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The Employer Edit: Five Tactical Lessons from Restaurant Cheese Louise

  • Writer: Sara Horowitz
    Sara Horowitz
  • 2 days ago
  • 5 min read

When Cheese Louise opened its first brick-and-mortar restaurant in 2021 after several years operating as a food truck, its founders made a straightforward commitment: be the most people-focused restaurant they could imagine. At the time, that meant guaranteeing every team member would earn $20 per hour—which was more than what similar restaurants in the area were offering—but not yet tied to the local cost of living. A few years later, the living wage for a single working adult in Portland, Maine exceeded $20 an hour, and Cheese Louise had to answer a hard question: how do you maintain a durable pay structure when the cost of living keeps changing?


The answer involved a three-component pay formula anchored to the Living Wage Institute’s county-level living wage data, a creative tip-pooling model that backstops worker pay through slow seasons, and a performance incentive structure tied to team-level operational metrics. 


This employer edit, curated specifically for compensation and benefits teams, offers deeper insights on five tactical lessons from Cheese Louise’s experience building and sustaining living wage jobs from the ground up. For additional background, read the companion case study on the Living Wage Institute blog. 


Lesson 1: Benchmark to a location-specific living wage to address cost pressures


The cost pressures workers face aren't uniform, and critically, these pressures don't affect every community the same way. In New England counties, where Cheese Louise operates, both housing and childcare costs continue to push the cost of living up for workers. For employers operating across multiple markets, a single companywide wage floor calibrated to one location could systematically underestimate what workers might need in another location.


Cheese Louise directly encountered this. When the living wage in Portland, ME exceeded their original $20 floor a few years ago, it forced the company to build a more precise solution. They added a location-specific living wage adjustment to their pay formula on top of their base rate. Each year, the adjustment gets updated to match our latest living wage data. The result is a pay floor that reflects what it actually costs to live in each of their three markets: $27.48 per hour in Portsmouth (Rockingham County, NH), $26.51 per hour in Portland (Cumberland County, ME), and $24.23 per hour in North Conway (Carroll County, NH).



Lesson 2: Design pay structures so the company absorbs pay volatility


Tip-based pay is structurally unstable. Tips fluctuate with volume, and in seasonal markets like New England, the swings can result in strong summer earnings followed by months where pooled tips fall well below a livable wage. For most restaurant workers, that volatility shows up directly on their pay stubs, while exacerbating workforce churn for employers. 


Cheese Louise pools tips across all staff and uses them to help meet a living wage. When pooled tips fall short—which happens regularly in the slow season—the company makes up the difference out of its own operating budget. When tips are strong, any overage goes back to workers as additional income. 


This is a meaningful structural decision. Restaurant industry turnover exceeds 70% annually, driven in part by the income unpredictability workers experience. Absorbing that unpredictability at the company level changes the employment equation for workers entirely. With this model, employees can stay to build institutional knowledge and operational expertise that compound in ways reduced hiring costs alone don't capture.



Lesson 3: Tie performance incentives to team-wide metrics that align company and worker interests 


While a living wage sets the baseline, Cheese Louise layered in a performance bonus of up to $5.00 per hour. 


Rather than tying these bonuses to traditional server-style metrics that can create competition within teams, Cheese Louise uses team-level operational metrics that the whole restaurant has a stake in. One example is sales per labor hour (SPLH), which is a measure of how efficiently the team is converting labor into revenue. When SPLH improves, the bonus pool grows for everyone on the team. This creates a shared incentive across roles such that managers cut staff when it's slow, team members support efficient operations during rushes, and the gains end up distributed across the team rather than concentrated among top performers.


Cheese Louise's approach to metric selection is deliberate. Metrics are reviewed annually at a companywide meeting and reset once goals are met. Examples of metrics include ticket time (speed of order delivery), reward program signups, and add-on sales. The rotation keeps incentives targeted at areas of improvement rather than optimizing indefinitely for the same number.


The resulting performance bonus functions as a complement to the living wage floor, not a substitute for it. 



Lesson 4: Track business outcomes alongside worker outcomes


Research shows that higher wages are associated with lower turnover and absenteeism and improved worker productivity. Further, those gains can offset a meaningful share of the cost of wage increases. But employers often don't track the metrics that would let them observe this dynamic and calibrate their own operations.


Cheese Louise has been running this experiment in real time. Since enacting a living wage pay structure, the team has logged steady applicant flow for open positions and low voluntary turnover relative to restaurant industry norms. Especially in a sector where labor shortages and hiring difficulty are ongoing complaints, both represent a real operational advantage.



Employers looking to measure the business impact of a living wage investment should consider tracking baseline workforce metrics like voluntary turnover rate before and after a wage floor change, time-to-fill for open positions, and employee engagement. Productivity measures like sales per labor hour (SPLH) or revenue per employee can further showcase operational outcomes. 


Metrics won't always tell the whole story, but they provide an early signal on whether wage investments are generating returns.


Lesson 5: Communicate your pay structure transparently so workers understand what they're earning


A well-designed pay structure only delivers its full value if workers understand it. This is particularly true for multi-component structures like Cheese Louise's, where total compensation includes a base rate, a location-specific adjustment, tip pooling, and performance bonuses.


Cheese Louise has invested in building that clarity. For public-facing communication, their mission page includes a step-by-step guide on what a living wage is, how it varies by location, and how a living wage is guaranteed on average over the year. For internal communication, the team has developed pay stub explainers that walk individual team members through exactly how each component of their pay is calculated: what comes from tips, what comes from the company, and how the performance bonus fits in.


The discipline required to build this infrastructure is easy to underestimate. It’s an ongoing feedback loop that includes developing consistent terminology, drafting accurate descriptions of how each component works, aligning with internal stakeholders, and identifying the right moment to communicate all of it back to workers. Cheese Louise is still iterating on this, but their materials are an example of what transparent compensation communication can look like in a frontline employer context.


Cheese Louise's experience is specific to the restaurant industry, but the underlying design questions—how to set the right floor, how to absorb compensation volatility, how to tie incentives to shared goals, and how to communicate the full value of a compensation package—apply across many hourly and frontline employer contexts.


Interested in using our living wage data to anchor your own compensation strategy? Reach out to the Living Wage Institute team to learn more about our compensation data and tools.

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