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Food Costing
Culinary OS

The Food Data Mastery Checklist

July 30, 2021

The phrase data is power is a modern cliche, but in the enterprise food world, we’re just waking up to how true it really is. Mastering food data is the single greatest lever an enterprise food business can pull to maintain and accelerate healthy growth.

Tracking the right metrics enables you to measure operational efficiency, quantify improvements (or slow-downs) over time, identify clear growth paths, command higher margins, and build a more resilient business.

It’s the difference between a slow-moving giant that rivals can run circles around, and the titan that’s always one step ahead of the competition.

We’ve worked with dozens of growing food businesses over the years and have identified the eight essential metrics that make up a healthy food data system. These metrics inform each other, creating a system loop that’s ever-informing itself and offering you greater precision and control over your operations and profitability.

Food Costing

Food costing metrics give you power to optimize for profit margins across accounts, concepts, and geographical locations. Very few enterprise food businesses track them effectively—if you can command these three data points, you’re already ahead of the curve.

Food Cost Per Recipe

How It Works

The standard food costing system is too high-level to be actionable. It typically looks something like this: Starting Inventory + Purchasing Inventory - Ending Inventory = Food Cost. Calculating food costs this way is helpful for recordkeeping, but it doesn’t enable insight in real-time. Only after the fact, since calculations are generally made looking 1-2 weeks backward.

Instead, we strongly suggest having crystal clarity about your per-recipe food costs in real-time. Imagine being able to look at vendor pricing and current recipes, and know exactly what your profit margins are for today—the benefits of that are compounding.

Housing all your recipes in a single hub, then connecting that hub to live vendor pricing, allows you to see real-time costs and margins.

What It Enables

  • Optimize Recipes — Breaking out the costs of a recipe by each ingredient offers powerful clarity into which recipes are most profitable. Your culinary team has the data it needs to optimize recipes for both flavor and profitability.
  • Pivot Quickly — Vendor prices change frequently, and if the cost of an ingredient shoots up unexpectedly, you’re capable of identifying it—and all the recipes it impacts—in real-time. Now you can make adjustments, like substituting ingredients, at a moment’s notice to ensure you don’t have a low-margin day.

Food Waste Cost

How It Works

Understanding food waste—especially at the scale of a growing enterprise food business—is essential to mastering costs, margins, and financial planning. Unfortunately

We suggest measuring trim yield on a per-recipe level, going so far as to measure the trim of specific cooking techniques, like dicing vs skinning potatoes. When you input measurements in your food ERP, you can precisely see how much food you’re wasting across recipes and menus.

What It Enables

  • More Accurate Costing — Most food costing formulas and software lump food waste costs in with the rest of COGS, failing to identify exactly how much money you spend on food that isn’t plated. Isolating food waste cost gives you a clearer picture at how the margins of your recipes and menus are harmed by waste.
  • Food Waste Control — Tracking food waste cost means you’re also tracking waste generally. With this data, you have greater control over managing trim and spoilage across all your locations.

Inventory and Purchasing

Food costing is essential for strong planning, but things don’t always go as planned in the kitchen. An inventory and purchasing system that captures information in real-time can inform your team exactly what to buy, and when, to achieve the most optimal flow of ingredients.

Predicted Demand

How It Works

Gathering the ingredients and tools you’ll need for the next menu cycle, whether that’s weeks or months long, can only happen when you have an idea for how much of those you’ll need. To get an idea, you’ll need to make some predictions.

Demand predictions are almost always based on historical trends, but the COVID-19 pandemic revealed that we need to be more lean and agile to remain resilient. We suggest leveraging machine learning to make more precise and dynamic demand predictions.

What It Enables

Purchase For What’s Next — Rather than only using historical data to purchase ingredients for what happened last time, layering in real-time trends, most easily spotted with machine learning help, gets you away from the theoretical and allows you to purchase for what’s about to happen with greater accuracy.

Real-Time Inventory and Shelf-Life

How It Works

Taking inventory is standard procedure, but few cycle count systems can account for shelf-life and spoilage. Agile food organizations can measure not only what they have currently, but what they’ll have days from today.

Taking existing stock measures a single data point: what we have right now. Calculating shelf-life with every count introduces another data point: how long it will remain viable. Now that there are two data points to measure, you can track change over time.

What It Enables

  • Smarter Purchasing — Imagine counting 14 days worth of potatoes. If you’re tracking shelf-life with every inventory count, you’d see that half will spoil in 10 days. To meet your predicted demand for the next two weeks, you’ll need to order more potatoes than it initially would have appeared. Purchasing with shelf-life as an additional data point, spread across hundreds of ingredients and locations, can mean the difference of thousands of dollars in waste per year.
  • Cross-Utilization — Now that you can clearly measure ingredients that will spoil before being put to use, you can do something about it at scale without compromising your ability to meet upcoming demand.

Purchase Lead Time

How It Works

Ingredients don’t arrive immediately when ordered. There’s a period between when the order is placed and when the food will actually arrive at your various locations. The purchase lead time is the measurement of that period.

Measuring purchase lead time—whether it’s 24 hours for fresh tomatoes or six days for a rare type of mushroom—shows you how far in advance you need to order certain ingredients in order for them to arrive when you actually need them.

What It Enables

  • No More Late Orders — Vendors have differing shipping schedules. Some ingredients take longer to procure than others. And remote locations might require an extra day for far-away supplies to arrive. With accurate purchase lead times, you can plan for it all.
  • Optimized Inventory Flow — Predicted demand identifies what you need. Inventory shows what you have today. Shelf-life reveals what you’ll actually have tomorrow. And purchase lead time reveals when to order to ensure you always have exactly what you need, right when you need it.

Day-to-Day Production

You have precise costs and margins, and your purchasing system is running like a well-oiled and efficient machine. Now it’s time to track the metrics that help you optimize daily production.

Food Prep Workflows

How It Works

You already have documented processes for different techniques and workflows in your kitchen, like how to chop onions or pack a dish for takeout. The next step is to time all those production steps, then fit them together like puzzle pieces to form a more efficient workflow.

When you measure exactly how long it takes to slice chicken breasts, cook them, and prep them into a finished dish—then do the same for the accompanying potatoes and salad—you can more effectively divide labor and batch production like a high-efficiency manufacturing facility. This approach is particularly valuable for commissary production models.

What It Enables

  • Lean Manufacturing — Organizing your production kitchens through a Lean Manufacturing lens gives you unprecedented clarity into how to organize labor and delegate tasks to complete the most number of dishes possible in a given amount of time, with the lower amount of workers.
  • Production Flexibility — With a clear division of labor and expected output, you can quickly shift around recipes, prep techniques, and cooks to re-optimize as your menu or environment changes, then measure performance improvements.

Future Kitchen Labor Cost

How It Works

Like with food costing, large food organizations tend to look backward when estimating future labor costs. Historical trends can offer some guidance, but when you’re managing hundreds or thousands of line cooks, the importance of precision when predicting future costs can’t be understated.

When you adopt a Lean Manufacturing kitchen approach, you can attribute costs to production steps. For example, a stir fry dish is made via three steps—chopping, stir frying, and packaging. Since you know exactly how long each step takes and how many cooks it takes to produce x number of meals, you can also calculate labor costs per step too.

What It Enables

  • Forward-Looking Labor Costing — Now you can take the menu and demand prediction for next week or month and break down upcoming labor costs in advance, rather than having to look back after the fact.

The Problem: Disjointed Software Doesn’t Get You There

We’ve seen it all: management teams using dozens of tools and hundreds of spreadsheets to run their growing multi-unit operation. The problem is, the data from these tools and sheets is siloed off, unable to communicate with the data from other tools.

That’s why we built Galley, the single hub for all your food data

It doesn’t take long for good data to become messy data as prices, workflows, teams change—which happens every few days.

That’s why we built Galley, a Food ERP built just for enterprise food organizations. With a single hub for all your food data, you can track the metrics that are most essential for your business with unprecedented clarity (something repurposed accounting ERPs can’t dream of for complex food businesses).

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