. Process improvement and rationalization
While the first two examples lean toward larger organizations, any business size or type can make the effort to improve and automate their processes. From unpopular in-office tasks to cross-department updates; an AutomationAnywhere poll from earlier in the year showed that:
- Data entry is the world’s most hated computer task.
- Workers waste more than 40% of their day on manual digital administrative processes.
- Over 75% say workers shouldn’t spend time on tasks that can be automated.
From moving data from one application to another, managing customer queries to migrating data to modern cloud systems, there are plenty of ways that any business can embrace intelligent automation.
Use case: A French bank
A French bank opened a new online account, with iRPA helping to handle the many back-end processes to streamline tasks and ensure the quality of applicants, while alerting staff to any issues, all while reducing error rates.
4. Robots in Human Resources
Automation in human resources has always been a prickly subject, with HR professionals proud of the personal touch. But in high growth companies where hundreds of jobs are advertised and receive thousands of applications, intelligent automation can help sort the higher quality candidates. This allows HR to use their skills while leaving intelligent automation to handle the rest:
- Automating the workflow process
- Intelligently filtering applications and alerting workers to issues with a posting (attracting the wrong type of applicant)
- Handling first-level interviews or delivering automated tests and evaluations
- Helping to measure the quality of new hires as they enter the business.
Use cases: Beamery and SAP
Beamery points out, the use of iRPA should be to unlock new value in HR, not just automate existing processes, while SAP identifies how it can be used to remove bias from hiring processes.
5. Bringing traditional businesses up to date
There are many areas of business where tradition holds firm, even in the cloud era. From law to real estate and many others, there are markets using age-old applications and processes, with huge amounts of time wasted.
The new generation of leaders and workers, and market-specific vendors trying to sell them tools to improve their work, are using iRPA to digitize processes and tasks, and add smartness to improve business performance.
Companies that automate in these fields can do more business and move beyond the limitations of how much work one person can do per day, and innovate to add value to their clients and agencies.
Use case: Eversheds Sutherland
A top-50 global legal practice, Eversheds Sutherland, was created to meet the demand from in-house legal teams to: outsource and automate high volume, low risk work.