Do you keep your old menus? If you have a stack somewhere in your office, try to locate the menu from 2004. I would suggest you put your current menu side-by-side and perform the following checklist:
1. Count the number of choices in each major category for both menus. Fewer is better in this environment. If your current menu has more selections in the appetizer and entree zones, make a list of the items added in the last 5 years.
2. How do the prices compare between the two menus? Normal inflation over the 5 year period was low but food commodity markets had tremendous volatility during the oil price boom and bust. Perhaps you have cut menu prices to encourage more customers. Look for the highest and lowest priced entrees and put this information in perspective.
In 2004, proper pricing of the highest priced entree was very important. Diners were spending more 5 years ago. Today, the lowest priced entree is quite important. Many diners are searching for value. You may not be charging enough for your budget selections.
3. Try to remember your previous pricing strategy. Look back 5 years ago and think of your game plan. Were you raising menu prices 10% each year? Maybe 5%. A 10% annual increase will add up to 60% over 5 years. The 5% annual increases amount to 28% over the same 5 years.
If your current prices are looking similar to 5 years ago, your average increase for the 10 year period is about half of the number from the 2004 strategy. Should you bring your costs in line with this new reality? In the short run, most companies have been forced to make drastic cuts. Take a long term view and decide what the future holds for the next 5 years.
In summary, this is a great time to review your most recent 5 years. Sometimes people look at the future through an optimistic lens. Other times (like now), the pessimistic lens is used. By looking at the complete picture, you will see things as a realist.
Rabu, 24 Februari 2010
Kamis, 18 Februari 2010
Is Your Ideal Food Cost Number Real?
A veteran restaurateur asked me to check out his numbers to see if I could see a problem. Initially, he assumed the program he purchased was defective. As I started asking questions, my focus turned to yield data from his butchering department.
In addition to a very ambitious menu, this restaurant offers a top cuts of beef in a small retail shop. Along with T-Shirts and ball caps, customers can take home a filet mignon or porterhouse steak. The butchering department produces cuts of meat for both the restaurant and the retail shop.
The retail shop has a consistent cost of goods sold percentage.
After tracing the food cost percentage backwards, it became clear the restaurant suffered from butchering yield volatility. The accounting method utilized by the owner treats the butchering operation as part of the restaurant. Steaks are "sold" to the retail shop at cost. This cost is determined using a formula which has a standard yield and only varies with market price fluctuations.
The main issue is the normal volatility in yield (i.e. edible pounds as a function of as purchased pounds) is borne by the restaurant. The owner is using ideal cost data which assumes the yield is constant. One of the most popular large cuts has a "typical" yield of 61%. The actual results vary between 57% and 64%. The 61% standard occurs about 18% of the time. The rest of the time (82%), the butchering operation has a variance from the standard.
Click on the banner above for information about our next Menu Analysis Webinar.
When the yield is on the high side, the restaurant has a good week. The rest of the time, the restaurateur is scratching his head. The number one point to take from this story: he keeps tremendous records. I would never be able to explain this situation with clarity without his butchering archive. He keeps a three ring binder with a butcher yield sheet for each batch.
After I helped him tie the butchering yield data to his ideal usage model, the variance due to butcher yield declined and the problem was solved. Should we be happy with the virtual elimination of the variance? Probably not.
The previous uncertainty produced plenty of heated discussions between the production team members. These interactions produced a decent number of innovations over time. Now the calm waters have caused a level of indifference which never existed before the model was tweaked.
I personally enjoy variances. Many operators hate any variance from the ideal. They build recipe models which are designed to hide normal variances. When deciding on a yield, these people imagine the worst case scenario (57% in the operation above). By the time a variance is recognized using these reports, there is a huge problem.
The range between 57% and 64% is 7%. When expressed as a function of the low yield figure, this range is nearly one eighth. If the butcher was crooked, he could grab a box of meat for every eight when the yields are good. His theft would go completely undetected. The same restaurant may never get on the phone with the meat supplier and complain about the substandard yields. Inconsistent portion sizes would stay hidden as well.
So what is the best way to approach this situation? The restaurant needs to treat the butchering operation as a separate entity. In this entity, yield variances need to be front page news. Daily variance should be dealt with decisively and quickly. This butcher should "sell" portions to both the restaurant and the retail shop. These portions should be closely monitored using a POS system.
In addition to a very ambitious menu, this restaurant offers a top cuts of beef in a small retail shop. Along with T-Shirts and ball caps, customers can take home a filet mignon or porterhouse steak. The butchering department produces cuts of meat for both the restaurant and the retail shop.
The retail shop has a consistent cost of goods sold percentage.
After tracing the food cost percentage backwards, it became clear the restaurant suffered from butchering yield volatility. The accounting method utilized by the owner treats the butchering operation as part of the restaurant. Steaks are "sold" to the retail shop at cost. This cost is determined using a formula which has a standard yield and only varies with market price fluctuations.
The main issue is the normal volatility in yield (i.e. edible pounds as a function of as purchased pounds) is borne by the restaurant. The owner is using ideal cost data which assumes the yield is constant. One of the most popular large cuts has a "typical" yield of 61%. The actual results vary between 57% and 64%. The 61% standard occurs about 18% of the time. The rest of the time (82%), the butchering operation has a variance from the standard.
Click on the banner above for information about our next Menu Analysis Webinar.
When the yield is on the high side, the restaurant has a good week. The rest of the time, the restaurateur is scratching his head. The number one point to take from this story: he keeps tremendous records. I would never be able to explain this situation with clarity without his butchering archive. He keeps a three ring binder with a butcher yield sheet for each batch.
After I helped him tie the butchering yield data to his ideal usage model, the variance due to butcher yield declined and the problem was solved. Should we be happy with the virtual elimination of the variance? Probably not.
The previous uncertainty produced plenty of heated discussions between the production team members. These interactions produced a decent number of innovations over time. Now the calm waters have caused a level of indifference which never existed before the model was tweaked.
I personally enjoy variances. Many operators hate any variance from the ideal. They build recipe models which are designed to hide normal variances. When deciding on a yield, these people imagine the worst case scenario (57% in the operation above). By the time a variance is recognized using these reports, there is a huge problem.
The range between 57% and 64% is 7%. When expressed as a function of the low yield figure, this range is nearly one eighth. If the butcher was crooked, he could grab a box of meat for every eight when the yields are good. His theft would go completely undetected. The same restaurant may never get on the phone with the meat supplier and complain about the substandard yields. Inconsistent portion sizes would stay hidden as well.
So what is the best way to approach this situation? The restaurant needs to treat the butchering operation as a separate entity. In this entity, yield variances need to be front page news. Daily variance should be dealt with decisively and quickly. This butcher should "sell" portions to both the restaurant and the retail shop. These portions should be closely monitored using a POS system.
Jumat, 12 Februari 2010
Menu Price Trends
Histograms profile the number of data points for each class using a standard bar chart format. In constructing a menu map, I like to see the action in terms of popularity and dollars of sales produced. For this analysis, the data points per bin is the starting point. Knowing the number of menu items offered at each price point helps you later in the analysis.
The chart below shows the additional information in columns. Almost 3/4 of sales are produced by menu items priced between $23 and $40.
Should this restaurant eliminate the high priced items which are seldom ordered?
Menu psychology suggests the very high priced items help make the popular item's prices look attractive. Given the current economy, this philosophy may not work as well as in 2008 (source year for the test data). In fact, the operator is currently pushing pasta entrees during mid-week dinner periods.
I'd like to get my hands on the data from last year and make a comparison. In a side by side comparison, I'd expect a shift to lower priced menu items.
Here in the Mid-Atlantic, crab cake dinners are very popular. Although jumbo lump crab meat is pricey, diners expect to pay below $30 for two cakes with a salad and sides. The cakes with minimal filler are recommended in the local press and by word of mouth. This means a competitive dinner house serving Maryland jumbo lump meat needs to use about $10 of crab for the entree.
Last week, I had a conversation with a neighbor who loves to dine out. He and his wife ordered crab cakes at one of the most well known restaurants in the area. The two cake dinners sold for $28.95.
He said the cakes were loaded with bread crumbs. He was quite disappointed due to the treatment he received when he told the manager. He was offered an apology and a free appetizer card. This free card was good for a future meal. They lost a loyal patron and fan.
The chart below shows the additional information in columns. Almost 3/4 of sales are produced by menu items priced between $23 and $40.
Should this restaurant eliminate the high priced items which are seldom ordered?
Menu psychology suggests the very high priced items help make the popular item's prices look attractive. Given the current economy, this philosophy may not work as well as in 2008 (source year for the test data). In fact, the operator is currently pushing pasta entrees during mid-week dinner periods.
I'd like to get my hands on the data from last year and make a comparison. In a side by side comparison, I'd expect a shift to lower priced menu items.
Here in the Mid-Atlantic, crab cake dinners are very popular. Although jumbo lump crab meat is pricey, diners expect to pay below $30 for two cakes with a salad and sides. The cakes with minimal filler are recommended in the local press and by word of mouth. This means a competitive dinner house serving Maryland jumbo lump meat needs to use about $10 of crab for the entree.
Last week, I had a conversation with a neighbor who loves to dine out. He and his wife ordered crab cakes at one of the most well known restaurants in the area. The two cake dinners sold for $28.95.
He said the cakes were loaded with bread crumbs. He was quite disappointed due to the treatment he received when he told the manager. He was offered an apology and a free appetizer card. This free card was good for a future meal. They lost a loyal patron and fan.
Selasa, 09 Februari 2010
Three Classic Menu Engineering Approaches
There are 3 classic menu engineering models taught in hotel/restaurant management courses. These models produce much different results when applied to a restaurant with a large number of entree choices.
Many people are familiar with the Star, Plowhorses, Puzzles, and Dogs approach which was developed by Kasavana and Smith. This model uses popularity as a function of gross contribution to split entrees into 4 quadrants. The popularity cutoff is 70% of the average number sold. If you sold 1,000 entrees and had 10 choices, any entree with over 70 sold is either a Star or a Plowhorse. The contribution test uses the mean. If the average contribution per plate is $12, items with higher profit would be labeled as a Star or a Puzzle (depending on popularity).
The second popular method was developed by Miller. He uses a similar popularity test but focuses on food cost % instead of gross margin. His Winners are popular menu items with a low food cost %.
Finally, Pavesic's menu engineering approach uses weighted statistics and looks at profitability as a function of food cost %. There is no 70% applied to his figures since the numbers are weighted by their overall impact on results.
I used the 3 methods to evaluate the menu at a seafood and steak dinner house with 41 entree choices. Comparing the ratings to my initial recommendations to the owner, I find myself most in sync with the Pavesic method. I tend to focus on profitability improvement through tighter food cost control. Someone employing the Pavesic method with reliable recipe cost data would come to many of the same conclusions I reached without running the statistics.
Miller rated a block of popular menu items as Winners when the Kasavana/Smith approach rating was Plowhorse and the Pavesic rating was Standard. Although I like the Miller approach for the current recession, entrees with lower gross margins may not rate a Winner class unless they achieve a low food cost % figure.
[My test data came from work I did in 2008 and the recession was mostly an autumn event in this seashore restaurant. The summer figures were in line with previous boom years and this season dominates the annual sales volume results.]
If I were advising the same operator today, the Miller approach would factor heavily in my recommendations. Since there is a ceiling on menu item prices imposed by the thrifty diners of 2010, restaurants need to rely more heavily on tight food cost control to achieve profits. I would expect to see fewer sales of high ticket menu items with high gross margins and high food cost % figures since the high selling prices which would support this profile have declined in popularity. Fewer diners are trying to impress with their choices. More diners are looking for a lower check at the end of the meal.
Many people are familiar with the Star, Plowhorses, Puzzles, and Dogs approach which was developed by Kasavana and Smith. This model uses popularity as a function of gross contribution to split entrees into 4 quadrants. The popularity cutoff is 70% of the average number sold. If you sold 1,000 entrees and had 10 choices, any entree with over 70 sold is either a Star or a Plowhorse. The contribution test uses the mean. If the average contribution per plate is $12, items with higher profit would be labeled as a Star or a Puzzle (depending on popularity).
The second popular method was developed by Miller. He uses a similar popularity test but focuses on food cost % instead of gross margin. His Winners are popular menu items with a low food cost %.
Finally, Pavesic's menu engineering approach uses weighted statistics and looks at profitability as a function of food cost %. There is no 70% applied to his figures since the numbers are weighted by their overall impact on results.
I used the 3 methods to evaluate the menu at a seafood and steak dinner house with 41 entree choices. Comparing the ratings to my initial recommendations to the owner, I find myself most in sync with the Pavesic method. I tend to focus on profitability improvement through tighter food cost control. Someone employing the Pavesic method with reliable recipe cost data would come to many of the same conclusions I reached without running the statistics.
Miller rated a block of popular menu items as Winners when the Kasavana/Smith approach rating was Plowhorse and the Pavesic rating was Standard. Although I like the Miller approach for the current recession, entrees with lower gross margins may not rate a Winner class unless they achieve a low food cost % figure.
[My test data came from work I did in 2008 and the recession was mostly an autumn event in this seashore restaurant. The summer figures were in line with previous boom years and this season dominates the annual sales volume results.]
If I were advising the same operator today, the Miller approach would factor heavily in my recommendations. Since there is a ceiling on menu item prices imposed by the thrifty diners of 2010, restaurants need to rely more heavily on tight food cost control to achieve profits. I would expect to see fewer sales of high ticket menu items with high gross margins and high food cost % figures since the high selling prices which would support this profile have declined in popularity. Fewer diners are trying to impress with their choices. More diners are looking for a lower check at the end of the meal.
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