A piecemeal approach to automation has been doing more harm than good when it comes to ROI from digital transformation. In the AI era, companies need a new approach that can tie together their tech investments to transform end-to-end user journeys. Read this article to understand what this approach can be and the magnitude of benefits it can deliver.
Imagine having a Star Wars lightsaber – a device that can cut, melt, and burn virtually anything and gives you the status symbol of space-age coolness. But instead of using it to its full power, you just use it as a torch. That’s what businesses are doing with automation. Their piecemeal and short-sighted approach to automation is curtailing its potential.
What if enterprises approached automation differently? What if they could increase the scale and scope of automation and leverage it to maximize straight through processing (STP) and augment human potential?
Taking a holistic and well-thought-through approach to automation can unlock exponential gains. For instance, a U.S.-based healthcare insurer expanded the scope of automation to increase ROI. They served a large customer base of ~ 39 million people, and complex business processes led to inefficient customer service. While they had some automation in place, a siloed approach limited the scope and resulted in sub-optimal ROI. As only a patchwork of small tasks were automated, their operations still needed heavy manual intervention to stitch the tasks together and complete the process.
They revisited their automation program and moved the focus away from task-level automation to look at end-to-end operational processes. They identified opportunities for optimization and automation with process discovery and leveraged the insights to automate entire processes (not individual tasks).
This new approach helped them clear a backlog of 70,000 records with <3% errors in claims processing and led to a 7% productivity improvement. Saving the bandwidth of over 170 full-time employees led to a potential annual savings of USD 6 Mn. The visible increase in automation ROI was incentive enough for the company to quickly roll out a similar program across six business areas deploying 120 cross-functional bots for 5000 users. In addition to scope, increasing the scale of automation also has transformative outcomes.
And finally, a cohesive approach to automation can go a long way in augmenting the workforce potential. For instance, a large U.S. telecom company improved customer experience by unearthing workforce insights and fixing the gaps in performance to augment agent productivity by 20%. However, driving scale, scope, and automation requires AI-driven automation maturity, multi-dimensional insights, and holistic process execution via centrally managed automation journeys. And this is where most organizations fail.
One of the core challenges businesses face in realizing automation ROI is the inability to tap into automation ideas across Lines of Businesses (LOBs). It’s like having a ton of ideas for a Netflix binge but getting stuck with the wrong recommendation engine. The result? Departments operate in silos, with a myopic view of automation, missing out on the broader spectrum of possibilities.
Then there’s the issue of automating sub-optimal, broken, and complex processes. It’s like slapping a high-tech band-aid on a broken leg – it doesn’t solve the problem and often makes it worse. Task-level automations create more siloes and insights locked away in unstructured and complex documents and processes result in disjointed workflows leading to automation failures and fallouts. Adding to the complexity, businesses must deal with linearly increasing infrastructure and workforce costs and cumbersome management of sub-optimally working automation, infrastructure, and bots. This leads to poor coverage and hinders the scale of automation programs. A less visible but equally debilitating issue is the limited visibility into hybrid workforce productivity. Without clear visibility into employee operations, companies are hard-pressed to empower them with the right insights and productivity tools.
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To maximize straight through processing across their operations, businesses must embrace a mature strategy that overcomes the challenges to scale, scope, and augmentation.
Then there’s the issue of automating sub-optimal, broken, and complex processes. It’s like slapping a high-tech band-aid on a broken leg – it doesn’t solve the problem and often makes it worse. Task-level automations create more siloes and insights locked away in unstructured and complex documents and processes result in disjointed workflows leading to automation failures and fallouts. Adding to the complexity, businesses must deal with linearly increasing infrastructure and workforce costs and cumbersome management of sub-optimally working automation, infrastructure, and bots. This leads to poor coverage and hinders the scale of automation programs. A less visible but equally debilitating issue is the limited visibility into hybrid workforce productivity. Without clear visibility into employee operations, companies are hard-pressed to empower them with the right insights and productivity tools.
1. Increasing the scale of automation
An automation scaling strategy begins with process intelligence for process discovery, prioritization, optimization, and automation. Simply put, it’s about finding out the ‘who,’ ‘what,’ ‘where,’ and ‘how’ before sending in the automation troops. And then, it’s about automating your automation journey. Yes, you heard that right. Automate everything from process discovery to bot scaling, creation, migration, validation, deployment, self-healing, and central monitoring. Automated bot scaling, planning, and management will help superfast expansion while reducing the total cost of ownership. In addition, reducing infra overheads, leveraging flexible deployment and one-click migration, and SaaS-based models can help you scale economically. And finally, and most importantly, connect the dots to achieve straight through processing. Move away from task-level automation to look at the entire process to see how you can cohesively streamline and digitize it. Process orchestration and LCNC platforms are essential to achieve highly automated processes with minimal (and augmented) human intervention.
2. Increasing the scope of automation
The same process may have hundreds of tiny variations across the enterprise depending on how the people perform the required tasks. Manually understanding all these variations is expensive, time-consuming, and often inaccurate. Your automation strategy should include a provision for automated process analysis to get multi-dimensional insights from across the business and create optimal process maps. This also helps reduce the automation footprint, expand automation coverage with cross-functional bots, and improve the effectiveness of processes, bots, and machines.
3. Augmenting human capabilities
Automation’s objective should be to augment human capabilities. Planning for smooth workflow integration creates synergies between digital bots and human workers that aid decision-making and performance. In addition, discovering work insights with task mining can highlight productivity gaps that can be plugged with automation, intelligent guided support with generative A.I. models, and workforce training. Finally, empower users to automate personal bots with minimal setup, democratizing automation. It’s like offering everyone their personal A.I. assistant, a real-life Jarvis, if you will, running independently on their machines
The time for a piecemeal approach to automation has passed. An era of warp-speed digitalization requires an approach to automation that can keep up with the new business demands. Companies that are able to embrace a connected approach to automation will reap significant benefits in the coming years.
Disclaimer Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the respective institutions or funding agencies
