Rising labour costs and tightening margins mean many multi-site hospitality operators only identify issues when monthly reports arrive, often too late to take action. While large volumes of data exist across EPOS, labour and finance systems, this data is typically fragmented, siloed across different platforms, trapped in Excel spreadsheets, and difficult to interpret at site level.

This was the challenge facing both Tortilla and Pho, whose teams spent hours consolidating and manipulating data yet still lacked clarity on controlling labour cost, underperforming venues or early sales declines.
Join our session to see how they addressed it using Ometis' A.I.I. Framework:
Automation – reduce manual processes, and spot problems earlier
Insight – uncover patterns buried in fragmented systems
Innovation – use forecasting and modern tech to make better planning decisions

Both operators gained clearer visibility across their sites and can identify performance issues far earlier, without replacing core systems.