Next Level Automation

As the industry embarks on its continuous automation journey, we find many methods to choose from when it comes to getting started. These include starting slow and methodical, while others attempt the big bang approach and many variations in between. Some of the main concerns we face when starting this journey is how to learn as we go and pivot quickly when it comes to the many headwinds. Some of the obstacles to overcome are as follows: 

  • Securing Senior Level support and preliminary investment 
  • Determining when your first success will be realized and how to measure its inherent value
  • Creating a scalable set of solutions to drive acceleration 
  • Tool selection and where do we find the resources to ensure success 

End-to-end automation - is a methodology that enables the delivery of automation solutions across an entire process/value chain, which may involve using multiple tools. 

The chart below depicts the journey and although it is proven successful for some to start with task based, the key is to focus on getting to the end to end as quickly as possible. You will find most of your business value as you enter that space.

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Let’s first start by understanding the benefits between task-based automation and end to end.

Many organizations start their automation journey with basic tools, such as OCR and RPA, to automate tasks in targeted areas, such as finance operational processes. These initiatives typically deliver value, but the limitations of using one or two tools to automate existing processes soon become apparent. Additional software tools were then added to the toolkit, and process redesign was brought into scope 

The end-to-end automation method of delivering automation allows organizations to achieve more significant benefits across the whole value chain. At the other extreme, task automation seeks to automate discrete tasks – typically fragments of an end-to-end process. The most advanced adopters of intelligent automation have steadily moved from task-based automation towards end-to-end.

End-to-end automation as a remedy for process fragmentation

  • Fragmented processes exist in siloes; a mantra often accompanies this situation: ‘This is just how we do things.’ Reimagination is a radical approach to process improvement that calls for the end-to-end rewiring of processes aligned to the organization’s objectives. It can also help organizations realize more significant benefits through designing automatable workflows across the entire process
  • Using the end- to-end automation approach, they can benefit from simplified business processes, an increased number of processes that could be automated end-to-end and an improved range of potential use cases

Reimagination forces business units to step out of siloes to understand and redefine how processes interact with each other. Instead of pushing the bottlenecks upstream or downstream, reimagination requires taking a step back and reviewing the whole chain of processes: remove all the duplication, waste, and complexity, and take advantage of the digital tools available to do things in a better way. 

Integrating different solutions

  • Leaders should be aware that while new technologies offer new possibilities, it is not the case that the more technologies, the better. Each technology needs to be connected. IT needs to be on board to ensure the new technology can be integrated and is appropriate for the overall architecture.
  • Intelligent automation teams should be plugged into the business, work closely with transformation teams, and be aligned on the process improvement initiatives taking place in each department. 

Intelligent Automation - has proved itself and is now firmly in the mainstream with organizations realizing a broad set of benefits: improved accuracy, increased productivity, enhanced customer and employee experience, and cost reduction. 

The diagram below illustrates the natural evolution that occurs in your automation journey and helps paint the picture for how best to navigate to AI-Powered Point of Arrival.

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  • Significant opportunities exist for organizations that can integrate enterprise-wide automation with process improvement, process intelligence, and other complementary capabilities from across the organization to bring value to end customers holistically.  
  • The first indicator of this shift, which we expect to continue, is automation leaders re-inventing their operating models to take a customer-centric approach where process outcomes and customer value take ultimate precedence over functional distinctions and departmental boundaries  
  • Tapping into a wide range of intelligent automation technologies comes with many benefits. Organizations are adopting intelligent automation solutions to benefit from increased productivity, cost reduction, improved accuracy, and better customer experience.  

Overcoming barriers to scaling - The top barriers are process fragmentation, lack of a clear vision, lack of IT readiness and resistance to change  

  • PROCESS FRAGMENTATION: Immature and fragmented processes that are difficult to manage with a unified flow  
  • CLEAR VISION: With so many existing and emerging technologies available at their fingertips, organizations need to have a vision and strategy for intelligent automation to succeed  
  • IT READINESS: Organizations still rely heavily on their IT functions to enable various technologies.  
  • RESISTANCE TO CHANGE: The workforce remains the least supportive stakeholder groups for intelligent automation  

Low Code & Citizen led development -  

  • The rise of low-code and citizen-led intelligent automation development can help organizations engage and empower their workforce  
  • Citizen-led development (CLD) is a framework that encourages non-IT employees to use IT-sanctioned low-code/no-code platforms to develop low - complexity, attended automations within their function. This framework empowers business users to create new task-based automations for their own use and helps to break the misconception of automation replacing humans versus enabling them to be more effective. 

Top Tips 

  • To leverage the power of the whole automation toolkit, organizations should not stop at process redesign. To maximize value, end-to-end automation, and process reimagination should be components of the vision of becoming a truly transformed organization.  

Process mining - Process mining is a leading data-driven capability that enables organizations to analyze processes as they are executed 

Process mining's time has come as business complexity accelerates. Process Mining is a significant breakthrough today, particularly as businesses struggle with the emerging impact and complexities of automation, which can create massive fragmentation of traditional processes. Process Mining uses specialized data mining algorithms to identify trends, patterns and details in event logs recorded by an information system to define and understand the underlying business process: 

  • In today's increasingly complex and volatile environment, managing business processes is posing immense challenges.  
  • It's clear that businesses should raise their game to precisely manage critical processes as never before — particularly amid the ongoing quest to effectively manage digital transformation, emerging automation capabilities and the need to truly understand today's fast-moving customer journey. 
  • The key to effective process management is process transparency that can drive consistent and reliable monitoring and improvement of existing and evolving processes 

Process Mining is viewed as nothing less than a `disruptive accelerator' for business transformation today. One of the biggest challenges of business process analysis for today's increasingly complex organizations is precisely understanding how current processes are being executed. 

Simply put, process mining delivers, and helps bridge the gap between traditional process analysis - simulation and other process-management techniques that include lean management and six sigma - and data-centric analysis capabilities involving machine learning and datamining. Process mining is not only used for analysis of processes - it can also help predict future process execution needs and recommend suitable actions: 

  • Provide fact-based insights into processes, allowing the identification of inefficiencies, potential irregularities, misconduct, and internal control risks. 
  • Generate understandable process maps quickly and efficiently based on the vast array of timely data that today's business systems deliver. 
  • Perform root-cause analysis to investigate exceptions and limit false-positives. 
  • Define key performance indicators (KPI) and measurable improvement objectives for process-based performance management. 

Process mining is process and system `agnostic,' meaning it can be used to analyze a wide range of processes — from back-office and mid-office to customer-facing.