Jumpstarting your hyperautomation journey

“Hyperautomation” may sound like a buzzword, but it describes a very real—and very relevant—push towards more comprehensive and capable forms of automation in business.

Specifically, hyperautomation refers to the use of advanced technologies like artificial intelligence (AI), machine learning (ML), robotic process automation (RPA), and other intelligent automation tools to automate and optimize a wide range of business processes. Unlike traditional automation, which focuses on individual tasks, hyperautomation aims to streamline entire end-to-end workflows. 

It has been said again and again that modern organizations need to automate wherever possible, but why? Because automation allows organizations to accomplish more in less time. And if automation has the power to effect some positive changes within business processes, hyperautomation is completely transformative across entire organizations. This allows for impressive benefits. By harnessing the power of AI, ML, and RPA, hyperautomation allows companies of all sizes to enjoy:

• Improved productivity and accuracy 
  Hyperautomation empowers businesses by streamlining and optimizing tasks both mundane and strategic, eliminating time-consuming activities and freeing up valuable resources to be applied to other essential work.

• Enhanced collaboration 
  As hyperautomation handles processes across different departments, it promotes seamless collaboration. Information and data are readily accessible, enabling teams to work together more efficiently and make well-informed decisions.

• Advanced data analytics and accessibility 
  Hyperautomation generates vast amounts of data in real-time, providing valuable insights into process performance, which can then be cataloged and stored for easy review. This data-driven approach empowers businesses to identify bottlenecks, discover opportunities for improvement, and make data-backed decisions.

• Increased employee engagement 
  With advanced automation capabilities providing support, employees can accomplish more and perform at higher levels than was ever possible—boosting job satisfaction, increasing engagement, and creating a more motivated workforce in the process.

• Automation at scale 
  Once they're deployed and fully integrated, hyperautomation solutions are capable of handling massive amounts of data and tasks. Implemented across various teams, departments, and functions, hyperautomation facilitates effortless scalability without any significant increases in expenses.

• Optimized agility 
  In a rapidly changing business landscape, hyperautomation enables organizations to adapt quickly to changing markets, customer trends, and emergent events. By automating processes and leveraging AI-driven insights, businesses can pivot when it matters most, ensuring continuity and resilience in an unstable world.

• Near-limitless use cases 
  Hyperautomation is not limited to specific industries or processes. It offers a vast array of use cases, ranging from automating customer support, finance, and HR functions to optimizing supply chain management and even predicting maintenance needs in manufacturing. If a human can do it, there is a chance that hyperautomation can do it faster and more accurately—or at least support the human employee in achieving better results.

As previously stated, hyperautomation is not a single tool; it is an amalgamation of various cutting-edge automation solutions that operate in harmony to streamline business processes and enhance decision-making. This requires a broad technological base to automate workflows, integrate tasks, and create a cohesive hyperautomated unit. 

What kind of technologies are we talking about? Essential automation technologies, such as:

AI
Artificial intelligence forms the cornerstone of hyperautomation. AI empowers machines to learn from vast datasets, enabling them to make informed decisions, recognize patterns, and even perform the kinds of cognitive tasks that until only recently were entirely dependent on humans. AI enhances the decision-making process and adds essential intelligence to the automation framework.

RPA

Robotic process automation involves the use of software bots to automate repetitive, rule-based tasks across various systems and applications. These bots interact with user interfaces, performing tasks just as a human would. RPA significantly improves process speed, efficiency, and accuracy.

ML
Machine learning algorithms enable systems to learn from data and experiences without overly explicit programming. In hyperautomation, ML helps optimize business processes, forecast outcomes, and continuously improve automation models based on changing conditions.

iBPMS
Combining traditional process management with AI, ML, and other intelligent technologies, intelligent business process management suites (iBPMS) play a significant role in hyperautomation. The goal is to deliver complete end-to-end visibility into critical processes, offer optimization recommendations, and enable dynamic adjustments based on real-time data and insights.

Process mining
Process mining involves the analysis of event logs and data from existing systems to create visual representations of actual business processes. This technology helps identify inefficiencies, bottlenecks, and deviations, aiding in the design and implementation of more efficient automated workflows. 

APIs
Application programming interfaces (APIs) facilitate the seamless integration and communication between different software applications. In the context of hyperautomation, APIs play a vital role in connecting multiple systems, enabling data exchange, and orchestrating complex processes.

NLP
Natural language processing (NLP) allows machines to understand, interpret, and respond to human language in a contextually meaningful way. In hyperautomation, NLP enables chatbots, virtual assistants, and sentiment analysis, leading to enhanced customer experiences and efficient handling of unstructured data.

Intelligent document processing
This technology involves the use of AI and machine learning to extract and process data from unstructured documents—invoices, receipts, contracts, etc. Intelligent document processing helps automate document-centric workflows, reducing manual data entry efforts and errors and allowing organizations to make better use of their paper documentation.

By combining these key hyperautomation technologies, organizations can elevate their automation initiatives to new levels of efficiency and effectiveness. The synergy created by integrating multiple technologies allows formerly isolated, semi-automated, or unautomated tasks to become fully integrated and seamlessly automated, transforming businesses into agile and hyperautomated entities

Thanks to its comprehensive approach to automating processes organization-wide, hyperautomation requires careful planning and execution at every stage. Unlike the automated processes themselves, the journey towards hyperautomation is not something that can be turned loose and left to perform under its own power.

Integrating hyperautomation within an organization involves three critical phases: the pre-implementation stage, the mid-implementation stage, and the post-implementation stage. Each stage plays a crucial role in ensuring the success and effectiveness of the hyperautomation initiative, and that means that every stage must be closely monitored for any potential obstacles.

Stage 1: Pre-implementation

They say that a journey of a thousand miles begins with a single step. The hyperautomation journey, on the other hand, begins with several steps, all of which are critical to ensuring that the organization is in the best position to benefit from automation throughout its essential processes. Unfortunately, these pre-implementation steps are not only critical, but they can also represent some of the greatest challenges in the entire journey:

• Assessment and strategic development 
  Before hyperautomation is possible, organizations must conduct a comprehensive assessment of their existing processes, systems, and pain points. Identifying areas where automation can bring significant value is crucial. This involves working with stakeholders from different departments to gain insights into their challenges and requirements. 
   
  Based on this assessment, the beginnings of a hyperautomation strategy can be developed, outlining the objectives, scope, and expected outcomes of the initiative. This strategy will likely need to be reconsidered and revised at multiple points during the pre-implementation stage but will eventually serve as a guiding document throughout the hyperautomation journey. 
   

• Business case 
  With a clearer understanding of where hyperautomation can benefit the organization and what it will take to get there, the next step is to create a compelling business case. This will need to answer several relevant questions about the need for hyperautomation and present the argument in a way that is compelling and informed.  
   
  This business case needs to discuss the problems facing the business and identify the opportunities presented by hyperautomation. It should then evaluate possible alternatives and finally make a recommendation regarding how and where hyperautomation should be implemented within the organization, and the metrics by which the success of the hyperautomation initiative will be evaluated. 
   

• Stakeholder buy-in 
  Without support from the right people in the organization, the hyperautomation journey will be over before it begins. Work directly with individual stakeholders as you present your business case. Help them understand how hyperautomation can improve efficiency and productivity in their teams and departments. Perform research and present data that details what kinds of returns they can expect. 
   
  Remember that these stakeholders want what’s best for the business, but their perspective may be focused elsewhere; demonstrate the value of hyperautomation by identifying the advantages in both the short term and long term.   
   

• Technology selection 
  Hyperautomation is not confined to a single tool, but it relies heavily on having the right platforms and tools on hand. As such, the last step in the pre-implementation stage is to choose a technology partner capable of helping the organization meet its hyperautomation needs in terms of resources and support. 
   
  For best results, work with a partner and platform that has already demonstrated a deep understanding of the industry and is backed by a track record of success. This will help ensure that, should any unexpected issues occur, the partner has the experience to help guide the organization forward. 

Stage 2: Mid-implementation

With the right foundation in place, the hyperautomation journey is finally ready to pick up some speed. At this point implementation efforts are in full swing, and the focus should shift from preparation to application—executing on the previously-established hyperautomation journey and optimizing processes for greater returns:

• Integration 
  Hyperautomation is most effective when it synchronizes with existing systems rather than supplants them. Overhauling and replacing infrastructure is expensive, time consuming, and introduces more complications to an already complex process. Integration is a critical aspect of mid-implementation. Organizations need to ensure that the automated processes are seamlessly integrated with existing systems and applications to enable end-to-end automation. 
   

• Training and change management 
  As automation takes root in the organization, employees need to be trained to work alongside the automated systems effectively. Change management is an integral part of the mid-implementation stage, as it addresses any concerns or resistance to automation and fosters a positive automation culture. 
   
  Employee training must focus on upskilling the workforce to manage and collaborate with automated processes, empowering them to take on more strategic and creative roles. 
   

• Monitoring, fine tuning, and security 
  Continuous monitoring of automated processes is essential to identify any issues or inefficiencies. Organizations deploy monitoring tools and analytics to track process performance and identify potential bottlenecks or deviations. 
   
  Fine-tuning the automation models and algorithms based on real-world data and feedback is necessary for continuous improvement and optimal performance in a hyperautomated organization. Additionally, comply with data-protection regulations and secure the various technologies and processes against possible cyberthreats, so the new automation solution does not place the company or its customers at risk. 

Stage 3: Post-implementation

The post-implementation stage marks the completion of the initial hyperautomation deployment. However, the journey doesn't end here; it transitions into a continuous improvement and expansion phase that will remain in effect for as long as the automated processes permeate the organization:

• Risk evaluation 
  After the initial implementation, it is essential to conduct a thorough risk evaluation to identify any potential challenges or vulnerabilities that may arise during the ongoing operation of the hyperautomated processes. This evaluation involves assessing security risks, compliance considerations, and potential impacts on business continuity. 
   
  Addressing these risks proactively ensures that the automated processes remain robust, secure, and resilient to unforeseen circumstances. 
   

• Recovery planning 
  As the risk evaluation will attest, there are dangers involved in placing so many processes in the hands of automated systems. Having a comprehensive recovery plan in place will prevent lost revenue in the event of any unexpected failures or disruptions. This plan must outline the steps to be taken in case of system failures, data breaches, or other unforeseen incidents. 
   
  A well-defined recovery plan helps minimize downtime, reduces the impact of outages, and enables the organization to swiftly resolve the problem at hand so that they may resume normal operations. Make sure that all employees understand their responsibilities in following the plan. 
   

• Scaling and expansion 
  Having successfully implemented hyperautomation in specific processes, the organization can now consider scaling and expanding automation efforts to even more areas within the company. This involves identifying new processes that can benefit from automation and extending the use of existing technologies to streamline additional workflows. 
   
  Scaling and expanding hyperautomation across various departments amplify its positive impact and contribute to a more efficient and agile organization. It also allows the automation leaders to apply earlier learnings for a more effective rollout. 
   

• Ongoing innovation 
  Hyperautomation is not a one-time project; it is an ongoing journey of innovation. Organizations must foster a culture of continuous improvement, regularly assessing the performance of automated processes and seeking opportunities for enhancement. Staying abreast of the latest developments in automation technologies and exploring emerging trends allows businesses to capitalize on new capabilities and maintain a competitive edge. 
   
  Throughout the post-implementation stage, organizations should maintain a close collaboration between the automation team and business stakeholders. Regular reviews and feedback loops ensure that automation efforts align with evolving business needs and strategic needs. 
  

Thanks to its comprehensive approach to automating processes organization-wide, hyperautomation requires careful planning and execution at every stage. Unlike the automated processes themselves, the journey towards hyperautomation is not something that can be turned loose and left to perform under its own power.

Integrating hyperautomation within an organization involves three critical phases: the pre-implementation stage, the mid-implementation stage, and the post-implementation stage. Each stage plays a crucial role in ensuring the success and effectiveness of the hyperautomation initiative, and that means that every stage must be closely monitored for any potential obstacles.

Stage 1: Pre-implementation

They say that a journey of a thousand miles begins with a single step. The hyperautomation journey, on the other hand, begins with several steps, all of which are critical to ensuring that the organization is in the best position to benefit from automation throughout its essential processes. Unfortunately, these pre-implementation steps are not only critical, but they can also represent some of the greatest challenges in the entire journey:

• Assessment and strategic development 
  Before hyperautomation is possible, organizations must conduct a comprehensive assessment of their existing processes, systems, and pain points. Identifying areas where automation can bring significant value is crucial. This involves working with stakeholders from different departments to gain insights into their challenges and requirements. 
   
  Based on this assessment, the beginnings of a hyperautomation strategy can be developed, outlining the objectives, scope, and expected outcomes of the initiative. This strategy will likely need to be reconsidered and revised at multiple points during the pre-implementation stage but will eventually serve as a guiding document throughout the hyperautomation journey. 
   

• Business case 
  With a clearer understanding of where hyperautomation can benefit the organization and what it will take to get there, the next step is to create a compelling business case. This will need to answer several relevant questions about the need for hyperautomation and present the argument in a way that is compelling and informed.  
   
  This business case needs to discuss the problems facing the business and identify the opportunities presented by hyperautomation. It should then evaluate possible alternatives and finally make a recommendation regarding how and where hyperautomation should be implemented within the organization, and the metrics by which the success of the hyperautomation initiative will be evaluated. 
   

• Stakeholder buy-in 
  Without support from the right people in the organization, the hyperautomation journey will be over before it begins. Work directly with individual stakeholders as you present your business case. Help them understand how hyperautomation can improve efficiency and productivity in their teams and departments. Perform research and present data that details what kinds of returns they can expect. 
   
  Remember that these stakeholders want what’s best for the business, but their perspective may be focused elsewhere; demonstrate the value of hyperautomation by identifying the advantages in both the short term and long term.   
   

• Technology selection 
  Hyperautomation is not confined to a single tool, but it relies heavily on having the right platforms and tools on hand. As such, the last step in the pre-implementation stage is to choose a technology partner capable of helping the organization meet its hyperautomation needs in terms of resources and support. 
   
  For best results, work with a partner and platform that has already demonstrated a deep understanding of the industry and is backed by a track record of success. This will help ensure that, should any unexpected issues occur, the partner has the experience to help guide the organization forward. 

Stage 2: Mid-implementation

With the right foundation in place, the hyperautomation journey is finally ready to pick up some speed. At this point implementation efforts are in full swing, and the focus should shift from preparation to application—executing on the previously-established hyperautomation journey and optimizing processes for greater returns:

• Integration 
  Hyperautomation is most effective when it synchronizes with existing systems rather than supplants them. Overhauling and replacing infrastructure is expensive, time consuming, and introduces more complications to an already complex process. Integration is a critical aspect of mid-implementation. Organizations need to ensure that the automated processes are seamlessly integrated with existing systems and applications to enable end-to-end automation. 
   

• Training and change management 
  As automation takes root in the organization, employees need to be trained to work alongside the automated systems effectively. Change management is an integral part of the mid-implementation stage, as it addresses any concerns or resistance to automation and fosters a positive automation culture. 
   
  Employee training must focus on upskilling the workforce to manage and collaborate with automated processes, empowering them to take on more strategic and creative roles. 
   

• Monitoring, fine tuning, and security 
  Continuous monitoring of automated processes is essential to identify any issues or inefficiencies. Organizations deploy monitoring tools and analytics to track process performance and identify potential bottlenecks or deviations. 
   
  Fine-tuning the automation models and algorithms based on real-world data and feedback is necessary for continuous improvement and optimal performance in a hyperautomated organization. Additionally, comply with data-protection regulations and secure the various technologies and processes against possible cyberthreats, so the new automation solution does not place the company or its customers at risk. 

Stage 3: Post-implementation

The post-implementation stage marks the completion of the initial hyperautomation deployment. However, the journey doesn't end here; it transitions into a continuous improvement and expansion phase that will remain in effect for as long as the automated processes permeate the organization:

• Risk evaluation 
  After the initial implementation, it is essential to conduct a thorough risk evaluation to identify any potential challenges or vulnerabilities that may arise during the ongoing operation of the hyperautomated processes. This evaluation involves assessing security risks, compliance considerations, and potential impacts on business continuity. 
   
  Addressing these risks proactively ensures that the automated processes remain robust, secure, and resilient to unforeseen circumstances. 
   

• Recovery planning 
  As the risk evaluation will attest, there are dangers involved in placing so many processes in the hands of automated systems. Having a comprehensive recovery plan in place will prevent lost revenue in the event of any unexpected failures or disruptions. This plan must outline the steps to be taken in case of system failures, data breaches, or other unforeseen incidents. 
   
  A well-defined recovery plan helps minimize downtime, reduces the impact of outages, and enables the organization to swiftly resolve the problem at hand so that they may resume normal operations. Make sure that all employees understand their responsibilities in following the plan. 
   

• Scaling and expansion 
  Having successfully implemented hyperautomation in specific processes, the organization can now consider scaling and expanding automation efforts to even more areas within the company. This involves identifying new processes that can benefit from automation and extending the use of existing technologies to streamline additional workflows. 
   
  Scaling and expanding hyperautomation across various departments amplify its positive impact and contribute to a more efficient and agile organization. It also allows the automation leaders to apply earlier learnings for a more effective rollout. 
   

• Ongoing innovation 
  Hyperautomation is not a one-time project; it is an ongoing journey of innovation. Organizations must foster a culture of continuous improvement, regularly assessing the performance of automated processes and seeking opportunities for enhancement. Staying abreast of the latest developments in automation technologies and exploring emerging trends allows businesses to capitalize on new capabilities and maintain a competitive edge. 
   
  Throughout the post-implementation stage, organizations should maintain a close collaboration between the automation team and business stakeholders. Regular reviews and feedback loops ensure that automation efforts align with evolving business needs and strategic needs.