Hyperautomation Use Cases

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FountainBlue’s October 14 VIP Roundtable was on the topic of ‘Hyperautomation Use Cases’ with opening remarks by IBM. We were fortunate to have such an eclectic, experienced and diverse group of executives for this month’s VIP Roundtable. 

The conversation began with mention of the Gartner definition for hyperautomation, a top business trend over the past few years:

Hyperautomation is a business-drivendisciplined approach that organizations use to rapidly identify, vet and automate as many business and IT processes as possible. Hyperautomation involves the orchestrated use of multiple technologies, tools or platforms, including:

  • Artificial intelligence (AI)
  • Machine learning
  • Event-driven software architecture
  • Robotic process automation (RPA)
  • Business process management (BPM) and intelligent business process management suites (iBPMS)
  • Integration platform as a service (iPaaS)
  • Low-code/no-code tools
  • Packaged software
  • Other types of decision, process and task automation tools

Our executives point out key aspects of the hyperautomation definition –

  • It’s an initiative that’s driven by the business, but it leverages technology and counts on execution by people.
  • It’s a disciplined, methodical approach which leverages a wide range of data, in collaboration with large swaths of people, while focused on generating rapid results.
  • It rapidly integrates strategy, planning and execution, and agilely moves from one problem to the next, while serving the organization and its people as a whole.
  • It leverages a wide host of technologies and solutions and relies on ongoing collaboration, communication and leadership.

The adoption of hyperautomation use cases is a key differentiator for leaders and organizations, and will continue to evolve for greater impact because businesses are inundated by data and need to quickly collect, filter, process, manage, communicate, store, distribute, that data to better strategically plan and run operations, processes, and the organization overall.

Below are best practices for adopting hyperautomation use cases for your organization:

  • Think BIG – broadly and widely about how to design and implement hyperautomation use cases for workflows which are complicated, involve a lot of people, works with a wide range of data, and must be done efficiently.  
  • Hyperautomation is not just for specific use cases, people, organization, offering, etc., It is for all aspects of a business which 1) works with a lot of data, 2) relies on workflow and processes which touch a number of groups and people, 3) can be more efficient/resilient/sustainable and productive if automated, 4) can help better serve internal and external customers, and 5) is the inevitable wave of the future.
  • Consider creating a center of excellence (COE) to collect and manage a repository of (reusable/adaptable) individual hyperautomation use cases as well as an Advisory board on the adoption of hyperautomation use cases.
  • Think not just about the tools and solutions which can be used for any individual solution, but also about the unique combination necessary to solve the current (and anticipated) challenges.
  • Measure and report on the impact of each adopted hyperautomation use case.
  • Keep evolving hyperautomation use case solutions so they continue to be relevant and useful for internal and external clients and their evolving needs.
  • Consider using internal customers as ‘Customer Zero’, designing hyperautomation use cases which address internal needs makes your organization more effective while also potentially piloting a solution which might be useful for other organizations.

Our executives also mentioned the double-edged sword brought on by the huge volumes of data brought in from on-site sensors for everything from temperature to usage, or pressure to light, etc., 

We did not go into detail on this data, for next month’s topic is on the data collection and management itself, but the point is that hyperautomation use cases 1) are reliant on this on-site data, 2) must quickly filter in relevant data, providing automated responses where appropriate, 3) provide a dashboard of recommended actions with detailed charts, graphs and data, 4) connect the right internal and external people to facilitate joint problem-solving and decision-making, 5) track and report on historic, current choices made and consequences, and even 6) make recommendations based on historical and current and projected future data.

Below are some interesting and exciting new offerings in this space:

  • Digital Blueprinting so you can more efficiently generate user cases and acceptance test criteria 
  • Designing Modules of solutions rather than full customizations 
  • Hyperautomation use cases for robots and cobots (collaborative robot – a robot intended for direct human robot interaction within a shared space, or where humans and robots are in close proximity)
  • Leveraging Citizen Development Frameworks to manage local (especially edge case) hyperautomation use case implementations using no-code and low-code tools.
  • Adopting Value Stream Mapping and other LEAN strategies to optimize value and minimize risk

The bottom line is that again leadership and innovation will win the day as successful organizations increasingly adopt hyperautomation use cases, but only if there is collaboration and communication to support it.


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