Process Management 3 mins read

How to Cover the Costs of RPA

Many RPA initiatives fail because the value achieved doesn’t cover the cost of gathering the process knowledge – and then implementing, refining and maintaining the robots – to a meaningful extent.

Tom Thaler Tom Thaler

Finding value in a robotic process automation project is relatively easy if you pick the low-hanging-fruits first.

Quick wins can be gained by focusing on closing integration gaps, where APIs are missing, or by automating highly repetitive and time-consuming tasks.

Many RPA initiatives fail because the value achieved doesn’t cover the cost of gathering the process knowledge – and then implementing, refining and maintaining the robots – to a meaningful extent.

A lot of automation opportunities are missed because the wrong processes are automated, or there’s no structured and comprehensive approach to managing the robotic landscape.

So how can we maximize the value of RPA?

There are many different angles to consider – but there are four critical RPA success factors:

  1. Show me the value:

Focus on delivering maximum value from a business perspective, rather than solving work issues for individual employees.

Typical RPA initiatives often start with the easiest or most painful use cases. Although, this is understandable (particularly for POCs), it doesn’t always solve real business problems. A better approach is to estimate the business value of robotization. Consider the end-to-end process. Will the automation candidate overcome a bottleneck or positively impact the customer experience?  What are the expected costs and time savings?

  1. Avoid the cost sink hole:

Be precise and avoid biases in the pre-development phase.

Experience shows that up to 70% of RPA project resources are spent on pre-automation. This early phase involves identifying and selecting automation opportunities and capturing the detailed process knowledge required to implement the robot. The latter is usually the main cost driver. Talking to people about their daily work leads to some bias, requiring several iterations until the process detailed. Here, task mining can speed up pre-development and prevent bias.

  1. Write the manual:

Document your robotization and share with the organization – and read it.

Good documentation of the robotic landscape is key to success with RPA. Explaining how robots are used in the organization is a key factor influencing the acceptance, dissemination and ultimately the success of the RPA project. But it is also essential for the management and maintenance of the robots.

  1. Show them the money:

Evaluate RPA initiatives using business-relevant metrics that “speak management.”

As soon as the first robots are in place, share the experiences and benefits. Collect all relevant data to quantify the project’s outcome. Speak the language of management by using KPIs and use dashboards to visualize them in an appealing way. This helps get management buy-in and the budget required for growth.

Go structured and follow best practices that scale across the company (see chart).

Use BPA and process mining to prioritize the automation opportunities from an outcome perspective. Auto-discover the actual step flow. Document your RPA landscape in detail, make it accessible to all relevant stakeholders. Develop, refine and continuously monitor the robots not only for operability, but also for compliance.

Finally, pitch your RPA success to the management to ensure buy-in, ownership and budget.

Learn more about the latest features in the ARIS 10 SR 10 product release by clicking below.

Related articles