From 2006 to 2016, full service restaurant (FSR) sales kept pace with the overall restaurant industry, increasing by 56.58% to $291.4 billion compared with a 55.77% growth rate for total restaurant sales of $658.6 billion for the same time period. With the growth of so many dining alternatives, however, it is more difficult than ever to compete as a table service restaurant. Starting in the early 2010s, infrastructure-as-a-service (IaaS) gave restaurants access to cloud-based solutions, meaning they no longer had to have computer servers heating up their back rooms or deal with space and time constraints that took away from managers’ day-to-day routines.
Since then, off-premises ordering has skyrocketed, with 67% of restaurants in a 2019 survey agreeing that curbside pickup is more important than two years ago. According to the same survey, the majority of restaurant operators said that off-premises ordering generates more sales, adds new customers, increases profitability, and boosts check averages. As we covered in last Friday’s post, FSRs need to reconsider many aspects of their restaurant’s design, packaging and product offerings in order to compete effectively, emphasizing the need for better technology management to maintain a consistent experience for consumers regardless of how they choose to order.
Artificial intelligence (AI) can now be found in a multitude of technologies for table service restaurants, including an app that allows for guests to order, split checks, and even pay before being seated. Through integrating with a restaurant’s existing point of sale system, more apps are capturing sales data and using AI to adjust the rate at which they send orders to help ease strain on restaurant staff during peak hours. When combined with other POS integrations that give restaurants more control over their employee scheduling, food costing and inventory management, automated reservation apps can increase restaurants’ return on investment and improve guest satisfaction by creating a steady flow of prepaid customers rather than the usual boom and bust cycle that comes with walk in-only business.
In the age of cloud computing and AI, here are some tips your restaurant can’t afford to overlook when implementing different technologies:
Let Historical Data Guide Your Future Purchases
As we covered in our post on PAR’s acquisition of Restaurant Magic, analyzing historical consumption and sales data allows restaurant operators to know when to reorder. Restaurant Magic’s Data Central provides your restaurant with often-overlooked aspects of inventory management, including thaw and preparation times, vendor delivery schedules and tracking each ingredient individually.
Tracking individual ingredients not only helps restaurants maximize their margins by switching to cheaper foods when prices go up, it prepares restaurants to handle foodborne illnesses. According to the CDC, contaminated foods negatively affect 48 million people and cost companies $15.6 billion every year, creating many opportunities for things to go wrong if you’re not able to correctly identify the source of an outbreak. Restaurant management software allows you to quickly perform a cost analysis, so you won’t have to worry about drastically reducing your profit margin when swapping out ingredients.
Create and Optimize Zones for Servers
Hosts are often the first impression customers will get of your restaurant, and many table service restaurant owners and operators rightly focus on the intangible aspects of this job. For example, they may train them in opening the door, greeting guests by their names, and making the time go by faster through recommending bar drinks and appetizers to order while guests wait for a table.
With the start of Yelp in 2004, restaurants began to focus on generating positive experiences, leading to more pressure on hosts to address issues before they escalate to restaurant managers. According to one study, restaurants that raise their Yelp rating by just one star can increase their profit by as much as 9%. In order to make this happen, you should train your hosts to seat guests evenly through all servers’ zones to avoid disparities between your wait staff in terms of tips and workload. Traditionally, this has been a manual process, but table management software can integrate with POS systems and kitchen display systems (KDS) to set up zones for servers based on historical sales data, informing hosts on the best ways to seat guests for that particular time of day.
Account for the Unplanned
Spoilage, spillage, wrong or inaccurately prepared orders, giveaways to handle customer complaints, and stolen food are just some of the unplanned scenarios that can deplete your inventory and disrupt your operations. By syncing accounting software with your POS system, you can more accurately estimate inventory write-offs and adjust your purchases to account for slower than expected sales.
Labor management and scheduling tools allow you to compare actual hours with scheduled hours, and some technologies are incorporating machine learning to make schedule adjustments based on gaps between the two metrics. One technique, called deep reinforcement learning, uses the same technology behind the algorithm that allowed a computer to win the Go board game against the best human players in the world just 40 days after learning the game from scratch. Deep reinforcement learning maps out various permutations of scenarios, from employees not showing up for their shift during peak hours to too many workers scheduled for a slow time of day, in order to find the ideal combination of variables that maximizes a particular goal, like reducing nightly labor costs.
To learn more, check out our post on using AI to transform your restaurant’s workforce.