By Vimal Nair, Vice President & Global Head for Automation & Testing Services in ITC Infotech &
Divya Darshan Jannu, Intelligent Automation Practice Lead in ITC Infotech
“Change is the only constant”, – Heraclitus (Ancient Greek, 540 BCE).
Let’s work towards directing the change for human progress in a sustainable value focused path. The advancement of humans and their needs have influenced the evolution of the learning paradigms to support the change. In this modern era where ‘Sustainable Growth’, is the key need, any transformational program is incomplete without ‘Automation’.
In the digital world, automation is typically achieved through scripts and Robotic Process Automation (RPA) technologies. A program which runs as instructed performing repetitive tasks so that humans can focus on progressive activities. This further fuels the need for autonomous capabilities for digital entities. Recent years have seen huge development in the areas of artificial intelligence and data analytics. The progression of technology has opened up opportunities to combine multiple technologies like Automation, Analytics and Artificial Intelligence to provide solutions of autonomous nature.
Implementing automation presents a complex landscape for organizations. Beyond the allure of efficiency gains, significant challenges lurk. The initial hurdle is cost; investing in automation technologies, including software licenses, hardware upgrades, and system integration, can strain budgets, especially for SMEs. According to a Deloitte study, the average cost of implementing a robotic process automation (RPA) solution is around $15,000 per bot, not accounting for maintenance and scalability. Resistance to change from employees fearing job displacement is another major obstacle.
A McKinsey Global Institute report suggests that up to 30% of the global workforce could be displaced by automation by 2030, fueling anxieties and impacting morale. Furthermore, identifying the right processes for automation requires a thorough understanding of existing workflows and data structures, which can be time-consuming and resource intensive. Data security and integration with legacy systems also pose significant risks that must be addressed proactively.
Preparing for automation demands a strategic and holistic approach, beginning with a comprehensive assessment of the organization’s current state. This involves mapping out key processes, identifying bottlenecks, and evaluating the potential for automation. Crucially, organizations need to invest in upskilling and reskilling programs to equip their workforce with the skills needed to manage and maintain automated systems. For example, a manufacturing company could invest in training programs to teach employees how to program and troubleshoot robotic arms.
Creating a robust data governance framework is also essential to ensure data quality and security. Before automation, pilot projects should be implemented to test and refine the chosen solutions, allowing for adjustments and employee feedback. This phased approach allows for a measured implementation and helps demonstrate the value and effectiveness of automation, paving the way for broader adoption.
Successfully implementing automation requires a well-defined strategy with clear objectives and measurable KPIs. Focus on automating repetitive, rule-based tasks first, such as data entry, invoice processing, or report generation, which offer quick wins and demonstrate the value of automation. Utilize agile methodologies for project management, allowing flexibility and adaptation as the implementation progresses. When selecting automation tools, prioritize solutions that are scalable, interoperable, and user-friendly. Consider cloud-based solutions for increased flexibility and reduced infrastructure costs. Monitor performance closely using metrics like processing time, error rates, and cost savings. Regularly evaluate and optimize the automated processes to ensure they continue to deliver the desired results. Remember to engage employees throughout the process, soliciting their input and addressing their concerns to foster a collaborative and positive environment.
Ensuring the success and sustainability of automation hinges on continuous improvement and a focus on creating long-term value. This involves establishing a center of excellence (COE) dedicated to automation, responsible for identifying new opportunities, developing best practices, and providing ongoing support. The COE can track quantitative metrics, like a 15% reduction in manual errors year-over-year post automation, as a benchmark for progress.
Proactively address the ethical implications of automation, ensuring fairness, transparency, and accountability. Invest in AI and machine learning to continuously improve the efficiency and intelligence of automated systems. Foster a culture of innovation, encouraging employees to identify and implement new automation solutions. Finally, prioritize cybersecurity to protect automated systems from cyber threats, ensuring the long-term security and reliability of the automation infrastructure.