Restaurant Data: Segment by Segment

When you imagine “the modern restaurant” what do you see? Sleek, frictionless surfaces gleaming beneath blue lights? Automaton chefs, synthetically intelligent, putting space-age technology to work? Space cruisers? Food replicators? OK. We might not be there (yet), but we’re close. As restaurant technology pushes us, operator and consumer, closer and closer to automated futures, it does beg the question: what makes a restaurant modern? What makes it smart? What makes it futuristic? Sure, a swanky menu loaded with trendy items will help. Branding and a buzzworthy location factor in as well. A cool website and off-premise dining options will supplement your reach. But deep in the heart of a smart operation, between restaurants of every segment, lies one common trait: restaurant data. Restaurant data can be an open-ended concept, encompassing many different facets, from your finances to your inventory. By utilizing restaurant data and smart analytics, you can get a whole-picture view of your restaurant to identify weaknesses in your workflow. Restaurant data is the “language” your devices use to make adjustments in real time. It’s what powers an off-premise dining strategy!  Still, what’s pertinent data to a small operator may not matter to one running a national chain. Our list should be a  “launch pad” for restaurant operators in various segments and business types. It details the data you should be collecting, how to do it, and how it can help your restaurant.

Restaurant Segments

Quick Service

In this space, your primary concern is taking orders and processing them quickly. Guests typically come to a QSR to get their food ASAP, without the table services present in other segments. With this in mind, the most critical area of your restaurant is the kitchen or back-of-house.

The Quick Service Operator Should Track:

• Cook Times: This metric indicates the start and finishing time of an entree. It’s the measure of how long it takes to prepare. Quality technology will even show you the average cook times for an item so you get a specific idea of its prep time in a given environment.
• Plating to Table/Counter times: When your food finishes cooking, how long does it take to get from the kitchen, out to the floor? This metric helps determine your efficiency and speed as well as the entree’s freshness.  An inflated plate-to-table figure means that an entree has been sitting beneath a heat lamp for longer, wilting and drying out.

How to track:

These data streams make up your speed of service, the metric you use to determine how efficiently you’re processing orders. These speed of service figures help in targeting bottlenecks in your kitchen workflow, so technology, like a kitchen display system, will come in handy. Look for a device with convenient analytics features (like reports), as well as “expo views” that section the different areas of your kitchen, for more targeted quick service restaurant analytics. For example: is there only one particular grill that’s having problems over another? By analyzing peak traffic times, and where these metrics dip and fall, you can strategize around your kitchen staffing.

Fast Casual

Fast Casual restaurants include many of the calling cards present in quick service, with an added emphasis on guest management. Fast-casual guests can be a bit of a “toss-up” with their dining preferences, some eating in-store with many dining off-premise, so being versatile, yet consistent, is the aim. With these fast-casual data metrics, operators should seek to manage off-premise pick-up, delivery, and walk-in traffic, without diminishing any diner’s experience.

The Fast Casual Operator Should Track:

• Average party size – This helps you determine how many guests you’re likely to see per order. While fast-casual restaurants don’t typically offer table service, it’s still useful to consider with limited seating. You can also determine the average party size at different times of the day. Does this figure increase later at night? If so, you can plan for it.
• Average Order – This data shows the average amount a guest spends in your restaurant, per visit. By analyzing trends and upticks, you can determine peak hours, shifts and seasons for revenue.

How to Track:  

To track this data, you’ll need technology that integrates with your point-of-sale system. With traffic coming in from such varied sources, capacity management features, like order throttling, will streamline it all. A Kitchen Display System with these features can interpret the workload in your restaurant to validate your existing bandwidth. When your restaurant is particularly busy, a good KDS will throttle orders and adjust off-premise pick-up times to account for it. Then, when things cool off, these off-premise quotes will adapt. This feature helps off-premise guests receive their food hot, fresh, and without a wait while walk-in traffic continues uninterrupted.

Casual Dining/Table Service

While every restaurant operator should prioritize the guest experience, casual dining restaurant data provides a window into that experience. It’s in this dining sphere where an atmosphere, i.e., the unspoken “vibe” of your restaurant, should shine. Guests come expecting a low-stress meal. Since casual restaurants generally offer table service, your back-of-house processes should be in order along with their guest management outreach. Another challenge is staying conscious of the actual seating real-estate on hand.

The Casual Dining Operator Should Track:

• Wait times: How long will a guest or party wait to order and be seated?
• Turnaround Time: The metaphorical “lifespan” of a guest in your restaurant. Turnaround time tracks how long it takes them to order, be seated, eat and then leave.
• Seating Efficiency: A metric which lets you know how well you’re using your available seating, in relation to the number of guests in your store. The ultimate efficiency benchmark is 100% here, though it’s not always feasible.

How to Track:

There’s no way around it; you’ll need a restaurant reservation system to track this data in real-time. Besides the advantages of reservation and waitlist features, the benefit of an automated solution is that you can obtain this data, as well as historical averages, to identify times, places and circumstances in your restaurant where these metrics inflate. For example: if you notice your turnaround times routinely swell on Thursdays, you can make a staffing or kitchen decision to account for the uptick.

Fine Dining

The fine-dining restaurant utilizes all the stations and processes in this list and then some! These restaurants promise a top-tier dining experience, exceptional food and an atmosphere of prompt service and class. Guests typically pay a premium for an evening in your establishment, will reserve their seats in advance and dress up formally.

The Fine Dining operator should track:

• Wait times, turnaround and seating efficiency: We can collectively call this data “table service data.” This table service data is crucial to fine dining restaurant analytics. As in the casual dining example, any restaurant that seats guests should keep a close eye on their performance, and where they can improve.

How to Track:

With such emphasis placed on guest experience, you want a robust waitlist device that integrates with your back-of-house technology. With these integrations and features like real-time order status and capacity management, you’ll keep your orders perfectly coursed, hot and fresh. Furthermore, connected technology, which considers your entire restaurant from the kitchen to the floor, will prevent you from overbooking.

Catch-All Data:

This list is meant to be a focused starting point. Restaurants should really track all the data presented in this list, not just those restricted to a particular section. With that, here are some pertinent data for operators in every segment:

• Inventory Management – This data denotes the physical resources you have on hand. Technology can help you manage your stock and strategize around future purchases.
• Customer Data – Some restaurants may find it useful to track customer data, like contact info, to target their marketing efforts. Many restaurants utilize this data to structure their rewards and loyalty programs. Remember that while this data is often available in the point-of-sale system while you’re using it, not all companies let you “own” it.
• Recipe Data – If you’re running a multi-unit restaurant (we’ll get to that soon), a technology solution, like a recipe viewer, which stores your recipes and in an easy-to-read way helps maintain consistency across them.

Restaurant Business Types

Independent

Independent restaurant operators must wear many “hats” in their efforts. Most decisions are made by one or two individuals who have to handle staffing, finances, marketing and operations processes themselves. In turn, granular restaurant metrics trotted out in corporate boardrooms probably won’t hold much sway. The most pertinent data feature an independent operator can use is something that integrates, like a KDS which can integrate with multiple point-of-sale systems. Many restaurants, especially independents, go through many POS systems in their lifespan. Seeking restaurant data technology which is known to integrate with these, as well as your guest management system, helps you protect that back-of-house investment. In other words, no matter how many times you change your POS, you can keep the same KDS. From there, an independent can use focus their data analytics efforts to generate repeat business, like customer data to enrich a focused loyalty program.

Multi-Unit Restaurants

A Multi-unit operator, whether in quick-service or fine dining, must think about their data and the way it relates to all of their sites, not just one. For data analytics, choose something accessible from a central, or portal location, to track data on all their different restaurants. Obtaining targeted speed of service metrics from a KDS can help you determine which of your sites are performing well at various times, and which need additional concentration. Additionally, redundancy and recoverability features become increasingly vital at this level, as they’ll help your processes stay up and running should something else in the chain (like WiFi) go down by rolling to a backup server. Redundant features prevent you from losing everything in the moment and help you recover when you’re back up and running.

The Large Chain

At this level, operators are looking to optimize every parameter and corner of their restaurant (sometimes across continents!) to fire on every cylinder, and add to the bottom line. Besides the data mentioned above, large chains need robust, customizable features for specific goal setting in particular sites or regions. Customization helps you focus on the restaurant data most relevant to a store. Many restaurant analytics tools allow you to set specific thresholds for metrics like turnaround or plate-to-table times. When a time exceeds this metrics, it will indicate negatively on the report. If you’ve got one site which consistently outperforms another, you can adjust these thresholds accordingly. Ultimately, restaurant data “happens” whether you track it or not. It doesn’t matter what segment you’re in, or your primary customer base. The key to a modern restaurant is smart data and analytics. Those restaurants who monitor their data can make actionable changes in their workflow and communications, guest satisfaction metrics and their revenue. Subscribe to the blog for more interesting restaurant content!

---

About the Author

Brian leads the Implementation, Project Management, Training, and Support Services groups, guiding customers to get the most out of QSR products. He has dual degrees in Information Systems and Operations Management and is a big baseball fan—he’s visited most of the Major League Baseball parks and loves spending summer evenings at Louisville Bats games with his family.