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A lot has changed in the last two years. As the pandemic disrupted business operations, a host of trends, including distributed (remote) working, came into the spotlight. However, within the larger digital transformation scheme, hyperautomation, after first appearing in the pre-pandemic era as a top 2020 strategic trend by Gartner Research, continues to be a hot topic in 2022.
And it is so for good reason.
Hyperautomation is not just about technologies, but combines them to achieve the strategic goals defined by the organization. Gartner even redefined hyperautomation as “a disciplined, business-driven approach that organizations use to quickly identify, verify, and automate as many business and IT processes as possible.” Additionally, according to Gartner, hyperautomation involves the orchestrated use of multiple technologies, tools, or platforms to achieve their goals.
This is where it differs from other tech trends. Unlike specific technologies, such as robotic process automation (RPA), for example, the goals of hyperautomation can vary widely from company to company. How one company goes about implementing hyperautomation can also be very different from another.
make it work
Since hyperautomation is a broader approach, it comes with its own set of challenges. And most of these challenges involve establishing clarity on several fronts:
- Explicit identification and delineation of strategic objectives
- Identification of use cases and their priorities
- Assessing the roles of various technologies
- Establish a roadmap and an implementation methodology
These challenges are linked. A clear vision of the end goal helps.
Take the example of a financial institution that intends to transform its account opening into products and services.
Depending on the determining factors or chosen objectives, the vision of the transformed process varies. These goals can be one of the following or a combination of them:
- Increase the number of account opening requests by x%
- Reduce dropouts throughout the process by y%
- Measurably improve the prospect and employee experience
- Reduce cycle time by m%
- Reduce cost per closure by n%
- Launch a 100% contactless/no-one account opening experience in p months
After identifying these goals, it is essential to establish a roadmap, which includes identifying and acquiring various technologies with good justification and defining a long-term architectural stack. After all, account opening in this case is only the starting point, and the real value of hyperautomation lies in quickly leveraging the stack for multiple processes and applications across the enterprise.
This brings us to various technological capabilities that combine to make hyperautomation powerful. It is essential to define how they combine to offer a digital account opening in this case. Here is an efficient way to put them together:
- Prospects apply for any account, for any product or service, from a device of their choice, with the help of an AI-powered chatbot
- A natural language processing (NLP) engine processes all incoming requests to analyze and classify them based on prospect status (new/existing/premium), product/service, category, geography, etc. , and triggers the relevant process
- Intelligent image and document processing captures all information based on uploaded documents and initiates a fully automated digital customer identification (CIP) program to establish authentication/identity verification, security, financial situation and credibility
- Intelligent process automation enables the end-to-end process in real time with straight-through processing (and the flexibility to step in or route it for exceptions, if any). It also triggers RPA bots for real-time automated execution of routine (traditionally manual) steps throughout the process.
- At various stages of the process, the AI/ML and RPA-based rules engine automates approvals and other key decisions, including routing, that are traditionally made by knowledge workers. This frees up their time for other value-added tasks that require human judgment, such as complex credit analysis for high-value transactions.
- All relevant documents (or media) are automatically processed with content analysis and integrated into the context of the process, with authenticated access throughout the lifecycle enabling contextual engagement with customers
- Throughout the process, prospects are kept engaged across all channels of their preferences through omnichannel customer communication
- Upon final approval, the welcome kit is automated generated and digitally delivered to the prospect, while the backend integration takes care of account setup and funding, if required.
- At the appropriate times (at the application stage for existing customers or at close for new prospects), the AI/ML algorithm presents the relevant cross-sell options to the prospects’ preferences and profile and triggers the corresponding automated process if the prospect accepts the offer
Achieve enterprise-scale hyperautomation
Using the example above, it’s easy to see how hyperautomation can have a real impact by leveraging a combination of technologies. However, this is just one example. Enterprises are replete with thousands of applications and processes ranging from small support applications to large and deep critical processes.
This is why Gartner emphasizes the “approach” part. It’s not just about doing it once, but doing it again and again, for various processes and applications, with speed.
This is where a digital transformation platform comes in. Consider the following:
- A set of key technologies forms the backbone of the hyperautomation strategy. This includes low-code process automation (combining what is traditionally called business process management – or BPM – with rapid development through low-code capability), RPA, business rule management, case management and decision management
- Another key ingredient of hyperautomation is contextual content services that enable end-to-end lifecycle management of all forms of content (documents and media in all formats) to provide context to transactions and processes. .
- All applications and processes involve collaboration and communication in one form or another, requiring omnichannel customer engagement capability
- These technologies are further enhanced with AI, machine learning (ML), and content analytics to increase speed and intelligence
- Hyperautomation only impacts enterprise-wide with end-to-end automation that is holistic in nature and can be achieved with speed and repeatability. For example, once account opening is digitized, are you able to extend it to the lending industry and allow your existing customers to benefit from a similar digital interface for their lending needs?
While it’s possible to do all of this by building an architectural stack or adding technologies like RPA to existing processes, it takes a lot of time and risk, not to mention all the opportunity costs associated with delays. Often, even implementing AI or RPA with incremental improvement over existing processes may not even yield the desired results, as larger silos persist.
A platform approach not only provides a boost, but also mitigates the long-term risks of technical debt. Additionally, a digital transformation platform with low code capacity helps realize the true potential of hyperautomation with speed and across all lines of business at enterprise scale, as promised.
Anurag Shah is Head of Products and Solutions for the Americas at Newgen Software.
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