What is hyperautomation?
Hyperautomation is the concept of automating everything in an organization that can be automated. Organizations that adopt hyperautomation aim to streamline processes across their business using artificial intelligence (AI), robotic process automation (RPA), and other technologies to run without human intervention.
Hyperautomation is an emerging approach to automation, but Gartner (link resides outside IBM) has already identified it as one of the top 10 strategic technology trends. They conducted a recent survey which showed that 85% of participants will “either increase or sustain their organization’s hyperautomation investments over the next 12 months, and over 56% already have four or more concurrent hyperautomation initiatives. According to Gartner (link resides outside IBM), “Hyperautomation is rapidly shifting from an option to a condition of survival”, ranking "outdated work processes as the No. 1 workforce issue”.
It is also important to note that the role that the pandemic has played in the adoption and acceleration of hyperautomation within the market, fueling the prioritization of digital transformation and automation initiatives over the last year. With the business ecosystem operating in a distributed manner, hyperautomation eases the burden that repetitive processes and legacy infrastructure incur on an organization and its resources. The transformation that hyperautomation affords an organization enables it to operate in a more streamlined manner, often resulting in reduced costs and a stronger competitive position.
Legacy infrastructure and processes can slow an organization down and affect their ability to be competitive. Simple, task-based automation does not deliver the cross-functional results that will drive business decision making and results. Hyperautomation transforms an organization by automating as many processes and tasks as possible.
Automation vs. hyperautomation
The difference between automation and hyperautomation is often unclear. Automation refers to the achievement of a repetitive task without manual intervention. It typically occurs on a smaller scale, creating solutions designed to address individual tasks. In contrast, hyperautomation refers to the use of multiple automation tools that enable intelligent automation, including machine learning and robotic process automation to scale automation initiatives.
Getting started with hyperautomation
Several steps and components can help organizations navigate their hyperautomation journey. These steps are as follows:
1. Gather insights on the processes, workflows, and environment. Use process mining to research how existing processes operate, where gaps, latency and bottlenecks exist, and identify opportunities for digital process automation. To generate a clear view of existing processes, some organizations will create a duplicate model of a process, also known as a digital twin. A digital twin uses technology to duplicate an ecosystem to better visualize processes, inputs, and outcomes, identify areas for improvement, and create efficiencies.
2. Identify the structured and unstructured data and other inputs that will be needed to accomplish the processes.
3. Predict outcomes in terms of efficiencies and return on investment (ROI).
4. Determine the automation platform and automation technologies that best serve your needs, possibly leveraging tools and algorithms that already exist. This may include using RPA, optical character recognition (OCR), AI, and machine learning with other strategic technology tools to design purpose-built bots that will perform the automated tasks.
5. Automate complex business and technology processes and tasks, often even automating the automated to gain greater efficiencies or further cost reductions.
6. Use AI tools to achieve the identified tasks, including technologies such as cognitive learning, OCR, and natural language processing (NLP). Low-code or no-code technologies, which use a graphical user interface for configuration, are incorporated to simplify the automation process, requiring less technical expertise and faster deployment.
Benefits and challenges of hyperautomation
Hyperautomation transforms businesses by streamlining business processes by eliminating repetitive tasks and automating manual ones. This has a number of key benefits. It allows organizations to complete tasks with consistency, accuracy, and speed. This, in turn, reduces costs, and generally improves the customer experience.
Any new approach to business processes or infrastructure is bound to present challenges, and hyperautomation is no exception. Many companies do not feel ready to tackle automation efforts due to raw or poor-quality data and lack of resources with technical skills to address it. Retraining programs are available which can help organizations address these needs and develop an approach that is well-suited to accomplish their goals.
Other challenges include choosing from the ever-growing and evolving marketplace of products. The decision regarding which products organizations should make available to their clients can be daunting. Given this flooded marketplace, the market expects a series of mergers and acquisitions to narrow redundancies across product offerings, helping clients evaluate potential vendors more effectively.
Hyperautomation use cases
Hyperautomation in healthcare
The healthcare industry can benefit from hyperautomation, providing a better patient experience, stronger bottom line, and more accurate data. Hyperautomation is used to automate billing cycles, customer communication and collection. It can also address patient record management, collecting and collating data, and providing useful output for more accurate treatment plans.
Hyperautomation is also often used to ensure compliance with regulations, which is critical to the viability and success of any healthcare organization. It can also be used to manage drug inventory and procurement, and schedule staff and other resources. The uses for hyperautomation in the healthcare industry are endless, and the benefits can provide improvements for the organization, partners, and patients. Read our healthcare case study here.
The pandemic has greatly affected the ability to receive materials in a timely fashion, and low staffing levels have resulted in process delay, creating logistical challenge at best.
Using RPA, inventory stock checks can occur 24x7, ensuring that a current view of inventory levels and product availability is accessible at all times. In addition to inventory checks, RPA can be used for procurement, pricing, billing, quote request, follow-up and data input, and system maintenance and repair. Removing the dependency on manual intervention for repetitive processes, hyperautomation can increase speed, efficiency and accuracy. Read our supply chain case study with Inter Aduaneira here.
Banking and finance
Banking and finance industries are under constant pressure to reduce costs, improve efficiencies, and provide a more available and more personal customer experience.
Hyperautomation can provide staff members with higher data quality so they can more effectively use business process management (BPM) to provide customers with information that enables them to make more informed decisions. Hyperautomation also provides the back-end efficiencies that support 24x7 availability of online banking and finance applications, and the regulations and reporting that it requires. Both banking and finance industries involve large volumes of data, which can be cumbersome to manage. Hyperautomation streamlines the tasks involved, making the processes quicker, more consistent, and less prone to error. Some more specific examples from Gartner (link resides outside IBM) include:
- Airbus SE used AI-based hyperautomation to read expense receipts and match them against accepted vendors and expenses to spot anomalies and learn over time. This decreased the average time between submission and approval of an expense report from a couple weeks to a few days, and reduced reviewers’ workloads by more than half.
- Equinix, Inc. uses computer vision technology to automate accounts payable processes. The team uses AI-based optical character recognition technology to extract data from PDF-based vendor invoices, leaving the team to handle only exceptions and data extractions with low statistical confidence. This frees up over 14,000 hours per year for the finance team, increasing its focus on higher-value tasks.
Both the banking and finance industries are also subject to many regulations and compliance requirements. Hyperautomation has transformed many of their core processes, which enables them to meet these requirements with greater efficiency and at a lower cost. Read our banking case study with Banco Galicia here.
The retail industry is ripe with opportunities for automation. E-commerce has a stronghold on order processing with more people than ever ordering online and utilizing loyalty programs. AI-assisted hyperautomation can streamline front-end processes such as targeted marketing through ad placement in social media and targeted email marketing, loyalty recognition online, facial recognition when a customer enters a store, and more.
Hyperautomation can reduce costs and improve the efficiency and accuracy of back-end retail processes affecting procurement, billing, supplier management, inventory, and transportation.
In addition, hyperautomation has been used to track and analyze criteria in the marketplace such as competitive pricing and customer feedback, enabling faster, more accurate decision-making which drives revenue and profitability.
Hyperautomation and IBM
Start your hyperautomation journey with IBM Cloud Pak® for Business Automation. It is a set of integrated market-leading software designed to help you solve your toughest operational challenges. With actionable AI-generated recommendations, built-in analytics to measure impact, and business-friendly low-code tooling, IBM Cloud Pak for Business Automation is helping clients reduce the amount of time spent on manual processes by 80%, decrease customer wait times by half, comply with regulations to reduce risk, and save thousands of work hours that were then reallocated to higher-value work.
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