Why it makes sense to standardize processes before deploying RPA

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Many companies design RPA implementations to support their ‘as-is’ processes, without evaluating or standardizing the existing process map. As a result, they achieve modest savings at best, and in most cases forego the opportunity to dramatically improve process outcomes, quality, costs and turn times. If you’re considering an RPA implementation and are looking to sidestep this pitfall, it’s important to first understand why standardization issues occur.

Why standardization issues occur

Standardization issues primarily occur due to a lack of clear Standard Operating Procedures (SOPs) or process maps. The lack of clarity can stem from either poor documentation or outdated guidelines.  Without a clear and consistent guiding framework, businesses end up capturing the input data in a non-standardized format or implementing different processes across multiple regions. In our experience, addressing such issues through process mapping, analysis and standardization – prior to RPA implementation – leads to significant improvements in the processes being automated.

A leading Commercial Finance business, for instance, operated out of two different locations. One of the company’s processes required emails to be sent to clients informing them about unverified amounts in their accounts relating to debtors. Process mapping and analysis by Firstsource experts revealed that one location was disseminating emails to the clients while the other location communicated with the clients’ debtors – resulting in two distinctly different processes.  The SMEs at both locations agreed to adopt a standardized process prior to RPA deployment, leading to superior efficiencies and reduced costs.

Working with RPA is easy when you know what to do

It’s important to recognize that this approach can sometimes delay the deployment of RPA. For companies concerned about losing time, the solution is to first deploy RPA and then drive process standardization. One of our clients required its customer service representatives to enter inputs in a standard format for bots to process.  But ensuring 100% adherence would have taken considerable time, delaying the RPA deployment. Firstsource experts decided to deploy the bots without standardizing the process, knowing that they may not achieve the expected penetration percentage in the first month. They then used the non-processed data thrown out by the bots as ‘exceptions’ to provide feedback to non-compliant customer service representatives to drive standardization. With consistent and rigorous coaching and feedback, penetration of this process significantly improved from 20% to 90% in less than six months.

For businesses, bots going live is a huge milestone. But the challenges don’t end there. Post-go-live failures can erode business confidence, causing organizations to fall off the RPA bandwagon and return to manual methods and inefficient processes. Another challenge is the need to make constant changes to bots due to frequent changes in the process. This can occur due to the dynamic nature of the process or issues related to standardization. All of these challenges can be tackled using a well-thought-out approach that includes:

  • Deploying a robust structure to ensure BAU delivery continuity.
  • Monitoring bots continually and documenting resolved issues to ensure smooth functioning.
  • Ensuring that all changes are routed through a formal change request process that assesses upstream and downstream impact before they are deployed.
  • Testing every change before it goes live into production.
  • Establishing a strong reporting structure that captures weekly/monthly data around issues, efficiency benefits, bot penetration and accuracy.

Driving sustained RPA success need not be complicated

A successful RPA deployment can significantly improve stakeholder confidence as it results in long-term productivity gains, improved quality and superior customer experience. Once the confidence is established, businesses can broaden the scope of RPA by bringing larger and more complicated customer-facing processes under the preview of RPA for sustained competitive advantage.

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