Repetitive Task Pattern Identification
Most operational inefficiencies go unnoticed because teams are too busy executing to observe. I built a systematic approach to step back from BAU execution and analyse the patterns beneath it — identifying which tasks were truly repeatable, which required judgment, and which could be automated entirely. This work became the foundation for all subsequent automation initiatives.
"Repetition is not work — it is a signal." I started logging recurring tasks not just for volume, but for structure. What triggered them? What decision was made? What was the output? After weeks of observation, patterns emerged that no one had formally acknowledged.
Observed recurring workflows across multiple delivery programs over several months. Tagged each recurring task with: trigger type, action taken, frequency, variation level. Categorised into Repeatable (same trigger → same action, every time) and Variable (requires judgment, context-dependent). Repeatable tasks became automation candidates. Variable tasks became targets for better decision frameworks.
Observation + structured logging · Excel tracking system · Internal delivery dashboards · Pattern frequency analysis
Task → Pattern Detection → Frequency Mapping → Logic Extraction → Standardisation
Built the analytical foundation for all subsequent automation work. Reduced redundant effort across the team. Created a shared language for talking about operational inefficiency. Improved team awareness of process gaps that had previously been invisible.
Repetition is operational data. Organisations that fail to analyse it remain inefficient; those that leverage it unlock automation opportunities. The first step is simply deciding to look.