Understanding how an organization truly operates, rather than how it is supposed to work, is essential for optimization, resilience, innovation, and long-term growth. However, traditional process discovery methods to gain that understanding, while thorough, are often slow, resource-intensive, and difficult to scale.
In contrast, a Rapid Process Discovery (RPD) approach focuses on combining digital tools, data analytics, and structured modelling to provide meaningful process insights in a shorter time frame, with less disruption.
Conventional approaches to process discovery rely heavily on in-person workshops, one-on-one interviews, and manual documentation. While this can surface valuable insights, it also brings several challenges:
These limitations make it difficult to gain a reliable, organization-wide view of how work actually gets done.
RPD aims to overcome these limitations by using digital tools and data-led techniques to streamline the process. It combines three core elements:
Rather than relying on extended interviews, use short, structured surveys that can be completed in under 15 minutes per person. These are designed to capture a wide range of perspectives with minimal time investment from staff.
Process survey responses using generative AI to identify common patterns, inconsistencies, and pain points. This enables a broader and more consistent view of how processes operate across the organization.
Use insights from the survey analysis to build visual process models, enriched with key metrics, pain points, and contextual commentary. These models serve as a shared reference point for further analysis or change initiatives.
This approach is not intended to replace all traditional discovery methods, but to provide a more efficient starting point, particularly when a high-level view is needed quickly, or when time and resources are limited.
RPD has practical constraints in mind, offering a range of benefits including faster results - insights can typically be delivered within a 10-week period. A technology-led approach allows for fixed pricing and clearer scoping, while short surveys mean less disruption to staff and analysis tied to process metrics, enabling links to performance indicators like EBITDA, CAC, or cost-to-serve. Process knowledge is made explicit and structured, reducing dependency on individual subject matter experts, and the outputs from RPD can support future automation or AI efforts, thanks to structured, reusable process data.
RPD is particularly relevant when time is limited or when a broad, consistent view is needed across multiple teams or departments. It may be useful in several contexts, including:
To bring the process to life, let’s look at what a typical RPD engagement with Clarasys might look like. It would take around 10 weeks and follow a structured, phased approach:
Initial planning and alignment with leadership to define objectives, scope, and communication plans.
Survey design and identification of key teams and systems with a small group of internal stakeholders.
Survey rollout, AI-driven analysis, and model development. Targeted follow-up workshops with a focus on priority areas.
Findings and models are reviewed with the client team, with a focus on next steps and prioritization.
This structure is designed to balance speed with thoroughness, providing usable insights without the delays or overheads of more traditional methods.
Being clear on how your organization really works is essential, but the path to that understanding doesn't need to be slow or disruptive. RPD provides a practical approach that combines digital tools with structured analysis to deliver insight faster and more efficiently.
While it won’t answer every question, it can provide a valuable foundation for more targeted follow-up, helping organizations make informed decisions based on a clearer operational picture.
If you're exploring ways to better understand your operations or prepare for change, download our brochure or contact us to discuss how RPD could help you.