The Secret(s) Behind Automation Disasters - And How to Avoid Them | HCLTech

The Secret(s) Behind Automation Disasters - And How to Avoid Them

The Secret(s) Behind Automation Disasters - And How to Avoid Them
June 10, 2021

Introduction

RPA has become a quintessential part of the modern enterprise. According to Gartner, 90% of large enterprises will have implemented RPA solutions by 2022. Today, that number hovers around 57%. And yet, only a handful of enterprises are able to translate the theoretical benefits of RPA technologies and RPA solutions into tangible business value. Over 50% of RPA projects fail before they can be scaled- demonstrating a significant gap in the understanding and limitations of a technology that promises to add $15tn worth of value to the economy over this century.

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Automation in theory

When enterprises set out to inject into their operating models, CIOs often get stuck at the benefits of RPA technologies and RPA solutions that are seen only in theory. For instance, 30% of tasks across 60% of today’s jobs are automatable through an existing cluster of . This can:

  • Fuel an extraordinary 25-60% cost savings
  • Reduce error rates to a sub-1% figure
  • Reduce the repeatable workload on the human workforce
  • Improve both customer and employee satisfaction scores, and reduce the churn rates

These business benefits of RPA technologies, however, are not merely theoretical. But, attaining these benefits of RPA is a different story altogether- one that doesn’t consider RPA as a drag-and-drop solution to the enterprise’s bottlenecks and inefficiencies.

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Automation in deployment

When it comes to automation deployment, businesses tend to realize the ugly and the rough side of RPA projects well after the costs have sunk. Here are some markers of an automation deployment that’s going off-track, and well on its way to a business disaster:

  1. There is a silo in the organization in the form of a technology partner or the IT team that is responsible for delivering RPA deployments to other silos. This is an early red signal in the automation process that CIOs can pick on and course-correct by engaging the senior management at the top levels and business units at the lower levels.
  2. The project is running well beyond the designated timelines- this is often a symptom of working toward hyper-automation with the wrong toolset, adopting inflexible RPA solutions, or trying to automate what doesn’t lend itself well to the chosen toolset.
  3. The teams are automating processes as-is, before a thorough process redesign has even been considered. This demonstrates a lack of long-term vision in the automation process.
  4. Most end-to-end processes only lend a part of themselves to automation (McKinsey suggests this number is well below 30%). Therefore, end-to-end autopilot can become a significant deterrent of business value in the first go at injecting automation into an existing operating model.

But beyond these symptoms, what is it that actually eats away at the business value under the hood of an automation deployment?

Under the hood: How automation breaks the business value

Here are four ways in which RPA undertakings break business value over an adoption and deployment roadmap:

  1. A lack of thorough understanding of costs (and thereby, benefits): Like the human workforce, an army of bots is not a zero-maintenance, fixed cost-based ticket to getting work done. Beyond the fee that is paid to RPA solution providers, bots require regular maintenance, compliance, and security-related actions and reconfigurations depending on changes in underlying business processes, policies, and regulations in the larger ecosystem.
  2. Looking at technologies in isolation: Most enterprises that exhibited success with RPA were simultaneously leveraging other technologies like NLP, AI, and ML to inject intelligence into the automation process. Unintelligent RPA can bring rigidity that is often difficult to navigate. On the other hand, intelligent RPA can alleviate deployments from bottlenecks of hard-coded automation, which is where the true value proposition of RPA begins.
  3. Following a one-off approach to deployment: RPA adoption, whether it is being delivered under a waterfall or agile model, must be taken one step at a time. This means that instead of attempting to take a process auto-pilot, enterprises must consider a roadmap that incrementally reduces the degree of human intervention that a process requires. In this roadmap, a thorough consideration must be given to whether bits of the process must be automated as-is, or whether a process redesign can optimize it better for a bionic, bot-human workflow.
  4. Scheduling change management for the end: Change management should not be a last-minute implementation. Or worse, keeping it out of the equation altogether. This leads to a lack of synchronicity between the teams that are accountable for the delivery of an RPA deployment, and the end users that will be affected by such a deployment. Treating RPA implementation as a one-off project rather than a part of the operations routine is usually an early symptom of the ideology that results in an ineffective approach to change management.

So what’s the way around these errors? The answer is simple- CIOs must treat RPA as a toolset that can help enterprises navigate the digital reality of an operating model in a nimble, cost-effective manner - rather than a lift-and-shift lever that will automatically inject value into a business model with mere adoption and hyper-automation.

Conclusion

In sum, the theoretical business benefits of RPA do exist in reality, and in fact, these benefits of RPA are allowing companies to compete with their rivals across all industries today. What is needed, however, is a realization that the adoption of RPA calls for an incremental makeover of an operating model, and fine-tuning it for an optimal bot-human workforce rather than trying to achieve hyper-automation through the wrong toolset and/or a lack of process redesigns. This is the cornerstone of value delivery through automation, and enterprises need to embrace this reality for the sake of their digital future. As AI and ML exhibit further business maturity, the benefits of RPA adoption will be subjected to a multiplier effect that will deepen the chasm between the leaders and the laggards. The time to act is now- and enterprises must partner with experienced RPA teams in order to set themselves on the way to leadership in their lines of business.

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