Danny Major FBCS looks at how enterprises can adopt intelligent automation (IA), exploring the commonalities and cross-industry successes he has witnessed.
As enterprises embrace digital transformation IA continues to gain traction, with the following all having a significant role to play: robotic process automation (RPA), intelligent document processing (IDP), task and process mining, conversational AI, and business process management (BPM). To succeed in adopting such technologies, enterprises need a structured approach that addresses not only the technology itself but also the broader business, strategic and cultural factors. Here are some of the key considerations and steps for enterprises seeking to not only maximise the value returned, but also to avoid stagnation or failure.
Align with business strategy
Automation initiatives should not exist in isolation but be driven by well-defined business goals in line with strategic objectives, such as cost reduction, operational efficiency, customer experience enhancement or risk management. Leaders should establish a vision for automation, identifying key processes where automation can have the most significant impact.
Start by conducting an analysis to identify areas where automation will deliver the highest value against what is strategically important. Use metrics such as potential cost savings, process cycle times, or service-level improvements to demonstrate the value of IA to key stakeholders.
Assess your readiness
Understanding the organisation’s readiness involves evaluating the current maturity of processes, technology, and data quality. Automation efforts will be more effective if the existing processes are well documented and standardised; if they are not, it may be necessary to undertake process improvement initiatives first.
Consider your organisation’s existing technology landscape. A fragmented or outdated infrastructure can hamper automation initiatives, making integration difficult and limiting scalability. Enterprises should establish a roadmap for technology modernisation where needed, ensuring that automation tools can seamlessly interact with core systems.
Establish governance and frameworks
The deployment of IA from the release of the first process or use case requires robust governance and change management frameworks to guide ongoing implementation. These frameworks should outline how automation projects are prioritised, funded, and managed, as well as how risks and dependencies are addressed.
Change management is particularly crucial, as automation can alter job roles and impact employee morale. Leaders should position automation as a means to empower the workforce by shifting repetitive tasks to machines, allowing employees to focus on higher-value activities.
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Develop skills and training programs
Adopting IA requires not just technical implementation but also an investment in training and upskilling the workforce. Organisations should assess the skills gap within their workforce and develop targeted training programs to ensure employees can work effectively with automation tools and technologies while also helping to identify additional uses. Ensuring the right skills mix within your enterprise is one of the fundamental factors to achieve ongoing scale.
Focus on adoption and scaling
Enterprises should focus on scaling their automation initiatives across the business. This involves identifying repeatable use cases, establishing automation frameworks and creating reusable components that can be leveraged across multiple processes.
Ensure that automation solutions are user friendly and provide clear value to end-users. Collect feedback to help continuously refine and improve automation. Establish metrics to track the impact of automation on business outcomes and link back to strategic aims. This will help maintain momentum and guide future investments.
Monitor, optimise and innovate
The journey does not end once automation is in place. Continuous monitoring and optimisation are essential to ensure that automation continues to deliver value. Use process mining and analytics to identify bottlenecks or opportunities for further improvement. Additionally, stay abreast of new technologies that can complement or enhance existing automation solutions.
In summary
Following a structured approach that aligns with strategy, addresses organisational readiness, establishes governance, invests in skills and focuses on scaling will enable enterprises to realise the full potential of IA. With the right approach, enterprises can navigate the complexities of IA adoption and build a foundation for sustainable success.
