Unveiling the Truth: Is Robotic Process Automation the New Tech Debt?

Robotic Process Automation (RPA) enables the automation of repetitive, rule-based tasks traditionally performed by human workers, freeing up human resources for more complex tasks. By utilizing intelligent automation technology to perform monotonous tasks, software robots, or “bots,” emulate and integrate actions typically carried out within digital systems. These bots can interact with applications, manipulate data, trigger responses, and communicate with other systems to perform a variety of tasks efficiently and accurately.

What is Tech Debt?

Technical debt is the hidden costs incurred when shortcuts are taken, or suboptimal solutions are implemented, to meet the immediate needs of an organization. 

The problem with these band aid fixes is that over time, these shortcuts accumulate and compound interest, manifesting as increased complexity, decreased flexibility, and higher maintenance costs. While RPA can deliver rapid efficiency gains, its implementation can inadvertently increase the risk of tech debt. For example, by introducing invisible and undocumented dependencies on UI details that can cause bots to fail without warning.  

The Band Aid Effect: Addressing Symptoms, Ignoring Causes 

RPA excels at automating routine, rule-based tasks, and offering a quick fix to alleviate manual workload and free up human resources. But RPA treats the symptom rather than addressing the underlying causes of inefficiency. By automating existing processes without critically evaluating their efficacy, organizations risk outdated workflows and perpetuating inefficiencies. 

There are several alternatives and complementary technologies that can be considered, depending on the specific needs and goals of the organization.

The Scalability Conundrum: Struggling to Keep Pace 

One of the hallmark characteristics of tech debt is its tendency to hinder scalability and inhibit future growth. Similarly, RPA solutions, while initially effective, can struggle to adapt to evolving business needs and changing technological landscapes. As processes become more complex or organizational requirements shift, RPA bots may require constant maintenance and updates, leading to increased overhead and diminished scalability.  

Integration Challenges: Stitching Together a Fragile Patchwork 

Another concern to keep in mind with RPA implementation is its integration with existing systems and processes. RPA bots operate within predefined parameters, often in isolation from the broader ecosystem of enterprise applications and databases. This fragmented approach can result in brittle automation solutions that fail to seamlessly interact with other systems, exacerbating interoperability issues and hindering cross-functional collaboration. 

The Legacy Dilemma: Reinforcing Outdated Infrastructure 

In some cases, RPA may inadvertently perpetuate reliance on legacy systems and outdated technology. Instead of investing in comprehensive modernization efforts, organizations may opt for RPA as a stopgap measure to automate tasks performed on antiquated platforms. While this approach may yield short-term gains, it risks entrenching legacy infrastructure and impeding long-term digital transformation initiatives. 

Mitigating the Risks: A Strategic Approach to RPA Implementation 

Despite the potential pitfalls, RPA still delivers significant benefits when implemented strategically and judiciously. To avoid falling prey to the allure of quick fixes and accumulating technical debt, organizations must adopt a holistic approach to RPA implementation: 

  • Align with Business Objectives: Prioritize RPA initiatives that align closely with strategic business objectives and long-term goals. What are our strategic business goals, and how can RPA help achieve them? Focus on processes that align with these goals and offer the highest potential for improvement through automation.

  • Conduct Thorough Process Analysis: Which processes are suitable for RPA, and what are their current inefficiencies? Evaluate based on their complexity, volume, rule-based nature, and stability. Pinpoint inefficiencies, bottlenecks, and areas prone to human error.

  • Evaluate Processes Holistically: Conduct thorough process analysis to identify inefficiencies and opportunities for optimization before implementing RPA solutions. 

  • Set A Data Review:  Review data for each RPA process and its execution history. This is a necessity to avoid lingering processes and in keeping awareness of dependencies. 

Specific questions to address when analyzing an RPA solution:

  1. What are the primary goals for implementing RPA?
    • Are you looking to reduce costs, improve efficiency, enhance accuracy, or free up human resources for higher-value tasks?
  2. Which processes are suitable for automation?
    • Are the processes repetitive, rule-based, and high-volume? Do they involve structured data? Do they rely on stable interfaces?
  3. What are the expected benefits and ROI?
    • What are the tangible and intangible benefits of automating these processes? How do you plan to measure the return on investment?
    • Focus on Governance and Maintenance: Implement robust governance frameworks and dedicated maintenance procedures to ensure the ongoing viability and scalability of RPA solutions.


      • Ensure that RPA initiatives align with the organization’s strategic goals.
      • Defined and assigned roles and responsibilities for RPA implementation and management.
      • Regularly review and update these frameworks to stay aligned with evolving business needs and regulatory requirements
      • Ensure continuous monitoring and auditing of RPA processes to identify and mitigate risks promptly.
      • Develop a maintenance schedule that includes routine updates, bug fixes, and performance optimization to keep the RPA systems running efficiently.
      • Structure your RPA solutions to fail fast and fail loudly; check for expected fields and stop with an error message if an expected field is not found.
      • Invest in training programs to keep the team skilled in the latest RPA technologies and best practices, fostering a culture of continuous improvement and innovation.


While Robotic Process Automation (RPA) offers a powerful way to automate repetitive, rule-based tasks, it might not be the best fit for every situation or process. Its indiscriminate adoption without careful consideration of long-term implications can indeed give rise to a new form of tech debt. 

By acknowledging the potential risks and adopting a strategic, forward-thinking approach to RPA implementation, organizations can harness its potential while safeguarding against the pitfalls of technical indebtedness. After all, the true measure of success lies not in the immediacy of automation, but in the sustainability and resilience of our digital ecosystem. 

Your Organizational Needs

Those that have implemented RPA seamlessly and without issues are in the minority and are doing a great job with their automation implementation. For everyone else who are seeing the early signs of an increase in tech debt, consult with our team at MCANTA to understand the automation solutions we offer our clients to keep their digital ecosystem scalable, resilient, and free of potential risks. 

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