Author : Tommy Yionoulis

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Predictive analytics helps Chicago prioritize restaurant inspections

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Found a really cool article on how the city of Chicago teamed up with the Civic Consulting Alliance and researchers from Allstate Insurance’s Quantitative Research & Analytics Department to put together a predictive model using 311 calls, previous inspections, permits, and other data points to identify high risk restaurants.  Here is what I found most interesting:

  • Leverages public data to identify Chicago restaurants most likely to face health code challenges, so health inspectors to prioritize inspections for those restaurants.
  • Using 311 requests, sanitation complaints at restaurants and information on previous inspections and permits, the researchers identified a group of factors that could lead to health code violations.
  • These factors were then brought together to create a predictive analytics model that was used to identify which restaurants should be inspected first in order to stop critical violations that could lead to illnesses.
  • The model evaluation calculates risk scores for more than 10,000 Chicago food establishments using publically available data, most of which is updated nightly on Chicago’s data portal.

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Using a tool like OpsAnalitica you can generate reports and conduct analysis like the city of Chicago on your locations.  They aren’t doing anything super special they are just using data points that they collect from a couple of different systems and bringing it together to identify risk factors.  If you were doing daily line checks, temp logs, daily logs and combining that data with sales, costs, and customer service data; you could have a complete understanding of how your operations really work and what things are driving costs and reducing profits.

I have clipped the article below, or to see the original article click here.

Chicago is using predictive analytics to better ensure food safety for city residents and visitors.

The new system, built by the Chicago Department of Public Health (CDPH) and Department of Innovation and Technology, leverages public data to identify Chicago restaurants most likely to face health code challenges, so health inspectors to prioritize inspections for those restaurants. “The use of open data will result in a more streamlined approach to overseeing food safety, targeting our resources at higher-risk establishments without compromising safety oversight at any food business across the city,” Mayor Rahm Emanuel said.

Research for the new system was conducted in collaboration with Civic Consulting Alliance and researchers from Allstate Insurance’s Quantitative Research & Analytics Department to identify various factors that can result in a restaurant facing health code violations.

Using 311 requests, sanitation complaints at restaurants and information on previous inspections and permits, the researchers identified a group of factors that could lead to health code violations. These factors were then brought together to create a predictive analytics model that was used to identify which restaurants should be inspected first in order to stop critical violations that could lead to illnesses.

The model evaluation calculates risk scores for more than 10,000 Chicago food establishments using publically available data, most of which is updated nightly on Chicago’s data portal.

CDPH performed a simulation that allowed it to identify establishments with more violations using the predictive model than using risk categories alone. As a result of these findings, CDPH is now using the predictive model to prioritize inspections among the highest risk establishments.

“Researchers, cities and the public are able to freely access and download all the information needed to replicate the research,” said Brenna Berman, CIO of the Department of Innovation and Technology. “Releasing the data and research on GitHub allows for collaboration with other scientists and institutions to improve the city’s forecasts and allows the technique to be adopted by other cities conducting food inspections.”

Funding for the project came from a $1 million award in 2013 from the Bloomberg Philanthropies’ Mayors Challenge to develop a data-based approach to decision making.

This isn’t the first time Chicago has used analytics to protect residents from food-borne illness. In 2013, the city developed a predictive analytics model to fight its growing rat population. The Department of Innovation and Technology used 311 city requests ranging from stray animal calls to vacant and abandoned buildings as well as missing or overflowing garbage cans and restaurant code violations. Through the requests and the model built to analyze them, the city could visualize on a map where and when rat populations spiked.

The same year, researchers in Chicago created another program called Foodborne Chicago, which examined Twitter for food poisoning complaints from residents, employees and tourists in the city. The program led to 150 additional inspections by the FSD that year.

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Scientific Trick to Increase Server Tips

I was watching this YouTube video, a summary of Robert Cialdini’s book Influence.   They talked about experiments that were run in restaurants and how the server’s used the rule of reciprocation to increase tips. The reciprocation principle recognizes that people feel indebted to those who give them a gift.  The social obligation to return a gift is overwhelming in some cases, even if the original gift wasn’t wanted.  This may have been the origin of giving mints or fortune cookies when presenting the bill.

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Here are the results of the experiments:

  • When people were surveyed and asked if they received a mint would they tip more – most people said no, but the experiment showed that tips did increase.
  • Giving diners a single mint increased tips by 3%
  • Giving diners two mints quadrupled tips by 14%
  • This is the most interesting stat:
    • If the server gives the table one mint and walks away
    • Stops and returns to the table and says “For you nice people here is another mint.”
    • Tips went up 23%.
    • It wasn’t what was given but how the mints were given that increased the tips.
  • The key to reciprocation:
    • Give First
    • Ensure what you give is personalized and unexpected.

I encourage our restaurant manager’s to run this experiment in their own restaurants and we would love to hear how it works.

Running Restaurants is Getting Harder – Part 3

To read part two click here

Labor cost is another issue that is going to affect restaurant operations. We can’t just look at labor as bodies and do we have enough. We are going to have to redesign our entire operations strategy to minimize labor and operating complexity so we can operate with fewer people in the future. We were all trained to freak out when we saw a server at $2.85 standing around on the clock imagine how that is going to be when your waiter costs you $15 an hour.

Labor cost is going to affect our make vs. buy decisions on menu items, the complexity of our menu items, and how we serve guests.

Daily restaurant operations from cooler temperatures to dining room cleanliness and everything in between has been an area devoid of data for decision making.  This is crazy because it is our operations that drive sales not the other way around. The reason for this is because there hasn’t been a way to easily collect, store, and aggregate/report on this data, until now.

The invention of the smartphone and tablet have given us the hardware that we need to collect data easily from around our locations. Platforms like OpsAnalitica with our ability to capture, aggregate, and report; allow restaurant managers to look at how operations are running across all of their locations.

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With our advanced reporting engine, you can merge your operations data with your cost and sales data and for the first time you can see how operations affect costs and sales. This increased visibility is a game changer for the industry.

There are things in your operations that you think you know today that with data we could show you you’re wrong. They look to be causal because you don’t look at them every shift, every day, consistently. When you capture data points consistently across your locations, and you can compare those data points to costs or sales you will see that there isn’t a correlation.

We are seeing that people are leaving money on the table or not realizing their full sales potential because of small operations issues that aren’t being paid attention to on a daily basis. Once again because these issues happen in real time and because they aren’t being tracked in a format that allows them to be analyzed they get missed in the fog of running a restaurant. People have operational issues that they don’t even know exist, and often times the solution doesn’t cost any additional money.  The solution is a slight change in how they do something and they can get out of their own way.

In a lot of ways, it’s like flying a plane with no instruments.  You can see what’s in front of you, but you don’t know where you are going.

Don’t fool yourself either, every penny and dollar of cost that you can wrench out of your operations cost is worth it. Walmart has been able to be consistently the low-cost leader and one of the largest companies in the world because of their focus on efficiency and cost control. If Walmart used the same back office and fulfillment infrastructure today as it did even ten years ago, it’s prices would be much higher. Do you know how they do it; operations data!

They know everything about every part of their business, and they track it. Like our industry they use technology like registers to capture some parts of the data but they have also had to go out and invest in other systems to capture other forms of operations data. They use their data and analysis advantage to win on the playing field.

The same is true for restaurants who are operating on the edge of efficiency. They get every penny of waste out of their operations, and they can use those profits to press their advantage in the marketplace.

What is crazy is that you see that profit advantage every day; here are some examples:
* Getting the endcap location in a strip center vs. being stuck in the middle. That takes cash flow
* Redesigning a website or implementing mobile ordering or curbside pickup
* Expanding number of locations
* Advertising
* Being able to keep prices lower than competitors which create a marketing advantage

It takes money to grow and when you are running efficient operations it is easier to generate the capital needed to push your competition around in the marketplace.

In conclusion, the restaurant business is getting harder because there are more outside factors that are determining success at the unit level. At the same time the tools available to operators at the unit level are getting more advanced and cheaper, giving restaurant manager’s huge advantages over their predecessors.

We have always been an operations business, I think for a lot of people, that was limited to executing on service and food. Our business will always be about taking care of the guests, but it has expanded into creating management systems that will allow you to capture data and make data-driven decisions vs. gut decisions.

Gone are the Mel’s Diner days where Mel yelled at the waitresses and cooked eggs. Mel today would be sitting at a table with a tablet trying to figure out how the avian flu was affecting egg prices and redoing his website and menu.

 

Check out this short video to learn more about OpsAnalitica

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Running Restaurants is Getting Harder – Part 2

To read part one click here

Food trucks are another segment of the industry that have prospered from wireless technology. Until recently it was incredibly expensive to take mobile credit card payments. Now it’s comparable to hardwired credit card payments. Mobile technology has made it easier for food trucks to service customers.

It used to be the only place you saw food trucks were construction sites and fairs where cash was the only form of payment taken. Now they are parked in high rent districts right next to brick and mortar restaurants for the cost of parking.

Not to mention food trucks who tweet their specials and locations throughout the day, can come to customers and can create rushes outside of normal dining periods maximizing sales time and their mobile advantage.

Technology is changing the industry. Depending on what side of some of these issues you’re on will determine if you think it is good or bad. For every manager that embraces new technology and can implement and run their businesses more efficiently, there is a Dinosaur Manager, who is finding it tougher to compete and make money.

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The one thing that is for certain is that restaurant industry isn’t an industry anymore where you go to work because you want to avoid technology. Restaurant managers need to be tech savvy, or they are going to have a hard time finding the really good positions.

With all of these things happening simultaneously it can feel overwhelming to say the least. How do you move forward, stay competitive, do everything you need to do while you have customers in your location every day.

Not doing anything and hiding from reality is not the answer. It is by far the easiest way to proceed up until the day you shut down your location and lay off all of your employees.

Making decisions off of incomplete data isn’t an option either. We live in the world where data is available to us, and we have to use it to make smart decisions and not react in a knee-jerk manner.

For instance raising prices significantly above competitors in the market just because protein prices are increasing could be a quick fix for food cost but hurt sales and anger customers. Remember, social media, Yelp reviews, will expose knee jerk reactions for all to see.

The most successful restaurants are developing restaurant operations systems that are repeatable and flexible, which allow you to make data-driven decisions. For you technophobes, this is going to require you to start using technology to help.

Let’s look at a couple of examples:

Food cost and rising commodity prices. We recently saw a demo of a tool, ChefMetric, that is a quick and easy food cost calculator. You add your order guide and recipes to the system, and you can easily calculate your food cost and what you should be charging at different food cost percentages.

Knowing your plate cost in an environment where there is a lot of commodity fluctuation will allow you to make adjustments to portion sizes and core ingredients quickly and easily. Take that one step further and maybe leave cuts and sizes off of menu descriptions, let your waiters give those answers, so you can make adjustments without having to reprint menus when you do.

Example:

  • Today’s Description: A delicious 10oz NY Strip sliced to….
  • New Description: A delicious USDA Prime Steak sliced to….

To read part 3 click here

Check out this short video to learn more about OpsAnalitica

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Running Restaurants is Getting Harder – Part 1

If you are a restaurant manager responsible for one location or thousands of locations, then you need to keep reading.

Is running restaurants getting harder?

Profitability is being squeezed from every direction. From $15 hr minimum wages, increased competition, commodity prices, and technology to name a few.

When I came up in the industry in the 80’s and 90’s running restaurants was physically hard. You worked 80 hours a week, and you almost always worked on weekends and holidays. There were a lot of managers burning out.

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Now it seems like managing restaurants is still physically hard but it’s also mentally hard. You have to concern yourself with gas prices, be on the forefront of technology, and government affairs. You can’t just provide great food and service with a smile anymore and expect to cruise.

We have new $15 minimum wage laws being put into effect across the country, if it hasn’t hit your state yet, don’t worry it is coming. After $15 minimum wages, my bet will be more breaks and shorter shifts.

We have commodity prices being affected heavily by oil and corn prices making menu staples more expensive than they were just a few years ago. Because corn is no longer just corn it is an alternative fuel when oil prices go higher corn prices also rise making it more expensive to feed livestock, to transport food to market, etc.

We are still recovering from several years of drought that drove up feed prices and took their toll on cattle stocks; we should start to see more cattle supply in 2016 & 2017.

Commodity prices fluctuating means that you have to know your plate cost and adjust your menus more frequently or run the risk of running higher than budgeted food costs. Adjusting menus and reprinting carry their costs.

Technology has been a blessing and curse depending on where you sit. Technology is increasing competition in the restaurant industry in several ways.

It is cheaper to start restaurants today than it was in the past. It used to take years of work and lots of money to develop and implement restaurant management systems. Now POS and back office systems have come so far down in price that any restaurant can have a world-class inventory, register, checklist, and accounting system. At NRA this year there was a Free POS system as long as you used their credit card processing.

Before cloud based apps, if you wanted to have a system like OpsAnalitica you would have had to build it from scratch. Developing enterprise level software is incredibly cost prohibitive and in the past ensured that only the largest restaurant chains could afford to have advanced systems.

Our platform was originally conceived when I worked for a national sandwich franchisor with over 4,000 locations. The features in our platform were built to work in a system with a lot of locations and complexity. Now an individual restaurant owner can use the OpsAnalitica checklist and reporting platform for around $1 a day and have the same tools and advantages as their chain competitors.

Restaurant websites, a relatively new requirement in the industry, are getting easier to build and maintain. At NRA this year there was a vendor who had people building their websites on the floor of the show.

In our town, we have a local 4 location Italian chain. Their website and online ordering portal, in my opinion, are as good as Pizza Hut’s; I have used them both in the last couple of weeks. Before the internet, you would have to spend millions of dollars to compete with a Pizza Hut or Dominoes on an ordering system. Now you can get it for pennies on the dollar and as a template that you just plug your logo, menu, and photos into and play.

Technology has made it possible for single locations to reach outside of their normal trade area. Take GrubHub for example, a business that can handle a lot of sales volume can implement GrubHub and can have food delivery outsourced.

They can start impacting restaurants miles away that in the past would never have had to worry about their existence. You now have customers that are close to your location ordering from your competitor when in the past they would have been eating at your establishment.

To read part two click here

Check out this short video to learn more about OpsAnalitica

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What is the deal with GMO’s?

I would like to thank Chef Russell Furdell from Chef Resources for sending me this Slate.com article on GMO’s.  We usually like to cut and paste these types of articles so you can just read them here, but this one is so long and has so many pictures that it wasn’t going to look good.

Here is the URL to the original article:  Unhealthy Fixation: The war against genetically modified organisms is full of fearmongering, errors, and fraud. Labeling them will not make you safer.

I feel like the case on GMO’s is similar to other modern issues, global warming, that have become so politicized that it’s hard to find the truth.

I thought the article was informative, it cited scientific studies and did a nice job of showing the history of GMO’s.  It is a long article, but I think it worth a read.

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The Value of Pre-Shift Meetings

I had the opportunity in 2002 to go through hospitality and customer service training similar to what the Ritz Carlton organization uses.  This program was implemented at one of the premier shopping malls in the country, The Grove in Los Angeles. I was a Concierge Services Manager at the mall. Our concierge team was so good that we won the 2002 Wall Street Journal Battle of the Concierges. We beat the W Hotel in San Francisco and the Ritz in NYC.

 The training program was simple and straight forward:

  1. Intense customer service training before new employees interact with guests.
  2. Wallet card with customer service guidelines on it.
  3. Memorization of customer service guidelines.
  4. Customer service test, must pass before assuming position.
  5. Daily Pre-shift Meeting for all employees including managers.
I want to focus on the pre-shift meeting aspect of the system because it was key to the overall implementation of the program and what maintained our customer service standards after the initial training.
Over my years of managing restaurants I have built upon that foundation and created the OpsAnalitica Pre-shift Methodology that I would like to share with you today.
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Your Pre-shift is broken into the following sections:
  1. Customer Service Tenant
    • This is one of 10 to 15 customer service tenants that you train and hold your team responsible for implementing.
  2. Quick explanation of the service tenant as a story.
    • Make the story relatable and short.
  3. Team member Experience
    • A team member shares a real life experience where they discuss a time when they gave or received service highlighted in the service tenant.
    • How did that make them or the guest feel?
  4. Important shift Information
    • 86’d items
    • Specials
  5. Quote or Joke of the day
    • Share a quote or joke of the day.
    • Make sure joke is appropriate for your audience.
  6. Shift contest
    • Every shift you should run a contest to motivate the team and you reward the winners with a meal, or credit, or post shift drink, etc.
      • You can run longer contests, like bottles of wine in a month but you really have to work to keep the team motivated and the prize has to be a lot bigger. Sometimes distributors will provide the prize.
    • Serving guests can become monotonous, use contest to motivate your team and to focus them on high contribution margin or items that are nearing expiration. By using contests to move these types of products you can lower waste and increase profits.
      • When I worked at Changs over a decade ago the food cost on Chicken Lettuce Wraps was $.39 an order and they sold for $6.95. Chicken Lettuce Wraps had a 6% food cost.  Don’t you want to be incenting your servers to sell items that have high contribution margins?
    • Make sure you announce the winner of last shift’s contest at the next Pre-shift meeting.
    • Examples of server games:
      • Server Bingo
      • Ticket times contests
      • Food or drink Item contest
      • Compliment contests
      • Comment card contests
I’ve seen first hand at a Changs the power of pre-shifts. Taking that couple of minutes before every shift to focus your team on service, give them a goal, and communicate vital information works wonders. I was a part of a management team that increased weekly sales by 50k a week from 125 to over 170k a a week in an 8 month period and pre-shifts were a major part of the strategy.
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The Restaurant Industry Warned You – Look at What is Happening in Seattle

Fox news just published an article about some of the unintended consequences that are showing up in Seattle because of their new minimum wage law.  To read the full article click here.

Here are the points that I found most interesting:

  • People are asking their bosses for fewer hours so they can make less and stay on public assistance.
  • “If they cut down their hours to stay on those subsidies because the $15 per hour minimum wage didn’t actually help get them out of poverty, all you’ve done is put a burden on the business and given false hope to a lot of people,” said Jason Rantz, host of the Jason Rantz show on 97.3 KIRO-FM.
  • The fifteen dollar minimum wage has not really moved the needle very much on moving people off of welfare:  In March 130,851 people were enrolled in the Basic Food program. In April, the caseload dropped to 130,376.
  • Some restaurants have tacked on a 15 percent surcharge to cover the higher wages. And some managers are no longer encouraging customers to tip, leading to a redistribution of income. Workers in the back of the kitchen, such as dishwashers and cooks, are getting paid more, but servers who rely on tips are seeing a pay cut.

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Seattle’s $15 minimum wage law is supposed to lift workers out of poverty and move them off public assistance. But there may be a hitch in the plan.

Evidence is surfacing that some workers are asking their bosses for fewer hours as their wages rise – in a bid to keep overall income down so they don’t lose public subsidies for things like food, child care and rent.

Full Life Care, a home nursing nonprofit, told KIRO-TV in Seattle that several workers want to work less.

“If they cut down their hours to stay on those subsidies because the $15 per hour minimum wage didn’t actually help get them out of poverty, all you’ve done is put a burden on the business and given false hope to a lot of people,” said Jason Rantz, host of the Jason Rantz show on 97.3 KIRO-FM.

The twist is just one apparent side effect of the controversial — yet trendsetting — minimum wage law in Seattle, which is being copied in several other cities despite concerns over prices rising and businesses struggling to keep up.

The notion that employees are intentionally working less to preserve their welfare has been a hot topic on talk radio. While the claims are difficult to track, state stats indeed suggest few are moving off welfare programs under the new wage.

Despite a booming economy throughout western Washington, the state’s welfare caseload has dropped very little since the higher wage phase began in Seattle in April. In March 130,851 people were enrolled in the Basic Food program. In April, the caseload dropped to 130,376.

At the same time, prices appear to be going up on just about everything.

Some restaurants have tacked on a 15 percent surcharge to cover the higher wages. And some managers are no longer encouraging customers to tip, leading to a redistribution of income. Workers in the back of the kitchen, such as dishwashers and cooks, are getting paid more, but servers who rely on tips are seeing a pay cut.

Some long-time Seattle restaurants have closed altogether, though none of the owners publicly blamed the minimum wage law.

“It’s what happens when the government imposes a restriction on the labor market that normally wouldn’t be there, and marginal businesses get hit the hardest, and usually those are small, neighborhood businesses,” said Paul Guppy, of the Washington Policy Center.

Seattle was followed by San Francisco and Los Angeles in passing a $15 minimum wage law. The wage is being phased in over several years to give businesses time to adjust. The current minimum wage in Seattle is $11. In San Francisco, it’s $12.25.

And it is spreading. Beyond the city of Los Angeles, the Los Angeles County Board of Supervisors this week also approved a $15 minimum wage.

New York state could be next, with the state Wage Board on Wednesday backing a $15 wage for fast-food workers, something Gov. Andrew Cuomo has supported.

Already, though, there are unintended consequences in other cities.

Comix Experience, a small book store in downtown San Francisco, has begun selling graphic novel club subscriptions in order to meet payroll. The owner, Brian Hibbs, admits members are not getting all that much for their $25 per month dues, but their “donation” is keeping him in business.

“I was looking at potentially having to close the store down and then how would I make my living?” Hibbs asked.

To date, he’s sold 228 subscriptions. He says he needs 334 to reach his goal of the $80,000 income required to cover higher labor costs. He doesn’t blame San Francisco voters for approving the $15 minimum wage, but he doesn’t think they had all the information needed to make a good decision.

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Operations Data Use Cases Finale

In yesterday’s post, Operations Data Use Cases. We discussed two Ops Data use cases and how Ops Data could be used to make better decisions, drive better operations, and run more profitable restaurants.  In Today’s blog post, we are going to discuss one more use case and draw some conclusions.

Line Pars

Do you check that your different kitchen stations are stocked and that there is enough thawed product to meet your pars every shift?  More importantly do you track that metric so you refer can back to it when looking at sales.  Have you ever considered how much longer it takes to cook a frozen burger patty than a thawed patty?  I’ve heard that it can take up 50% longer to cook a frozen patty vs. thawed patty.  That is the difference between 4 minutes and 6 minutes per patty.  If you were to cook a case of burgers one after the other, the frozen patties would take 80 minutes longer to cook than the thawed patties.

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Ensuring that your line is stocked every shift with thawed product is massively important.  A 50% increase in cook times on a key item like burgers can be the difference between getting a third turn at lunch and having a second turn just sort of fade out.

When you are looking at lunch sales for weeks or months at a time, and you can’t understand why on certain days your sales dip; what else do you look at today?  If you track operations data, you can merge your sales data with other data to try and uncover what may be the cause.

We had a client that determined that on Wednesday’s they always had a dip in sales, they served a ton of burgers at this bar, and they got their food deliveries on Tuesdays.  A lot of the time they coasted into Wednesday lunch with 1/2 their burger par for the shift still frozen which killed their ticket times and their 3rd turn.  It wasn’t until they merged their checklists with their sales and looked at them by days of the week that this reality showed up.

The amazing thing was how easy it was to fix.  They worked with their suppliers to increase the number of thawed burger cases they received and instructed their cooks to ensure that they had enough frozen patties thawing to cover Wednesday dinner and Thursday.  They got their sales on Wednesdays to match or exceed their Tuesday sales, and it didn’t cost them anything but a few minutes of looking at their Ops Data.

Conclusions

Using digital checklists to track your operations data can provide context for your sales numbers.  Remeber, Operations Drive Sales – Sales don’t drive Operations.  Plus well-written checklists guide your managers to look at the most important items of your operations every day.  Digital checklists aren’t going to solve the world’s problems but they are going to help you run better operations.  If you would like to learn more about our SMART Inspection philosophy and what kinds of questions you should be asking you should sign up for our weekly webinar here.

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Operations Data Use Cases

In yesterday’s post, What is Operations Data. We discussed the importance of Operations Data (Ops Data) and how it could be used to make better decisions, drive better operations, and run more profitable restaurants.  In Today’s blog post, we are going to discuss more Ops Data use cases.

Is your manager any good?

The GM of a restaurant has more to do with the restaurant’s success or failure than any other person you employ; the buck stops with the boss, and it is ultimately their responsibility to run profitable operations.  How do you know if your GM is doing a good job?  Do you base that on sales or cost percentages?  Do you base that on complaints and compliments?  Do you base that on how well the staff likes them?  If you are not at the location every day; then how do you know?

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I’m going to tell you a real story from my past. At one point in my career, I was a member of a team of managers that turned in our GM to corporate because he was cooking the books around labor cost.  He was going into the register and rolling back employees times to 40 hours per week on Monday mornings before he submitted the weekly numbers to corporate.  We found out about this because one of our best employees quit when he got his paycheck and all of the hours that he had worked weren’t on there. We found out the GM was doing this for all employees, a lot of employees knew this was happening to them, but they were not speaking up because they were being intimidated.  By stealing from the employees, he was able to keep his labor cost in-line and inflate profits and subsequently his bonuses.

To the outside world, he was running an incredibly profitable restaurant.  Corporate proved that he was stealing, after we tipped them off, by using POS metadata.  Metadata is the data of data.  An example of metadata in a POS might be the server’s name and the time they closed the ticket.  You have the order, but you also have the other data around the order that helps tell the story.  The POS system we used had advanced keystroke logging; it could record what buttons were pushed by what people.  So the forensic team at corporate was able to verify that what we told them was true, and they fired this person immediately.

That POS metadata is operations data; it was used to tell the story that the sales and cost data couldn’t tell.  Another example of metadata, in the OpsAnalitica system, we record metadata on every inspection, we know who logged in and when then answered each question and how long their inspection took to complete, we know if you pencil whipped or if you took time to answer the questions correctly.

Appearance of the Restaurant

Do you track how ready your restaurant is for each shift?  Do you think that a clean and tidy restaurant is better for guests than a dirty restaurant?  Of course, you do. How would you know if the cleanliness of your restaurant was affecting sales?  Think about the last five times you started your dinner shift and your restaurant wasn’t 100% ready for the shift.  Could you write down those dates on a piece of paper right now?  I would be impressed if you could.  Have you ever gone back and looked at the sales from those nights and compared them to averages sales on those days of the week and the year before?

If you tracked this question on a digital checklist daily and you merged that data with your sales data you could determine how much a dirty restaurant may be costing you per night.  It could be thousands of dollars, or it could be $15.  If you can’t look at sales with other operation factors to provide context, then you don’t know the why behind performance and profits.

One last point to make about tracking data using digital logs vs. digital checklists.  I think digital logs are great for communicating data between managers and between shifts, that is what they are designed to do.  From a query writing and reporting perspective, it is much easier to compare a question or a series of individual data points that are defined than it is to compare the free text that is written in a log.  If you want to use operations data to make better decisions, track specific data points in a checklist and don’t try to compare sales to log notes because it won’t be helpful.

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