ShootAtlas

Identify information silos in complex field productions.

• • On-site production audits
• • Workflow mapping of location crews
• • Analyzed schedule drift data

• • Underestimated the speed of on-set pivots
• • Assumed stable connectivity in remote zones

• • Central intelligence must be asynchronous by default

• • Designed for offline-first data persistence

Visualize the resource and schedule dependencies.

• • Created dependency graphs for assets and talent
• • Mapped signal flow from field to HQ

• • Initial maps were too linear for chaotic media workflows

• • Production is recursive; maps must reflect circular feedback

• • Updated system map to include multi-path escalation triggers

Test unified intelligence layer with active production teams.

• • Deployed mobile prototypes to location crews
• • Simulated resource failures to test response

• • Crews rejected high-friction data entry requirements

• • Data capture must be incidental to the workflow

• • Integrated automated signal detection to reduce manual input

Build the production orchestration layer.

• • Resource tracking system
• • Risk detection engine
• • Asynchronous sync layer

• • Over-built the feature set for talent management initially

• • Precision in logistics beats breadth in HR tools

• • Focused on critical resource pathing and schedule stability

Assess reduction in logistical waste and drift.

• • Schedule variance
• • Resource utilization
• • Information clarity

• • Vanity metrics obscured actual operational efficiency early on

• • Hours shaved per cycle is the only metric that matters to heads of production

• • Refined KPIs to focus on time-to-resolution for field signals