There are clear guidelines that help companies prepare for their automation projects and leverage sustainable competitive advantage by creating a comprehensive roadmap.
Automation is best approached in three phases - implemented, executed, and leveraged, thus allowing companies to increase efficiencies and achieve instant ROI.
3 stages to an automation program
1. Exploratory Phase
Understand RPA - Initiative business leaders must be fully self-aware of the suitable practices for RPA and the strategy to align it with business goals. A significant component of this process recognizes the most appropriate tasks for automation, and it is not suited to all operations.
Define RPA governance – automation programs can be handled through different leadership styles, each having its benefits and weaknesses. A centralized governance structure can encourage collective automation programs as per the requirements of various business units. A decentralized management style enables different departments to innovate and execute RPA solutions in their functions. In practice, most leading organizations adjust depending on their requirement. A hybrid method is popular that establishes a Center of Excellence (CoE), thus allowing stakeholders to explore solutions for their own needs whilst implementing compliance standards at the same time.
Build support – the change management teams require substantial support from key stakeholders, top management and end-users. Business leaders must take responsibility for the pilot case, to achieve transformation success early on and prove how to deliver value via automation.
2. Setup Phase
The second phase explains setting up the structure to expand the Intelligent Automation journey. There can also be pitfalls that may lead to failed AI & Automation programs: unclear vision, poor governance, the wrong choice of candidate processes to automate, poor change management and communication, and choice of partner.
Test on a small scale – the program should focus on the low-hanging fruit rather than an enterprisewide automation program that requires significant capital investment. Afterwards, the test can showcase how results can be easily achieved with no significant risk to time and resources, thus attracting executive sponsorship for other automation programs.
Change management – stakeholder alignment and communication is critical in the setup phase. The internal technical talents should closely participate in this phase to ensure the success of the automation program.
Governance Council – A Governance Council overseeing all aspects of the CoE needs to be established and should include key stakeholders involved in program execution success. Experienced senior heads running an automation program should include -
• Process Discovery Lead
• Automation Execution Lead
• Heads of Key Departments
• IT Representatives
• Heads of Finance
3. Execution and Expansion Phase
Set timeline and expectations – In the first step of the pilot phase, stakeholders should recalibrate their expectations and establish realistic benchmarks for success. Before taking action, the implementation team should reconvene with automation & AI vendors. For a successful proactive planning phase it’s important to understand how an adjustment in the timelines can affect the subsequent deployments and actions.
Work closely with the vendor – The transformational vendor plays a crucial role in any RPA initiative. Their help and input are significant during the implementation stage. Therefore, all the stakeholders should collaborate to ensure necessary guidance and timely implementation.
Leveraging Intelligent Automation – An initial implementation may focus on the most apparent targets for RPA solutions. Nevertheless, there are many more areas where RPA can potentially deliver innovation with significant gains. Advanced machinery can routinely diagnose and fix the system ideas, enhance customer services, and provide comprehensive data insights when introducing independent technologies such as artificial intelligence and machine learning. Conversational AI technology such as Chatbot, backed by NLP (Natural Language Processing), can encourage internal and external customers to leverage self-service thus significantly impacting the customer experience.
Manage and monitor – the CoE constantly monitors the entire unit and benchmarks processes and principles across the board. An inclusive data generation and analytics machinery promotes the company to strengthen the process, look for potential growth in automation and determine the RPA solutions' return on investment. In such a manner, analyzing the common errors in bot execution, environment-specific reasons for failure, and creating a checklist and standard for avoiding such mistakes in the newer implementations allows growth to be achieved.