Process Modelling to Enable Scalable Delivery

Project Overview

A mid-sized organization was preparing to modernize core systems, but their processes lived in people's heads and scattered documents. Without a clear shared understanding, delivery teams were misaligned, and decision-makers couldn’t evaluate trade-offs or define priorities. The project focused on translating business operations into visual, decision-ready process models that could support both system design and team alignment.

The Challenge

No centralized view of how work flowed across teams or systems
Stakeholders had differing mental models of the same process, leading to conflicting requirements
Existing documentation (where it existed) was either too technical or too vague to support decision-making
Process improvement efforts were stalling due to unclear ownership and a lack of transparency

The Approach

Conducted collaborative discovery sessions to surface the real flow of work, including exceptions and manual workarounds
Used plain-language mapping to reduce abstraction and bring alignment between business and technical stakeholders
Layered process maps from high-level overviews to detailed swimlanes, supporting different audiences and purposes
Identified decision points, bottlenecks, handoffs, and opportunities for automation or redesign
Embedded context and rationale into the models, so they could evolve beyond static documentation

Key Deliverables

End-to-End Process Maps: Visualized workflows across departments, tools, and teams
Decision Trees: Outlined conditional logic for key decision points within processes
RACI Diagrams: Clarified ownership and accountability at each stage
Process Narratives: Accompanying documentation describing rationale, dependencies, and business rules
Improvement Backlog: Prioritized list of known pain points, friction areas, and potential automation candidates

The Impact

Aligned stakeholders around a shared view of current-state operations, reducing rework and miscommunication
Enabled development and product teams to scope solutions based on real-world workflows, not assumptions
Provided a foundation for future automation and system enhancements
Shifted process knowledge from individuals to the organization, reducing key-person risk and supporting scaling

What Made This Work

By meeting teams where they were — combining interviews, whiteboarding, and lived experience — I created process models that felt real and useful, not academic. The result was documentation that people actually referenced, shared, and used to guide better decisions.