Failure Modes – Robotic Process Automation Technologies

Looking at cost pressure, dynamic business requirements and huge IT legacy, “Robotic Process Automation” has slowly emerged as one of the key levers to expedite Business transformation journey for many organizations. Every other Business function, BPO service Provider & the complete IT industry is busy sharing numerous success stories around RPA implementation. Also, at the same time, RPA product organizations are busy oversimplifying the technology. Over-all, the RPA industry is continuously evolving on daily basis and creating a positive mark on many large business organizations.

Like every coin has two faces, RPA also has got significantly high failure rate. It is then important to critically evaluate the “success” element of RPA case studies and carefully understand various failure modes.

1. LACK of alignment with all concerned stakeholders

Typically, RPA Initiatives are driven by the Business side of the Organization with very late involvement of IT Organization. In an enthusiasm to accomplish early benefits of RPA and considering simplified approach from various RPA products, Business organizations are often tending towards over confidence. And thus, ended up defining half-baked transformation strategy.

The fear of losing RPA early benefits in the over-all long-term IT transformation strategy compels Business leaders to hide their initiatives. Thus, it is important for CIO organization to consider RPA as a catalyst towards their long-term IT strategies and collaborate with Business to accomplish desired outcome.

2. LACK of thorough due diligence on process selection and business case creation

In order to expedite transformation journey, agree on the outcome based on surficial process assessment and then force fitting the RPA solution to meet the numbers often results in long term failure. Selective Automation is the key. Many a times, the rule of 80-20 is applied to reap maximum benefits. Low volume exceptions are typically kept out of scope for the Robots. There exist few cases in the Industry where RPA is implemented with huge effort to automate processes worth 20-40 person hours of effort per month. This aspect is critical to success and thus should be dealt carefully with thorough due diligence.

Each RPA problem can be solved using multiple solution patterns. Striking a right balance between business process re-engineering and technology is the key. Too much technology often impacts the return on investment and poses huge risk of failure. Cognitive is the biggest buzz world today in the Industry. It’s good to include cognitive aspects as part of over-all solution but only when it is individually providing the desired corresponding benefits.

3. LACK of adequate time investment in Design

Exploiting the term, “agile”, many times RPA is implemented by the Developer sitting along with Business process SMEs with minimal investment of time on design. “Componentization & generalization” is the key towards design to accomplish desired re-usability, scalability and maintainability. Typically, business process involves multiple queues spanned across same applications and screens with minor business logic differences. Reusable components bring expedited RPA delivery with high level of scalability and maintainability.

It is important to study historical business process change patterns to define the right level of generic design. As a rule of thumb, all threshold limits and business logic components are potential candidates.

4. LACK of best practices utilization during Implementation

Often, we observe BOTs being developed considering only short-term execution approach and thus, gets into trouble or discontinued after some time. The code is not optimized in terms of Readability, Configurability, Reliability, Scalability, Security and Performance. Applying all best practices from both RPA concept and Product perspective is the key.

5. LACK of clearly defined test strategy

Here are few common discussion points during user acceptance testing. “It was working absolutely fine in development environment but not stable in production environment”. “Not all test scenarios were tested due to lack of test data”. “BOT is not robust as it fails for every other exception”. This debate goes on and takes away the positive energy of the collaborated workforce. This finally results in significant delay and sometimes even project itself get scrapped.

 Thorough tracking of functional defects and exceptions having tight coupling with desired outcome is the key. It is important to define the test phases considering test data availability, differences between test and production environment of underlying source applications, functional testing, exception testing and the real data testing. Most occurring un-known exceptions like dynamic application performance, un-known pop-ups, credential failure, memory leakage, etc. need to be designed and factored in appropriately during build phase.

6. LACK of focus on change management, reporting & proactive monitoring

Once BOTs get deployed, it is required to holistically define an approach to execute and operate them in more secured and efficient manner.  It is then important to upfront define the clear strategy around it. Often it is observed that the rush to accomplish quick benefits results in a huge mushroom farm of Robots, managed manually through localized teams. Thus, it is highly recommended to focus on areas like change management, Credential management, Robot monitoring & Control, and high availability & scalability of over-all RPA Infrastructure.

 Changes can come due to changes in Infrastructure, Applications or even the processes. The key here is to have robust change management process established with all the three different groups in such a way where Changes are recognized much earlier in lifecycle and BOTs get adequate time to get fixed accordingly. Also, proactive monitoring and continuous improvement is not optional in case of RPA implementation. It is required to continuously adjust BOTs with optimal frequency to deal with changes in Volume patterns and sustain the same productivity levels as envisaged before.

“In summary, Robotic Process Automation technology has successfully emerged as one of the strong business transformation levers if strategized, implemented and deployed in structured scientific manner and not as a technology of “Work around”.

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