Cao Bakery & Café: Rebuilding The Operating Layer Behind 23 Locations
Cao Bakery & Café operates bakery-cafés across South Florida, running its own corporate stores alongside a franchise network, all supplied out of one central commissary. An embedded AI partnership is rebuilding the operating layer underneath the group, so a growing franchise runs like an AI-native business without replacing the systems it already has.
The Challenge
Cao Bakery & Café has grown into twenty-three locations across South Florida, sixteen of them corporate and seven franchised, all supplied out of a single central commissary. Stores carry drive-thru service alongside the full bakery and café menu, more than two hundred people work across the system, and new locations keep opening. The back office grew with it: regional managers opening stores, a franchise support function, and a finance team closing the numbers for every site.
The operation was already working. The point of sale, the accounting platform and the delivery platforms each did their job, and the team knew how to run them. The constraint was growth. Every location adds another set of daily numbers to check, another payout to reconcile, another set of monthly goals to build, and that coordination work scales in a straight line with the store count. None of it appears on an org chart and none of it can be skipped, so the more the brand opens, the more operational overhead the group carries.
Our Approach
OTZ did not replace anything the group relies on. We built an intelligence layer above the systems already in place, so the routine numbers keep moving on their own and the people running the business spend their time deciding rather than assembling. Finance came first because it touches every location and its numbers are unarguable. The group's own team feeds a shared backlog covering every idea, bottleneck and recurring task, and we score each one on value against complexity and sequence them together on a standing weekly call. Priorities are reset monthly, by the operators, against what the business actually needs that month.
Implementation Phases
A full inventory of where the manual effort actually sits across the bakery group and its affiliated businesses: who does it, how often, how long it takes, and what breaks when they are out. The output is a prioritized roadmap and a shared backlog the client contributes to directly, so the queue reflects the operators rather than the consultants.
Monthly management-fee invoicing across every location now runs on a schedule and arrives ready for the controller to review. She approves rather than assembles. What was a recurring multi-hour build each month became an approval step.
Each location's monthly sales goal, and the day-by-day calendar managers work against, now arrive for review already built and already reasoned. Operations challenges and adjusts rather than starting from a blank sheet, and the system explains its own thinking per store so the recommendation can be argued with rather than taken on faith. Prime-cost targets sit alongside the sales goal, so a manager sees what they are allowed to spend to hit it, not just what to sell.
Daily cash and sales figures now line up across locations on their own, and close cleanly without anyone chasing them. A person looks at the exceptions rather than re-checking every store, every day.
Weekly third-party delivery payouts are reconciled to what actually landed in the bank, with the platform fees properly accounted for.
Payroll hours and pooled-tip preparation, a weekly cash-management routine for store managers, and a cluster of work on the affiliated property business covering lease renewals, tenant payment history, and fee enforcement. Re-prioritized with the operators every month.
System Architecture
The group's existing sales, labor, accounting, delivery and property systems, with no replacements and no migrations
- A shared backlog the client's own team feeds, scored on value against complexity
- Work sequenced together on a standing weekly call and re-prioritized monthly by the operators
- Recurring manual tasks rebuilt as review-and-approve steps rather than build-from-scratch steps
- Exceptions routed to the named person who owns them, instead of everything routed to everyone
- Every recommendation shows its reasoning, so operators can challenge it rather than trust it blindly
- Recurring finance work that runs on schedule without being chased
- Operators reviewing and deciding rather than assembling
- Time given back to the people carrying the coordination work
- A prioritized queue the client controls, month to month
The governing rule across every workflow: if the numbers do not tie, nothing is approved automatically. It gets flagged and a person looks at it. A finance system that reports an approximation as an actual destroys trust in everything else it produces, so where a step cannot be done accurately end to end, the work stops and hands off rather than guessing.
Results & Impact
The monthly goal calendars store managers work to now arrive built and reasoned, turning most of a working day into a review
Cash and sales figures land where they need to be across every location without the finance team chasing them store by store
Corporate stores, franchised stores and the central commissary running off a single prioritized queue, re-sequenced with the operators every month