Article

Scale RPA at an Enterprise Level

This article from The Silicon Partners (TSP) explains how an Automation Operating Model (AOM) helps organizations move robotic process automation (RPA) beyond the proof of concept. It is for automation and business leaders, and covers program goals, process pipeline management, ROI and KPIs, training and adoption, and infrastructure and security.

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Automation is becoming the primary digital transformation need for most of the enterprises. Irrespective of the business size, levering automation technologies like Artificial Intelligence (AI), and Robotic Process Automation (RPA) in combination is the futuristic vision. According to Gartner, the total spending on RPA on a global level will be approximately US$ 2.4 billion by 2022. Surprisingly, when it comes to the least scaled IA or intelligence automation technology, RPA tops the list, says HFS Research in collaboration with KPMG. At the same time, automation is shift of mindset for industries, as it requires change in practice with current manual processes which enterprises have been following from decades. Hence demonstrating an automation success story with a distinguished ROI is essential for this compelling shift of mindset.

Several organizations are facing the challenge of not realizing the much-anticipated Benefits of Automation Program. The main reason is the fact that these organizations lack the strategy to move forward. Simply put, they do not have fitting Automation Operating Model, which stalls automation program after initial RPA proof of concept.

Transforming from initial RPA proof of concept to enterprise and establishing a suitable automation strategy with robust Automation Operating Model (AOM) is where organizations want to be.

Having a thoughtful Automation Operating Model (AOM) in place creates balance between “Developing the Capability” and “Supporting Demand”

Here the capability is developed by defining automation program goals and building the services to implement accordingly. On the other side, the demand is supported by pipeline management for automation and creating awareness for adoption within the organization. The AOM ensures advancement in the governance and infrastructure to support the future process automation needs by business. At the same time, it also ensures that regular investment by business in program is justified i.e., business gains the right ROI to measure the success.

  1. RPA proof of concept

    Pick a couple of processes to pilot, choose the right tool or tools, identify the key stakeholders and capture the baseline to measure ROI.

  2. Automation operating model (AOM)

    Set the corporate strategy, the program’s goals, the expectations and the technology focus.

  3. Process pipeline management

    Define the operating model and governance, find processes through process mining or business requests, agree how they are listed and submitted, build feasibility assessments and business cases, and set up an approval model.

  4. ROI and KPIs

    Define the ROI parameters and the KPIs that measure RPA success in your organization.

  5. Resources, training and adoption

    Validate the bots in action, set the delivery and support model, plan for adoption and awareness, and train for the change.

  6. Launch the AOM and scale RPA across the enterprise

    Bots live in production, ready to scale and to support.

AOM Program

  • Is your organization looking towards more on Task Automation, Process Automation, Enterprise Automation, Test Automation, or all of them?
  • Understand your organization’s vision from Automation?
  • Are you looking to bring intelligent automation in the future?
  • Are you looking to improve the quality of your data, save costs or enhance customer/ user experience by providing quicker, more accurate responses?

Goals

Establishing Program Goals tied to business objectives will provide guidance on the type or types of automation the program should support

Benefits

This will help you understand what your organization wants to achieve from robotic process automation, and what kind of tools, skills, infrastructure would be required in future.

Process Pipeline Management

  • Are you open for end users submitting the task/ process ideas for assessment?
  • Are you looking at Data driven process identification using process mining tools?
  • Have you identified any specific tool?
  • How would you do the assessment scoring to approve or priorities the one process over other?

Goals

Identifying the right candidate for automation is another challenge that organizations face; hence it is important to define an approach for Business and IT to collaborate and create demand which can include process listing/ submission, any need to utilize the process mining tool, your ability to do an assessment and get process feasibility score for automation.

Benefits

You have successfully created a model for demand generation as well as how are you nurturing this automation demand. A thoughtful assessment, approval mechanism is created, and your automation prioritization process is established.

ROI and KPI

  • How will you capture the baseline?
  • Are you thinking of aggregate ROI or each bot ROI?
  • Do you need to define the function based KPIs? Or Process based KPIs?
  • How will you measure the ROI after automation and compare with baseline?

ROI & KPI Definition–

ROI from Automation defines a success story and it is the ultimate result which every organization wants to achieve. You want to make sure that you understand how your organization looks at ROI? Are you only looking at manual effort saving as criteria?

Benefits

This ensures that you have a mechanism to capture the baseline, calculate ROI after automation and compare with baseline for actual benefits. At the same time, you have a framework to review every process and understand the gap by measuring the ROI via defined KPIs and compare it to the expected ROI.

Have you explored other criteria like accuracy, cycle time, productivity, delays, customer satisfaction, and employee satisfaction?

Have you reviewed the right ROI parameters with your business and leadership to understand their importance for organizations or the business units?

Resource Training and Adoption

You may want to understand and setup the appropriate plan for resource, skill requirements. Plan adequate trainings so that you can manage and support in long term.

Infrastructure and Security

Understanding your organizations data security, compliance needs and accordingly defining the infrastructure i.e. Cloud vs On Premise model. What kind of tool you should be reviewing for automation?

Scale RPA to Enterprise

Now you are ready to scale the robotic process automation at enterprise/ global level in your organization, as each step as mentioned above have crucial and you have successfully created a workable automation operating model for your organization which has governance and incorporate CoE to achieve your organizations automation program goal.

The key benefits of an automation operating model:

  • A reliable program to meet the demand for automation
  • More adoption, and more contributions
  • Governance that sets the vision and supports it
  • Higher efficiency and productivity
  • A thin CoE with clear responsibilities
  • Specific KPIs to measure success
  • The most return on the investment
  • No duplicated effort across business units
  • The ability to scale the automation program quickly
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About the author

  • Amit Tiwari

    SVP Agentic AI, Intelligent Automation & Innovation

    Technology leader with 24+ years of experience driving enterprise transformation through Agentic AI, Intelligent Automation, SAP, AI/ML, and Digital Modernization. Focuses on shaping the Agentic Enterprise, orchestrating AI Agents, automation, enterprise systems, and people to accelerate transformation, improve productivity, reduce operational risk, and deliver sustainable ROI. Experience spans Agentic AI, AI/ML, RPA and Intelligent Automation, SAP transformation, Test Automation, Process Orchestration, Cloud, and enterprise application modernization. I am particularly interested in the convergence of AI Agents + RAG + MCP + Agent-to-Agent (A2A) collaboration + APIs + Automation + Human-in-the-Loop, and how these capabilities can transform complex enterprise processes.

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