### Panera Bread still yummy

When I wrote my report on Panera Bread last week, I felt like I was conservative - but I came up with a $75 target. Apparently, people are loving those cinnamon crunch bagels more than me, because today they came out and reported a 10.2% increase in same-store sales for January. I had predicted about 6%...given that last year's first Q was the weakest of its 4 quarters.

For Panera, I have my investor / analyst hat on, and not the trading hat (it's a fun stock to trade though). Analysts have to be careful not to be TOO optimistic so as to not be ridiculous, like the idiot who put a $2,000 price target on Google. Yeah, $2,000. That was just irresposible -> although at least the guy who did it can fall back on the fact that there are tons of scheisters in the financial services industry. Congrats, dude, you're right at home.

Back to Panera...if they can continue at this pace, the stock could be worth my initial price estimate in the hundreds, but it's just still hard to imagine this continuing! Time to break out the model and play with the numbers...it appears that in my model, same-store sales for the year don't have a HUGE impact, maybe to $76, because I'm not assuming 10% for the year. That would be irresponsible by me. So I'm still watching the new store openings...for which I think we're going to see a big year for Panera...

BTW - The coffee is better here than at most places, too. When I first saw the a restaurant in 2000, I hated it...it was all "trendy" but I should have thought about how many people stood in line. The place is nothing but a cash cow in a really competitive line of business. Cash cows are good :-)

## 4 Comments:

How did you came with a forecast of 6% for panera bread? I havw never figured out how do analysts model the same store sales estimates. For earnings, they use earnings model by assuming certain sales tax, etc. but how do they come up with the SSS estimates?

Well, it's an estimate! But, there are a few ways that I approached it. First, I go to Panera and check out the lines at peak times. Sounds like alot of work, but it's a great way to get a guess. Have to be careful not to have a regional or store bias, however.

I also look at previous year's same-store sales. If a month is very low, generally it is easier to beat in the following year. So, January of '05 was only 5.6%, so the 10.2% number was easier to attain than, say, perhaps expecting 10.2% next year. But, the first piece - going to stores can completely trump that estimate.

Finally, I have a revenue model where I know roughly how much Panera receives from its franchisees and using the same-store number changes the amount of cash they get. I have an idea that my *estimate* is not perfect, so I try ranges of numbers from -4% to 11% to see what effect it has on the model, then using a probability distribution, I have an idea of what the price of the stock should roughly be.

I understand that. But my point is that there is no definite model per se for coming up with sss estimates. Instead of an estimate of 6%, it could be 7%. Lets say panera had an actual sss of 6.5%. in your case they beat by .5% but if you had selected 7%, they missed! What i am struggling with is that there is no definite model per se to come up with sss estimate as there is in case of earnings estimates. Or in other words, say the analyst consensus is 6% and you know that if the company beats this estimate, the stock goes up 10$, now the question is how do you decide if the 6% consensus is over or under estimates. In case of earnings , you can see what difference in the analysts estimates by looking at their earnings model.

You raise a good point about ifficult comparisions. even in that cae, how do you know what is too high or too low. e.g. next year, panera is going to have a tough comparision of10.2%. now the question is if someone has an estimate if say 5%, how do you know if this is over or under estimate?

Yes, you're right, there is no model you can use. It's art, not science. You seem bothered by that. What you have to do is what I mentioned earlier, and maybe also throw in the fact that a company has momentum in its popularity, or the company has given you a hint on a conference call or something like that. It's not 100% scientific like you seem to wish it to be.

Secondly, the "earnings model" actually includes same-store sales growth. SSG translates into more earnings. They're not exclusive, in fact, they're part of the same.

Next, much of what you do to determine what the market thinks is still educated guessing. You can never "know" what the right answer is until after the fact. If you did, you'd be Biff from Back to the Future Part II, or you'd be guilty of insider trading and should go to jail.

For analyst consensus, I suppose you could pour through the sell-side reports to get an idea or whatever...but you can also look for "Price Implied Expectations". This is hard, though, also, mainly because the current price can be ascertained from a slew of different "solutions" to the equations that give the current stock price.

Also, remember that we're trying to estimate "company value" per share, which gives our share price. A 4% surprise in a single month's same-store sales growth is never worth $10 per share in stock price, unless:

1) The surprise was completely unexpected and

2) The math per share means that the value has been increased by the # of shares times $10...which is very unlikely.

I got $0.13 in share price value for Panera when it "surprised" with Jan. SSG at 10% in my earnings model.

Am I making any sense?

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