How &pizza Delivers Self-Service Performance Analytics Across 46 Locations With Sapien

About

&pizza is a fast-casual pizza company founded in 2012, known for its custom craft approach and strong presence in the Washington D.C. metro area. The company operates 38 company-owned shops and eight franchised locations across five states, with a lean corporate team of about 20 people. 

Challenge

Manual data processes couldn't keep up with daily performance questions

With 46 locations competing against much larger national chains, &pizza operates with a fraction of the corporate overhead. That lean structure means every function has to maximize efficiency, including analytics.

As SVP of Strategy and Analytics, Doug Poppen maintains a complete view of how the business runs: financial planning and analysis, operations performance insights, and marketing analytics covering traffic and loyalty. The problem: he was effectively a team of one for enterprise analytics.

&pizza ran on an internal data warehouse containing transaction, customer, and labor data, with dozens of SQL queries on top feeding manual CSV and Excel-based reporting. Some queries ran automatically on daily or weekly schedules, but any question outside those pre-built reports required manual intervention. If Doug needed to understand why performance unexpectedly deviated from the forecast, the existing SQL query needed to be modified, and the raw data pulled, exported, and manually analyzed.

Root cause analysis was especially time-consuming. To isolate which stores were driving elevated or decreased performance, Doug had to drill down into the data and analyze multiple factors: traffic, product mix, store-level dynamics, and daypart patterns. Then he had to triangulate the results. A question that should take minutes with tools like AI could consume hours.

And that created a bottleneck. Store managers and district leaders had to depend on static daily or weekly PDF reports to analyze performance. They had no way to ask their own questions and receive insights in real time.

Doug knew that operating without self-service, ad-hoc analytics meant slower reactions to performance changes, with more time spent on manual data work instead of strategic decisions. He evaluated both traditional BI tools and restaurant-specific analytics solutions, but both paths would have required dedicated headcount to build and maintain dashboards. 

What Doug needed was the ability to understand profitability and the impact of his decisions on a per-store basis. And given his small analytics function, he needed something that did not require additional IT resources.

That meant an AI platform that could connect to existing data sources and let users ask questions in plain English instead of writing SQL or waiting on analysts. That's when he found Sapien. 

“When we see variances that deviate from the forecast, it's important to quickly dive in and assess the root causes. We'd have to modify a SQL query and go through the raw data manually. We didn’t have the time or layers to fully flush out all the nuances that occur in a restaurant environment week in and week out.”

‍Solution

AI-powered analytics built for multi-location restaurant operators

Sapien's core value proposition fit &pizza's needs: an AI-native platform that lets teams run natural-language, ad-hoc analysis across unified sales and labor data without writing SQL or learning a BI tool. 

Flexible onboarding for a lean team

With a small IT team and a third-party vendor managing their data warehouse, &pizza needed an implementation that could flex around limited internal bandwidth. Sapien worked within those constraints, gradually connecting transaction data, product mix, daypart, time-of-day patterns, and store-level labor performance so the first module was genuinely useful on day one.

Sapien's open-ended, natural-language query model was new for the team. Sapien’s specialists spent time helping Doug and his colleagues unpack their existing reporting habits and turn them into plain-English questions the platform could answer. That groundwork made it easier to roll out across locations to non-technical users.

Self-service analytics across 46 locations

After connecting &pizza's data warehouse and restaurant systems, Sapien was functional within a day. Within roughly three months of starting implementation, Sapien was fully live across all 46 locations. Every shop leader and executive now receives a daily prompt at 7:00 a.m. confirming the platform has fresh data.

Sapien automated the daily sales report, turning what used to be a static PDF into an interactive, natural-language workspace where operators can drill into any time range or metric on their own. Store and district leaders now diagnose traffic drops or LTO performance in minutes instead of waiting for the next static report cycle, enabling faster decisions that improve shop-level performance as &pizza continues to expand.

While traditional BI would require predefined dashboards and heavy report building, Sapien lets &pizza's teams ask open-ended questions in plain English and get explainable, drillable answers in minutes.

From manual Excel workflows to AI-driven insights

Doug now uses Sapien to replace manual, Excel-based workflows with automated, audit-ready analysis. He can identify common factors among the top five highest-performing and bottom five lowest-performing locations across any dimension. That includes traffic trends, lunch versus dinner performance, and operational metrics.

For example, Doug can now compare the most recent limited-time offer's performance with the same period last year and analyze store performance before and after a nearby competitor opens. As &pizza asks more questions, Sapien's Company Engine learns their definitions of locations, products, and daypart breakdowns. At the same time, AI agents suggest relevant follow-up questions that help Doug dig deeper into root causes he may not have considered on his own.

Over time, the system adapts to the patterns in &pizza's questions instead of requiring a library of pre-defined reports.

When Doug flags an area of friction or suggests improvements, he often finds Sapien's team already working on those enhancements or shipping updates quickly, proactively supporting &pizza’s growth.

“Sapien reduces my workload answering important but low enterprise impact questions as a team of one. Now shop leaders aren't beholden to a static daily report. They can view their business over any span of time, which is invaluable.”

Results

Faster decisions at store and district level

Doug and the leadership team now structure future promotions based on clear patterns in store performance and competitive openings. Store and district managers make confident decisions because they can get answers quickly instead of waiting on corporate. That helps &pizza to respond faster and more confidently when they launch new offers or respond to local competition.

1. Saved 3+ hours per week in total across IT, Finance, and Analytics by eliminating manual workflows and cross-team handoffs

2. Fully automated daily sales reporting, replacing a previously manual, error-prone process

3. Rolled out AI-powered analytics to 46 locations in under 3 months, fully live in days after connecting

&pizza plans to expand Sapien's scope by adding cost of goods, food costs, and paper costs into the platform. 

"Sapien has clearly helped us take a very different look at how we evaluate the business. As we grow, we have a partner that’s proven to support and accentuate our growth and maturity."