Getting hyperautomation done

Getting hyperautomation done ...

In the last two years, a slew of changes have entered the limelight as the epidemic swept across businesses. However, in the long-distance era, hyperautomation, after making the first appearance in the pre-pandemic era as the major 2020 strategic trend by Gartner Research, remains a hot topic in 2022.

For a good reason, it is so.

Hyperautomation is not just about technology, but rather about combining them in order to achieve its strategic objectives as defined by the organization. Moreover, Gartner has redefined hyperautomation as a business-driven, disciplined approach that can quickly identify, vet, and automate as many business and IT tasks as possible. Moreover, hyperautomation is influenced by the use of multiple technologies, tools, or platforms to achieve their objectives.

That''s where it differs from other technological developments. Unlike specific technologies, such as robotic process automation (RPA), the objectives for hyperautomation can vary greatly from enterprise to enterprise. The way in which an enterprise tries to implement hyperautomation can vary greatly from one another.

Making it work

Since hyperautomation is a more widespread business, it presents its own challenges. Most of these challenges include establishing clarity on multiple fronts:

  • Explicit identification and delineation of strategic goals
  • Identification of use cases and their priorities
  • Assessment of roles of various technologies
  • Establishing a roadmap and an implementation methodology

These challenges are intertwined. A clear understanding of the end goal helps.

Let''s look at the example of a financial institution that intends to transform its account opening across products and services.

The process''s motivation and purpose may vary depending on the key factors. Depending on the chosen objectives, the vision for the transformed process may be based on any of the following or a combination thereof:

  • Increase the number of account opening applications by x%
  • Reduce abandonments throughout the process by y%
  • Improve the prospect and employee experience measurably
  • Reduce the cycle time by m%
  • Reduce the cost per closure by n%
  • Launch a 100% touch-free/human-less account opening experience in p months

The following are critical to establish a roadmap, which includes identifying and purchasing various technologies with good grounds 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 leveraging the stack for many different processes and applications across the globe with speed.

In this case, this brings us to various technologies that combine to make hyperautomation powerful. It is critical to define how they come together to allow for digital account opening. Here is one effective way to get them together:

  • Prospects apply for any account, for any product or service, from a device of their preference, with help from an AI-supported 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, et al., and triggers the relevant process
  • Intelligent image and document processing captures all the information based on uploaded documents and kicks off a fully automated digital customer identification program (CIP) to establish id authentication/verification, security credentials, financial status and creditability
  • Intelligent process automation enables the end-to-end process in real-time with straight-through processing (and flexibility to intervene or route it for exceptions, if any). It also triggers RPA bots for automated real-time execution of routine (traditionally manual) steps across the process
  • At various points in the process, AI/ML-driven rules-engine and RPA automate approvals and other key decisions, including routing, that are traditionally taken by knowledge workers. This frees up their time for other value-add tasks that require human judgment, such as complex credit analysis for high-value deals
  • All the relevant documents (or media) are auto-processed with content analytics and are embedded in the context of the process, with authenticated access across the cycle enabling contextual engagement with customers
  • Throughout the process, prospects are kept engaged across channels of their preferences through omnichannel customer communication
  • Upon final approval, the welcome kit is generated in an automated manner and delivered to the prospect digitally, while backend integration takes care of account set-up and funding, whenever applicable
  • At appropriate times (at the application stage for existing customers or at closure for new prospects), AI/ML algorithm presents the cross-sell options relevant to the prospects preferences and profile and triggers the respective automated process if the prospect takes up the offer

Realizing hyperautomation at the enterprise level

Through the above example, it is simple to see how hyperautomation can make a real difference by leveraging a variety of technologies. However, this is only one example. Enterprises are filled with tens of thousands of applications and processes, from small supporting applications to large and profound mission-critical operations.

Because of this, Gartner believes on the approach bit. It''s not only about doing it once, but also, over and over again, for various applications and applications, with patience.

On the back of a digital transformation platform, here are some ideas.

  • A set of key technologies form the fulcrum of hyperautomation strategy. This includes low code process automation (combining what is traditionally referred to as business process management or BPM with rapid development through low code capability), RPA, business rules management, case management and decision management
  • Another key ingredient in hyperautomation is contextual content services that enable the end-to-end lifecycle management of all forms of content (documents and media across formats) to supply context to transactions and processes
  • All applications and processes involve collaboration and communication in some form, requiring omnichannel customer engagement capability
  • These technologies are further augmented by AI, machine learning (ML) and content analytics to boost speed and intelligence
  • Hyperautomation is only impactful at the enterprise scale with end-to-end automation that is holistic in nature and can be achieved with speed and repeatability. For example, after the account opening is digitalized, are you able to extend it to lending line of business and let your existing customers experience a similar digital interface for their loan needs?

It''s possible to do all this by employing an architectural stack or applying technologies such as RPA to existing processes, but it''s time- and risk-consuming, noting all the opportunity costs associated with any delays. A lot of times, it may not even provide the desired results to only implement AI or RPA with incremental improvement over existing processes because the broader flaws persist.

A platform approach does not only provide a start, but reduces technical debt''s long-term consequences. A digital transformation platform with low code capability helps realize the real potential of hyperautomation with speed and across sectors of business enterprise-wide, as promised.

Newgen Software''s Anurag Shah is the head of business development for the Americas.

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